==== Front BMC Cardiovasc Disord BMC Cardiovasc Disord BMC Cardiovascular Disorders 1471-2261 BioMed Central London 1725 10.1186/s12872-020-01725-5 Research Article Physical functional performance and prognosis in patients with heart failure: a systematic review and meta-analysis Fuentes-Abolafio Iván José 1 Stubbs Brendon 234 Pérez-Belmonte Luis Miguel 567 Bernal-López María Rosa 58 Gómez-Huelgas Ricardo 58 http://orcid.org/0000-0002-8880-4315Cuesta-Vargas Antonio Ignacio acuesta@uma.es 19 1 grid.10215.370000 0001 2298 7828Department of Physiotherapy, Faculty of Health Science, University of Malaga, The Institute of Biomedical Research in Malaga (IBIMA), Clinimetric Group FE-14, Malaga, Spain 2 grid.37640.360000 0000 9439 0839Physiotherapy Department, South London and Maudsley NHS Foundation Trust, Denmark Hill, London, UK 3 grid.13097.3c0000 0001 2322 6764Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK 4 grid.5115.00000 0001 2299 5510Positive Ageing Research Intitute (PARI), Faculty of Health Social Care and Education, Anglia Ruskin University, Chelmsford, UK 5 grid.452525.1Internal Medicine Department, Instituto de Investigación Biomédica de Malaga (IBIMA), Regional University Hospital of Málaga, Málaga, Spain 6 grid.10215.370000 0001 2298 7828Unidad de Neurofisiología Cognitiva, Centro de Investigaciones Médico Sanitarias (CIMES), Instituto de Investigación Biomédica de Málaga (IBIMA), Universidad de Málaga (UMA), Campus de Excelencia Internacional (CEI) Andalucía Tech, Málaga, Spain 7 grid.413448.e0000 0000 9314 1427Centro de Investigación Biomédica en Red Enfermedades Cardiovasculares (CIBERCV), Instituto de Salud Carlos III, Madrid, Spain 8 grid.413448.e0000 0000 9314 1427CIBER Fisio-patología de la Obesidad y la Nutrición, Instituto de Salud Carlos III, Madrid, Spain 9 grid.1024.70000000089150953School of Clinical Sciences, Faculty of Health at the Queensland University of Technology, Brisbane, Queensland Australia 9 12 2020 9 12 2020 2020 20 51223 7 2020 4 10 2020 © The Author(s) 2020Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.Background Patients with Heart Failure (HF) show impaired functional capacities which have been related to their prognosis. Moreover, physical functional performance in functional tests has also been related to the prognosis in patients with HF. Thus, it would be useful to investigate how physical functional performance in functional tests could determine the prognosis in patients with HF, because HF is the leading cause of hospital admissions for people older than 65 years old. This systematic review and meta-analysis aims to summarise and synthesise the evidence published about the relationship between physical functional performance and prognosis in patients with HF, as well as assess the risk of bias of included studies and the level of evidence per outcome. Methods Major electronic databases, such as PubMed, AMED, CINAHL, EMBASE, PEDro, Web of Science, were searched from inception to March 2020 for observational longitudinal cohort studies (prospective or retrospective) examining the relationship between physical functional performance and prognosis in patients with HF. Results 44 observational longitudinal cohort studies with a total of 22,598 patients with HF were included. 26 included studies reported a low risk of bias, and 17 included studies showed a moderate risk of bias. Patients with poor physical functional performance in the Six Minute Walking Test (6MWT), in the Short Physical Performance Battery (SPPB) and in the Gait Speed Test showed worse prognosis in terms of larger risk of hospitalisation or mortality than patients with good physical functional performance. However, there was a lack of homogeneity regarding which cut-off points should be used to stratify patients with poor physical functional performance from patients with good physical functional performance. Conclusion The review includes a large number of studies which show a strong relationship between physical functional performance and prognosis in patients with HF. Most of the included studies reported a low risk of bias, and GRADE criteria showed a low and a moderate level of evidence per outcome. Keywords Functional testsHeart failureHospitalisationMortalityPhysical functional performancePrognosisissue-copyright-statement© The Author(s) 2020 ==== Body Background Cardiovascular diseases continue to be the leading cause of disability-adjusted life-years (DALYs) due to non-communicable diseases and the leading cause of death [1–3]. Within cardiovascular diseases, Heart Failure (HF) is the only cardiovascular disease which is increasing in incidence and prevalence due to the aging of the world population, because its prevalence increases with age [4–8]. In addition, heart failure constitutes the most important hospital diagnosis in older adults, is the leading cause of hospital admissions for people older than 65 years old and contributes to the increase of medical care costs [5–9]. Heart Failure is characterised by a weak myocardium with decreased cardiac output that is unable to meet the body metabolic demands [4–6, 8, 10–12]. There are several functional symptoms that appear in patients with HF, such as reduced aerobic capacity, decreased muscle strength, low weekly physical activity and exercise intolerance, which are accompanied by fatigue and dyspnea symptoms [12–17]. Furthermore, patients with HF show impaired functional capacities, experience a declined ability to carry out their activities of daily living and suffer a reduced quality of life [12, 14, 17]. It has also been reported that patients with chronic HF show a slower gait speed than healthy subjects of the same age [18]. The maximal aerobic capacity has been inversely correlated to the severity of HF and has been directly correlated to the prognosis and the life expectancy [14, 19, 20]. Similarly, the lower extremities muscle mass and muscle strength have also been related to long-term survival in patients with HF [14, 21]. Some functional tests have been used to predict prognosis in patients with HF. Thus, the 6-min walk test (6-MWT) has been proposed as a simple, inexpensive, safe and reproducible exercise test to assess functional capacity in patients with HF, which could also predict the prognosis of patients with HF based on distance walked [12, 22–24]. The Short Physical Performance Battery (SPPB) provides a useful and indirect measure of muscle functional capacity [12]. Moreover, the SPPB and the Timed Up and Go test (TUG) could be used to assess physical or functional frailty in patients with HF, which has been associated with an increased risk of hospitalisation and mortality in chronic heart failure [25, 26]. The utility of Gait Speed ​​has also been shown to predict functional independence loss, cardiovascular disease, hospitalisation, and mortality in older adults [27–31]. The 6-MWT measures the distance which patients can walk during 6 min [32]. The test is usually conducted in a closed corridor of 30 m where two marks are placed on the ground at a distance of 30 m, and patients walk from one end to the other, during 6 min [32]. The SPPB includes 3 tests: balance (feet together, semitándem and tandem during 10 s each), gait speed (4 m) and standing up and sitting on a chair 5 times. Each test is scored from 0 (worst performance) to 4 (best performance). The total score for the whole battery that is the addition of the 3 tests and ranges from 0 to 12 [33]. In the TUG test patients are sat down in a chair, and at the order to “go”, they stand up from the chair, walk 3 m until a reach a line that is on the floor. Then, patients should turn, return to the chair walking and sit again [34]. Hence, it would be necessary to conduct a synthesis of evidence that explores the relationship between the physical functional performance in functional tests and the prognosis in patients with HF. A systematic review may permit the formation of firm conclusions through an exhaustive synthesis of data [35]. Thus, the aim of this study was to answer the following PECOS (P, participant; E, exposure; C, comparator; O, outcome; S, study design) question through a systematic review of the literature on observational longitudinal cohort studies (prospective or retrospective) (S): Do older patients with HF (P), who have poor physical functional performance in some functional tests, such as 6-MWT, SPPB, TUG or Gait Speed (E), show a worse prognosis (O) than those patients with good physical functional performance (C)? Methods The Systematic Review and Meta-analysis was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement [36]. The systematic review protocol was registered at the International Prospective Register of Systematic Reviews (PROSPERO: CRD42020177427). Data sources and search strategy Two independent reviewers (IJF-A and AIC-V) conducted a systematic search using relevant search terms that were developed from Medical Subject Headings (MeSH) and keywords from other similar studies from inception to March, 24th 2020 using optimised search strategies in the following electronic databases: PubMed, AMED, CINAHL, EMBASE, PEDro, Web of Science (Additional file 1). A manual search of relevant eligible studies, to select any studies missed during the electronic search, was also conducted using cross-references identified in the reference lists within both original and review articles. The grey literature databases, such as New York Academy of Medicine Grey Literature Report, Open Grey and Google Scholar [37] were examined to identify any relevant unpublished data. References were exported, and duplicates were removed using the Mendeley desktop V.1.19.2 citation management software. Eligibility criteria The aforementioned PECOS framework was followed to determine which studies were included in the present systematic review and meta-analysis. Each study had to meet the following inclusion criteria: Observational longitudinal cohort studies (prospective or retrospective)(S) examining whether older patients with HF (P), who have a poor physical functional performance in some functional tests, such as 6-MWT, SPPB, TUG or Gait Speed (E), show worse prognosis, assessed as larger risk of hospitalisation or mortality, (O) than those patients with good physical functional performance (C). No restriction was applied on the participants’ age, ethnicity, gender, HF diagnosis or on the New York Heart Association (NYHA) scale score. No restriction was applied on the language. Studies recruiting participants from any setting (general population, primary or secondary care). Studies providing Odds Ratio (OR) or Hazard Ratio (HR) data. The exclusion criteria were as follows: All studies that did not include an observational longitudinal cohort design (e.g cross-sectional studies, randomised controlled trials). Studies exploring the prognosis value of functional tests in patients with other cardiovascular diseases different from HF. Studies examining the relationship between physical functional performance in functional tests and other outcomes different from mortality or hospitalisation. Studies investigating the prognosis value of physical activity assessed as daily activity, exercise time per week or physical activity scales. Study selection Two independent reviewers (IJF-A and AIC-V) carried out the screening of titles and abstracts to detect potentially relevant records and also excluded those documents that were not original papers. The same reviewers conducted the screening of those articles that met all inclusion criteria. A short checklist was carried out and followed in order to select the relevant studies (Additional file 2). In case of disagreements, the articles were always included. Data extraction Two independent reviewers (IJF-A and AIC-V) identified the following relevant data from each study: study details (first author and year of publication), region, setting, study design, sample size, functional tests with their cut-off points and characteristics of participants (mean age, %males), HF diagnosis, follow-up, outcome and main results. When necessary, an email was sent to the original authors to try to get OR or HR data that was not included in their original articles. Quality assessment The same two reviewers (IJF-A and AIC-V) assessed the risk of bias of the included observational longitudinal cohort studies using the Newcastle Ottawa Scale (NOS) [38]. The NOS has been decribed as a reliable and valid tool for assessing the quality of observational longitudinal cohort studies [38, 39]. Data synthesis and analysis To assess the overall quality and the strength of the evidence per outcome, the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach was used [40, 41]. Two researchers (IJF-A and AIC-V) judged whether these factors were present for each outcome reported at least in two studies. Meta-analysis was conducted for each outcome reported in two or more studies, as long as studies assessed the same outcome with the same functional test and the same measurement unit, that is, HR or OR. Outcomes not included in the meta-analysis were reported using a descriptive quantitative analysis. Thus, the most relevant summary measure with the 95% Confidence Interval (95%CI) for each study was provided. The most relevant summary measure with its 95%CI was extracted of adjusted multivariate models when it was possible. In each meta-analysis it was decided to use the inverse variance as statistical method, fixed effects as analysis model and the HR or OR as effect measures. Heterogeneity was assessed using I2 statistic [42, 43]. Values of > 25% is considered as low heterogeneity, > 50% moderate heterogeneity, and > 75% high heterogeneity [42, 43]. When heterogeneity was moderate or high, random effects were used as analysis model. Moreover, when meta-analyses included patients with HF with reduced (HFrEF) and preserved (HFpEF) ejection fraction or meta-analyses revealed high heterogeneity, as long as the outcome was reported by three or more studies, sensitivity analyses were conducted including studies dealing only with patients with HFrEF because the inclusion of patients with different ejection fraction could be a source of heterogeneity or could bias the results. The mean effect sizes, 95% CI, and I2 were calculated for each outcome and used to create forest plots for visualization of each meta-analysis using the Review Manager (RevMan) version 5.3 [44]. Results Characteristics of included studies A total of 3881 citations were identified through electronic databases, with 263 additional studies identified through Grey Literature Sources and 14 studies identified through manual search. One thousand six hundred seventy-one titles and abstracts were screened and 110 original papers were assessed. The number of studies retrieved from each database and the number of studies excluded in each screening phase are shown in Fig. 1. The full reference of excluded studies in the second stage (n = 66) is reported in Additional file 3. The conflict of interest of included studies is shown in Additional file 4. Of these, 44 observational longitudinal cohort studies (prospective or retrospective) with a total of 22,598 patients with HF were included. Twenty of the included studies (45.45%) reported only patients with HFrEF. Twenty one of the included studies (47.72%) showed patients with HFrEF and HFpEF. The 6MWT was the most used test (n = 33) followed by the Gait Speed test (n = 8) and the SPPB (n = 4). The characteristics of the included observational longitudinal cohort studies are reported in Table 1. Fig. 1 Flow-Diagram. PRISMA 2009. From: Moher D, Liberati A, Tetzlaff J, Altman DG, The PRISMA Group (2009). Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement. PLoS Med 6(6): e1000097. doi:10.1371/journal.pmed1000097. For more information, visit www.prisma-statement.org Table 1 Characteristics of included studies Study (first author and year) Region Setting Design Study Characteristics: Groups, Sample Size (%Male), Age Heart Failure Diagnosis Six Minutes Walking Test (6MWT)  Brenyo et al. [45], 2012. United States, Canada, and Europe Clinical Care Setting (110 Secondary Care Centres) Retrospective High Performance. > 350 m: n = 1021 (82%). 62.5 ± 10.5 years. Low Performance. ≤ 350 m: n = 744 (66.4%). 66.8 ± 10.7 years. HFrEF LVEF < 30% (29 ± 3%)  Ferreira et al. [46], 2019 11 European Countries Clinical Care Setting (69 Secondary Care Centres) Prospective High Performance. > 360 m: n = 537 (86.6%). 62 ± 11.0 years. Middle Performance. 241-360 m: n = 586 (77.3%). 67 ± 12.0 years. Low Performance. ≤ 240 m: n = 591 (63%). 73 ± 10.0 years. HFrEF LVEF = 30% (25–38%)  Wegrzynowska-Teodorczyk et al. [47], 2013. Poland Clinical Care Setting (Secondary Care) Prospective All: n = 243 (100%). 60 ± 11.0 years. High Performance. > 468 m. NS. Low Performance. ≤ 468 m. NS. HFrEF LVEF ≤ 45% (29 ± 8%)  Bittner et al. [48], 1993. United States, Canada, and Belgium Clinical Care Setting (20 Tertiary Care Hospitals) Prospective All: n = 898 (78%). 59 ± 12.0 years. High Performance. ≥ 450: n = 201. NS. Middle Performance. 375–450: n = 215. NS. Low Performance. 300–375: n = 241. NS. Very Low Performance. < 300: n = 176. NS. Congestive HFrEF LVEF ≤ 45%  Arslan et al. [49], 2007. Turkey Not Reported Prospective All: n = 43 (86%). 62 ± 10.0 years. High Performance. > 300 m. NS. Low Performance. ≤ 300 m. NS. HFrEF LVEF ≤ 40% (0.35 ± 0.06%)  Lee et al. [50], 2006. Singapore (Asian) Clinical Care Setting (Primary and Secondary Care) Prospective All: n = 668 (67.4%). 66.1 ± 12.3 years. High Performance. > 370 m: n = 87. NS. Middle Performance. 311-370 m: n = 84. NS. Low Performance. 231-310 m: n = 87. NS. Very Low Performance. 75-230 m: n = 128. NS. HFrEF LVEF < 40%  Curtis et al. [51], 2004. United States and Canada Clinical Care Setting (39 Secondary Care Centres) Prospective High Performance. > 400 m: n = 131 (91.6%). 60.0 ± 11.0 years. Middle Performance. 301-400 m: n = 210 (76.7%). 63.4 ± 10.8 years. Low Performance. 201-300 m: n = 118 (61.9%). 66.8 ± 10.4 years. Very Low Performance. ≤ 200 m: n = 82 (54.9%). 70.9 ± 12.8 years HFrEF and HFpEF LVEF < 45% (HFrEF) LVEF > 45% (HFpEF)  Ingle et al. [52], 2014. United Kingdom Not Reported Prospective All: n = 1667 (75%). 72 (65–77) years. High Performance. > 360 m: n = NS. 64.9 ± 10.6 years. Middle Performance. 241-360 m: n = NS. 71.3 ± 8.8 years. Low Performance. 46-240 m: n = NS. 72.9 ± 9.6 years. Very Low Performance. ≤ 45 m: n = NS. 72.4 ± 10.6 years. HFrEF LVEF < 45%  Alahdab et al. [53], 2009. USA Clinical Care Setting (Tertiary Care Hospital) Prospective High Performance. > 200 m: n = 103 (75.7%). 50.4 ± 12.2 years. Low Performance. ≤ 200 m: n = 95 (49.5%). 59.4 ± 12.2 years. Acute Decompensated HFrEF and HFpEF LVEF ≤ 40% (HFrEF) LVEF > 40% (HFpEF)  Mangla et al. [54], 2013. USA Clinical Care Setting (Secondary Care) Prospective All: n = 900 (53%). 63.6 years. High Performance. > 189 m. NS. Low Performance. ≤ 189 m. NS. HFpEF and HFrEF LVEF ≤ 40% (HFrEF) LVEF > 40% (HFpEF)  Hasin et al. [55], 2012. USA Clinical Care Setting (Secondary Care) Retrospective High Performance. ≥ 300 m: n = 45 (87%). 65 (53–69) years. Low Performance. < 300 m: n = 20 (75%). 68 (59–74) years. HFrEF LVEF < 40% (20–31%)  Passantino et al. [56], 2006. Italy Clinical Care Setting (Secondary Care) Prospective All: n: 476 (79%). 63.6 ± 11.9 years. High Performance. ≥ 300 m: n = 301. NS. Low Performance. < 300 m: n = 175. NS. HFrEF LVEF < 40% (29.8 ± 9.7)  Howie-Esquivel et al. [57], 2008. USA An Academic Medical Centre Prospective High Performance. > 200 m: n = 21 (73.3%). 61.7 ± 17.3 years. Low Performance. ≤ 200 m: n = 23 (26.7%). 57.6 ± 20.0 years. Descompensated HFpEF and HFrEF LVEF < 40% (HFrEF) LVEF ≥ 40% (HFpEF)  Zotter-Tufaro et al. [58], 2015. Austria Not Reported Prospective High Performance. > 300 m: n = 72 (31.95%). 67.8 ± 9.1 years. Low Performance. ≤ 300 m: n = 70 (28.6%). 73.1 ± 7.4 years. HFpEF LVEF ≥ 50%  Boxer et al. [59], 2010. USA University of Connecticut Health Centre Prospective All: n = 60 (71.66%). 78 ± 12.0 years. High Performance. > 300 m. NS. Low Performance. ≤ 300 m. NS. HFrEF LVEF ≤ 40%  Ingle et al. [60], 2014 United Kingdom Not Reported Prospective All: n = 600 (75%). 77.8 (71.5–83.6) years. High Performance. >  365 m. n = NS. Middle Performance. 271–365 m. n = NS. Low Performance. 61–270 m. n = NS. Very Low Performance. <  60 m. n = NS. HFrEF LVEF < 45%  Guazzi et al. [61], 2009. Italy Clinical Care Setting (Secondary Care) Prospective All: n = 253 (78.66%). 61.9 ± 10.1 years. High Performance. >  300 m. n = 175. NS. Low Performance. ≤ 300 m. n = 78. NS HFpEF and HFrEF LVEF < 50% (HFrEF) LVEF ≥ 50% (HFpEF)  McCabe et al. [62], 2017. USA An University Hospital Prospective All: n = 71 (57.7%). 52.6 ± 12.3 years. High Performance. >  300 m. NS. Low Performance. ≤ 300 m. NS. HFpEF and HFrEF LVEF = 24.4 ± 13.5  Vegh et al. [63], 2014. USA Clinical Care Setting (Secondary Care) Prospective All: n = 164 (77%). 67.3 ± 12.9 years. High Performance. ≥ 350 m. NS. Middle Performance. 280-350 m. NS. Low Performance. <  280 m. NS. HFrEF LVEF = 25% ± 7%.  Roul et al. [64], 1998. France Not Reported Prospective All: n = 121 (81.8%). 59 ± 11 years. High Performance. >  300 m. NS. Low Performance. ≤ 300 m. NS. HFrEF LVEF = 29.6% ± 13%  Frankenstein et al. [65], 2008. Germany Specialised HF clinic at the University of Heidelberg Prospective All: n = 1035 (80.2%) 54.9 ± 11.5 years. Mean 6MWT: 459 m ± 113 m HFrEF LVEF ≤ 40%  Mene-Afejuku et al. [66], 2017. Nigeria Not Reported Prospective All: n = 100 (NS). 64.02 ± 12.88 years. High Performance. 314.66 m ± 48.17 m. n = 59 (NS). 66.32 ± 12.29 years. Low Performance. 260.59 m ± 66.65 m. n = 41 (NS). 61.71 ± 13.46 years. HHF (HFrEF and HFpEF) LVEF ≤ 40% (HFrEF) LVEF > 40% (HFpEF)  Ingle et al. [67], 2007 United Kingdom Not Reported Prospective All: n = 1592 (60%). 74 (67–80) years. High Performance. ≥ 421 m. NS. Middle Performance. 346–420 m. NS. Low Performance. 241–345 m. NS. Very Low Performance. ≥ 240 m. NS. HFrEF LVEF ≤ 45%  Rostagno et al. [68], 2003. Italy Clinical Care Setting (Secondary Care) Prospective All: n = 214 (93%). 53.7 (29–70) years. High Performance. ≥ 450 m. NS. Middle Performance. 300–450 m. NS. Low Performance. <  300 m. NS. Congestive HFpEF and HFrEF LVEF < 50% (HFrEF) LVEF ≥ 50% (HFpEF)  Cahalin et al. [69], 1996. USA Clinical Care Setting (Secondary Care) Prospective All: n = 45 (89%). 49 ± 8 years. High Performance. ≥ 300 m. NS. Low Performance. <  300 m. NS. HFrEF LVEF = 20 ± 6  Frankenstein et al. [70], 2008. Germany Specialised HF clinic at the University of Heidelberg Prospective All: n = 1069 (80.6%) 55.2 ± 11.7 years. Mean 6MWT: 456 m ± 114 m HFrEF LVEF = 29% ± 10%  Rubim et al. [71], 2006. Brazil Clinical Care Setting (Secondary Care) Prospective All: n = 176 (67%). 58.32 ± 12.7 years. Mean 6MWT: 521.11 m ± 76.1 m. High Performance. ≥ 520 m. NS. Low Performance. <  520 m. NS. HFpEF and HFrEF LVEF = 34.91% ± 12.4%  Kanagala et al. [72], 2019. United Kingdom Clinical Care Setting (Tertiary Care Hospital) Prospective All: n = 140 (49%). 73 ± 9.0 years. Mean 6MWT: 180 m (120 m–250 m) HFpEF and HFrEF LVEF > 50%  Zugck et al. [73], 2001. Germany Medical Clinic of the University of Heidelberg Prospective All: n = 208 (82%). 54 ± 10 years. Mean 6MWT: 455 m ± 107 m (170 m–692 m) HFrEF LVEF ≤ 40% Cahalin et al. [74], 2013. Italy Clinical Care Setting (Secondary Care) Prospective All: n = 258 (NS). 63 ± 8.7 years. High Performance. >  300 m. NS. Low Performance. ≤ 300 m. NS. HFpEF and HFrEF LVEF < 50% (HFrEF) LVEF ≥5 0% (HFpEF)  Reibis et al. [75], 2010. Germany Clinical Care Setting (Secondary Care) Prospective All: n = 1346 (73%). 64 ± 10 years. Mean 6MWT: 350.1 m ± 148.6 m HFrEF LVEF < 45%  Castel et al. [76], 2009. Spain Not Reported Retrospective All: n = 155 (82%). 68.6 ± 7.8 years. High Performance. >  400 m. NS. Middle Performance. 310-400 m. NS. Low Performance. 225-310 m. NS. Very Low Performance. <  225 m. NS. HFrEF LVEF ≤ 45%  Kamiya et al. [77], 2017. Japan Clinical Care Setting (Secondary Care Centre) Retrospective All: n = 1474 (68%). 72.2 ± 7.1 years. High Performance. ≥ 446 m: n = 485 (84%). 68.5 ± 5.6 years. Middle Performance. 342-445 m: n = 497 (69%). 71.5 ± 6.3 years. Low Performance. ≤ 341 m: n = 492 (52%). 76.5 ± 7.0 years. HFpEF and HFrEF LVEF = 52.7 ± 15.4 Short Physical Performance Battery (SPPB)  García et al. [78], 2019. Spain Clinical Care Setting (Secondary Care) Prospective High Performance. SPPB > 7: n = 37 (54.1%). 83 ± 5.7 years. Low Performance. SPPB≤ 7: n = 49 (30.6%). 86 ± 6.7 years. Acute HF  Hornsby et al. [79], 2019. USA University of Michigan Prospective High Performance. SPPB≥ 10 points: n = 22 (55%). 64 ± 13.0 years. Middle Performance. SPPB = 7–9 points: n = 53 (42%). 67 ± 12.0 years. Low Performance. SPPB≤ 6 points: n = 39 (36%). 72 ± 13.0 years. HFpEF HF LVEF ≥ 50%  Chiarantini et al. [80], 2010. Italy Clinical Care Setting (Secondary Care) Prospective All: n = 157 (50.3%). 80 ± 0.5 years. High Performance. SPPB = 9–12: n = 32. NS. Middle Performance. SPPB = 5–8: n = 45. NS. Low Performance. SPPB = 1–4: n = 33. NS. Very Low Performance. SPPB = 0: n = 47. NS. Descompensated HFrEF and HFpEF LVEF < 45% (HFrEF) LVEF ≥ 45% (HFpEF)  Zaharias et al. [81], 2014. USA Clinical Care Setting (Secondary Care) Prospective All: n = 32 (78.1%). 58.2 ± 13.6 years. High Performance. SPPB = 10–12: n = 7. NS. Middle Performance. SPPB = 7–9: n = 8. NS. Low Performance. SPPB = 4–6: n = 12. NS. Very Low Performance. SPPB = 0–3: n = 4. NS. HFrEF and HFpEF LVEF < 40% (HFrEF) LVEF ≥ 40% (HFpEF) Gait Speed (GS)  Lo et al. [82], 2015. USA Community Based Population Prospective High Performance. GS ≥ 0.8 m/s: n = 553 (59%). 73 ± 5.0 years. Low Performance. GS < 0.8 m/s: n = 566 (39%). 76 ± 6.0 years. HFpEF and HFrEF LVEF < 45% (HFrEF) LVEF ≥ 45% (HFpEF)  Pulignano et al. [83], 2016. Italy Clinical Care Setting (7 Secondary Care Centres) Prospective High Performance. GS ≥ 1.0 m/s: n = 88 (64.8%). 76.4 ± 4.8 years. Middle Performance. GS = 0.66–0.99 m/s: n = 128 (60.9%). 77.1 ± 4.7 years Low Performance. GS ≤ 0.65 m/s: n = 115 (48.7%). 80.2 ± 5.6 years. HFpEF and HFrEF LVEF < 45% (HFrEF) LVEF ≥ 45% (HFpEF)  Chaudhry et al. [84], 2013. USA Not Reported Prospective All: n = 758 (49.5%). 79.7 ± 6.2 years. High Performance. GS > 0.8 m/s: n = 441. NS. Low Performance. GS ≤ 0.8 m/s: n = 317. NS. HFpEF and HFrEF LVEF < 45% (HFrEF) LVEF ≥ 45% (HFpEF)  Tanaka et al. [85], 2018. Japan Kitasato University Hospital Retrospective All: n = 603 (62.7%). 74.9 ± 6.2 years. High Performance. GS > 1.14 m/s: n = 154. NS. Middle Performance. GS = 1.0–1.14 m/s. n = 149. NS. Low Performance. GS = 0.82–0.99 m/s. n = 150. NS. Very Low Performance. GS < 0.82 m/s: n = 150. NS. Acute HFpEF and HFrEF LVEF < 40% (HFrEF) LVEF ≥ 40% (HFpEF)  Tanaka et al. [86], 2019. Japan Kitasato University Hospital Retrospective High Performance. GS ≥ 0.8 m/s: n = 194 (72.7%). 73.1 ± 6.7 years. Low Performance. GS < 0.8 m/s: n = 194 (44.8%). 76.5 ± 8.4 years. Acute HFpEF and HFrEF LVEF < 40% (HFrEF) LVEF ≥ 40% (HFpEF)  Rodríguez-Pascual et al. [87], 2017. Spain Clinical Care Setting (6 Secondary Care Centres) Prospective High Performance. GS ≥ 0.65 m/s: n = 211 (47.9%). 84.4 ± 9.4 years. Low Performance. GS < 0.65 m/s: n = 286 (32.5%). 85.7 ± 5.1 years. HFpEF and HFrEF LVEF ≤ 45% (HFrEF) LVEF > 45% (HFpEF)  Vidán et al. [88], 2016. Spain Clinical Care Setting (Secondary Care Centre) Prospective All: n = 416 (50.5%). 80.0 ± 6.1 years. High Performance. GS ≥ 0.65 m/s. NS. Low Performance. GS < 0.65 m/s. NS. HFpEF and HFrEF LVEF < 50% (HFrEF) LVEF ≥ 45% (HFpEF) LVEF = 43.4% ± 14.7%  Kamiya et al. [77], 2017. Japan Clinical Care Setting (Secondary Care Centre) Retrospective All: n = 1474 (68%). 72.2 ± 7.1 years. High Performance. GS ≥ 1.17 m/s: n = 489 (82%). 68.7 ± 5.5 years. Middle Performance. GS = 0.95–1.160 m/s: n = 489 (67%). 71.8 ± 6.6 years. Low Performance. GS ≥ 0.94 m/s: n = 496 (55%). 76.1 ± 7.2 years. HFpEF and HFrEF LVEF = 52.7 ± 15.4 m Meters. HF Heart Failure. LVEF Left Ventricular Ejection Fraction. NS Not Specified. HFrEF Patients with Heart Failure with Reduced Ejection Fraction (Systolic Heart Failure). HFpEF Patients with Heart Failure with Preserved Ejection Fraction (Diastolic Heart Failure). HHF Hypertensive Heart Failure. SPPB Short Physical Performance Battery. GS Gait Speed Meta-analyses The outcomes assessed by each study, as well as the main results, the risk of bias summary and the GRADE summary are shown in Table 2. Forest plots and effect sizes of each meta-analysis can also be seen in Additional file 5. Table 2 Outcomes, Results, Risk of Bias of Included Studies and Level of Evidence per Outcome according to GRADE Criteria Study (first author and year) Functional Test Follow-Up Outcomes Main Results Risk of Bias Level of Evidence (GRADE)  Brenyo et al. [45], 2012. 6MWT 4 years Incident HF and Mortality ≤ 350 m VS > 350 m HR = 1.73 95%CI [1.29–2.33]*** Low Not Reported Incident HF and Mortality Per 100-m decreased HR = 1.25 95%CI [1.09–1.44]*** All-Cause Mortality ≤ 350 m VS > 350 m HR = 2.40 95%CI [1.42–4.08]*** Moderate All-Cause Mortality Per 100-m decreased HR = 1.32 95%CI [1.05–1.66]**  Ferreira et al. [46], 2019. 6MWT 21 months (9–26 months) Hospitalisation and Mortality 241-360 m VS > 360 m HR = 1.44 95%CI [1.14–1.80]** Moderate Low Hospitalisation and Mortality ≤ 240 m VS > 360 m HR = 1.73 95%CI [1.38–2.18]*** Hospitalisation and Mortality Per each 50 m decreased HR = 1.08 95%CI [1.04–1.11]*** All-Cause Mortality 241-360 m VS > 360 m HR = 1.49 95%CI [1.08–2.06]** Moderate All-Cause Mortality ≤ 240 m VS > 360 m HR = 2.41 95%CI [1.76–3.29]*** All-Cause Mortality Per each 50 m decreased HR = 1.14 95%CI [1.09–1.18]***  Wegrzynowska-Teodorczyk et al. [47], 2013. 6MWT 1 year HF Mortality ≤ 468 m VS > 468 m HR = 3.22 95%CI [1.17–8.86]** Low Moderate Hospitalisation and Mortality ≤ 468 m VS > 468 m HR = 2.77 95%CI [1.30–5.88]** Low 3 years HF Mortality ≤ 468 m VS > 468 m HR = 2.18 95%CI [1.18–4.03]** Moderate Hospitalisation and Mortality ≤ 468 m VS > 468 m HR = 1.71 95%CI [1.08–2.72]** Low  Bittner et al. [48], 1993. 6MWT 1 year (242 ± 82 days) All-Cause Mortality Per each 120 m decreased OR = 1.50 95%CI [1.11–2.03]** Low Moderate HF Hospitalisation Per each 120 m decreased OR = 2.60 95%CI [1.78–3.80]*** Low Hospitalisation and Mortality Per each 120 m decreased OR = 1.77 95%CI [1.38–2.26]*** Low All-Cause Mortality <  300 m VS ≥ 450 m OR = 3.7 95%CI [1.44–9.55]** Moderate All-Cause Mortality 300-375 m VS ≥ 450 m OR = 2.78 95%CI [1.09–7.11]** All-Cause Mortality 375-450 m VS ≥ 450 m OR = 1.42 95%CI [0.50–4.06]* All-Cause Hospitalisation <  300 m VS ≥ 450 m OR = 14.02 95%CI [4.90–40.14]*** Low All-Cause Hospitalisation 300-375 m VS ≥ 450 m OR = 6.21 95%CI [2.14–18.08]*** All-Cause Hospitalisation 375-450 m VS ≥ 450 m OR = 1.90 95%CI [0.56–6.42]*  Arslan et al. [49], 2007. 6MWT 2 years (18 ± 6 months) HF Mortality ≤ 300 m VS >  300 m HR = 2.38 95%CI [2.02–5.76]** Moderate Moderate  Lee et al. [50], 2006. 6MWT 36 ± 12 months Hospitalisation and Mortality 75-230 m VS > 370 m. OR = 3.5 95%CI [1.1–11.7]** Low Low Hospitalisation and Mortality 231-310 m VS > 370 m OR = 3.4 95%CI [1.01–11.5]** Hospitalisation and Mortality 311-370 m VS > 370 m OR = 4.9 95%CI [1.5–16.0]**  Curtis et al. [51], 2004. 6MWT 32 months All-Cause Mortality ≤ 200 m VS > 400 m HR = 1.59 95%CI [0.88–2.86]* Low Moderate All-Cause Mortality 201-300 m VS > 400 m HR = 1.01 95%CI [0.57–1.79]* All-Cause Mortality 301-400 m VS > 400 m HR = 1.16 95%CI [0.72–1.88]* HF Mortality ≤ 200 m VS > 400 m HR = 2.62 95%CI [1.02–6.74]** Moderate HF Mortality 201-300 m VS > 400 m HR = 0.93 95%CI [0.34–2.55]* HF Mortality 301-400 m VS > 400 m HR = 0.86 95%CI [0.35–2.09]* All-Cause Hospitalisation ≤ 200 m VS > 400 m HR = 1.76 95%CI [1.19–2.60]** Low All-Cause Hospitalisation 201-300 m VS > 400 m HR = 1.41 95%CI [1.01–1.99]** All-Cause Hospitalisation 301-400 m VS > 400 m HR = 1.09 95%CI [0.80–1.47]* HF Hospitalisation ≤ 200 m VS > 400 m HR = 1.84 95%CI [0.97–3.49]* Low HF Hospitalisation 201-300 m VS > 400 m HR = 1.84 95%CI [1.04–3.29]** HF Hospitalisation 301-400 m VS > 400 m HR = 1.45 95%CI [0.85–2.45]*  Ingle et al. [52], 2014. 6MWT 5 years All-Cause Mortality Per each 10 m increased. HR = 0.980 95%CI [0.974–0.985]*** Low Moderate  Alahdab et al. [53], 2009. 6MWT 40 months-Mortality All-Cause Mortality ≤ 200 m VS >  200 m HR = 2.14 95%CI [1.20–3.81]** Low Moderate 40 months-Mortality All-Cause Mortality Per each 1 m increased HR = 0.998 95%CI [0.995–0.999]** 18 months-Hospitali- zation HF Hospitalisation ≤ 200 m VS >  200 m HR = 1.62 95%CI [1.10–2.39]** Low  Mangla et al. [54], 2013. 6MWT 1080 days Hospitalisation and Mortality ≤ 189 m VS > 189 m in HFpEF. OR = 2.81 95%CI [1.24–6.40]** Low Low Hospitalisation and Mortality ≤ 189 m VS > 189 m in HFrEF. OR = 1.94 95%CI [1.30–2.90]**  Hasin et al. [55], 2012. 6MWT Median 592 days (115–1453 days) All-Cause Mortality Per 10 m walked short of 300 m HR = 1.211 95% CI [1.108–1.322]*** Moderate Moderate  Passantino et al. [56], 2006. 6MWT 23.9 months All-Cause Mortality <  300 m VS ≥ 300 m HR = 2.66 95%CI [1.60–4.42]*** Low Moderate All-Cause Mortality Per each 70 m decreased HR = 2.03 95%CI [1.29–3.18]** Howie-Esquivel et al. [57], 2008. 6MWT 90 days HF Hospitalisation > 200 m HR = 0.99 95%CI [0.99–1.00]* High Low  Zotter-Tufaro et al. [58], 2015. 6MWT 14.0 ± 10.0 months Hospitalisation and Mortality >  300 m VS ≤ 300 m HR = 0.992 95%CI [0.990–0.995]*** Moderate Low  Boxer et al. [59], 2010. 6MWT 4 years All-Cause Mortality Per each 30 m increased HR = 0.84 95%CI [0.74–0.94]** Moderate Moderate  Ingle et al. [60], 2014. 6MWT 8 years All-Cause Mortality Per each 10 m increased HR = 0.988 95%CI [0.981–0.995]*** Low Moderate  Guazzi et al. [61], 2009. 6MWT 20.4 ± 16.6 months. Cardiac Mortality Per each 1 m increased HR = 0.998 95%CI [0.995–1.001]* Low Moderate  McCabe et al. [62], 2017. 6MWT 30 days HF Hospitalisation Per each 30 m increased OR = 0.84 95% CI [0.71–0.99]** Moderate Low  Vegh et al. [63], 2014. 6MWT 3 years HF Hospitalisation ≥ 350 m VS < 280 m HR = 0.61 95% CI [0.44–0.85]** Moderate Low Hospitalisation and Mortality ≥ 350 m VS < 280 m HR = 0.58 95% CI [0.43–0.80]*** Low HF Hospitalisation ≥ 402 m VS < 256 m HR = 0.60 95% CI [0.44–0.82]*** Low Hospitalisation and Mortality ≥ 402 m VS < 256 m HR = 0.55 95% CI [0.43–0.75]*** Low  Roul et al. [64], 1998. 6MWT 1000 days Hospitalisation and Mortality ≤ 300 m VS > 300 m Log rank = 6.16 ** Moderate Low  Frankenstein et al. [65], 2008. 6MWT 52.9 ± 36.2 months All-Cause Mortality Per each 1 m increased HR = 0.996 95% CI [0.995–0.997]*** Low Moderate  Mene-Afejuku et al. [66], 2017. 6MWT 6 months Hospitalisation and Mortality 314.66 m ± 48.17 m VS 260.59 m ± 66.65 m OR = 0.819 95% CI [0.206–3.257]* Moderate Low  Ingle et al. [67], 2007. 6MWT 36.6 months (28.2–45.0 months) All-Cause Mortality Per each 1 m increased HR = 0.998 95% CI [0.996–1.000]* Low Moderate  Rostagno et al. [68], 2003. 6MWT 34 months All-Cause Mortality Per each 1 m increased HR = 0.995 95% CI [0.993–0.997]*** Low Moderate  Cahalin et al. [69], 1996. 6MWT 62 ± 45 weeks (1–183 weeks) Hospitalisation and Mortality <  300 m VS ≥ 300 m X2 = 40% vs 12% ** Moderate Low  Frankenstein et al. [70], 2008. 6MWT 42 months (22–80 months) All-Cause Mortality Per each 1 m increased HR = 0.996 95% CI [0.995–0.997]** Moderate Moderate  Rubim et al. [71], 2006. 6MWT 18 months (12–24 months) All-Cause Mortality ≥ 520 m VS < 520 m OR = −0.0081 95% CI [0.0029–0.0133]*** Low Moderate  Kanagala et al. [72], 2019. 6MWT 1429 days (1157–1657 days) Hospitalisation and Mortality Per each 1 m increased HR = 0.659 95% CI [0.465–0.934]** Low Low  Zugck et al. [73], 2001. 6MWT 28.3 ± 14.1 months All-Cause Mortality Per each 1 m increased HR = 0.99 95% CI [0.98–0.99]** Moderate Moderate  Cahalin et al. [74], 2013. 6MWT 22.8 ± 22.1 months Cardiac Mortality Per each 1 m increased HR = 0.99 95% CI [0.99–0.99]** Low Moderate Cardiac Mortality >  300 m VS ≤ 300 m HR = 0.18 95% CI [0.04–0.89]**  Reibis et al. [75], 2010. 6MWT 731 ± 215 days All-Cause Mortality Per each 50 m increasd HR = 0.93 95% CI [0.86–1.00]** Low Moderate  Castel et al. [76], 2009. 6MWT 24.4 ± 18.1 months Cardiac Mortality <  225 m VS > 400 m HR = 5.60 95% CI [1.23–25.30]** Low Moderate Cardiac Mortality 225-310 m VS > 400 m HR = 1.28 95% CI [0.23–7.08]* Cardiac Mortality 310-400 m VS > 400 m HR = 4.10 95% CI [0.79–21.52]*  Kamiya et al. [77], 2017. 6MWT 2.3 ± 1.9 years All-Cause Mortality Per each 10 m increased HR = 0.96 95% CI [0.94–0.97]*** Low Moderate  García et al. [78], 2019. SPPB 1 year HF Hospitalisation SPPB ≤ 7 VS SPPB > 7 OR = 6.7 95%CI [1.5–30.4]** Moderate Not Reported All-Cause Mortality SPPB ≤ 7 VS SPPB > 7 OR = 1.2 95%CI [0.3–5.4]* Very Low Hospitalisation and Mortality SPPB ≤ 7 VS SPPB > 7 OR = 3.6 95%CI [1.0–12.9]** Very Low  Hornsby et al. [79], 2019. SPPB 6 months Hospitalisation and Mortality Per 1-unit change in SPPB OR = 0.81 95%CI [0.69–0.94]** Moderate Very Low Number of All-Cause Hospitalisations Per 1-unit change in SPPB IRR = 0.92 95%CI [0.86–0.97]** Not Reported Days Hospitalized or Dead Per 1-unit change in SPPB IRR = 0.85 95%CI [0.73–0.99]** Not Reported  Chiarantini et al. [80], 2010. SPPB 30 months (median 444 days) All-Cause Mortality SPPB 0 VS SPPB 9–12 HR = 6.06 95%CI [2.19–16.76]*** Moderate Very Low All-Cause Mortality SPPB 1–4 VS SPPB 9–12 HR = 4.78 95%CI [1.63–14.02]** All-Cause Mortality SPPB 5–8 VS SPPB 9–12 HR = 1.95 95%CI [0.67–5.70]*  Zaharias et al. [81], 2014. SPPB 3 months Hospitalisation and Mortality Per each 1 point decreased HR = 1.042 95%CI [0.89–1.23]* Moderate Very Low  Lo et al. [82], 2015. Gait Speed 10 years All-Cause Mortality < 0.8 m/s VS ≥ 0.8 m/s HR = 1.37 95%CI [1.10–1.70]** Low Low  Pulignano et al. [83], 2016. Gait Speed 1 year All-Cause Mortality Gait speed (tertiles) HR = 0.620 95%CI [0.434–0.884]** Low Low HF Hospitalisation Gait speed (tertiles) OR = 0.697 95%CI [0.547–0.899]** Low All-Cause Hospitalisation Gait speed (tertiles) HR = 0.741 95%CI [0.613–0.895]** Low  Chaudhry et al. [84], 2013. Gait Speed 20 years All-Cause Hospitalisation ≤ 0.8 m/s VS > 0.8 m/s HR = 1.28 95%CI [1.06–1.55]** Low Low Hospitalisation and Mortality ≤ 0.8 m/s VS > 0.8 m/s HR = 1.31 95%CI [1.08–1.58]** Low  Tanaka et al. [85], 2018. Gait Speed 1.7 ± 0.5 years All-Cause Mortality 1.0–1.14 m/s VS > 1.14 m/s HR = 0.80 95%CI [0.37–1.74]* Moderate Low All-Cause Mortality 0.82–0.99 m/s VS > 1.14 m/s HR = 1.46 95%CI [0.75–2.83]* All-Cause Mortality < 0.82 m/s VS > 1.14 m/s HR = 2.65 95%CI [1.35–5.20]**  Tanaka et al. [86], 2019. Gait Speed 2.1 ± 1.9 years All-Cause Mortality Per each 0.1 m/s increased HR = 0.83 95% CI [0.73–0.95]** Low Low HF Hospitalisation Per each 0.1 m/s increased HR = 0.91 95% CI [0.83–0.99]** Low Hospitalisation and Mortality Per each 0.1 m/s increased HR = 0.90 95% CI [0.83–0.97]** Low  Rodríguez-Pascual et al. [87], 2017. Gait Speed 1 year All-Cause Mortality GS < 0.65 m/s VS GS ≥ 0.65 m/s HR = 1.86 95% CI [0.95–3.65]* Low Low All-Cause Hospitalisation GS < 0.65 m/s VS GS ≥ 0.65 m/s HR = 1.57 95% CI [0.98–2.52]* Low  Vidán et al. [88], 2016. Gait Speed 1 year All-Cause Mortality GS < 0.65 m/s VS GS ≥ 0.65 m/s HR = 1.48 95% CI [0.95–2.32]* Low Low All-Cause Hospitalisation GS < 0.65 m/s VS GS ≥ 0.65 m/s OR = 1.67 95% CI [0.98–2.85]* Low  Kamiya et al. [77], 2017. Gait Speed 2.3 ± 1.9 years All-Cause Mortality Per each 0.1 m/s increased HR = 0.87 95% CI [0.81–0.93]*** Low Low 6MWT Six Minutes Walking Test. m Meters. HF Heart Failure. HR Hazard Ratio. CI Confidence Interval. OR: Odds Ratio. X2: Chi-square test. HFrEF Patients with Heart Failure with Reduced Ejection Fraction (Systolic Heart Failure). HFpEF Patients with Heart Failure with Preserved Ejection Fraction (Diastolic Heart Failure). SPPB Short Physical Performance Battery. GS Gait Speed. IRR Incidence Rate Ratio. * p > 0.05. ** p < 0.05. *** p < 0.001 Patients with HFrEF, HFpEF and acute HF who showed a poor physical functional performance in the 6MWT reported a larger risk of All-Cause of Mortality [HR = 2.29 95%CI (1.86–2.82), p <  0.001] than those patients who showed a good physical functional performance (Fig. 2a). Moreover, patients with HFrEF who decreased the meters (m) they walked in the 6MWT during follow-up showed larger risk of All-Cause of Mortality [HR = 1.22 95%CI (1.10–1.36), p <  0.001], although there was no lower risk of All-Cause of Mortality between patients with HFrEF, patients with HFpEF and patients with acute HF who increased the meters they walked in the 6MWT during follow-up (Additional file 5). Patients with HFrEF and HFpEF who showed a poor physical functional performance in the 6MWT also reported a larger risk of HF Mortality [HR = 2.39 95%CI (2.21–2.59), p <  0.001] than those patients who showed a good physical functional performance (Fig. 2b). Patients with HFrEF who showed a poor physical functional performance in the 6MWT also reported a larger risk of the combined endpoint of Hospitalisation and Mortality for any cause [HR = 1.80 95%CI (1.45–2.23), p <  0.001] or [OR = 2.07 95%CI (1.41–3.02), p < 0.001] than those patients who showed a good physical functional performance (Fig. 2c and Fig. 2d, respectively). Furthermore, patients with HFrEF, HFpEF and acute HF who showed a poor physical functional performance in the 6MWT reported a larger risk of HF Hospitalisation [HR = 1.68 95%CI (1.20–2.33), p = 0.002] than those patients who showed a good physical functional performance (Additional file 5). On the other hand, patients with HFrEF, HFpEF and acute HF who showed a slower gait speed reported a larger risk of All-Cause of Mortality [HR = 1.49 95%CI (1.24–1.79), p < 0.001] than those patients who showed a faster gait speed (Fig. 3), above all, when gait speed was slower than 0.65 m/s [HR = 1.59 95%CI (1.10–2.30), p = 0.01] (Additional file 5). Moreover, patients with HFrEF, HFpEF and acute HF who increased their gait speed during follow-up showed a lower risk of All-Cause of Mortality [HR = 0.85 95%CI (0.81–0.91) (Additional file 5). Patients with HFrEF and HFpEF who showed a slower gait speed (< 0.80 m/s) also reported a larger risk of All-Cause of Hospitalisation [HR = 1.32 95%CI (1.10–1.57), p = 0.002] than patients with a faster gait speed (> 0.80 m/s) (Additional file 5). Fig. 2 Forest Plots ilustrating the risk of All-Cause Mortality (a), the risk of HF Mortality (b) and the risk of the combined endpoint of Hospitalisation and Mortality for any cause (c and d) in the 6MWT. Patients with Poor Physical Functional Performance Versus Patients with Good Physical Functional Performance Fig. 3 Forest Plot ilustrating the risk of All-Cause Mortality in the Gait Speed Test. Patients with slower Gait Speed Versus Patients with faster Gait Speed Sensitivity analyses The risk of All-Cause of Mortality in the 6MWT was larger when only patients with HFrEF and poor physical functional performance were assessed [HR = 2.46 95%CI (1.94–3.12), p < 0.001] (Additional file 6). However, the risk of HF Mortality [HR = 2.39 95%CI (2.21–2.58), p < 0.001] as well as the risk of All-Cause of Mortality in the 6MWT per increased units did not change when only patients with HFrEF were assessed (Additional file 6). Descriptive quantitative analysis Physical functional performance and mortality A score between 1 and 4 points on the SPPB was associated with a larger risk of All-Cause of Mortality (HR = 4.78 95%CI [1.63–14.02, p < 0.05]) in patients with HFrEF and HFpEF [80], while a score below 7 points on the SPPB was not associated with a larger risk of All-Cause of Mortality in patients with acute HF [78]. Physical functional performance and the combined endpoint of hospitalisation and mortality A score below 7 points on the SPPB was associated with a larger risk of the combined endpoint of hospitalisation and mortality for any cause (OR = 3.6 95%CI [1.0–12.9, p < 0.05]) in patients with acute HF [78]. However, per each 1-unit improved in SPPB the risk of the combined endpoint of hospitalisation and mortality for any cause could be reduced OR = 0.81 95%CI [0.69–0.94, p < 0.05] in patients with HFpEF [79]. Patients with HFrEF and HFpEF with a gait speed slower than 0.8 m/s also showed a larger risk of the combined endpoint of hospitalisation and mortality for any cause (HR = 1.31 95%CI [1.08–1.58, p < 0.05]) [84]. Physical functional performance and hospitalisation Patients with HFrEF with poor physical performance in the 6MWT showed a larger risk of All-Cause of Hospitalisation [OR = 14.02 95%CI (4.90–40.14), p = 0.001] [48] as patients with HFrEF and HFpEF [HR = 1.41 95%CI (1.01–1.99), p < 0.05] [51]. A score below 7 points on the SPPB was also associated with a larger risk of HF Hospitalisation (OR = 6.7 95%CI [1.5–30.4, p < 0.05]) in patients with acute HF [78]. Risk of Bias assessment The risk of bias of included observational longitudinal cohort studies is shown in Table 3. In summary, 26 studies (59.10%) reported a low risk of bias, and 17 studies (38,63%) showed a moderate risk of bias. Selection bias (97,72%) were usual across the included studies. Using GRADE criteria, observational longitudinal cohort studies reported a low evidence in most of the prognostic outcomes. However, HF mortality and all-cause mortality showed a moderate evidence in the 6-MWT (Table 4). Table 3 Risk of Bias Assessment of Cohort Studies (The Newcastle Ottawa Scale (NOS)). Note: The NOS assigns up to a maximum of nine points for the least risk of bias based on 3 domains: selection of study groups (four points); comparability of groups (two points); and ascertainment of exposure and outcomes (three points). This checklist has been recommended for cohort studies. The risk of bias based on the NOS was classified as: Low Risk of Bias (7–9 points), Moderate Risk of Bias (4–6 points) and High Risk of Bias (0–3 points). Abbreviations: Quality: High Risk of Bias (H); Moderate Risk of Bias (M); Low Risk of Bias (L); NOTE. Newcastle-Ottawa Quality Assessment Scale: cohort studies: 1 = Representativeness of the exposed cohort; 2 = Selection of the non-exposed cohort; 3 = Ascertainment of exposure; 4 = Demonstration that outcome of interest was not present at start of study; 5–6 = Comparability of cohorts on the basis of the design or analysis; 7 = Assessment of outcome; 8 = Was follow-up long enough for outcomes to occur; 9 = Adequacy of follow-up of cohorts Table 4 Summary of Findings and Quality of Evidence Assessment of Included Observational Longitudinal Cohort Studies (GRADE) Summary of findings Quality of evidence assessment (GRADE) Outcomes N° studies N° participants Designa Risk of Biasb Inconsistencyc Indirectness d Imprecisione Other f Level of Evidence Importance Six Minutes Walking Test (6-MWT)  All-Cause Mortality 18 15,033 Observational NO Consistency (+ 1) NO NO NO Moderate Critical  All-Cause Hospitalisation 2 1374 Observational NO Not Serious NO NO NO Low Critical  HF Mortality 6 1493 Observational NO Consistency (+ 1) NO NO NO Moderate Critical  HF Hospitalisation 6 1851 Observational Not Serious Not Serious NO Not Serious NO Low Critical  Hospitalisation and Mortality 11 4788 Observational Serious (−1) Consistency (+ 1) Not Serious NO NO Low Critical Short Physical Performance Battery (SPPB)  All-Cause Mortality 2 243 Observational Very Serious (−2) Serious (−1) Not Serious Serious (−1) NO Very Low Critical  Hospitalisation and Mortality 3 231 Observational Serious (−1) Not Serious Not Serious Not Serious NO Very Low Critical Gait Speed  All-Cause Mortality 7 4828 Observational NO Not Serious NO Not Serious NO Low Critical  All-Cause Hospitalisation 4 2002 Observational NO Not Serious NO Not Serious NO Low Critical  HF Hospitalisation 2 719 Observational NO Not Serious NO Not Serious NO Low Critical  Hospitalisation and Mortality 2 1146 Observational NO Not Serious NO Not Serious NO Low Critical In brief, the GRADE classification was carried out according to the presence, or not, of the following identified factors: (1) study design, (2) risk of bias, (3) inconsistency of results (4) indirectness (5) imprecision, and (6) other considerations (e.g. reporting bias). The quality of the evidence based on the GRADE criteria was classified as: (1) high (further research is unlikely to change our confidence in the estimate of effect and there are no known or suspected reporting bias); (2) moderate (further research is likely to have an important effect on our confidence in the estimate of effect and could change the estimate); (3) low (further research is likely to have an important effect on our confidence in the estimate of effect and is likely to change the estimate); or (4) very low (we are uncertain about the estimate) [38] a Design: Observational Longitudinal Cohort Studies show a Low Level of Evidence according to GRADE b Risk Of Bias: > 50% (NO) of the information is from studies with low risk of bias which rarely can affect the interpretation of results. 50% (Not Serious) of the information is from studies with moderate risk of bias which could affect the interpretation of results, and 50% of the information is from studies with low risk of bias. > 50% (Serious) or > 75% (Very Serious) of the information is from studies with high/moderate risk of bias which sufficiently can affect the interpretation of results c Inconsistency: > 50% (Consistency) presence of high degree of consistency in the results, such as effects in same directions and not variations in the degree to which the outcome is affected (large significant effects (Hazard Ratio or Odds Ratio > 2)). > 50% (Not Serious) presence of high degree of consistency in the results, such as effects in same directions although variations in the degree to which the outcome is affected (small significant effects or large significant effects). > 50% (Serious) or > 75% (Very serious) presence of high degree of inconsistency in the results, such as effects in opposite directions, or large variations in the degree to which the outcome is affected (eg, very large and very small effects or no significant effect) d Indirectness: > 50% (NO) of included studies report similar population (similar HF diagnosis and similar age), as well as the same functional test (although different distances or cut-off points) and the same outcome. > 50% (Not Serious) of included studies show different HF diagnosis but population with similar age, and the same functional test (although different distances or cut-off points) and the same outcome is reported e Imprecision: > 50% (NO) of included studies report a 95% CI, with a narrow range (it excludes 1.0), includes large effects in the same direction and the sample size is large. > 50% (Not Serious) of included studies report a 95% CI, with a narrow range (it excludes 1.0), includes large or small effects in the same direction and the sample size could be small. > 50% (Serious) or > 75% (Very Serious) of included studies present 95% CIs with wide range (it does not exclude 1.0) and includes small effects in both directions f Other: Publication Bias is not suspected, and > 75% of included studies included the outcome data in a multivariate models adjusted by variables which could change the effect (NO) Discussion Main findings and comparison with other studies The current systematic review and meta-analysis showed that patients with HFrEF and HFpEF who reported a poor physical functional performance in 6-MWT have an increased risk of all-cause of mortality and an increased risk of HF mortality. There was consistency in the risk of all-cause of mortality and HF mortality between the studies included in each meta-analysis (Fig. 2a and Fig. 2b) and the GRADE criteria also reported a moderate level of evidence per otucome. Although patients with HFrEF who decreased the meters they walked in the 6MWT during follow-up showed an increased risk of all-cause of mortality, there was no decreased risk of all-cause of mortality between patients with HFrEF and HFpEF who increased the meters they walked in the 6MWT during follow-up [52, 53, 59, 60, 65, 67, 68, 70, 73, 75, 77]. Maybe this is beacuse the most of included studies in the meta-analysis reported a decreased risk of mortality for every 1 m increased [53, 65, 67, 68, 70, 73] or every 10 m [52, 60, 77] increased, while a systematic review determined that 45 m is the clinically meaningful change in the 6MWT [89]. Patients with HF who showed a poor physical functional performance in the 6MWT also reported an increased risk of the combined endpoint of hospitalisation and mortality for any cause (Fig. 2c and Fig. 2d), an increased risk of HF hospitalisation (Additional file 5) and an increased risk of all-cause of hospitalisation [48, 51]. However, the level of evidence of those outcomes was low according to the GRADE criteria. Moreover, there was a lack of homogeneity regarding which cut-off point should be used to stratify patients with HF based on their physical functional performance in the 6MWT. A distance traveled < 300 m was the most used distance to define patients with poor physical performance in the 6MWT in this study [47, 49, 55, 56, 58, 59, 61, 62, 64, 69, 74], while a previous review reported that a distance traveled ≤350 m in 6-MWT could be the most indicative distance of poor physical functional performance and worse prognosis in patients with HF [24]. A score between 1 and 4 points on the SPPB was associated with an increased risk of all-cause of mortality in this systematic review [80]. However, in the current study a score below 7 points on the SPPB seems to be the most indicative of a worse prognosis in patients with HF since it was associated with a larger risk of the combined endpoint of hospitalisation and mortality for any cause and a larger risk of HF hospitalisation [78]. GRADE criteria showed a very low level of evidence per outcome in each outcome examined by the SPPB. Moreover, meta-analysis on physical functional performance on the SPPB and prognosis in patients with HF could not be performed. As the present review, a score below 7 points on the SPPB was also associated with large risk of all-cause mortality in older adults [90]. However, other studies reported a large risk of mortality or hospitalisation in older adults who showed a score below 5 points [80, 91–93]. Patients who showed a slower gait speed also reported an increased risk of all-cause of mortality (Fig. 3), above all, when gait speed was slower than 0.65 m/s (Additional file 5). Moreover, patients with HF who showed a slower gait speed also reported an increased risk of all-cause of hospitalisation (Additional file 5) and an increased risk of the combined endpoint of hospitalisation and mortality for any cause [84], specially when gait speed was slower than 0.80 m/s [83, 84, 86]. GRADE criteria reported a low level of evidence per outcome in each prognostic outcome in Gait Speed Test. Other studies have shown the relationship between gait speed and survival, death and hospitalisation due to HF [27, 94]. In fact, Dodson et al. [95] revealed that patients who showed a gait speed slower than 0.8 m/s were more likely to experience one-year mortality or hospitalisation than patients with gait speed faster than 0.8 m/s. Alfredsson et al. [96] also reported that patients with a gait speed slower than 0.8 m/s after a transcatheter aortic valve replacement, had 35% higher 30-day mortality than patients with faster gait speed. Chainani et al. [97] reported that gait speed and handgrip strength are associated with increased risk of cardiovascular mortality. A meta-analysis published by Yamamoto et al. [98] reported that 6MWT were significantly associated with mortality and cardiovascular disease. Frailty has also been associated with larger risk of mortality and hospitalisation in patients with chronic HF [25, 26, 30, 31, 99]. Bagnall et al. [100] revealed that frailty patients had a risk of mortality 2- to 4-fold compared with non-frail patients after acardiac surgery or transcatheter aortic valve implantation. Gait speed is a marker of frailty, although frailty could be also assessed by the 6MWT, the SPPB or the TUG [25, 26, 30, 31, 99]. In this way, the use of functional tests seem to be useful to stratify patients with HF based on their physical functional performance and to determine their prognosis. To our knowledge, our review is the first systematic review reporting the level of evidence per each prognostic outcome using GRADE criteria. Other reviews showed the prognostic role of the 6MWT test or the impact of the physical performance on prognosis in patients with HF, but not reported the risk of bias of included studies or the level of evidence per outcome according to GRADE criteria [22, 23, 98, 101–103]. Implications for clinical practice The current findings may be useful to promote functional assessments that allow stratify patients with HF according to their functional impairment. Furthermore, accurate prognostic stratification could be essential for optimizing clinical management and treatment decision making, with the aim of maintaining functionality, improving quality of life and reducing the number of hospitalisations, as well as increasing the life expectancy of patients with HF. Adjusted medical-pharmacological treatment, in addition to improve symptoms, could prevent further cardiovascular accidents and prolong the life expectancy of patients with HF [13]. Moreover, adjusted exercise programs could reduce mortality, may improve functional capacity and quality of life, and may reduce hospitalisations [5, 8]. It has also been shown that patients with more physical activity performed weekly reported a lower risk of mortality [104–106]. Functional tests such as 6MWT, Gait Speed or SPPB may provide incremental prognostic value and could help to individualize the exercise prescription [107]. Future research Future research should aim to determine the optimal cut-off points for prognostic prediction and to determine the utility of functional assessments in the management and treatment of patients with HF. The following recommendations should guide future research: 1) use the same cut off point in functional tests; 2) include a large sample size with patients with HF who show different characteristics. Strengths and limitations of the study The strengths of this systematic review and meta-analysis included the use of a pre-specified protocol registered on PROSPERO, the PRISMA checklist, the NOS to determine the risk of bias of each study, the GRADE criteria to assess the overall quality and the strength of the evidence per outcome, a robust search strategy complemented by a manual search, so that all studies that met the eligibility criteria could have been identified. Thus, our systematic review included 44 studies, while a previous similar review carried out by Yamamoto et al. [98] included only 22 studies. However, there are several limitations that should be mentioned. First, the lack of uniformity among included studies, which included different cut-off points in functional tests, should be taken into account when interpreting the results. Finally, most of prognositc outcomes showed a low level of evidence per outcome according to GRADE criteria. Conclusion Patients with HF who report a poor physical functional performance in the 6MWT, in the SPPB or in the Gait Speed Test, show worse prognosis than patients who report a good physical functional performance in terms of an increased risk of hospitalisation or an increased risk of mortality. However, there is a lack of homogeneity regarding which cut-off point should be used to stratify patients with HF based on their physical functional performance in the different functional tests and GRADE criteria show a low level of evidence per outcome in most of examined prognostic outcome variables. Supplementary information Additional file 1. Additional file 2. Additional file 3. Additional file 4. Additional file 5. Additional file 6. Abbreviations HFHeart failure 6MWTSix minute walking test SPPBShort physical performance battery DALYsDisability-adjusted life-years TUGTimed up and go test PECOSParticipant, exposure, comparator, outcome, study design PRISMAPreferred reporting items for systematic reviews and meta-analyses statement PROSPEROInternational prospective register of systematic reviews NYHANew York heart association OROdds ratio HRHazard ratio NOSThe Newcastle Ottawa scale GRADEGrading of recommendations assessment, development and evaluation HFrEFHeart failure with reduced ejection fraction HFpEFHeart failure with preserved ejection fraction CIConfidence interval mMeters Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Supplementary information Supplementary information accompanies this paper at 10.1186/s12872-020-01725-5. Not Applicable. Authors’ contributions IJF-A and AC-V contributed to the conception of this study. IJF-A and AC-V were involved in the selection and analysis of the included studies. IJF-A, AC-V, B-S, LMP-B, MRB-L and RG-H were involved in the writing and in the review of the manuscript. All authors read and approved the manuscript. Funding Brendon Stubbs is supported by a Clinical Lectureship (ICA-CL-2017-03-001) jointly funded by Health Education England (HEE) and the National Institute for Health Research (NIHR). Brendon Stubbs is part funded by the NIHR Biomedical Research Centre at South London and Maudsley NHS Foundation Trust. Brendon Stubbs is also supported by the Maudsley Charity, King’s College London and the NIHR South London Collaboration for Leadership in Applied Health Research and Care (CLAHRC) funding. This paper presents independent research. The views expressed in this publication are those of the authors and not necessarily those of the acknowledged institutions. María Rosa Bernal-López was supported by “Miguel Servet Type I” program (CP15/00028) from the ISCIII-Madrid (Spain), cofinanced by the Fondo Europeo de Desarrollo Regional-FEDER. Availability of data and materials Not Applicable. Ethics approval and consent to participate Not Applicable. Consent for publication Not Applicable. Competing interests The authors declare that they have no conflict of interest. ==== Refs References 1. Abajobir AA Abate KH Abbafati C Abbas KM Abd-Allah F Abdulkader RS Global, regional, and national disability-adjusted life-years (DALYs) for 333 diseases and injuries and healthy life expectancy (HALE) for 195 countries and territories, 1990–2016: a systematic analysis for the global burden of disease study 2016 Lancet 2017 390 10100 1260 1344 10.1016/S0140-6736(17)32130-X 28919118 2. Abajobir AA Abbafati C Abbas KM Abd-Allah F Abera SF Aboyans V Global, regional, and national age-sex specific mortality for 264 causes of death, 1980–2016: a systematic analysis for the global burden of disease study 2016 Lancet 2017 390 10100 1151 1210 10.1016/S0140-6736(17)32152-9 28919116 3. Wang H Abajobir AA Abate KH Abbafati C Abbas KM Abd-Allah F Global, regional, and national under-5 mortality, adult mortality, age-specific mortality, and life expectancy, 1970-2016: a systematic analysis for the global burden of disease study 2016 Lancet 2017 390 10100 1084 1150 10.1016/S0140-6736(17)31833-0 28919115 4. Bui A Horwich T Fonarow G Epidemiology and risk profile of heart failure Nat Rev Cardiol 2011 8 3 30 41 10.1038/nrcardio.2010.165 21060326 5. Rogers C, Bush N. Heart failure: pathophysiology, diagnosis, medical treatment guidelines, and nursing management. Nurs Clin North Am. 2015;50(4): 787–799. DOI: http://dx.doi.org/10.1016/j.cnur.2015.07.012. 6. Tendera M Epidemiology, treatment, and guidelines for the treatment of heart failure in Europe Eur Heart J 2005 7 1 5 9 10.1093/eurheartj/sui056 7. Smith AC Effect of telemonitoring on re-admission in patients with congestive heart failure Medsurg Nurs 2013 22 1 39 44 23469498 8. Yancy C Jessup M Bozkurt B ACCF/AHA guideline for the management of heart failure: a report of the American College of Cardiology Foundation/American Heart Association task force on practice guidelines J Am Coll Cardiol 2013 62 16 147 10.1016/j.jacc.2013.05.019 9. Wheeler EC Plowfield L Clinical education initiative in the community: caring for patients with congestive heart failure Nurs Educ Perspect 2004 25 1 16 21 15017795 10. Fletcher L, Thomas D. Heart failure: understanding the pathophysiology and management. J Am Acad Nurse Pract. 2001;13(6):249–57. 11. Siracuse J Chaikof E The pathogenesis of diabetic atherosclerosis Diab Peripher Vasc Dis Diagn Manage 2012 158 5 13 26 12. Kaminsky LA, Tuttle MS. Functional assessment of heart failure patients. Heart Fail Clin. 2015;11(1):29–36. doi: http://dx.doi.org/10.1016/j.hfc.2014.08.002. 13. Ponikowski P Voors AA Anker SD ESC guidelines for the diagnosis and treatment of acute and chronic heart failure: the task forcé for the diagnosis and treatment of acute and chronic heart failure of the European society of cardiology (ESC) developed with the special contribution of the heart failure association (HFA) of the ESC Eur Heart J 2016 37 2129 2200 10.1093/eurheartj/ehw128 27206819 14. Gutekunst DJ. Isokinetic torque timing parameters and ceramides as markers of muscle dysfunction in systolic heart failure. J Card Fail. 2016;22(5): 356–357. doi: http://dx.doi.org/10.1016/j.cardfail.2016.03.018. 15. Watson RD Gibbs CR Lip GY ABC of heart failure. Clinical features and complications BMJ 2000 320 7229 236 239 10.1136/bmj.320.7229.236 10642237 16. Barker J Byrne KS Doherty A Foster C Rahimi K Ramakrishnan R Physical activity of UK adults with chronic disease: cross-sectional analysis of accelerometer-measured physical activity in 96 706 UK biobank participants Int J Epidemiol 2019 48 4 1167 1174 30721947 17. Kinugawa S Takada S Matsushima S Okita K Tsutsui H Skeletal muscle abnormalities in heart failure Int Heart J 2015 56 5 475 484 10.1536/ihj.15-108 26346520 18. Bona RL, Bonezi A, da Silva PF, Biancardi CM, de Souza Castro FA, Clausel NO. Effect of walking speed in heart failure patients and heart transplant patients. Clin Biomech. 2017;42: 85–91. doi: http://dx.doi.org/10.1016/j.clinbiomech.2017.01.008. 19. Mancini DM Eisen H Kussmaul W Mull R Edmunds L Wilson J Value of peak exercise oxygen consumption for optimal timing of cardiac transplantation in ambulatory patients with heart failure Circulation 1991 83 3 778 786 10.1161/01.CIR.83.3.778 1999029 20. Myers J Prakash M Froelicher V Do D Partington S Atwood JE Exercise capacity and mortality among men referred for exercise testing N Engl J Med 2002 346 11 793 801 10.1056/NEJMoa011858 11893790 21. Hülsmann M Quittan M Berger R Crevenna R Springer C Nuhr M Muscle strength as a predictor of long-term survival in severe congestive heart failure Eur J Heart Fail 2004 6 1 101 107 10.1016/j.ejheart.2003.07.008 15012925 22. Rostagno C Gensini GF Six minute walk test: a simple and useful test to evaluate functional capacity in patients with heart failure Intern Emerg Med 2008 3 3 205 212 10.1007/s11739-008-0130-6 18299800 23. Du H Wonggom P Tongpeth J Clark RA Six-minute walk test for assessing physical functional capacity in chronic heart failure Curr Heart Fail Rep 2017 14 3 158 166 10.1007/s11897-017-0330-3 28421409 24. Rasekaba T, Lee AL, Naughton MT, Williams TJ, Holland AE. The six-minute walk test: A useful metric for the cardiopulmonary patient. Intern Med J. 2009;39:495–501. 25. Díez-Villanueva P Arizá-Solé A Vidán MT Bonanad C Formiga F Sanchis J Recomendaciones de la Sección de Cardiología Geriátrica de la Sociedad Española de Cardiología Para la valoración de la fragilidad en el anciano con cardiopatía Rev Esp Cardiol 2019 72 1 63 71 10.1016/j.recesp.2018.06.015 30269913 26. Yang X Lupón J Vidán MT Ferguson C Gastelurrutia P Newton PJ Impact of frailty on mortality and hospitalisation in chronic heart failure: a systematic review and meta-analysis J Am Heart Assoc 2018 7 23 e008251 10.1161/JAHA.117.008251 30571603 27. Studenski S Perera S Kushang P Rosano C Faulkner K Inzitari M Gait speed and survival in older adults JAMA 2011 305 1 50 58 10.1001/jama.2010.1923 21205966 28. Abellan van Kan G Rolland Y Andrieu S Gait speed at usual pace as a predictor of adverse outcomes in community-dwelling older people an international academy on nutrition and aging (IANA) task force J Nutr Health Aging 2009 13 881 889 10.1007/s12603-009-0246-z 19924348 29. Afilalo J Alexander KP Mack MJ Frailty assessment in the cardiovascular care of older adults J Am Coll Cardiol 2014 63 747 762 10.1016/j.jacc.2013.09.070 24291279 30. Singh M Stewart R White H Importance of frailty in patients with cardiovascular disease Eur Heart J 2014 35 1726 1731 10.1093/eurheartj/ehu197 24864078 31. Newman AB Gottdiener JS McBurnie MA Associations of subclinical cardiovascular disease with frailty J Gerontol A Biol Sci Med Sci 2001 56 M158 M166 10.1093/gerona/56.3.M158 11253157 32. Guyatt GH Sullivan MJ Thompson PJ Fallen EL Pugsley S0, Taylor DW, et al. the 6-minute walk: a new measure of exercise capacity in patients with chronic heart failure Can Med Assoc J 1985 132 8 919 923 3978515 33. Guralnik JM Simonsick EM Ferrucci L Glynn RJ Berkman LF Blazer DG A short physical performance battery assessing lower extremity function: association with self-reported disability and prediction of mortality and nursing home admission J Gerontol 1994 49 2 85 94 10.1093/geronj/49.2.M85 34. Podsiadlo D Richardson S The timed “up and go”: a test of basic functional mobility for frail elderly persons J Am Geriatr Soc 1991 39 2 142 148 10.1111/j.1532-5415.1991.tb01616.x 1991946 35. Chan ME Arvey RD Meta-analysis and the development of knowledge Perspect Psychol Sci 2012 7 79 92 10.1177/1745691611429355 26168427 36. Liberati A Altman DG Tetzlaff J Mulrow C Gotzsche PC Ioannidis JP Clarke M Devereaux PJ Kleijnen J Moher D The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate healthcare interventions: explanation and elaboration BMJ 2009 339 b2700 10.1136/bmj.b2700 19622552 37. Haddaway NR Collins AM Coughlin D The role of google scholar in evidence reviews and its applicability to grey literature searching PLoS One 2015 10 e0138237 e0138217 10.1371/journal.pone.0138237 26379270 38. Wells GA, Shea B, O’Connell D, Peterson J, Welch V, Losos M, et al. The Newcastle-Ottawa Scale (NOS) for assessing the quality of non-randomised studies in meta-analyses. 2008 [Accessed September 24, 2019]. Available from URL: http://www.ohri.ca/programs/clinical_epidemiology/oxford.asp. 39. Zeng X Zhang Y Kwong JSW Zhang C Li S Sun F The methodological quality assessment tools for preclinical and clinical studies, systematic review and meta-analysis, and clinical practice guideline: a systematic review J Evid Based Med 2015 8 2 10 10.1111/jebm.12141 25594108 40. Atkins D Best D Briss PA Grading quality of evidence and strength of recommendations BMJ 2004 328 1490 10.1136/bmj.328.7454.1490 15205295 41. Guyatt GH Oxman AD Vist GE Kunz R Falck-Ytter Y Alonso-Coello P Schünemann HJ GRADE working group: GRADE: an emerging consensus on rating quality of evidence and strength of recommendations BMJ 2008 336 924 926 10.1136/bmj.39489.470347.AD 18436948 42. Higgins JP Thompson SG Deeks JJ Altman DG Measuring inconsistency in meta-analyses BMJ. 2003 327 557 560 10.1136/bmj.327.7414.557 12958120 43. Higgins JP Thompson SG Quantifying heterogeneity in a meta-analysis Stat Med 2002 21 1539 1558 10.1002/sim.1186 12111919 44. Review Manager (RevMan) [Computer program]. Version 5.3. Copenhagen: The Nordic Cochrane Centre, The Cochrane Collaboration, 2014. 45. Brenyo A, Goldenberg I, Moss AJ, Rao M, McNitt S, Huang DT, et al. Baseline functional capacity and the benefit of cardiac resynchronization therapy in patients with mildly symptomatic heart failure enrolled in MADIT-CRT. Hear Rhythm 2012;9(9):1454–1459. Available from: http://dx.doi.org/10.1016/j.hrthm.2012.04.018. 46. Ferreira JP Metra M Anker SD Dickstein K Lang CC Ng L Clinical correlates and outcome associated with changes in 6-minute walking distance in patients with heart failure: findings from the BIOSTAT-CHF study Eur J Heart Fail 2019 21 2 218 226 10.1002/ejhf.1380 30600578 47. Wegrzynowska-Teodorczyk K Rudzinska E Lazorczyk M Nowakowska K Banasiak W Ponikowski P Distance covered during a six-minute walk test predicts long-term cardiovascular mortality and hospitalisation rates in men with systolic heart failure: an observational study J Physiother 2013 59 3 177 187 10.1016/S1836-9553(13)70182-6 23896333 48. Bittner V Weiner DH Yusuf S Rogers WJ Mcintyre KM Bangdiwala SI Prediction of mortality and morbidity with a 6-minute walk test in patients with left ventricular dysfunction JAMA 1993 270 14 1702 1707 10.1001/jama.1993.03510140062030 8411500 49. Arslan S Erol MK Gundogdu F Sevimli S Aksakal E Senocak H Prognostic value of 6-minute walk test in stable outpatients with heart failure Tex Heart Inst J 2007 34 2 166 169 17622362 50. Lee R Chan YH Wong J Lau D Ng K The 6-minute walk test predicts clinical outcome in Asian patients with chronic congestive heart failure on contemporary medical therapy: a study of the multiracial population in Singapore Int J Cardiol 2007 119 2 168 175 10.1016/j.ijcard.2006.07.189 17056135 51. Curtis JP Rathore SS Wang Y Krumholz HM The association of 6-minute walk performance and outcomes in stable outpatients with heart failure J Card Fail 2004 10 1 9 14 10.1016/j.cardfail.2003.08.010 14966769 52. Ingle L Cleland JG Clark AL The long-term prognostic significance of 6-minute walk test distance in patients with chronic heart failure Biomed Res Int 2014 2014 505969 10.1155/2014/505969 24800236 53. Alahdab MT, Mansour IN, Napan S, Stamos TD. Six minute walk test predicts long-term all-cause mortality and heart failure Rehospitalisation in African-American patients hospitalized with acute decompensated heart failure. J Card Fail 2009;15(2): 130–135. Available from: http://dx.doi.org/10.1016/j.cardfail.2008.10.006. 54. Mangla A Kane J Beaty E Richardson D Powell LH Calvin JE Comparison of predictors of heart failure-related hospitalisation or death in patients with versus without preserved left ventricular ejection fraction Am J Cardiol 2013 112 12 1907 12 10.1016/j.amjcard.2013.08.014 24063842 55. Hasin T, Topilsky Y, Kremers WK, Boilson BA, Schirger JA, Edwards BS, et al. Usefulness of the six-minute walk test after continuous axial flow left ventricular device implantation to predict survival. Am J Cardiol 2012;110(9): 1322–1328. Available from: http://dx.doi.org/10.1016/j.amjcard.2012.06.036. 56. Passantino A Lagioia R Mastropasqua F Scrutinio D Short-term change in distance walked in 6 min is an Indicator of outcome in patients with chronic heart failure in clinical practice J Am Coll Cardiol 2006 48 1 99 105 10.1016/j.jacc.2006.02.061 16814655 57. Howie-Esquivel J Dracup K Does oxygen saturation or distance walked predict rehospitalisation in heart failure? J Cardiovasc Nurs 2008 23 4 349 356 10.1097/01.JCN.0000317434.29339.14 18596499 58. Zotter-Tufaro C Mascherbauer J Duca F Koell B Aschauer S Kammerlander AA Prognostic significance and Determinantsof the 6-min walk test inPatients WithHeart failure and preserved EjectionFraction JACC Hear Fail 2015 3 6 459 466 10.1016/j.jchf.2015.01.010 59. Boxer R Kleppinger A Ahmad A Annis K Hager D Kenny A The 6-minute walk is associated with frailty and predicts mortality in older adults with heart failure Congest Hear Fail 2010 16 5 208 213 10.1111/j.1751-7133.2010.00151.x 60. Ingle L Cleland JG Clark AL The relation between repeated 6-minute walk test performance and outcome in patients with chronic heart failure Ann Phys Rehabil Med 2014 57 4 244 253 10.1016/j.rehab.2014.03.004 24835160 61. Guazzi M Dickstein K Vicenzi M Arena R Six-minute walk test and cardiopulmonary exercise testing in patients with chronic heart failure: a comparative analysis on clinical and prognostic insights Circ Hear Fail 2009 2 6 549 555 10.1161/CIRCHEARTFAILURE.109.881326 62. McCabe N Butler J Dunbar SB Higgins M Reilly C Six-minute walk distance predicts 30-day readmission after acute heart failure hospitalisation Heart Lung 2017 46 4 287 292 10.1016/j.hrtlng.2017.04.001 28551310 63. Vegh EM Kandala J Orencole M Upadhyay GA Sharma A Miller A Device-measured physical activity versus six-minute walk test as a predictor of reverse remodeling and outcome after cardiac resynchronization therapy for heart failure Am J Cardiol 2014 113 9 1523 1528 10.1016/j.amjcard.2014.01.430 24641966 64. Roul G Germain P Bareiss P Does the 6-minute walk test predict the prognosis in patients with NYHA class II or III chronic heart failure? Am Heart J 1998 136 3 449 457 10.1016/S0002-8703(98)70219-4 9736136 65. Frankenstein L Remppis A Graham J Schellberg D Sigg C Nelles M Gender and age related predictive value of walk test in heart failure: Do anthropometrics matter in clinical practice? Int J Cardiol 2008 127 3 331 336 10.1016/j.ijcard.2007.04.087 17689763 66. Mene-Afejuku TO Balogun MO Akintomide AO Adebayo RA Prognostic indices among hypertensive heart failure patients in Nigeria: the roles of 24-hour holter electrocardiography and 6-minute walk test Vasc Health Risk Manag 2017 13 71 79 10.2147/VHRM.S124477 28280349 67. Ingle L Rigby AS Carroll S Butterly R King RF Cooke CB Prognostic value of the 6 min walk test and self-perceived symptom severity in older patients with chronic heart failure Eur Heart J 2007 28 560 568 10.1093/eurheartj/ehl527 17314108 68. Rostagno C Olivo G Comeglio M Boddi V Banchelli M Galanti G Prognostic value of 6-minute walk corridor test in patients with mild to moderate heart failure: comparison with other methods of functional evaluation Eur J Heart Fail 2003 5 3 247 252 10.1016/S1388-9842(02)00244-1 12798821 69. Cahalin LP Mathier MA Semigran MJ Dec GW DiSalvo TG The six-minute walk test predicts peak oxygen uptake and survival in patients with advanced heart failure Chest 1996 110 2 325 332 10.1378/chest.110.2.325 8697828 70. Frankenstein L Zugck C Nelles M Schellberg D Katus H Remppis A Sex-specific predictive power of 6-minute walk test in chronic heart failure is not enhanced using percent achieved of published reference equations J Hear Lung Transplant 2008 27 4 427 434 10.1016/j.healun.2008.01.010 71. Rubim VSM Neto CD Martins-Romeo JL Montera MW Valor prognóstico do teste de caminhada de seis minutos na insuficiência cardíaca Arq Bras Cardiol 2006 86 2 120 125 10.1590/S0066-782X2006000200007 16501803 72. Kanagala P Arnold JR Cheng ASH Singh A Khan JN Gulsin GS Left atrial ejection fraction and outcomes in heart failure with preserved ejection fraction Int J Cardiovasc Imaging 2020 36 1 101 110 10.1007/s10554-019-01684-9 31401742 73. Zugck C Krüger C Kell R Körber S Schellberg D Kübler W Risk stratification in middle-aged patients with congestive heart failure: prospective comparison of the heart failure survival score (HFSS) and a simplified two-variable model Eur J Heart Fail 2001 3 5 577 585 10.1016/S1388-9842(01)00167-2 11595606 74. Cahalin LP Arena R Labate V Bandera F Lavie CJ Guazzi M Heart rate recovery after the 6 min walk test rather than distance ambulated is a powerful prognostic Indicator in heart failure with reduced and preserved ejection fraction: a comparison with cardiopulmonary exercise testing Eur J Heart Fail 2013 15 519 527 10.1093/eurjhf/hfs216 23397578 75. Reibis RK Treszl A Wegscheider K Ehrlich B Dissmann R Völler H Exercise capacity is the most powerful predictor of 2-year mortality in patients with left ventricular systolic dysfunction Herz. 2010 35 2 104 110 10.1007/s00059-010-3226-5 20376644 76. Castel MA Méndez F Tamborero D Mont L Magnani S Tolosana JM Six-minute walking test predicts long-term cardiac death in patients who received cardiac resynchronization therapy Europace. 2009 11 338 342 10.1093/europace/eun362 19136491 77. Kamiya K Hamazaki N Matsue Y Mezzani A Corrà U Matsuzawa R Gait speed has comparable prognostic capability to six-minute walk distance in older patients with cardiovascular disease Eur J Prev Cardiol 2018 25 2 212 219 10.1177/2047487317735715 28990422 78. García GL Sánchez SM García-Briñón MÁ Fernández-Alonso C González del Castillo J Martín-Sánchez FJ El efecto de la fragilidad física en el pronóstico a largo plazo en los pacientes mayores con insuficiencia cardiaca aguda dados de Alta desde un servicio de urgencias Emergencias 2019 31 6 413 416 31777214 79. Hornsby WE Sareini M Golbus JR Willer J Mcnamara JL Konerman MC Lower extremity function is independently associated with hospitalisation burden in heart failure with preserved ejection fraction J Card Fail 2019 25 1 2 9 10.1016/j.cardfail.2018.09.002 30219550 80. Chiarantini D Volpato S Sioulis F Bartalucci F Del Bianco L Mangani I Lower extremity performance measures predict long-term prognosis in older patients hospitalized for heart failure J Card Fail 2010 16 5 390 395 10.1016/j.cardfail.2010.01.004 20447574 81. Zaharias E, Cataldo J, Mackin L, Howie-Esquivel J. Simple measures of function and symptoms in hospitalized heart failure patients predict short-term cardiac event-free survival. Nurs Res Pract. 2014;815984.. 82. Lo AX Donnelly JP McGwin G Bittner V Ahmed A Brown CJ Impact of gait speed and instrumental activities of daily living on all-cause mortality in adults ≥65 years with heart failure Am J Cardiol 2015 115 6 797 801 10.1016/j.amjcard.2014.12.044 25655868 83. Pulignano G Del Sindaco D Di Lenarda A Alunni G Senni M Tarantini L Incremental value of gait speed in predicting prognosis of older adults with heart failure: insights from the IMAGE-HF study JACC Hear Fail 2016 4 4 289 298 10.1016/j.jchf.2015.12.017 84. Chaudhry SI McAvay G Chen S Whitson H Newman AB Krumholz HM Risk factors for hospital admission among older persons with newly diagnosed heart failure: findings from the cardiovascular health study J Am Coll Cardiol 2013 61 6 635 642 10.1016/j.jacc.2012.11.027 23391194 85. Tanaka S Kamiya K Hamazaki N Matsuzawa R Nozaki K Maekawa E Incremental value of objective frailty assessment to predict mortality in elderly patients hospitalized for heart failure J Card Fail 2018 24 11 723 732 10.1016/j.cardfail.2018.06.006 30010026 86. Tanaka S Kamiya K Hamazaki N Matsuzawa R Nozaki K Nakamura T Short-term change in gait speed and clinical outcomes in older patients with acute heart failure Circ J 2019 83 9 1860 1867 10.1253/circj.CJ-19-0136 31281168 87. Rodríguez-Pascual C Paredes-Galán E Ferrero-Martínez AI González-Guerrero JL Hornillos-Calvo M Menendez-Colino R The frailty syndrome is associated with adverse health outcomes in very old patients with stable heart failure: a prospective study in six Spanish hospitals Int J Cardiol 2017 236 296 303 10.1016/j.ijcard.2017.02.016 28215465 88. Vidán MT Blaya-Novakova V Sánchez E Ortiz J Serra-Rexach JA Bueno H Prevalence and prognostic impact of frailty and its components in non-dependent elderly patients with heart failure Eur J Heart Fail 2016 18 7 869 875 10.1002/ejhf.518 27072307 89. Shoemaker MJ Curtis AB Vangsnes E Dickinson MG Clinically meaningful change estimates for the six-minute walk test and daily activity in individuals with chronic heart failure Cardiopulm Phys Ther J. 2013 24 3 21 29 10.1097/01823246-201324030-00004 23997688 90. Fox KR Ku P-W Hillsdon M Davis MG Simmonds BAJ Thompson JL Objectively assessed physical activity and lower limb function and prospective associations with mortality and newly diagnosed disease in UK older adults: an OPAL four-year follow-up study Age Ageing 2015 44 2 261 268 10.1093/ageing/afu168 25377744 91. Corsonello A Lattanzio F Pedone C Garasto S Laino I Bustacchini S Prognostic significance of the short physical performance battery in older patients discharged from acute care hospitals Rejuvenation Res 2012 15 1 41 48 10.1089/rej.2011.1215 22004280 92. Legrand D Vaes B Matheï C Adriaensen W Van Pottelbergh G Degryse J-M Muscle strength and physical performance as predictors of mortality, hospitalisation, and disability in the oldest old J Am Geriatr Soc 2014 62 6 1030 1038 10.1111/jgs.12840 24802886 93. Volpato S Cavalieri M Sioulis F Guerra G Maraldi C Zuliani G Predictive value of the short physical performance battery following hospitalisation in older patients J Gerontol A Biol Sci Med Sci 2011 66 1 89 96 10.1093/gerona/glq167 20861145 94. Reeves GR, Forman DE. Gait speed: stepping towards improved assessment of heart failure patients. JACC Hear Fail. 2016;4(4): 299–300. doi: http://dx.doi.org/10.1016/j.jchf.2016.02.002. 95. Dodson JA Arnold SV Gosch KL Gill TM Spertus J Krumholz HM Slow gait speed and risk of mortality or hospital readmission following myocardial infarction in the TRIUMPH registry J Am Geriatr Soc 2016 64 3 596 601 10.1111/jgs.14016 26926309 96. Alfredsson J Stebbins A Brennan JM Matsouaka R Afilalo J Peterson ED Gait speed predicts 30-day mortality after Transcatheter aortic valve replacement: results from the Society of Thoracic Surgeons/American College of Cardiology Transcatheter Valve Therapy Registry Circulation 2016 133 14 1351 1359 10.1161/CIRCULATIONAHA.115.020279 26920495 97. Chainani V Shaharyar S Dave K Choksi V Ravindranathan S Hanno R Objective measures of the frailty syndrome (hand grip strength and gait speed) and cardiovascular mortality: a systematic review Int J Cardiol 2016 215 487 493 10.1016/j.ijcard.2016.04.068 27131770 98. Yamamoto S, Yamaga T, Nishie K, Sakai Y, Ishida T, Oka K, et al. Impact of physical performance on prognosis among patients with heart failure: systematic review and meta-analysis. J Cardiol. 2020;76(2):139–46. 99. Boxer RS Wang Z Walsh SJ Hager D Kenny AM The utility of the 6-minute walk test as a measure of frailty in older adults with heart failure Am J Geriatr Cardiol 2008 17 1 7 12 10.1111/j.1076-7460.2007.06457.x 18174754 100. Bagnall NM Faiz O Darzi A Athanasiou T What is the utility of preoperative frailty assessment for risk stratification in cardiac surgery? Interact Cardiovasc Thorac Surg 2013 17 2 398 402 10.1093/icvts/ivt197 23667068 101. Giannitsi S Bougiakli M Bechlioulis A Kotsia A Michalis LK Naka KK 6-minute walking test: a useful tool in the management of heart failure patients Ther Adv Cardiovasc Dis 2019 13 1 10 10.1177/1753944719870084 102. Zielinska D Bellwon J Rynkiewicz A Elkady MA Prognostic value of the six-minute walk test in heart failure patients undergoing cardiac surgery: a literature review Rehabil Res Pract 2013 2013 965494 23984074 103. Pollentier B Irons SL Benedetto CM Dibenedetto A-M Loton D Seyler RD Examination of the six minute walk test to determine functional capacity in people with chronic heart failure: a systematic review Cardiopulm Phys Ther J 2010 21 1 13 21 10.1097/01823246-201021010-00003 20467515 104. Jeong SW Kim SH Kang SH Kim HJ Yoon CH Youn TJ Mortality reduction with physical activity in patients with and without cardiovascular disease Eur Heart J 2019 40 43 3547 3555 10.1093/eurheartj/ehz564 31504416 105. Kraus WE Powell KE Haskell WL Janz KF Campbell WW Jakicic JM Physical activity, all-cause and cardiovascular mortality, and cardiovascular disease Med Sci Sports Exerc 2019 51 6 1270 1281 10.1249/MSS.0000000000001939 31095084 106. Blond K, Brinkløv CF, Ried-Larsen M, Crippa A, Grøntved A. Association of high amounts of physical activity with mortality risk: a systematic review and meta-analysis. Br J Sports Med. 2019:1–8. 107. Afilalo J Evaluating and treating frailty in cardiac rehabilitation Clin Geriatr Med 2019 35 4 445 457 10.1016/j.cger.2019.07.002 31543177