
==== Front
BMC Pulm Med
BMC Pulm Med
BMC Pulmonary Medicine
1471-2466
BioMed Central London

39272014
3274
10.1186/s12890-024-03274-5
Research
Prevalence and predictors of polypharmacy and comorbidities among patients with chronic obstructive pulmonary disease: a cross-sectional retrospective study in a tertiary hospital in Saudi Arabia
Alwafi Hassan 1
Naser Abdallah Y. abdallah.naser@iu.edu.jo

2
Ashoor Deema S. 3
Alsharif Alaa 4
Aldhahir Abdulelah M. 5
Alghamdi Saeed M. 6
Alqarni Abdallah A. 78
Alsaleh Nada 4
Samkari Jamil A. 9
Alsanosi Safaa M. 1
Alqahtani Jaber S. 10
Dairi Mohammad Saleh 11
Hafiz Waleed 11
Tashkandi Mohammed 12
Ashoor Abdullah 3
Badr Omaima Ibrahim 1314
1 https://ror.org/01xjqrm90 grid.412832.e 0000 0000 9137 6644 Department of Pharmacology and Toxicology, College of Medicine, Umm Al-Qura University, Makkah, Saudi Arabia
2 https://ror.org/04d4bt482 grid.460941.e 0000 0004 0367 5513 Department of Applied Pharmaceutical Sciences and Clinical Pharmacy, Faculty of Pharmacy, Isra University, Amman, Jordan
3 https://ror.org/01xjqrm90 grid.412832.e 0000 0000 9137 6644 Faculty of Medicine, Umm Al-Qura University, Mecca, Saudi Arabia
4 https://ror.org/05b0cyh02 grid.449346.8 0000 0004 0501 7602 Department of Pharmacy Practice, College of Pharmacy, Princess Noura Bint Abdulrahman University, Riyadh, Saudi Arabia
5 https://ror.org/02bjnq803 grid.411831.e 0000 0004 0398 1027 Respiratory Therapy Department, Faculty of Applied Medical Sciences, Jazan, Saudi Arabia
6 https://ror.org/01xjqrm90 grid.412832.e 0000 0000 9137 6644 Clinical Technology Department, Respiratory Care Program, Faculty of Applied Sciences, Umm Al-Qura University, Mecca, Saudi Arabia
7 https://ror.org/02ma4wv74 grid.412125.1 0000 0001 0619 1117 Department of Respiratory Therapy, Faculty of Medical Rehabilitation Sciences, King Abdulaziz University, Jeddah, 22230 Saudi Arabia
8 https://ror.org/02ma4wv74 grid.412125.1 0000 0001 0619 1117 Respiratory Therapy Unity, King Abdulaziz University Hospital, Jeddah, Saudi Arabia
9 https://ror.org/02ma4wv74 grid.412125.1 0000 0001 0619 1117 Family and Community Medicine Department, Faculty of Medicine in Rabigh, King Abdulaziz University, Rabigh, Saudi Arabia
10 https://ror.org/01k7e4s32 0000 0004 0608 1542 Department of Respiratory Care, Prince Sultan Military College of Health Sciences, Dammam, 34313 Saudi Arabia
11 https://ror.org/01xjqrm90 grid.412832.e 0000 0000 9137 6644 Department of Medicine, College of Medicine, Umm Al-Qura University, Makkah, Saudi Arabia
12 grid.415696.9 0000 0004 0573 9824 Ministry of Health, Mecca, Saudi Arabia
13 https://ror.org/01k8vtd75 grid.10251.37 0000 0001 0342 6662 Department of Chest Medicine, Faculty of Medicine, Mansoura University, Mansoura, 35516 Egypt
14 grid.517931.8 Department of Pulmonary Medicine, Al Noor Specialist Hospital, Mecca, 20424 Saudi Arabia
14 9 2024
14 9 2024
2024
24 45326 11 2023
4 9 2024
© The Author(s) 2024
2024
https://creativecommons.org/licenses/by-nc-nd/4.0/ Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, 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 you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. 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-nc-nd/4.0/.
Objective

This study aimed to determine the prevalence of polypharmacy, comorbidities and to investigate factors associated with polypharmacy among adult patients with Chronic Obstructive Pulmonary Disease (COPD).

Methods

This was a retrospective single-centre cross-sectional study. Patients with a confirmed diagnosis of COPD according to the GOLD guidelines between 28 February 2020 and 1 March 2023 were included in this study. Patients were excluded if a pre-emptive diagnosis of COPD was made clinically without spirometry evidence of fixed airflow limitation. Population characteristics were presented as frequency for categorical variable. Logistic regression analysis was used to identify predictors of polypharmacy.

Results

The study sample included a total of 705 patients with COPD. Most of the study sample were males (60%). The mean age of the study population was 65 years old. The majority of the study population had comorbid diseases (68%), hypertension and diabetes were the most common co-existent diseases. Around 55% of the study sample had polypharmacy. Females were significantly less likely to be on polypharmacy compared to males (OR = 0.68, 95% CI = [0.50–0.92], P-value = 0.012)). On the other hand, older patients aged 65.4 or more (OR = 2.31, 95% CI = [1.71–3.14], P-value ≤ 0.001), those with high BMI (≥ 29.2) (OR = 1.42, 95% CI = [1.05–1.92], P-value = 0.024), current smokers (OR = 1.9, 95% CI = [1.39–2.62], P-value ≤ 0.001), those who are receiving home care (OR = 5.29, 95% CI = [2.46–11.37], P-value ≤ 0.001), those who have comorbidities (OR = 19.74, 95% CI = [12.70–30.68], P-value ≤ 0.001) were significantly more likely to be on polypharmacy (p ≤ 0.05).

Conclusions

Polypharmacy is common among patients with COPD. Patients with high BMI, previous ICU hospitalization and older age are more likely to have polypharmacy. Future analytical studies are warranted to investigate outcomes in patients with COPD and polypharmacy.

Keywords

Hospital
COPD
Polypharmacy
Saudi Arabia
Comorbidity
issue-copyright-statement© BioMed Central Ltd., part of Springer Nature 2024
==== Body
pmcBackground

COPD has emerged as one of the most common respiratory diseases worldwide [1]. COPD is considered as the fourth leading cause of morbidity and mortality [2]. Chronic obstructive pulmonary disease (COPD) is a preventable and treatable disease caused by airway or alveolar abnormalities due to exposure to smoking and air pollutants. COPD is characterized by an irreversible airflow limitation and influenced by host factors [3].

Airway obstruction is a landmark in people with COPD [4]. However, it is mostly accompanied by other complex morbidities such as comorbidities disease [5]. Comorbidity is defined as when were more than two diseases are usually associated with patients [6], and this is common in COPD population [4]. The most common multiple morbidities associated with COPD includes cardiovascular diseases, lung neoplasms, obesity, gastroesophageal reflux disease [7], diabetes, obstructive sleep apnoea, and mental health conditions (40%) [8–10]. Cardiovascular disease (CVDs) and COPD co-existence are widely described in the literature [11]. It has been demonstrated that patients with COPD are at an increased risk of developing CVDs [12]. However, the distribution and the nature of other comorbidities appear to vary [12]. When considering clinical parameters such as survival, hospitalization, comorbidities, polypharmacy, and systemic inflammation, it has been reported that COPD is complex and includes several distinct phenotypes [13].

Comorbidity diagnosis and management are essential for the quality of life in COPD [14]. As a result, these comorbidities are taken into account by the COPD guidelines [15]. Bronchodilators, corticosteroids, long-term oxygen use, or pulmonary rehabilitation are all used treatments for COPD [16]. However, this will also be associated with polypharmacy (the concomitant use of more than 5 medications) and the use of other medications to treat the comorbidity [17]. Polypharmacy in general is associated with multiple health outcomes issues including adverse drug reactions, adherence, and hospitalizations, especially among the old age populations [4].

COPD-associated comorbidities, polypharmacy, exacerbation, and related hospitalization, have a detrimental effect on COPD patients' quality of life (HRQoL) [18, 19]. Both comorbidity and polypharmacy are associated with poorer quality of life and can be considered a major burden in the management of COPD which impact treatment outcomes [4, 20].

A previous study in Saudi Arabia found that the prevalence rate of COPD in 2019 has reached 2.05% [21]. The prevalence and extent of this coexistence of COPD and polypharmacy issue have not been described previously among the middle eastern population. Therefore, this study aims to determine the prevalence of polypharmacy, comorbidities and to investigate factors associated with polypharmacy among adult patients COPD.

Methods

Study design and study settings

This was a retrospective single-centre cross-sectional descriptive study. Data were collected between 28 February 2020 and 1 March 2023 from Al-Noor Specialist in Mecca, Saudi Arabia [22]. Details of the data collection method and study settings were previously described [23]. We included inpatients with a confirmed diagnosis of COPD according to the GOLD 2023 guidelines. Only patients with a spirometry evidence of fixed airflow limitation were included in the study. Comorbid conditions were addressed by different teams led by qualified consultant.

Study variables

A standardized spreadsheet was used to collect data regarding the demographics including (Age, gender, smoking status, and body mass index). Comorbidities data were collected based on the Charlson comorbidity index. Medications used including (respiratory medication, oxygen therapy, and other medications used were reported at the latest recorded in the files or the medical record). Polypharmacy was defined as the use of 5 or more medications including COPD medications [24–26].

Statistical analysis

Data were analyzed using Statistical Package for Social Science (SPSS) software, version 27 (IBM Corp, Armonk, NY, USA). Population characteristics were presented as percentage for categorical variables and mean (SD) for continuous variables. Logistic regression analysis was used to identify predictors of polypharmacy. A confidence interval of 95% (P < 0.05) was applied to represent the statistical significance, and the level of significance was predetermined as 5%.

Ethical approval and consent to participate

This study was approved by the institutional ethics board at the Ministry of Health in Saudi Arabia (No. H-02-K-076–0523-951). Patients were informed that their clinical data will be used for clinical or research purposes with keeping all their personal information confidential. The need for written informed consent was waived by the ethics committee due to the retrospective nature of the study. All procedures were performed according to the Helsinki declaration.

Results

Patients’ baseline characteristics

The study sample included a total of 705 patients. The majority of the study sample were males (60%). More than 70% of the study sample were either smokers or ex-smokers. The mean age of the study were 65 years. Details of patients' baseline characteristics are listed in Table 1. Table 1 Patients' baseline characteristics (N = 705)

Variable	Frequency	Percentage	
Gender	
 Males	425	60.3%	
Mean age (Standard deviation (SD)) years	65.4 (25.3) years	
Mean Body Mass Index (BMI) (Standard deviation (SD)) kg/cm2	29.2 (6.8) kg/cm2	
Smoking status	
 Non-smoker	182	25.8%	
 Ex-smoker	258	36.5%	
 Current smoker	265	37.5%	
Receive home care	
 Yes	55	7.8%	
Percentage of Comorbidities among COPD	
 Yes	482	68.4%	
 Hypertension	287	40.3%	
 Diabetes mellitus	288	40.9%	
 Peptic ulcer	186	26.4%	
 Ischemic heart disease	135	19.1%	
 Obstructive sleep apnea (OSA)	92	13.0%	
 Heart failure	65	9.2%	
 Chronic kidney disease	40	5.7%	
 Cerebrovascular accident or stroke	38	5.4%	
 Tuberculosis	32	4.5%	
 Connective tissue diseases	23	3.3%	
 Tumour or malignancy	21	2.9%	
 Hemiplegia	16	2.3%	
 Peripheral vascular diseases	11	1.6%	
 Dementia	9	1.3%	
 Liver disease	4	0.6%	
 AIDS/HIV	2	0.3%	
 Rheumatological disease	1	0.1%	
Hospital admission due to COPD exacerbations in the past two years	
 Yes	263	37.3%	
ICU hospital admission due to COPD exacerbations in the past two years	
 Yes	84	12.4%	

Comorbidity characteristics

The majority of the study population had comorbid diseases (68%). Diabetes was the highest co-morbid disease followed by hypertension, peptic ulcer diseases and ischemic heart diseases, respectively (40.9%, 40.3%, 26.4%, 19.1%). Details are listed in Table 1.

Medications use history

Around 55% of the study sample had polypharmacy. The most commonly prescribed respiratory medication was the Short acting beta agonist (SABA) 90% followed by the Long-acting muscarinic agonist (LAMA) 80%, Long-acting beta agonist (LABA) 60%, and Inhaled corticosteroid (ICS) 55%. Around 55% of the study population use 5 or more medications concomitantly. The highest concomitant medications used with COPD medications were antihypertensive medications, followed by antidiabetic medications 39%, proton pump inhibitors 27%, antihyperlipidemic 26%, and antiplatelet medications 21%, respectively. Details of medications history are listed in Table 2. Table 2 Most common prescribed respiratory medication (N = 705)

Variable	Frequency	Percentage	
Patients on polypharmacy (defined as 5 or more medications including COPD medications)	
 Yes	389	55.2%	
 Short acting beta agonist (SABA)	640	90.8%	
 Long-acting muscarinic agonist (LAMA)	567	80.4%	
 Long-acting beta agonist (LABA)	418	59.3%	
 Inhaled corticosteroid (ICS)	390	55.3%	
 Systematic corticosteroids	139	19.7%	
 Home oxygen and BIPAP	55	7.8%	
 Home oxygen	37	5.2%	
 Oral antidiabetic agents or insulin	279	39.6%	
 Antiplatelet	151	21.4%	
 Anticoagulants	45	6.4%	
 Antihypertensive	288	40.9%	
 Anti HF	76	10.8%	
 Antihyperlipidemic	182	25.9%	
 Antipsychotic and antidepressants	54	7.7%	
 Proton pump inhibitors	190	27.0%	
 H2 blockers	8	1.1%	
 Osteoporosis drugs	51	7.2%	
Oxygen	95	13.5%	
BIPAP	61	8.7%	
H2 blockers Histamine blockers, BIPAP Bilevel positive airway pressure

Predictors of polypharmacy

Females were significantly less likely to be on polypharmacy compared to males (OR = 0.68, 95% CI = [0.50–0.92], P-value = 0.012). On the other hand, older patients aged 65.4 or more (OR = 2.31, 95% CI = [1.71–3.14], P-value ≤ 0.001), those with high BMI (≥ 29.2) (OR = 1.42, 95% CI = [1.05–1.92], P-value = 0.024), current smokers (OR = 1.9, 95% CI = [1.39–2.62], P-value ≤ 0.001), those who are receiving home care (OR = 5.29, 95% CI = [2.46–11.37], P-value ≤ 0.001), those who have comorbidities (OR = 19.74, 95% CI = [12.70–30.68], P-value ≤ 0.001), and those who had hospital admission history(OR = 16.60, 95% CI = [4.58–9.49], P-value ≤ 0.001) or ICU admission history (OR = 27.44, 95% CI = [8.58–87.79], P-value ≤ 0.001) were significantly more likely to be on polypharmacy (p ≤ 0.05). Details of predictors of polypharmacy are listed in Table 3. Table 3 Binary logistic regression analysis (N = 705)

Variable	Odd ratio	
Gender	
 Females (Reference category)	1.00	
 Males	0.68 (0.50–0.92)	0.012	
Mean age (Standard deviation (SD)) years	
 Age ≤ 65.4 (25.3) years	1.00	
 Age ≥ 65.4 (25.3) years	2.31 (1.71–3.14)	 ≤ 0.001	
Mean Body Mass Index (BMI) (Standard deviation (SD)) kg/cm2	
 BMI ≤ 29.2 (6.8) kg/cm2	1.00	
 BMI ≥ 29.2 (6.8) kg/cm2	1.42 (1.05–1.92)	0.024	
Smoking status	
 Non-smoker (Reference category)	1.00	
 Ex-smoker	0.29 (0.21–0.40)	 ≤ 0.001	
 Current smoker	1.91 (1.39–2.62)	 ≤ 0.001	
Receive home care	
 No (Reference category)	1.00	
 Yes	5.29 (2.46–11.37)	 ≤ 0.001	
Comorbidities	
 No (Reference category)	1.00	
 Yes	19.74 (12.70–30.68)	 ≤ 0.001	
Hospital admission due to COPD in the past two years	
 No (Reference category)	1.00	
 Yes	6.60 (4.58–9.49)	 ≤ 0.001	
ICU hospital admission due to COPD in the past two years	
 No (Reference category)	1.00	
 Yes	27.44 (8.58–87.79)	 ≤ 0.001	

Discussion

To the best of our knowledge, this study is the first to investigate the prevalence of polypharmacy and comorbidities among COPD patients in the population of the Middle East. Our study revealed that polypharmacy and comorbidities are common among COPD patients. Patients with advanced age, elevated BMI, current smokers, long-term oxygen therapy, multiple comorbidities, and frequent hospital or ICU admissions were more likely to be on polypharmacy.

In our study, we found that comorbid conditions were common among COPD patients, as 68.4% of 705 COPD patients reported having comorbid conditions, the majority of which were hypertension (40.7%), diabetes mellitus (30.9%), peptic ulcer disease (26.4%), and ischemic heart disease (19.1%). According to a previous systematic review of 29 studies from Europe and North America, patients with COPD had a two- to five-fold higher risk of developing major cardiovascular disease types such as ischemic heart disease, cardiac dysrhythmia, heart failure, diseases of the pulmonary circulation, and arterial diseases [12]. They also had a roughly one-third higher risk of developing hypertension and diabetes [12]. Comorbid diseases are frequently present in COPD patients, according to an observational, cross-sectional multicentre study conducted in Spain with 866 COPD patients involved [27]. The most prevalent comorbidities across all groups of COPD were systemic hypertension (57.1%), followed by hyperlipidaemia (33.3%) and diabetes mellitus (31.1%) [27]. In addition, patients with COPD have an increased risk of developing mental health issue, and the prevalence of anxiety and depression is high among patients with COPD. This was also highlighted in our study which showed that around (7.7%) were utilising antipsychotic and/or antidepressants medications, which may provide a reflection of the mental health profile of the study population. All studies support our findings that comorbidities are prevalent among COPD patients, with variations that could be attributed to the difference in sample size or the populations that each study included; while the other study included people from Europe, North America, and Spain, ours included people from the Middle East.

In the present study, 55.2% of 705 COPD patients reported being on polypharmacy (≥ 5 medications). A previous observational, cross-sectional, and multicentre study conducted in Spain and included 398 patients showed a total of 224 (56.3%) patients presented polypharmacy and 22 (5.5%) excessive polypharmacy (≥ 10 medications) [28]. Another observational, cross-sectional, and multicentre study conducted in England, Scotland, and Wales and included 8317 self-reported COPD patients found that more than half (52%) reported polypharmacy and 15% reported excessive polypharmacy [4].

Our study revealed that short-acting beta-agonists (SABA) account for 90% of all medications taken, followed by long-acting muscarinic agonists (LAMA) at 80%, long-acting beta agonists (LABA) at 60%, inhaled corticosteroids (ICS) at 55%, antihypertensive drugs at 40.9%, oral diabetes medications at 39.6%, proton pump inhibitors at 27%, anti-hyperlipidemia at 25%, and antiplatelet at 21.4%, respectively, and they are compatible with the results of common comorbidities.

In our study, we discovered that individuals who were older had a higher BMI, and were current smokers had a higher likelihood of being on multiple medications. This conclusion could be explained by the fact that older individuals [4, 29, 30], obese or high BMI individuals [31–37], and current smokers [38–42] typically have other concomitant illnesses, and patients with comorbidity are more likely to get multi-drug therapy [28, 43–45]. Moreover, we found that polypharmacy is more prevalent in patients who have a history of hospitalization or ICU admission which could be explained by the fact that they are regularly admitted due to a severe illness course or the presence of concomitant conditions. A prior study found that patients with acute COPD exacerbations who were hospitalized received a mean of five prescription medicines prior to admission, and that number increased after discharge. [28] Comorbidities, particularly heart failure, and poor lung function are the conditions linked to higher pharmaceutical use [28].

COPD is associated with deteriorating health outcomes and a poorer quality of life [46]. Furthermore, comorbidity worsens COPD prognosis since a higher number of comorbidities is associated with a higher risk of mortality [47]. Polypharmacy or Complex pharmacotherapy is a major factor in nonadherence [48–50], increased risk of drug- to-drug and drug- to-disease interactions [4, 51–58], poor disease control [59], and significant cost of illness [60]. Yet, there are no clear guidelines for the optimum approach for treating individuals with comorbidity, which poses a problem for healthcare systems [61]. As a result, clinicians have little information or evidence on how to integrate care decisions for patients with various chronic illnesses. [61, 62].

There hasn't been a prior study in the Middle East that examines the prevalence of polypharmacy and comorbidities among COPD patients. In addition, we collected data on comorbidities using the Charlson Comorbidity Index. On the other hand, it is important to take into account some of our study's limitations. First, the patients whose data were gathered were admitted to internal medicine departments. Patients with COPD in these departments tend to be older and have more concomitant conditions. This might prevent our findings from being generalized outside of this setting. Second, the study had a limited sample size and was conducted in a single institution. Third, due to the nature of retrospective cross-sectional study design, a causal relationship cannot be determined from the study's findings. In addition, we were unable to investigate the quality of life, medications adherence, and drug-drug interactions of patients with COPD, and we urge for future research to address these important outcomes. Fourth, we did not investigate the prevalence of each comorbid conditions based on the GOLD-COPD severity scale, and if there is any association between the COPD severity and behaviour of each disease prevalence separately. Lastly, our study population had less prevalent psychiatric diseases compared to the published data likely attributed to our method utilized for data collection, namely Charlson Comorbidity Index.

Conclusion

Polypharmacy is common among patients with COPD. Patients with high BMI, previous ICU hospitalization and older age are more likely to have polypharmacy. Future analytical studies are warranted to investigate outcomes in patients with COPD and polypharmacy.

Acknowledgements

NA.

Authors’ contributions

Conceptualization, HA Data curation, AYN, OB and HA Formal analysis, AYN and HA; Investigation, AYN and HA; Methodology, HA; Project administration, OB and HA; Resources, OB and HA; Supervision, HA; Validation, AYN and HA; Writing original draft, AYN, DA, SA, JS, SA, AA and HA; Writing – review & editing, All authors.

Funding

NA.

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Declarations

Ethics approval and consent to participate

The ethics committee of the Ministry of Health in Saudi Arabia approved the study and waived informed consent due to the retrospective nature of the study (approval No. H-02-K-076–0523-951). All procedures were performed according to the Helsinki declaration.

Consent for publication

NA.

Competing interests

The authors declare no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
==== Refs
References

1. World Health Organization. Chronic obstructive pulmonary disease (COPD) 2023 Available from: https://www.who.int/news-room/fact-sheets/detail/chronic-obstructive-pulmonary-disease-(copd.
2. Ruvuna L Sood A Epidemiology of chronic obstructive pulmonary disease Clin Chest Med 2020 41 3 315 327 10.1016/j.ccm.2020.05.002 32800187
Ruvuna L, Sood A. Epidemiology of chronic obstructive pulmonary disease. Clin Chest Med. 2020;41(3):315–27.32800187 10.1016/j.ccm.2020.05.002
3. Venkatesan P GOLD report: 2022 update Lancet Respir Med 2022 10 2 1 12 10.1016/S2213-2600(21)00561-0 34973209
Venkatesan P. GOLD report: 2022 update. Lancet Respir Med. 2022;10(2):1–12.34973209 10.1016/S2213-2600(21)00561-0
4. Hanlon P Nicholl BI Jani BD McQueenie R Lee D Gallacher KI Examining patterns of multimorbidity, polypharmacy and risk of adverse drug reactions in chronic obstructive pulmonary disease: a cross-sectional UK Biobank study BMJ Open 2018 8 1 1 17 10.1136/bmjopen-2017-018404
Hanlon P, Nicholl BI, Jani BD, McQueenie R, Lee D, Gallacher KI, et al. Examining patterns of multimorbidity, polypharmacy and risk of adverse drug reactions in chronic obstructive pulmonary disease: a cross-sectional UK Biobank study. BMJ Open. 2018;8(1):1–17.10.1136/bmjopen-2017-018404
5. Divo M Celli BR Multimorbidity in patients with chronic obstructive pulmonary disease Clin Chest Med 2020 41 3 405 419 10.1016/j.ccm.2020.06.002 32800195
Divo M, Celli BR. Multimorbidity in patients with chronic obstructive pulmonary disease. Clin Chest Med. 2020;41(3):405–19.32800195 10.1016/j.ccm.2020.06.002
6. Valderas JM Starfield B Sibbald B Salisbury C Roland M Defining comorbidity: implications for understanding health and health services Ann Fam Med 2009 7 4 357 363 10.1370/afm.983 19597174
Valderas JM, Starfield B, Sibbald B, Salisbury C, Roland M. Defining comorbidity: implications for understanding health and health services. Ann Fam Med. 2009;7(4):357–63.19597174 10.1370/afm.983
7. Lee AL Goldstein RS Gastroesophageal reflux disease in COPD: links and risks Int J Chron Obstruct Pulmon Dis 2015 1 1 1935 1949 10.2147/COPD.S77562
Lee AL, Goldstein RS. Gastroesophageal reflux disease in COPD: links and risks. Int J Chron Obstruct Pulmon Dis. 2015;1(1):1935–49.10.2147/COPD.S77562
8. Vanfleteren L Spruit MA Wouters EFM Franssen FME Management of chronic obstructive pulmonary disease beyond the lungs Lancet Respir Med 2016 4 11 911 924 10.1016/S2213-2600(16)00097-7 27264777
Vanfleteren L, Spruit MA, Wouters EFM, Franssen FME. Management of chronic obstructive pulmonary disease beyond the lungs. Lancet Respir Med. 2016;4(11):911–24.27264777 10.1016/S2213-2600(16)00097-7
9. Agusti A Calverley PM Celli B Coxson HO Edwards LD Lomas DA Characterisation of COPD heterogeneity in the ECLIPSE cohort Respir Res 2010 11 1 1 13 10.1186/1465-9921-11-122 20047687
Agusti A, Calverley PM, Celli B, Coxson HO, Edwards LD, Lomas DA, et al. Characterisation of COPD heterogeneity in the ECLIPSE cohort. Respir Res. 2010;11(1):1–13.20047687 10.1186/1465-9921-11-122
10. Panagioti M Scott C Blakemore A Coventry PA Overview of the prevalence, impact, and management of depression and anxiety in chronic obstructive pulmonary disease Int J Chron Obstruct Pulmon Dis 2014 5 3 1289 1306
Panagioti M, Scott C, Blakemore A, Coventry PA. Overview of the prevalence, impact, and management of depression and anxiety in chronic obstructive pulmonary disease. Int J Chron Obstruct Pulmon Dis. 2014;5(3):1289–306.
11. Rabe KF Hurst JR Suissa S Cardiovascular disease and COPD: dangerous liaisons? Eur Respir Rev 2018 27 149 1 17 10.1183/16000617.0057-2018
Rabe KF, Hurst JR, Suissa S. Cardiovascular disease and COPD: dangerous liaisons? Eur Respir Rev. 2018;27(149):1–17.10.1183/16000617.0057-2018
12. Chen W Thomas J Sadatsafavi M FitzGerald JM Risk of cardiovascular comorbidity in patients with chronic obstructive pulmonary disease: a systematic review and meta-analysis Lancet Respir Med 2015 3 8 631 639 10.1016/S2213-2600(15)00241-6 26208998
Chen W, Thomas J, Sadatsafavi M, FitzGerald JM. Risk of cardiovascular comorbidity in patients with chronic obstructive pulmonary disease: a systematic review and meta-analysis. Lancet Respir Med. 2015;3(8):631–9.26208998 10.1016/S2213-2600(15)00241-6
13. Rennard SI Locantore N Delafont B Tal-Singer R Silverman EK Vestbo J Identification of five chronic obstructive pulmonary disease subgroups with different prognoses in the ECLIPSE cohort using cluster analysis Ann Am Thorac Soc 2015 12 3 303 312 10.1513/AnnalsATS.201403-125OC 25642832
Rennard SI, Locantore N, Delafont B, Tal-Singer R, Silverman EK, Vestbo J, et al. Identification of five chronic obstructive pulmonary disease subgroups with different prognoses in the ECLIPSE cohort using cluster analysis. Ann Am Thorac Soc. 2015;12(3):303–12.25642832 10.1513/AnnalsATS.201403-125OC
14. Putcha N Drummond MB Wise RA Hansel NN Comorbidities and chronic obstructive pulmonary disease: prevalence, influence on outcomes, and management Semin Respir Crit Care Med 2015 36 4 575 591 10.1055/s-0035-1556063 26238643
Putcha N, Drummond MB, Wise RA, Hansel NN. Comorbidities and chronic obstructive pulmonary disease: prevalence, influence on outcomes, and management. Semin Respir Crit Care Med. 2015;36(4):575–91.26238643 10.1055/s-0035-1556063
15. Mirza S Clay RD Koslow MA Scanlon PD COPD guidelines: a review of the 2018 GOLD report Mayo Clin Proc 2018 93 10 1488 1502 10.1016/j.mayocp.2018.05.026 30286833
Mirza S, Clay RD, Koslow MA, Scanlon PD. COPD guidelines: a review of the 2018 GOLD report. Mayo Clin Proc. 2018;93(10):1488–502.30286833 10.1016/j.mayocp.2018.05.026
16. Singh D Agusti A Anzueto A Barnes PJ Bourbeau J Celli BR Global strategy for the diagnosis, management, and prevention of chronic obstructive lung disease: the GOLD science committee report 2019 Eur Respir J 2019 53 5 1 15 10.1183/13993003.00164-2019
Singh D, Agusti A, Anzueto A, Barnes PJ, Bourbeau J, Celli BR, et al. Global strategy for the diagnosis, management, and prevention of chronic obstructive lung disease: the GOLD science committee report 2019. Eur Respir J. 2019;53(5):1–15.10.1183/13993003.00164-2019
17. Masnoon N Shakib S Kalisch-Ellett L Caughey GE What is polypharmacy? A systematic review of definitions BMC Geriatr 2017 17 1 1 23 10.1186/s12877-017-0621-2 28049446
Masnoon N, Shakib S, Kalisch-Ellett L, Caughey GE. What is polypharmacy? A systematic review of definitions. BMC Geriatr. 2017;17(1):1–23.28049446 10.1186/s12877-017-0621-2
18. Miravitlles M Ferrer M Pont A Zalacain R Alvarez-Sala JL Masa F Effect of exacerbations on quality of life in patients with chronic obstructive pulmonary disease: a 2 year follow up study Thorax 2004 59 5 387 395 10.1136/thx.2003.008730 15115864
Miravitlles M, Ferrer M, Pont A, Zalacain R, Alvarez-Sala JL, Masa F, et al. Effect of exacerbations on quality of life in patients with chronic obstructive pulmonary disease: a 2 year follow up study. Thorax. 2004;59(5):387–95.15115864 10.1136/thx.2003.008730
19. Stöber A Lutter JI Schwarzkopf L Kirsch F Schramm A Vogelmeier CF Impact of lung function and exacerbations on health-related quality of life in COPD patients within one year: real-world analysis based on claims data Int J Chron Obstruct Pulmon Dis 2021 16 1 2637 2651 10.2147/COPD.S313711 34588773
Stöber A, Lutter JI, Schwarzkopf L, Kirsch F, Schramm A, Vogelmeier CF, et al. Impact of lung function and exacerbations on health-related quality of life in COPD patients within one year: real-world analysis based on claims data. Int J Chron Obstruct Pulmon Dis. 2021;16(1):2637–51.34588773 10.2147/COPD.S313711
20. Berry CE Wise RA Mortality in COPD: causes, risk factors, and prevention COPD 2010 7 5 375 382 10.3109/15412555.2010.510160 20854053
Berry CE, Wise RA. Mortality in COPD: causes, risk factors, and prevention. COPD. 2010;7(5):375–82.20854053 10.3109/15412555.2010.510160
21. Alqahtani JS Prevalence, incidence, morbidity and mortality rates of COPD in Saudi Arabia: rends in burden of COPD from 1990 to 2019 PLoS ONE 2022 17 5 1 12 10.1371/journal.pone.0268772
Alqahtani JS. Prevalence, incidence, morbidity and mortality rates of COPD in Saudi Arabia: rends in burden of COPD from 1990 to 2019. PLoS ONE. 2022;17(5):1–12.10.1371/journal.pone.0268772
22. Hospital MoHANS. Al Noor Specialist Hospital. 2023. Available from: http://nsh.med.sa/Pages/AboutUs.aspx#.
23. Naser AY Dairi MS Alwafi H Ashoor DS Qadus S Aldhahir AM The rate of ward to intensive care transfer and its predictors among hospitalized COPD patients, a retrospective study in a local tertiary center in Saudi Arabia BMC Pulm Med 2023 23 1 1 14 10.1186/s12890-023-02775-z 36597085
Naser AY, Dairi MS, Alwafi H, Ashoor DS, Qadus S, Aldhahir AM, et al. The rate of ward to intensive care transfer and its predictors among hospitalized COPD patients, a retrospective study in a local tertiary center in Saudi Arabia. BMC Pulm Med. 2023;23(1):1–14.36597085 10.1186/s12890-023-02775-z
24. Varghese D IC, Haseer Koya H. Polypharmacy. Treasure Island (FL). 2023. Available from: https://pubmed.ncbi.nlm.nih.gov/30422548/.
25. Anne D Halli-Tierney CS Carroll D Polypharmacy: evaluating risks and deprescribing Am Fam Physician 2019 1 100 1 11
Anne D, Halli-Tierney CS, Carroll D. Polypharmacy: evaluating risks and deprescribing. Am Fam Physician. 2019;1(100):1–11.
26. Masnoon N Shakib S Kalisch-Ellett L Caughey GE What is polypharmacy? A systematic review of definitions BMC Geriatr 2017 17 1 1 23 10.1186/s12877-017-0621-2 28049446
Masnoon N, Shakib S, Kalisch-Ellett L, Caughey GE. What is polypharmacy? A systematic review of definitions. BMC Geriatr. 2017;17(1):1–23.28049446 10.1186/s12877-017-0621-2
27. Echave-Sustaeta JM Comeche Casanova L Cosio BG Soler-Cataluña JJ Garcia-Lujan R Ribera X Comorbidity in chronic obstructive pulmonary disease. Related to disease severity Int J Chron Obstruct Pulmon Dis 2014 1 1 1307 14 10.2147/COPD.S71849
Echave-Sustaeta JM, Comeche Casanova L, Cosio BG, Soler-Cataluña JJ, Garcia-Lujan R, Ribera X. Comorbidity in chronic obstructive pulmonary disease. Related to disease severity. Int J Chron Obstruct Pulmon Dis. 2014;1(1):1307–14.10.2147/COPD.S71849
28. Díez-Manglano J Barquero-Romero J Mena PA Recio-Iglesias J Cabrera-Aguilar J López-García F Polypharmacy in patients hospitalised for acute exacerbation of COPD Eur Respir J 2014 44 3 791 794 10.1183/09031936.00014814 24833769
Díez-Manglano J, Barquero-Romero J, Mena PA, Recio-Iglesias J, Cabrera-Aguilar J, López-García F, et al. Polypharmacy in patients hospitalised for acute exacerbation of COPD. Eur Respir J. 2014;44(3):791–4.24833769 10.1183/09031936.00014814
29. Chetty U McLean G Morrison D Agur K Guthrie B Mercer SW Chronic obstructive pulmonary disease and comorbidities: a large cross-sectional study in primary care Br J Gen Pract 2017 67 658 321 328 10.3399/bjgp17X690605 28663429
Chetty U, McLean G, Morrison D, Agur K, Guthrie B, Mercer SW. Chronic obstructive pulmonary disease and comorbidities: a large cross-sectional study in primary care. Br J Gen Pract. 2017;67(658):321–8.28663429 10.3399/bjgp17X690605
30. Koper D Kamenski G Flamm M Böhmdorfer B Sönnichsen A Frequency of medication errors in primary care patients with polypharmacy Fam Pract 2013 30 3 313 319 10.1093/fampra/cms070 23132894
Koper D, Kamenski G, Flamm M, Böhmdorfer B, Sönnichsen A. Frequency of medication errors in primary care patients with polypharmacy. Fam Pract. 2013;30(3):313–9.23132894 10.1093/fampra/cms070
31. Basques BA Bohl DD Golinvaux NS Leslie MP Baumgaertner MR Grauer JN Postoperative length of stay and 30-day readmission after geriatric hip fracture: an analysis of 8434 patients J Orthop Trauma 2015 29 3 115 10.1097/BOT.0000000000000222
Basques BA, Bohl DD, Golinvaux NS, Leslie MP, Baumgaertner MR, Grauer JN. Postoperative length of stay and 30-day readmission after geriatric hip fracture: an analysis of 8434 patients. J Orthop Trauma. 2015;29(3):115.10.1097/BOT.0000000000000222
32. Basques BA Varthi AG Golinvaux NS Bohl DD Grauer JN Patient characteristics associated with increased postoperative length of stay and readmission after elective laminectomy for lumbar spinal stenosis Spine 2014 39 10 1 18 10.1097/BRS.0000000000000276 24158180
Basques BA, Varthi AG, Golinvaux NS, Bohl DD, Grauer JN. Patient characteristics associated with increased postoperative length of stay and readmission after elective laminectomy for lumbar spinal stenosis. Spine. 2014;39(10):1–18.24158180 10.1097/BRS.0000000000000276
33. Pugely AJ Callaghan JJ Martin CT Cram P Gao Y Incidence of and risk factors for 30-day readmission following elective primary total joint arthroplasty: analysis from the ACS-NSQIP J Arthroplasty 2013 28 9 1499 1504 10.1016/j.arth.2013.06.032 23891054
Pugely AJ, Callaghan JJ, Martin CT, Cram P, Gao Y. Incidence of and risk factors for 30-day readmission following elective primary total joint arthroplasty: analysis from the ACS-NSQIP. J Arthroplasty. 2013;28(9):1499–504.23891054 10.1016/j.arth.2013.06.032
34. Clement RC Derman PB Graham DS Speck RM Flynn DN Levin LS Risk factors, causes, and the economic implications of unplanned readmissions following total hip arthroplasty J Arthroplasty 2013 28 8 7 10 10.1016/j.arth.2013.04.055 23953964
Clement RC, Derman PB, Graham DS, Speck RM, Flynn DN, Levin LS, et al. Risk factors, causes, and the economic implications of unplanned readmissions following total hip arthroplasty. J Arthroplasty. 2013;28(8):7–10.23953964 10.1016/j.arth.2013.04.055
35. Paxton EW Inacio MC Singh JA Love R Bini SA Namba RS Are there modifiable risk factors for hospital readmission after total hip arthroplasty in a US healthcare system? Clin Orthop Related Res® 2015 4731 1 3446 55 10.1007/s11999-015-4278-x
Paxton EW, Inacio MC, Singh JA, Love R, Bini SA, Namba RS. Are there modifiable risk factors for hospital readmission after total hip arthroplasty in a US healthcare system? Clin Orthop Related Res®. 2015;4731(1):3446–55.10.1007/s11999-015-4278-x
36. Zhang JQ Curran T McCallum JC Wang L Wyers MC Hamdan AD Risk factors for readmission after lower extremity bypass in the American College of Surgeons National Surgery Quality Improvement Program J Vasc Surg 2014 59 5 1331 1339 10.1016/j.jvs.2013.12.032 24491239
Zhang JQ, Curran T, McCallum JC, Wang L, Wyers MC, Hamdan AD, et al. Risk factors for readmission after lower extremity bypass in the American College of Surgeons National Surgery Quality Improvement Program. J Vasc Surg. 2014;59(5):1331–9.24491239 10.1016/j.jvs.2013.12.032
37. Hannan EL Zhong Y Lahey SJ Culliford AT Gold JP Smith CR 30-day readmissions after coronary artery bypass graft surgery in New York State JACC 2011 4 5 569 576 21596331
Hannan EL, Zhong Y, Lahey SJ, Culliford AT, Gold JP, Smith CR, et al. 30-day readmissions after coronary artery bypass graft surgery in New York State. JACC. 2011;4(5):569–76.21596331
38. Basques BA Gardner EC Varthi AG Fu MC Bohl DD Golinvaux NS Risk factors for short-term adverse events and readmission after arthroscopic meniscectomy: does age matter? Am J Sports Med 2015 43 1 169 175 10.1177/0363546514551923 25294869
Basques BA, Gardner EC, Varthi AG, Fu MC, Bohl DD, Golinvaux NS, et al. Risk factors for short-term adverse events and readmission after arthroscopic meniscectomy: does age matter? Am J Sports Med. 2015;43(1):169–75.25294869 10.1177/0363546514551923
39. Lovecchio F Farmer R Souza J Khavanin N Dumanian GA Kim JY Risk factors for 30-day readmission in patients undergoing ventral hernia repair Surgery 2014 155 4 702 710 10.1016/j.surg.2013.12.021 24612622
Lovecchio F, Farmer R, Souza J, Khavanin N, Dumanian GA, Kim JY. Risk factors for 30-day readmission in patients undergoing ventral hernia repair. Surgery. 2014;155(4):702–10.24612622 10.1016/j.surg.2013.12.021
40. Catanzarite T Vieira B Qin C Milad MP Risk factors for unscheduled 30-day readmission after benign hysterectomy South Med J 2015 108 9 524 530 10.14423/SMJ.0000000000000341 26332476
Catanzarite T, Vieira B, Qin C, Milad MP. Risk factors for unscheduled 30-day readmission after benign hysterectomy. South Med J. 2015;108(9):524–30.26332476 10.14423/SMJ.0000000000000341
41. Jennings DL Petricca JC Yageman LA O’Dell K Kalus JS Predictors of rehospitalization after acute coronary syndromes Am J Health Syst Pharm 2006 63 4 367 372 10.2146/ajhp050243 16452522
Jennings DL, Petricca JC, Yageman LA, O’Dell K, Kalus JS. Predictors of rehospitalization after acute coronary syndromes. Am J Health Syst Pharm. 2006;63(4):367–72.16452522 10.2146/ajhp050243
42. El Solh AA Brewer T Okada M Bashir O Gough M Indicators of recurrent hospitalization for pneumonia in the elderly J Am Geriatr Soc 2004 52 12 2010 2015 10.1111/j.1532-5415.2004.52556.x 15571535
El Solh AA, Brewer T, Okada M, Bashir O, Gough M. Indicators of recurrent hospitalization for pneumonia in the elderly. J Am Geriatr Soc. 2004;52(12):2010–5.15571535 10.1111/j.1532-5415.2004.52556.x
43. Wehling M Multimorbidity and polypharmacy: how to reduce the harmful drug load and yet add needed drugs in the elderly? Proposal of a new drug classification: fit for the aged J Am Geriatr Soc 2009 57 3 560 561 10.1111/j.1532-5415.2009.02131.x 19278399
Wehling M. Multimorbidity and polypharmacy: how to reduce the harmful drug load and yet add needed drugs in the elderly? Proposal of a new drug classification: fit for the aged. J Am Geriatr Soc. 2009;57(3):560–1.19278399 10.1111/j.1532-5415.2009.02131.x
44. Teljeur C Smith SM Paul G Kelly A O’Dowd T Multimorbidity in a cohort of patients with type 2 diabetes Eur J Gen Pract 2013 19 1 17 22 10.3109/13814788.2012.714768 23432037
Teljeur C, Smith SM, Paul G, Kelly A, O’Dowd T. Multimorbidity in a cohort of patients with type 2 diabetes. Eur J Gen Pract. 2013;19(1):17–22.23432037 10.3109/13814788.2012.714768
45. Corsonello A Pedone C Corica F Incalzi RA Polypharmacy in elderly patients at discharge from the acute care hospital Ther Clin Risk Manag 2007 3 1 197 203 10.2147/tcrm.2007.3.1.197 18360627
Corsonello A, Pedone C, Corica F, Incalzi RA. Polypharmacy in elderly patients at discharge from the acute care hospital. Ther Clin Risk Manag. 2007;3(1):197–203.18360627 10.2147/tcrm.2007.3.1.197
46. Miravitlles M Ribera A Understanding the impact of symptoms on the burden of COPD Respir Res 2017 18 1 1 11 10.1186/s12931-017-0548-3 28049526
Miravitlles M, Ribera A. Understanding the impact of symptoms on the burden of COPD. Respir Res. 2017;18(1):1–11.28049526 10.1186/s12931-017-0548-3
47. Miller J Edwards L Agustí A Bakke P Calverley P Celli B Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE) investigators comorbidity, systemic inflammation and outcomes in the ECLIPSE cohort Respir Med 2013 107 9 1376 1384 10.1016/j.rmed.2013.05.001 23791463
Miller J, Edwards L, Agustí A, Bakke P, Calverley P, Celli B, et al. Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE) investigators comorbidity, systemic inflammation and outcomes in the ECLIPSE cohort. Respir Med. 2013;107(9):1376–84.23791463 10.1016/j.rmed.2013.05.001
48. Claxton AJ Cramer J Pierce C A systematic review of the associations between dose regimens and medication compliance Clin Ther 2001 23 8 1296 1310 10.1016/S0149-2918(01)80109-0 11558866
Claxton AJ, Cramer J, Pierce C. A systematic review of the associations between dose regimens and medication compliance. Clin Ther. 2001;23(8):1296–310.11558866 10.1016/S0149-2918(01)80109-0
49. Trotta MP Ammassari A Melzi S Zaccarelli M Ladisa N Sighinolfi L Treatment-related factors and highly active antiretroviral therapy adherence JAIDS Acquir Immune Defic Syndr 2002 31 1 S128 S131 10.1097/00126334-200212153-00008
Trotta MP, Ammassari A, Melzi S, Zaccarelli M, Ladisa N, Sighinolfi L, et al. Treatment-related factors and highly active antiretroviral therapy adherence. JAIDS Acquir Immune Defic Syndr. 2002;31(1):S128–31.10.1097/00126334-200212153-00008
50. Franssen FM Spruit MA Wouters EF Determinants of polypharmacy and compliance with GOLD guidelines in patients with chronic obstructive pulmonary disease Int J Chron Obstruct Pulmon Dis 2011 1 1 493 501 10.2147/COPD.S24443
Franssen FM, Spruit MA, Wouters EF. Determinants of polypharmacy and compliance with GOLD guidelines in patients with chronic obstructive pulmonary disease. Int J Chron Obstruct Pulmon Dis. 2011;1(1):493–501.10.2147/COPD.S24443
51. Willson MN Greer CL Weeks DL Medication regimen complexity and hospital readmission for an adverse drug event Ann Pharmacother 2014 48 1 26 32 10.1177/1060028013510898 24259639
Willson MN, Greer CL, Weeks DL. Medication regimen complexity and hospital readmission for an adverse drug event. Ann Pharmacother. 2014;48(1):26–32.24259639 10.1177/1060028013510898
52. Guthrie B Makubate B Hernandez-Santiago V Dreischulte T The rising tide of polypharmacy and drug-drug interactions: population database analysis 1995–2010 BMC Med 2015 13 1 1 10 10.1186/s12916-015-0322-7 25563062
Guthrie B, Makubate B, Hernandez-Santiago V, Dreischulte T. The rising tide of polypharmacy and drug-drug interactions: population database analysis 1995–2010. BMC Med. 2015;13(1):1–10.25563062 10.1186/s12916-015-0322-7
53. Bourgeois FT Shannon MW Valim C Mandl KD Adverse drug events in the outpatient setting: an 11-year national analysis Pharmacoepidemiol Drug Saf 2010 19 9 901 910 10.1002/pds.1984 20623513
Bourgeois FT, Shannon MW, Valim C, Mandl KD. Adverse drug events in the outpatient setting: an 11-year national analysis. Pharmacoepidemiol Drug Saf. 2010;19(9):901–10.20623513 10.1002/pds.1984
54. Johnell K Klarin I The relationship between number of drugs and potential drug-drug interactions in the elderly: a study of over 600 000 elderly patients from the Swedish prescribed drug register Drug Saf 2007 30 1 911 918 10.2165/00002018-200730100-00009 17867728
Johnell K, Klarin I. The relationship between number of drugs and potential drug-drug interactions in the elderly: a study of over 600 000 elderly patients from the Swedish prescribed drug register. Drug Saf. 2007;30(1):911–8.17867728 10.2165/00002018-200730100-00009
55. Bayliss EA Edwards AE Steiner JF Main DS Processes of care desired by elderly patients with multimorbidities Fam Pract 2008 25 4 287 293 10.1093/fampra/cmn040 18628243
Bayliss EA, Edwards AE, Steiner JF, Main DS. Processes of care desired by elderly patients with multimorbidities. Fam Pract. 2008;25(4):287–93.18628243 10.1093/fampra/cmn040
56. Veehof L Stewart R Meyboom-de Jong B Haaijer-Ruskamp F Adverse drug reactions and polypharmacy in the elderly in general practice Eur J Clin Pharmacol 1999 55 1 533 536 10.1007/s002280050669 10501824
Veehof L, Stewart R, Meyboom-de Jong B, Haaijer-Ruskamp F. Adverse drug reactions and polypharmacy in the elderly in general practice. Eur J Clin Pharmacol. 1999;55(1):533–6.10501824 10.1007/s002280050669
57. Kadam UT Potential health impacts of multiple drug prescribing for older people: a case-control study Br J Gen Pract 2011 61 583 128 130 10.3399/bjgp11X556263 21276339
Kadam UT. Potential health impacts of multiple drug prescribing for older people: a case-control study. Br J Gen Pract. 2011;61(583):128–30.21276339 10.3399/bjgp11X556263
58. Negewo NA Gibson PG Wark PA Simpson JL McDonald VM Treatment burden, clinical outcomes, and comorbidities in COPD: an examination of the utility of medication regimen complexity index in COPD Int J Chron Obstruct Pulmon Dis 2017 1 1 2929 2942 10.2147/COPD.S136256
Negewo NA, Gibson PG, Wark PA, Simpson JL, McDonald VM. Treatment burden, clinical outcomes, and comorbidities in COPD: an examination of the utility of medication regimen complexity index in COPD. Int J Chron Obstruct Pulmon Dis. 2017;1(1):2929–42.10.2147/COPD.S136256
59. Yeh A Shah-Manek B Lor KB Medication regimen complexity and A1C goal attainment in underserved adults with type 2 diabetes: a cross-sectional study Ann Pharmacother 2017 51 2 111 117 10.1177/1060028016673652 28042735
Yeh A, Shah-Manek B, Lor KB. Medication regimen complexity and A1C goal attainment in underserved adults with type 2 diabetes: a cross-sectional study. Ann Pharmacother. 2017;51(2):111–7.28042735 10.1177/1060028016673652
60. Johnson J Booman L Drug-related morbidity and mortality J Manag Care Pharm 1996 2 1 39 47
Johnson J, Booman L. Drug-related morbidity and mortality. J Manag Care Pharm. 1996;2(1):39–47.
61. Boyd CM Fortin M Future of multimorbidity research: how should understanding of multimorbidity inform health system design? Public Health Rev 2010 32 2 451 474 10.1007/BF03391611
Boyd CM, Fortin M. Future of multimorbidity research: how should understanding of multimorbidity inform health system design? Public Health Rev. 2010;32(2):451–74.10.1007/BF03391611
62. Loza E, Jover JA, Rodriguez L, Carmona L, Group ES, editors. Multimorbidity: prevalence, effect on quality of life and daily functioning, and variation of this effect when one condition is a rheumatic disease. Seminars in arthritis and rheumatism; 2009: Elsevier.
