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Scientific Reports
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10.1038/s41598-024-72856-4
Article
C reactive protein albumin ratio as a new predictor of postoperative delirium after cholecystectomy for acute cholecystitis
Nakatake Richi nakatakr@hirakata.kmu.ac.jp

12
Funatsuki Toshiya 3
Koshikawa Yosuke 3
Okuyama Tetsuya 2
Ishizaki Morihiko 1
Takekita Yoshiteru 3
Kato Masaki 3
Kitade Hiroaki 12
1 https://ror.org/001xjdh50 grid.410783.9 0000 0001 2172 5041 Department of Hepato-Biliary-Pancreatic Surgery, Kansai Medical University Medical Center, 10-15 Fumizono-Cho, Moriguchi, Osaka 573-1010 Japan
2 https://ror.org/001xjdh50 grid.410783.9 0000 0001 2172 5041 Department of Pancreatobiliary Surgery, Kansai Medical University, 2-5-1 Shin-Machiachi, Hirakata, Osaka 573-1010 Japan
3 https://ror.org/001xjdh50 grid.410783.9 0000 0001 2172 5041 Department of Neuropsychiatry, Kansai Medical University, 10-15 Fumizono-Cho, Moriguchi, Osaka 573-1010 Japan
17 9 2024
17 9 2024
2024
14 2170421 6 2024
11 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/.
Postoperative delirium (POD) is one of the most common complications of surgery. This study aimed to identify the risk factors for POD in patients undergoing cholecystectomy for acute cholecystitis. This retrospective study included 77 patients who underwent cholecystectomy for acute cholecystitis between January 2015, and December 2020. Multiple logistic regression analysis was used to identify the factors associated with the development of delirium as the primary endpoint. Patients were divided into POD (n = 18) and non-POD (n = 59) groups and their demographic features and clinical results were compared. A significant model associated with delirium onset was predicted (Nagelkerke’s R2 = 0.382), and the significantly correlated factors were C-reactive protein/albumin ratio (CAR), Subjective Global Assessment (SGA) score, and history of psychiatric disease. The predictive value of CAR for POD was evaluated using ROC analysis; the area under the curve of CAR was 0.731, with a cutoff value of 3.69. CAR, SGA score, and a history of psychiatric disease were identified as factors associated with the development of POD in patients with acute cholecystitis. In particular, the new preoperative evaluation of CAR may be beneficial as an assessment measure of the risk factor for the development of POD.

Keywords

Acute cholecystitis
C-reactive protein/albumin ratio
Postoperative delirium
Subjective Global Assessment
Subject terms

Risk factors
Biomarkers
Predictive markers
Medical research
Biomarkers
http://dx.doi.org/10.13039/501100001691 Japan Society for the Promotion of Science 23K08203 23K08203 23K08203 23K08203 Nakatake Richi Funatsuki Toshiya Okuyama Tetsuya Takekita Yoshiteru issue-copyright-statement© Springer Nature Limited 2024
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pmcIntroduction

Delirium is a common postoperative complication. postoperative delirium (POD) is transient and reversible in most cases but is associated with worse functional outcomes, increased complications, prolonged hospital stay, and mortality1–3. Numerous studies have demonstrated the detrimental effect of higher POD severity on short- and long-term outcomes4. Therefore, identifying patients at high risk for delirium and providing more attentive care to prevent POD are essential for improving postoperative clinical outcomes in the postoperative period. Multiple risk factors for POD have been identified, and Pisani et al. published an evidence-based consensus statement on the preoperative, intraoperative, and postoperative risk factors for POD5. Preoperative factors included advanced age, comorbidities, preoperative fasting and dehydration, hyponatremia or hypernatremia, and use of anticholinergic medications. Intraoperatively, the surgical site (abdomen or chest) and intraoperative bleeding were significant factors for POD. Pain was identified as a postoperative risk factor. However, there are a variety of risk factors for POD, depending on the disease and surgical technique used.

Acute cholecystitis can lead to serious complications and even death, if left untreated. For acute cholecystitis, the Tokyo Guidelines recommend cholecystectomy as soon as possible within 72 h to 1 week of onset6. However, the Tokyo Guidelines do not mention POD and the risk factors are not clear. Low BMI, a history of neuropsychiatric disease, hypo or hyperkalaemia, and prolonged operative time have been reported as significant risk factors for delirium after chronic and acute cholecystitis7. Despite the widespread use of cholecystectomy for acute cholecystitis, predictors of POD after cholecystectomy remain unclear. Therefore, this study aimed to evaluate the association between the increased incidence of POD after acute cholecystitis and the pre- and intraoperative predictors.

Materials and methods

Study design and patients

Patients who underwent cholecystectomy under general anesthesia between January 2015 and December 2020 at Kansai Medical University Medical Center were included. Patients with a pathological diagnosis of acute cholecystitis were included, and those with a diagnosis of cholelithiasis, chronic cholecystitis, and gallbladder polyps were excluded. Finally, the patients with a pathological diagnosis of acute cholecystitis were divided into POD and non-POD groups to compare their demographic characteristics and clinical outcomes.

Data collection

Patient demographics and perioperative variables were obtained from the medical records at our institution. Demographic variables included age, sex, pathology, acute cholecystitis severity6, Data on Charlson comorbidity index (CCI)8, body mass index (BMI), Subjective Global Assessment (SGA)9, Prognostic Nutritional Index (PNI = (10 × albumin (g/dL) + (0.005 × TLC: total lymphocyte count (mm3))10, American Society of Anesthesiologists (ASA) classification, number of hospital days, smoking, alcohol consumption, medical history (mental illness, diabetes mellitus (DM), hypertension (HTN), cardiovascular disease (CVD), cerebrovascular disease (CVA), pulmonary disease, renal disease), and perioperative benzodiazepine (BZD) medication use were included. Preoperative laboratory values included measures for white blood cells (WBC), C-reactive protein (CRP), aspartate transaminase (AST), alanine transaminase (ALT), gamma-GTP, serum albumin (ALB), and CRP/ALB ratio (CAR). Surgical variables included additional epidural anesthesia, time from diagnosis to surgery, surgery within 72 h of onset, operative time, blood loss, technique (open, laparoscopic, or laparotomy transition), drain use, and need for blood transfusion. Outcome measures included postoperative complications (except delirium), mortality, and length of hospital stay. POD data (calculated from the date of surgery to the date of discharge) were collected from medical and nursing records. POD was diagnosed by an experienced psychiatrist, T. F., in accordance with the delirium section of the Diagnostic and Statistical Manual of Mental Disorders, 5th Edition (DSM-5).

Statistical analysis

Results are expressed as mean ± standard deviation (SD), median (interquartile range), or number (percentage), as appropriate. Chi-squared or Fisher’s exact tests were used to compare categorical data. Variables with p < 0.05 in univariate analysis were included in the multivariate analysis by backward elimination. Multiple logistic regression analysis was used to identify risk factors for POD. Receiver Operating Characteristic (ROC) curve analysis was used to determine the cutoff value of CAR for POD. p < 0.05 was considered statistically significant. All data were obtained using SPSS Statistics (version 27.0; IBM Corp., Armonk, NY, USA).

Results

Basic characteristics and intraoperative parameters

We studied 531 patients; 77 with a pathological diagnosis of acute cholecystitis were included (Fig. 1). The patients were divided into POD (n = 18) and non-POD (n = 59) groups. The demographic data and perioperative variables of the study population are presented in Table 1. The total incidence of POD was 23.3% (18/77). The mean age of the patients was 75.6 ± 11.772 (range: 44–93) years for the POD group and 69.2 ± 13.292 (range: 27–93) years for the non-POD group. In the POD group, 18 patients (100%) had a history of alcohol consumption, whereas 45 patients (76.3) had a history of alcohol consumption in the non-POD group, a significant difference between the two groups (P = 0.022). For SGA, the measures were 2.56 ± 0.86 in the POD group and 1.86 ± 0.8 in the non-POD group, a significant difference between the two groups (P = 0.002). The POD group was discharged 16.56 ± 16.41 days postoperatively and the non-POD group was discharged after 13.88 ± 11.43 days, with no significant difference (p = 0.438).Fig. 1 Flowchart of the inclusion and exclusion process for patient enrollment in the study. A total of 531 patients were enrolled, and 77 patients who underwent cholecystectomy for acute cholecystitis were divided into the POD (n = 18) and non-POD (n = 59) groups.

Table 1 Demographic and clinical parameters of the POD and non-POD groups.

Characteristic	POD group	Non-POD group	P value	
(n = 18)	(n = 59)	
Age (years)	75.67 ± 11.772	69.27 ± 13.292	0.071	
Male/female (n)	11/7	41 / 18	0.506	
Smoking (n)	11 (61.1%)	34 (57.6%)	0.793	
Alcohol (n)	18 (100%)	45 (76.3%)	0.022	
Pathology				
Acute cholecystitis (n)	6 (33.3%)	30 (50.8%)	0.192	
Acute gangrenous cholecystitis (n)	12 (66.7%)	29 (49.2%)	0.192	
Acute cholecystitis severity				
None & Severity I (n)	0 (0%)	3 (5.1%)	0.108	
Severity II (n)	17 (94.4%)	56 (94.9%)	0.108	
Severity III (n)	1 (1.7%)	0 (0%)	0.108	
CCI	1.61 ± 1.50	1.63 ± 1.69	0.971	
Past history				
DM (n)	3 (16.7%)	16 (27.1%)	0.368	
HTN (n)	3 (16.7%)	18 (30.5%)	0.248	
CVD (n)	3 (16.7%)	15 (25.4%)	0.442	
CVA (n)	8 (44.4%)	16 (27.1%)	0.165	
Pulmonary disease (n)	3 (16.7%)	14 (23.7%)	0.527	
Renal disease (n)	2 (11.1%)	9 (15.3%)	0.66	
Abdominal surgery (n)	6 (33.3%)	11 (18.6%)	0.188	
Psychiatry (n)	8 (44.4%)	9 (15.3%)	0.014	
Periodic BZD intake (n)	7 (38.9%)	11 (18.6%)	0.076	
BMI (kg/m2)	22.07 ± 4.58	23.46 ± 4.10	0.227	
SGA	2.56 ± 0.86	1.86 ± 0.8	0.002	
PNI	30.95 ± 7.71	42.92 ± 25.08	0.074	
ASA-PS				
1	0 (0%)	3 (5.1%)	0.104	
2	10 (55.6%)	41 (69.5%)	0.104	
3	8 (44.4%)	14 (23.7%)	0.104	
4	0 (0%)	1 (1.7%)	0.104	
Time from diagnosis to surgery (hour)	104.17 ± 127.79	79.21 ± 64.89	0.275	
Less than 72 h from diagnosis to surgery (n)	10 (55.6%)	33 (55.9%)	0.978	
The operation time (min)	128.28 ± 28.58	132.81 ± 37.08	0.635	
Bleeding (ml)	224.61 ± 354.2	159.81 ± 243.18	0.38	
Blood transfusion (n)	2 (11.1%)	1 (1.7%)	0.231	
Additional epidural anesthesia (n)	0 (0%)	1 (1.7%)	0.457	
Additional abdominal drainage (n)	16 (88.9%)	53 (89.8%)	0.603	
Surgical technique				
Open (n)	7 (38.9%)	21 (35.6%)	0.457	
Laparoscopic (n)	11 (61.1%)	37 (62.7%)	0.457	
Laparotomy transition (n)	0 (0%)	1 (1.7%)	0.457	
Outcome measures				
Postoperative complications (n)	3 (16.7%)	10 (16.9%)	0.644	
Mortality (n)	0 (0%)	0 (0%)	-	
Hospital stay (days)	16.56 ± 16.41	13.88 ± 11.43	0.438	
p < 0.05 was considered statistically significant.

Laboratory measurements

The preoperative CRP and ALB levels and CAR for patients in the POD group were 23.36 ± 10.76 mg/L, 2.72 ± 0.61 g/L, and 8.97 ± 5.82, respectively, while those in the non-POD group had CRP of 14.37 ± 10.82 mg/L, ALB of 3.38 ± 0.76 g/L, and CAR of 4.71 ± 3.88. There were statistically significant differences in CRP and ALB levels and CAR between the two groups (all p < 0.001) (Table 2).Table 2 The laboratory test of the POD and non-POD groups.

Characteristic	POD group (n = 18)	Non-POD group (n = 59)	P value	
WBC (/μl)	13,894.44 ± 4797.85	13,469.49 ± 6616.97	0.801	
AST (U/l)	40.33 ± 33.66	49.05 ± 59.95	0.559	
ALT (U/l)	45 ± 56.26	47.29 ± 51.99	0.873	
r-GTP (U/l)	92.72 ± 125.96	114.53 ± 117.69	0.501	
ALB (g/L)	2.72 ± 0.61	3.38 ± 0.76	0.002	
CRP (mg/L)	23.36 ± 10.76	14.37 ± 10.82	0.003	
CAR	8.97 ± 5.82	4.71 ± 3.88	0.001	
p < 0.05 was considered statistically significant.

Risk factors for POD

Variables with p < 0.05 in univariate analysis (alcohol consumption, history of psychiatric disease, SGA score, and CAR) were included in the multivariate analysis by backward elimination. Finally, eight factors (age, sex, alcohol consumption, CCI, history of psychiatric disease, SGA score, CAR, and operative time) were included in the multivariate logistic regression model (forward selection (likelihood ratio), p < 0.001, Nagelkerke’s R2 = 0.382). Results showed that CAR (β = 0.15; odds ratio = 1.161; 95% confidence interval (CI), 1.006–1.341; P = 0.041), SGA score (β = 0.953; odds ratio = 2.546; 95% CI, 1.05–6.174; P = 0.039), and history of psychiatric disease (β = 1.568; odds ratio = 4.796; 95% CI, 1.276–18.026; P = 0.02) were the three independent risk factors for POD (Table 3).Table 3 Risk factors for POD.

	β	OR	95% CI		P value	
CAR	0.15	1.161	1.006	1.341	0.041	
SGA	0.935	2.546	1.05	6.174	0.039	
History of psychiatric disease	1.568	4.796	1.276	18.026	0.02	
p < 0.001, Nagelkerke’s R2 = 0.382. using the forward stepwise model.

Predictive value of CAR for POD

The predictive value of preoperative CAR for POD was evaluated by ROC analysis. As shown in Fig. 2, the area under the curve of CAR for POD was 0.731, with a cutoff value of 3.69, sensitivity of 94.1%, and specificity of 43.9% (95% CI, 0.608–0.853; P = 0.004). The positive likelihood ratios (+ LR) and negative likelihood ratios (− LR) were 1.676 and 0.134, respectively, which of the Area Under the Curve (AUC) value of CAR (AUC: 0.731) were superior to those of CRP (AUC: 0.709) and ALB (AUC: 0.26). Based on a cutoff value of 3.69, patients were classified into a high CAR group (CAR ≥ 3.69) and a low CAR group (CAR < 3.69) (Table 4).Fig. 2 (A) Comparison of CARs between POD and non-POD groups. POD, postoperative delirium; CAR, C-reactive protein to albumin ratio. P < 0.05 was considered statistically significant. (B) The predictive value of CAR for POD by ROC curve analysis. The AUC of CAR for POD was 0.731, with a cut-off value of 3.69, a sensitivity of 94.1%, and a specificity of 43.9% (95% CI: 0.608–0.853, P = 0.004).

Table 4 Comparison of the AUC for the three inflammation-based prognostic scores.

Variable	AUC	Youden’s	Predictive	Sensitivity	Specificity	PPV	NPV	P value	
(95%CI)	Index 	Cut off 	 (%)	(%) 	 (%)	 (%)	
CAR	0.731	0.38	3.6931	94.1	43.9	33.3	96.1	0.004	
(0.608–0.853)	
CRP	0.709	0.33	6.018	100	33.9	31.6	100	0.009	
(0.577–0.841)	
ALB	0.26	0.42	3.35	5.9	43.9	3	61	0.003	
(0.142–0.378)	
p < 0.05 was considered statistically significant.

Discussion

In terms of basic characteristics and intraoperative parameters, SGA score, alcohol consumption, and history of psychiatric disorders differed significantly between POD and non-POD groups. In laboratory measurements, there were significant differences between POD and non-POD groups in CRP and ALB levels and CAR. There were no significant differences in other background factors. In the Tokyo Guideline, mortality, complication rates, bile duct injury rates, and open conversion rates were lower for early (72 h to 1 week) cholecystectomy for acute cholecystitis compared to standby surgery6. However, there was no significant difference in the time elapsed from the onset of acute cholecystitis to surgery between the two groups. Furthermore, patients were classified according to whether surgery was performed within 72 h, and there was no difference in the incidence of POD when surgery was performed within 72 h of onset.

The results of current study in the multivariate logistic regression model showed that the CAR and SGA score were higher in patients with POD than in those without. Furthermore, patients with psychiatric disorders were at higher risk of developing POD. Malnutrition and a history of neuropsychiatric disorders have been reported as significant risk factors for POD after chronic and acute cholecystitis7.

Neuroinflammatory changes in the central nervous system have been proposed as an explanatory mechanism for the background factors of POD11. CRP level is one of the most common biomarkers for systemic inflammation. Some studies have shown that the CRP level is an independent risk factor for POD after hip surgery12, vascular surgery13, and laparoscopic surgery for colon cancer14. Another study reported high serum CRP levels preoperatively and on postoperative day 2 as potential predictors of POD in elderly patients after major noncardiac surgery.15 ALB level is frequently used to assess the nutritional status of patients undergoing surgery. Previous studies have shown that hypoalbuminemia is significantly associated with an increased risk of POD16, 17. Several studies have reported that severe preoperative hypoalbuminemia is a predictor of POD and worse outcomes in patients undergoing noncardiac surgery18. CRP and ALB levels can also predict morbidity, mortality, and poor outcomes, such as longer hospitalization and intensive care unit (ICU) stays, respectively; elevated CRP levels are associated with malignancy, sepsis, and inflammatory disease; and decreased ALB levels are associated with pre-existing medical conditions, liver failure, renal failure, and malnutrition due to pre-existing hepatic, and renal conditions and malnutrition19, 20. Preoperative nutritional status correlates with postoperative complications, including POD, strongly suggesting the importance of improving nutritional status as much as possible before surgery.

In contrast to changes in CRP and ALB levels alone, which are nonspecific as each is associated with multiple pathologies, CAR correlates with prognostic potential by more accurately reflecting the severity of nutrient deprivation and inflammation19–21. Previous studies have demonstrated the predictive ability of the CAR for morbidity, mortality, and other outcomes in various patients, including critically ill19, pre-transplant or cirrhotic22–24, postoperative20, 25, 26, and oncological patients.27, 28 The CAR has also been reported as a preoperative predictive indicator of POD in total knee29, 30 and hip30, 31 arthroplasty surgeries in elderly patients. In the present study, a preoperative CAR of 3.69 or higher was a risk factor for POD in acute cholecystitis with surgery.

POD occurs on postoperative days 2–53, 16 and prolongs hospital stay by 2–3 days and intensive care unit stay by 2 days32, 33 POD is associated with 7–10% surgery-related mortality, but has been reported to be 1% in patients without delirium34. In the POD group, all patients experienced disease onset within 24 h. In our study, there was no difference in surgery-related mortality, complications, or length of hospital stay. There were no cases of rehospitalization in either group. However, because early detection of POD is expected to reduce medical resources and increase patient well-being, a new preoperative evaluation of CAR may be beneficial as an assessment measure of the risk factor for the development of POD. Since CRP and ALB are common items in preoperative blood tests for patients with acute cholecystitis, we believe that there is a significant advantage to adding CAR as a preoperative evaluation item, as there is no direct burden on the patient or additional medical resources. For patients predicted to develop POD based on the calculated CAR values, multidisciplinary POD countermeasures from preoperative to immediate postoperative period may contribute to the reduction of factors that promote POD.

POD is caused by multiple factors and presents with various clinical syndromes and pathophysiological changes. Our understanding of delirium captures only a subset of these symptoms. Although many previous studies show an association between POD and inflammation indices, few have been disease-limited studies. By limiting the disease, specific background factors included in previous studies can be excluded. And since there is no literature on POD in only acute cholecystitis. To our knowledge, this is the first study to report preoperative CAR as a predictor of POD in patients undergoing cholecystectomy. A limitation of this study is that it was a retrospective, single-center study that needs to be validated in a prospective, multicenter study. Furthermore, the predictors were measured only preoperatively, ignoring their relationship with the longitudinal improvement or worsening of delirium for each patient. Some residual confounding factors (for example, sample selection bias and preoperative comorbidities) cannot be completely excluded. In particular, CRP may contribute to the improvement or worsening of delirium, as it may increase or decrease between the preoperative and postoperative periods. We improved the clinical pathway starting in 2022 to standardize the schedule of blood draws and items to observe the course of POD and biomarker variability. And by adding new blood collection items, we plan to conduct a more in-depth study for the next report. It would be interesting to investigate the dynamic changes in the CAR after surgery in future studies to investigate POD outcomes and CAR dynamics. On the other hand, the application of CAR to other acute diseases and hepatobiliary-pancreatic surgery with highly invasive may contribute by adding new depth to existing literature. Because this study was retrospective, the definition and severity of delirium may not have been accurately identified. The patients with low-activity delirium were included in the non-delirium group. It is unclear whether CAR in combination with other variables (such as IL-6 and TNF-α) can predict the risk of POD, and further studies are needed to validate the same. As both CRP and ALB are synthesized in the liver, an improved assessment of the exact relationship between liver dysfunction and serum CAR levels in acute cholecystitis is also a topic for future study.

Conclusions

In conclusion, preoperative CAR, preexisting psychiatric disorders, and SGA score may be promising predictors of POD after cholecystectomy for acute cholecystitis. In particular, the new preoperative evaluation of CAR may be beneficial as an assessment measure of the risk factor for the development of POD.

Abbreviations

POD Postoperative delirium

CAR C-reactive protein/albumin ratio

SGA Subjective global assessment

CCI Charlson comorbidity index

BMI Body mass index

PNI Prognostic nutritional index

TLC Total lymphocyte count

ASA-PS American society of anesthesiologists physical status

DM Diabetes mellitus

HTN Hypertension

CVD Cardiovascular disease

CVA Cerebrovascular disease

BZD Benzodiazepine

WBC White blood cells

CRP C-reactive protein

AST Aspartate transaminase

ALT Alanine transaminase

ALB Albumin

DSM-5 Diagnostic and statistical manual of mental disorders, 5th Edition

SD Standard deviation

ROC Receiver Operating Characteristic

CI Confidence interval

 + LR Positive likelihood ratios

 − LR Negative likelihood ratios

AUC Area under the curve

Acknowledgements

We would like to thank Editage (www.editage.com) for the English language editing.

Author contributions

Conception and design of study: RN, YT; Acquisition of data: RN, TF, YK, MI; Analysis and interpretation of data: RN, TF, YK; Drafting of the manuscript: RN, TF, YK, TO, MK, HK. All authors critically revised the manuscript, agree to be fully accountable for ensuring the integrity and accuracy of the work, and read and approved the final manuscript.

Funding

This work was supported by JSPS KAKENHI Grant Number 23K08203.

Data availability

The authors affirm that all the data are true and valid. The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.

Competing interests

The authors declare that there are no conflicts of interest.

Ethics approval and consent

This retrospective study was approved by the Institutional Review Board of Kansai medical university medical center (approval number: 2022016). Due to the retrospective nature of the study, the Institutional Review Board of Kansai medical university medical center waived the need of obtaining informed consent’ in the manuscript. The study was performed in accordance with the ethical guidelines of the 1964 Declaration of Helsinki.

Publisher’s note

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

These authors contributed equally to this study: Richi Nakatake and Toshiya Funatsuki.
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References

1. Bai J Association between postoperative delirium and mortality in elderly patients undergoing hip fractures surgery: a meta-analysis Osteoporos Int. 2020 31 317 326 31741024
Bai, J. et al. Association between postoperative delirium and mortality in elderly patients undergoing hip fractures surgery: a meta-analysis. Osteoporos Int. 31, 317–326 (2020).31741024
2. Ha, A. et al. A contemporary population-based analysis of the incidence, cost, and outcomes of postoperative delirium following major urologic cancer surgeries. Urol Oncol. 36, 341 e315–341 e322 (2018).
3. Witlox J Eurelings LS de Jonghe JF Kalisvaart KJ Eikelenboom P van Gool WA Delirium in elderly patients and the risk of postdischarge mortality, institutionalization, and dementia: a meta-analysis JAMA. 2010 304 443 451 20664045
Witlox, J. et al. Delirium in elderly patients and the risk of postdischarge mortality, institutionalization, and dementia: a meta-analysis. JAMA. 304, 443–451 (2010).20664045
4. Rudolph JL Marcantonio ER Review articles: postoperative delirium: acute change with long-term implications Anesth Analg. 2011 112 1202 1211 21474660
Rudolph, J. L. & Marcantonio, E. R. Review articles: postoperative delirium: acute change with long-term implications. Anesth Analg. 112, 1202–1211 (2011).21474660
5. Pisani MA Murphy TE Araujo KL Van Ness PH Factors associated with persistent delirium after intensive care unit admission in an older medical patient population J Crit Care. 2010 25 540 e541 547
Pisani, M. A., Murphy, T. E., Araujo, K. L. & Van Ness, P. H. Factors associated with persistent delirium after intensive care unit admission in an older medical patient population. J Crit Care. 25(540), e541-547 (2010).
6. Okamoto K Tokyo Guidelines 2018: flowchart for the management of acute cholecystitis J Hepatobiliary Pancreat Sci. 2018 25 55 72 29045062
Okamoto, K. et al. Tokyo Guidelines 2018: flowchart for the management of acute cholecystitis. J Hepatobiliary Pancreat Sci. 25, 55–72 (2018).29045062
7. Park YM Postoperative delirium after cholecystectomy in older patients: A retrospective study Ann Hepatobiliary Pancreat Surg. 2023 27 301 306 37336783
Park, Y. M. et al. Postoperative delirium after cholecystectomy in older patients: A retrospective study. Ann Hepatobiliary Pancreat Surg. 27, 301–306 (2023).37336783
8. Charlson ME Pompei P Ales KL MacKenzie CR A new method of classifying prognostic comorbidity in longitudinal studies: development and validation J Chronic Dis. 1987 40 373 383 3558716
Charlson, M. E., Pompei, P., Ales, K. L. & MacKenzie, C. R. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 40, 373–383 (1987).3558716
9. Detsky AS What is subjective global assessment of nutritional status? JPEN J Parenter Enteral Nutr. 1987 11 8 13 3820522
Detsky, A. S. et al. What is subjective global assessment of nutritional status?. JPEN J Parenter Enteral Nutr. 11, 8–13 (1987).3820522
10. Sun K Chen S Xu J Li G He Y The prognostic significance of the prognostic nutritional index in cancer: a systematic review and meta-analysis J Cancer Res Clin Oncol. 2014 140 1537 1549 24878931
Sun, K., Chen, S., Xu, J., Li, G. & He, Y. The prognostic significance of the prognostic nutritional index in cancer: a systematic review and meta-analysis. J Cancer Res Clin Oncol. 140, 1537–1549 (2014).24878931
11. Maldonado JR Neuropathogenesis of delirium: review of current etiologic theories and common pathways Am J Geriatr Psychiatry. 2013 21 1190 1222 24206937
Maldonado, J. R. Neuropathogenesis of delirium: review of current etiologic theories and common pathways. Am J Geriatr Psychiatry. 21, 1190–1222 (2013).24206937
12. Lee HJ Hwang DS Wang SK Chee IS Baeg S Kim JL Early assessment of delirium in elderly patients after hip surgery Psychiatry Investig. 2011 8 340 347 22216044
Lee, H. J. et al. Early assessment of delirium in elderly patients after hip surgery. Psychiatry Investig. 8, 340–347 (2011).22216044
13. Pol RA C-reactive protein predicts postoperative delirium following vascular surgery Ann Vasc Surg. 2014 28 1923 1930 25017770
Pol, R. A. et al. C-reactive protein predicts postoperative delirium following vascular surgery. Ann Vasc Surg. 28, 1923–1930 (2014).25017770
14. Xiang D Xing H Tai H Xie G Preoperative C-Reactive Protein as a Risk Factor for Postoperative Delirium in Elderly Patients Undergoing Laparoscopic Surgery for Colon Carcinoma Biomed Res Int. 2017 2017 5635640 29181397
Xiang, D., Xing, H., Tai, H. & Xie, G. Preoperative C-Reactive Protein as a Risk Factor for Postoperative Delirium in Elderly Patients Undergoing Laparoscopic Surgery for Colon Carcinoma. Biomed Res Int. 2017, 5635640 (2017).29181397
15. Vasunilashorn SM High C-Reactive Protein Predicts Delirium Incidence, Duration, and Feature Severity After Major Noncardiac Surgery J Am Geriatr Soc. 2017 65 e109 e116 28555781
Vasunilashorn, S. M. et al. High C-Reactive Protein Predicts Delirium Incidence, Duration, and Feature Severity After Major Noncardiac Surgery. J Am Geriatr Soc. 65, e109–e116 (2017).28555781
16. Rudolph JL Derivation and validation of a preoperative prediction rule for delirium after cardiac surgery Circulation. 2009 119 229 236 19118253
Rudolph, J. L. et al. Derivation and validation of a preoperative prediction rule for delirium after cardiac surgery. Circulation. 119, 229–236 (2009).19118253
17. Karas PL Goh SL Dhital K Is low serum albumin associated with postoperative complications in patients undergoing cardiac surgery? Interact Cardiovasc Thorac Surg. 2015 21 777 786 26362629
Karas, P. L., Goh, S. L. & Dhital, K. Is low serum albumin associated with postoperative complications in patients undergoing cardiac surgery?. Interact Cardiovasc Thorac Surg. 21, 777–786 (2015).26362629
18. Zhang Y TNIP1 alleviates hepatic ischemia/reperfusion injury via the TLR2-Myd88 pathway Biochem Biophys Res Commun. 2018 501 186 192 29709475
Zhang, Y. et al. TNIP1 alleviates hepatic ischemia/reperfusion injury via the TLR2-Myd88 pathway. Biochem Biophys Res Commun. 501, 186–192 (2018).29709475
19. Park, J. E. et al. The C-Reactive Protein/Albumin Ratio as a Predictor of Mortality in Critically Ill Patients. J Clin Med. 7 (2018).
20. Saito H Prognostic Significance of the Preoperative Ratio of C-Reactive Protein to Albumin and Neutrophil-Lymphocyte Ratio in Gastric Cancer Patients World J Surg. 2018 42 1819 1825 29270656
Saito, H. et al. Prognostic Significance of the Preoperative Ratio of C-Reactive Protein to Albumin and Neutrophil-Lymphocyte Ratio in Gastric Cancer Patients. World J Surg. 42, 1819–1825 (2018).29270656
21. Park J Predictive utility of the C-reactive protein to albumin ratio in early allograft dysfunction in living donor liver transplantation: A retrospective observational cohort study PLoS One. 2019 14 e0226369 31821367
Park, J. et al. Predictive utility of the C-reactive protein to albumin ratio in early allograft dysfunction in living donor liver transplantation: A retrospective observational cohort study. PLoS One. 14, e0226369 (2019).31821367
22. Oikonomou T The significance of C-reactive protein to albumin ratio in patients with decompensated cirrhosis Ann Gastroenterol. 2020 33 667 674 33162744
Oikonomou, T. et al. The significance of C-reactive protein to albumin ratio in patients with decompensated cirrhosis. Ann Gastroenterol. 33, 667–674 (2020).33162744
23. Huang SS C-reactive protein-to-albumin ratio is a predictor of hepatitis B virus related decompensated cirrhosis: time-dependent receiver operating characteristics and decision curve analysis Eur J Gastroenterol Hepatol. 2017 29 472 480 27984322
Huang, S. S. et al. C-reactive protein-to-albumin ratio is a predictor of hepatitis B virus related decompensated cirrhosis: time-dependent receiver operating characteristics and decision curve analysis. Eur J Gastroenterol Hepatol. 29, 472–480 (2017).27984322
24. Amygdalos I Clinical value and limitations of the preoperative C-reactive-protein-to-albumin ratio in predicting post-operative morbidity and mortality after deceased-donor liver transplantation: a retrospective single-centre study Transpl Int. 2021 34 1468 1480 34157178
Amygdalos, I. et al. Clinical value and limitations of the preoperative C-reactive-protein-to-albumin ratio in predicting post-operative morbidity and mortality after deceased-donor liver transplantation: a retrospective single-centre study. Transpl Int. 34, 1468–1480 (2021).34157178
25. Haruki K The C-reactive Protein to Albumin Ratio Predicts Long-Term Outcomes in Patients with Pancreatic Cancer After Pancreatic Resection World J Surg. 2016 40 2254 2260 26956901
Haruki, K. et al. The C-reactive Protein to Albumin Ratio Predicts Long-Term Outcomes in Patients with Pancreatic Cancer After Pancreatic Resection. World J Surg. 40, 2254–2260 (2016).26956901
26. Ito T Impact of the Preoperative C-reactive Protein to Albumin Ratio on the Long-Term Outcomes of Hepatic Resection for Intrahepatic Cholangiocarcinoma Asian Pac J Cancer Prev. 2020 21 2373 2379 32856868
Ito, T. et al. Impact of the Preoperative C-reactive Protein to Albumin Ratio on the Long-Term Outcomes of Hepatic Resection for Intrahepatic Cholangiocarcinoma. Asian Pac J Cancer Prev. 21, 2373–2379 (2020).32856868
27. Kinoshita A The C-Reactive Protein/Albumin Ratio, a Novel Inflammation-Based Prognostic Score, Predicts Outcomes in Patients with Hepatocellular Carcinoma Annals of Surgical Oncology. 2014 22 803 810 25190127
Kinoshita, A. et al. The C-Reactive Protein/Albumin Ratio, a Novel Inflammation-Based Prognostic Score, Predicts Outcomes in Patients with Hepatocellular Carcinoma. Annals of Surgical Oncology. 22, 803–810 (2014).25190127
28. Cui, X., Jia, Z., Chen, D., Xu, C. & Yang, P. The prognostic value of the C-reactive protein to albumin ratio in cancer: An updated meta-analysis. Medicine (Baltimore). 99, e19165 (2020).
29. Zhao X EphA2 Promotes the Development of Cervical Cancer through the CXCL11/PD-L1 Pathway J Oncol. 2022 2022 4886907 36478746
Zhao, X. et al. EphA2 Promotes the Development of Cervical Cancer through the CXCL11/PD-L1 Pathway. J Oncol. 2022, 4886907 (2022).36478746
30. Peng J Wu G Chen J Chen H Preoperative C-Reactive Protein/Albumin Ratio, a Risk Factor for Postoperative Delirium in Elderly Patients After Total Joint Arthroplasty J Arthroplasty. 2019 34 2601 2605 31326244
Peng, J., Wu, G., Chen, J. & Chen, H. Preoperative C-Reactive Protein/Albumin Ratio, a Risk Factor for Postoperative Delirium in Elderly Patients After Total Joint Arthroplasty. J Arthroplasty. 34, 2601–2605 (2019).31326244
31. Kim HJ Lee S Kim SH Lee S Sim JH Ro YJ Association of C-reactive protein to albumin ratio with postoperative delirium and mortality in elderly patients undergoing hip fracture surgery: A retrospective cohort study in a single large center Exp Gerontol. 2023 172 112068 36549547
Kim, H. J. et al. Association of C-reactive protein to albumin ratio with postoperative delirium and mortality in elderly patients undergoing hip fracture surgery: A retrospective cohort study in a single large center. Exp Gerontol. 172, 112068 (2023).36549547
32. Brown, C. H. t. et al. The Impact of Delirium After Cardiac Surgical Procedures on Postoperative Resource Use. Ann Thorac Surg. 101, 1663–1669 (2016).
33. Scholz AF Oldroyd C McCarthy K Quinn TJ Hewitt J Systematic review and meta-analysis of risk factors for postoperative delirium among older patients undergoing gastrointestinal surgery Br J Surg. 2016 103 e21 28 26676760
Scholz, A. F., Oldroyd, C., McCarthy, K., Quinn, T. J. & Hewitt, J. Systematic review and meta-analysis of risk factors for postoperative delirium among older patients undergoing gastrointestinal surgery. Br J Surg. 103, e21-28 (2016).26676760
34. Raats JW van Eijsden WA Crolla RM Steyerberg EW van der Laan L Risk Factors and Outcomes for Postoperative Delirium after Major Surgery in Elderly Patients PLoS One. 2015 10 e0136071 26291459
Raats, J. W., van Eijsden, W. A., Crolla, R. M., Steyerberg, E. W. & van der Laan, L. Risk Factors and Outcomes for Postoperative Delirium after Major Surgery in Elderly Patients. PLoS One. 10, e0136071 (2015).26291459
