Systemic inflammation is associated with reduced functional recovery in older inpatients with chronic kidney disease

Systemic inflammation is associated with reduced functional recovery in older inpatients with chronic kidney disease | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Systemic inflammation is associated with reduced functional recovery in older inpatients with chronic kidney disease Keita Ohashi, Kentaro Iwata, Kanji Yamada, Yoshihiro Yoshimura, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6274942/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 21 Aug, 2025 Read the published version in International Urology and Nephrology → Version 1 posted You are reading this latest preprint version Abstract Purpose To investigate the association between systemic inflammation and activities of daily living (ADL) in older patients with chronic kidney disease (CKD) in the acute phase. Methods This observational, retrospective cohort study included patients with CKD aged 65 years and older with unscheduled admissions to the nephrology department between January 2019 and February 2022. Patients who underwent maintenance hemodialysis therapy; died during hospitalization; were treated in other departments; experienced serious events during hospitalization; or did not receive rehabilitation during hospitalization were excluded. Systemic inflammation was assessed by the modified Glasgow Prognostic Score (mGPS) on admission, and ADL was assessed by functional independence measure (FIM) at discharge. Results A total of 89 patients (median age, 80 years [interquartile range, 75–84 years]) were included in the analysis. Ann mGPS score of 0, 1, and 2 was assigned to 41 (46.1%), 15 (16.9%), and 33 (37.1%) patients, respectively. In multivariable analysis, the mGPS (SE = 2.16; β = −0.25; P = .001) was significantly associated with the FIM score at discharge. On the other hand, albumin ( ρ = 0.093; 95% CI, − 0.12 to 0.30; P = .384) and CRP level ( ρ = −0.176; 95% CI; −0.37 to 0.03; P = .098) were not significantly correlated with the FIM score at discharge. Conclusion Among older patients with CKD in the acute phase, systemic inflammation assessed using the mGPS may be useful for predicting ADL. activities of daily living chronic kidney disease functional independence measure modified Glasgow Prognostic Score systemic inflammation Figures Figure 1 Figure 2 Introduction In Japan, with an aging population, the number of patients with chronic kidney disease (CKD) has increased to 14.8 million, with the mean age also increasing[ 1 ]. In patients with CKD, physical function and activities of daily living (ADL) are likely to be impaired[ 2 , 3 ]. CKD causes physiological changes—such as malnutrition and inflammation—that lead to decreasing physical function[ 4 ]. Furthermore, hospitalization is associated with a decline in physical function among patients on hemodialysis[ 5 ]. Previous studies have shown that decreasing physical function and ADL are associated with subsequent mortality[ 2 , 6 ]. Therefore, assessment of physical function and ADL is important to avoid poor outcomes. In patients with CKD, systemic inflammation is common, and it is associated with cardiovascular events and mortality[ 7 , 8 ]. Therefore, the assessment of systemic inflammation in these patients is important. Moreover, systemic inflammation is one of the factors in the decline of physical function and ADL[ 9 ]. A study by Matsuo et al. showed that systemic inflammation is negatively associated with improvements in physical function and ADL in patients hospitalized with acute heart failure[ 10 ]. Systemic inflammation can lead to physical dysfunction, which in turn can result in impaired ADL, but the association between systemic inflammation and ADL is unclear among patients with CKD in the acute phase. The modified Glasgow Prognostic Score (mGPS), which is calculated using C-reactive protein (CRP) and albumin level, is one of the simple tools used to assess systemic inflammation, and it is the most validated prognostic score[ 11 , 12 ]. In patients with CKD, the mGPS is associated with disease severity[ 13 ] and mortality[ 14 , 15 ]; however, the association between the mGPS and ADL is unclear in this patient population. To assess the association, it is hypothesized that systemic inflammation was assessed using the mGPS associated with impaired ADL among patients with CKD in the acute phase. This study aimed to investigate whether the mGPS relates to ADL among hospitalized older patients with CKD in the acute phase. This study may make it possible to predict ADL at discharge from the time of admission and may contribute to the consideration of rehabilitation intervention plans during hospitalization to improve ADL. Methods Study design and population This observational, retrospective cohort study was conducted from January 2019 to February 2022 at the Kobe City Medical Center General Hospital. We included patients with CKD aged 65 years and older with unscheduled admissions for exacerbation of CKD to the nephrology department. Patients who were undergoing maintenance hemodialysis therapy; died during hospitalization; were treated in other departments; experienced serious events during hospitalization, e.g. bone fracture or stroke; or did not receive rehabilitation during hospitalization were excluded. This study was approved by the ethics committee of Kobe City Medical Center General Hospital (approval no. zn220612) and was conducted in accordance with the principles of the Declaration of Helsinki regarding investigations in humans. We applied the opt-out method to obtain participant consent. Outcomes and data collection The main outcome measure was the Functional Independence Measure (FIM) score at discharge. Data were retrospectively collected from medical records and included age, sex, body mass index, clinical frailty scale (CFS) score[ 16 ], CKD stages, laboratory values on admission (albumin, blood urea nitrogen, CRP, creatinine, hemoglobin, total protein, estimated glomerular filtration rate [eGFR], and creatinine clearance), mGPS score on admission, comorbidity defined by the Charlson comorbidity index (CCI)[ 17 ], complications of infection on admission, prevalent diseases, renal replacement therapy (RRT) during hospitalization, amount of rehabilitation, length of hospital stay (LOS), discharge destination, and FIM score on admission and at discharge. Amount rehabilitation was defined as the average number of rehabilitation units per day. In Japan, one rehabilitation unit consists of 20 minutes. Activities of daily living The FIM is a measurement tool for ADL that assesses 18 items in two domains—motor and cognitive[ 18 ]. The motor domain (FIM–motor) consists of 13 items—eating, grooming, bathing, upper body dressing, lower body dressing, toileting, bladder management, bowel management, transfers to the tub/shower, walk/wheelchair, and stairs. The cognitive domain (FIM–cognitive) consists of five items—comprehension, expression, social interaction, problem-solving, and memory. The FIM is scored on a 7-point rating scale, with 1 point indicating total assistance and 7 points indicating complete independence in ADL. The FIM score was assessed by a physical therapist at discharge. Systemic inflammation assessment Systemic inflammation was assessed using the mGPS[ 12 ], which is scored using serum CRP and albumin levels. Patients with a high CRP level (> 1.0 mg/dL) and low albumin level ( 1.0 mg/dL) and albumin level (≥ 3.5 mg/dL) were allocated a score of 1; and those with a CRP level of ≤ 1.0 mg/dL and any albumin level were allocated a score of 0. The mGPS was assessed on admission. Statistical analysis Parametric data were expressed as mean (standard deviation), whereas non-parametric data were expressed as median [interquartile range]. The normality of the distribution was assessed using the Shapiro-Wilk test. Qualitative variables are expressed as numbers (%). Multiple linear regression analysis was used to determine the effect of the mGPS on admission on the FIM score at discharge. Covariates were selected to adjust for bias included age, sex, eGFR on admission, CFS, LOS, and RRT during hospitalization. The variance inflation factor (VIF) was used to check for multicollinearity. To determine the association between the mGPS on admission and subitems of the FIM (FIM–motor and FIM–cognitive) at discharge, Spearman’s rank correlation coefficient was used. To examine the association of the mGPS on admission and known inflammation markers (albumin and CRP) on admission with FIM at discharge, Spearman’s rank correlation coefficient was used. All statistical analyses were performed using EZR ver. 2.7-1 (Saitama Medical Center, Jichi Medical University, Saitama, Japan), which is a graphical user interface for R ver. 4.1.1 (The R Foundation for Statistical Computing, Vienna, Austria)[ 19 ]. It is a modified version of R commander designed to include statistical functions frequently used in biostatistics. Statistical significance was set at P < .05. Results Fig. 1 shows a flowchart of the study. A total of 168 patients were initially considered eligible for inclusion. Among them, 79 were excluded because of undergoing maintenance hemodialysis therapy (n = 31), death during hospitalization (n = 5), receiving treatment in other departments (n = 4), experiencing serious events during hospitalization (n = 2), not receiving rehabilitation during hospitalization (n = 25), and missing data (n = 12). A final cohort of 89 patients was included in this study. The demographic data are shown in Table 1. The mean age of the cohort was 79.3 years (standard deviation [SD]: 6.7), 58 patients were men (65.2%), the median eGFR was 7.8 mL/min/1.73 m 2 (interquartile range [IQR]: 5.0–10.9). Patients were on stages 3b to 5. An mGPS score on admission of 0, 1, and 2 was assigned to 41 (46.1%), 15 (16.9%), and 33 patients (37.1%), respectively. The median LOS was 14.0 days (IQR: 9.0–21.0). The median FIM score at discharge was 93 points (IQR: 72–111). Table 1. Clinical characteristics of the participants Overall (n = 89) mGPS = 0 (n = 41) mGPS = 1 (n = 15) mGPS = 2 (n = 33) Age (years) 79.3 (6.7) 78.6 (6.0) 81.1 (8.4) 79.3 (7.2) Men, n (%) 58 (65.2) 24 (58.5) 11 (73.3) 23 (67.9) BMI (kg/m 2 ) 23.5 (4.64) 24.1 (4.5) 21.9 (4.1) 23.4 (5.1) CFS 5 [4, 6] 5 [4, 6] 5 [4, 6] 5 [4, 6] CKD stage, n (%) Stage 3b 1 (1.1) 1 (2.4) 0 (0) 0 (0) Stage 4 7 (7.9) 3 (7.3) 1 (6.7) 3 (9.1) Stage 5 81 (91.0) 37 (90.2) 14 (93.3) 30 (90.9) Clinical parameters Albumin (g/dL) 3.2 (0.54) 3.4 (0.52) 3.7 (0.26) 2.9 (0.39) BUN (mg/dL) 88.4 [62.1, 112.9] 75.6 [59.5, 102.6] 86.8 [67.4, 114.7] 104.0 [64.8, 119.5] CRP (mg/dL) 1.2 [0.3, 4.7] 0.2 [0.1, 0.4] 2.4 [1.5, 5.0] 5.3 [2.3, 8.8] Creatinine (mg/dL) 5.9 [4.3, 7.6] 5.7 [4.2, 7.6] 5.9 [4.3, 6.3] 6.4 [4.7, 8.1] Hemoglobin (g/dL) 9.5 [8.2, 10.5] 10.0 [8.7, 11.1] 9.5 [8.7, 10.0] 8.9 [7.5, 10.2] Total protein (g/dL) 6.7 (0.77) 6.5 (0.70) 7.4 (0.64) 6.6 (0.74) eGFR (mL/min/1.73 m 2 ) 7.8 [5.0, 10.9] 7.5 [5.0, 11.4] 8.2 [6.5, 11.0] 7.3 [4.6, 9.3] CCr (mL/min) 8.6 [5.0, 12.4] 8.5 [5.3, 12.7] 8.6 [5.9, 11.8] 8.3 [4.8, 12.2] CCI (points) 6 [5, 7] 6 [5, 7] 6 [5, 7] 6 [5, 7] Complications of infection, n (%) 14 (15.7) 1 (2.4) 3 (20.0) 10 (30.3) RRT in hospital, n (%) 61 (68.5) 26 (63.4) 11 (73.3) 24 (72.7) Prevalent diseases HF, n (%) 57 (64.0) 26 (63.4) 12 (80.0) 19 (57.6) DM, n (%) 52 (58.4) 25 (61.0) 9 (60.0) 18 (54.5) Stroke, n (%) 29 (32.6) 10 (24.4) 6 (40.0) 13 (39.4) RRT during hospital, n (%) 61 (68.5) 26 (63.4) 11 (73.3) 24 (72.7) Amount of rehabilitation (unit/d) 1.1 [0.7, 1.3] 1.1 [0.7, 1.4] 1.1 [0.7, 1.3] 1.1 [0.7, 1.3] LOS (days) 14.0 [9.0, 21.0] 14.0 [10.0, 17.0] 15.0 [9.5, 23.0] 13.0 [8.0, 21.0] Discharge destination, n (%) Home 45 (50.6) 20 (48.8) 9 (60.0) 16 (48.5) Hospital 43 (48.3) 21 (51.2) 6 (40.0) 16 (48.5) Nursing home 1 (1.1) 0 (0) 0 (0) 1 (3.0) FIM score on admission Total (points) 73.0 [53.5, 91.5] 85.0 [61.5, 96.5] 69.0 [55.5, 73.0] 68.5 [48.0, 88.5] Motor (points) 44.0 [27.0, 59.0] 54.0 [34.0, 66.0] 39.5 [30.3, 47.5] 37.0 [19.3, 55.0] Cognitive (points) 31.0 [24.5, 35.0] 34.0 [26.5, 35.0] 28.0 [23.0, 31.8] 30.5 [23.5, 35.0] FIM score at discharge Total (points) 93.0 [72.0, 111.0] 104.0 [85.0, 112.0] 98.0 [69.5, 101.0] 53.0 [59.0, 109.0] Motor (points) 66.0 [46.0, 79.0] 71.0 [57.0, 79.0] 66.0 [49.5, 75.5] 54.0 [35.0, 74.0] Cognitive (points) 30.0 [25.0, 35.0] 35.0 [28.0, 35.0] 28.0 [21.5, 32.5] 30.0 [24.0, 35.0] Data are presented as mean (standard deviation), median [interquartile range], or n (%). mGPS, modified Glasgow Prognostic Score; BMI, body mass index; CFS, clinical frailty scale; BUN, blood urea nitrogen; CRP, C-reactive protein; eGFR, estimated glomerular filtration rate; CCr, creatinine clearance rate; CCI, Charlson comorbidity index, RRT, renal replacement therapy; HF, heart failure; DM, diabetes mellitus; LOS, length of hospital stay; FIM, functional independence measure. Table 2 shows the results of the multiple regression analysis. No multicollinearity was found among the included variables. The mGPS (standard error [SE] = 2.16; β = −0.25; P = 0.001) was independently associated with the FIM score at discharge after adjustment for bias such as age, sex, eGFR on admission, CFS, LOS, and RRT during hospitalization. Table 2. Multiple regression analysis of the FIM score at discharge B (95%CI) SE β P value mGPS −7.22 (−11.5, −2.93) 2.16 −0.25 0.001 Age −0.40 (−1.02, 0.21) 0.31 −0.10 0.195 Sex −1.17 (−9.76, 7.42) 4.32 −0.02 0.787 eGFR −0.07 (−0.93, 0.78) 0.43 −0.02 0.866 CFS −14.8 (−18.3, −11.3) 1.75 −0.67 < .001 LOS 0.09 (−0.32, 0.51) 0.21 0.04 0.648 RRT during hospital −1.16 (−10.9, 8.56) 4.89 −0.02 0.812 CI, confidence interval; SE, standard error; mGPS, modified Glasgow Prognostic Score; eGFR, estimated glomerular filtration rate; CFS, clinical frailty scale; LOS, length of stay; RRT, renal replacement therapy. Upon Spearman’s rank correlation coefficient, the mGPS score was significantly correlated with the FIM–motor score at discharge ( ρ = −0.226; 95% CI, −0.42 to −0.02; P = 0.033), but not with the FIM–cognitive score at discharge ( ρ = −0.147; 95% CI, −0.34 to 0.06; P = 0.169). Figure 2 shows the results of the correlation analysis between the FIM score and the mGPS, albumin level, and CRP level. The FIM score at discharge was significantly correlated with the mGPS ( ρ = −0.226; 95% CI, −0.42 to −0.02; P = 0.033), but not with albumin ( ρ = 0.093; 95% CI, −0.12 to 0.30; P = 0.384) or CRP level ( ρ = −0.176; 95% CI; −0.37 to 0.03; P = 0.098). To rule out the effects of acute inflammation, subgroup analysis was carried out in 75 patients who were not complications of infection. Multiple regression analysis in the subgroup showed that mGPS (SE = 2.29; β = −0.18; P = 0.023) was independently associated with the FIM score at discharge after adjustment for bias such as age, sex, eGFR on admission, CFS, LOS, and RRT during hospitalization (Table 2). Table 3. Multiple regression analysis of the FIM score at discharge in subgroup B (95%CI) SE β P value mGPS −5.31 (−9.87, −0.75) 2.29 −0.18 0.023 Age −0.68 (−1.30, −0.07) 0.31 −0.18 0.031 Sex −7.63 (−16.7, 1.45) 4.55 −0.13 0.098 eGFR −0.07 (−0.97, 0.83) 0.45 −0.01 0.878 CFS −15.0 (−18.6, −11.4) 1.79 −0.68 < .001 LOS 0.15 (−0.25, 0.55) 0.20 0.06 0.465 RRT during hospital −0.75 (−10.5, 9.05) 4.91 −0.01 0.880 CI, confidence interval; SE, standard error; mGPS, modified Glasgow Prognostic Score; eGFR, estimated glomerular filtration rate; CFS, clinical frailty scale; LOS, length of stay; RRT, renal replacement therapy. Discussion The main findings of the present study are that higher degrees of systemic inflammation according to the mGPS obtained on admission was associated with the FIM score at discharge in older patients with CKD with unscheduled hospitalization. Furthermore, the FIM score at discharge was significantly related to the mGPS, but not to albumin and CRP levels, on admission. Among the patients in this study, the mean age was 79.3 years and the median eGFR, 7.8 mL/min/1.73 m 2 . According to the data of the Japan Chronic Kidney Disease Database (J-CKD-DB), the median age was 71 years and the median eGFR, 51.3 mL/min/1.73 m 2 among CKD outpatients[20]. In comparison, the patients in our study were older and had lower renal function. In this study, the mean albumin level was 3.2 g/dL and the median CRP level was 1.2 mg/dL. In J-CKD-DB, the median albumin level was 4.1 g/dL and median CRP level was 0.1 mg/dL. The patients in our study had low albumin and high CRP levels, meaning that this study population exhibited high systemic inflammation. Studies on hospitalization among patients with CKD are limited; however, these patients’ characteristics may be a clinical feature among older patients with CKD with unscheduled hospitalization. This difference in clinical features from CKD outpatients may be due to the overlap of acute inflammation, such as infection, with chronic inflammation in patients with CKD in the acute phase. We found that systemic inflammation assessed using the mGPS on admission was independently associated with the FIM score at discharge in patients with CKD. The mGPS is an assessment tool for systemic inflammation using albumin and CRP levels. Although previous studies reported the association between systemic inflammation and physical function[9, 10, 21], the mechanism of this association remains poorly understood. Chronic inflammation such as shown in CKD can lead to oxidative stress and, in turn, inflammation and oxidative stress can lead to frailty[4]. Moreover, inflammatory cytokines are thought to lead to skeletal muscle dysfunction[22]. Systemic inflammation is associated with loss of skeletal muscle mass[23, 24] and muscle strength[25], finally leading to the loss of physical function and ADL. Therefore, systemic inflammation is thought to play an important role in the decline in physical function. In this study, the mGPS was associated with the FIM–motor score, but not with the FIM–cognitive score. As aforementioned, this study population exhibited high systemic inflammation. The subgroup analysis to rule out the effect of acute inflammation showed similar results. These results suggest that systemic inflammation was associated with physical function and ADL in patients with CKD, similar to previous studies. Furthermore, the FIM score at discharge was associated with the mGPS but not with albumin and CRP level on admission in this study. Several studies have shown that CRP level, as a marker of inflammation, is associated with physical function[26, 27], whereas one study showed that CRP level is not associated with physical function[28]. The association between CRP level and physical function remains controversial. Moreover, previous studies have shown that albumin is associated with physical function[29–31]; however, in this study, no such association was found. The conflicting results may be because of the presence of high-grade inflammation in our study population. Among the patients in previous studies, the median albumin level ranged from 3.8 g/dL to 4.2 g/dL, whereas in our study the median Alb level was 3.2 g/dL. In the present study, the mGPS—scored using albumin and CRP level—was associated with physical function. These results suggest that among high systemic inflammatory patients with CKD in the acute phase, mGPS, which is assessed by combining albumin and CRP, may be useful for predicting ADL at discharge compared with albumin or CRP levels alone. In the acute phase, it is often not possible to assess physical function and ADL for reasons such as fatigue or medical treatment such as continuous renal replacement therapy. In this study, the mGPS on admission was associated with the FIM score at discharge among patients with CKD in the acute phase. Thus, the mGPS on admission could possibly predict ADL at discharge. The mGPS is a simple tool using routinely assessed laboratory values, including albumin and CRP. Our study suggests that the mGPS may be a useful predictive tool for ADL compared with albumin or CRP level among older patients with CKD in the acute phase. It may be important to plan rehabilitation programs during hospitalization to improve physical function and ADL based on the mGPS score on admission. Our study has some limitations. First, there was a risk of sampling bias, and the results cannot be generalized because this retrospective study was conducted at a single center with a small sample size. Second, the adjustment of covariates was limited. Not all covariates associated with the FIM score at discharge were adjusted for, for example, nutritional support and cognitive function. Third, there is no clear distinction between acute and chronic inflammation. Finally, skeletal muscle function, such as muscle strength and skeletal muscle mass, baseline renal function, and cardiac function, such as left ventricular ejection fraction, were difficult to investigate using a retrospective study design. Conclusion In conclusion, our study suggests that systemic inflammation assessed using the mGPS on admission among older patients with CKD in the acute phase was independently associated with the FIM score at discharge. The FIM score was significantly related to the mGPS, but not to albumin or CRP level. These findings indicate that the mGPS may be a useful predictive tool for ADL among older patients with CKD in the acute phase. Further studies are needed to investigate other factors, including muscle strength and muscle mass, and to identify effective interventions that can improve physical function and ADL among high inflammatory patients with CKD in the acute phase. Abbreviations ADL = activities of daily living, CCI = Charlson comorbidity index, CFS = crinical frailty scale, CKD = chronic kidney disease, CRP = C-reactive protein, eGFR = estimated glomerular filtration rate, FIM = Functional Indepenence Measure, IQR = interquartile range, LOS = length of hospital stay, mGPS = modified Glasgow Prognostic Score, RRT = renal replacement therapy, SD = standard deviation, SE = standard error, VIF = variance inflation factor. Declarations Data availability The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request. Acknowledgment We thank Chisato Miyakoshi (Department of Research Support, Center for Clinical Research and Innovation, Kobe City Medical Center General Hospital) for statistical consultation. We also thank Editage (www.editage.com) for English language editing. Funding None. Ethics declarations Conflict of interest The authors declare no competing interests. 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Arch Intern Med 162:2333–2341 Schaap LA, Pluijm SMF, Deeg DJH, Visser M (2006) Inflammatory markers and loss of muscle mass (sarcopenia) and strength. Am J Med 119:526.e9–17 Lai H-Y, Chang H-T, Lee YL, Hwang S-J (2014) Association between inflammatory markers and frailty in institutionalized older men. Maturitas 79:329–333 Hiraki K, Yasuda T, Hotta C, et al (2013) Decreased physical function in pre-dialysis patients with chronic kidney disease. Clin Exp Nephrol 17:225–231 Onem Y, Terekeci H, Kucukardali Y, et al (2010) Albumin, hemoglobin, body mass index, cognitive and functional performance in elderly persons living in nursing homes. Arch Gerontol Geriatr 50:56–59 Johansen KL, Chertow GM, da Silva M, et al (2001) Determinants of physical performance in ambulatory patients on hemodialysis. Kidney Int 60:1586–1591 Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6274942","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":436022030,"identity":"8e1b50ec-a636-4005-9b72-d256141fa26b","order_by":0,"name":"Keita Ohashi","email":"","orcid":"","institution":"Kobe City Medical Center General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Keita","middleName":"","lastName":"Ohashi","suffix":""},{"id":436022031,"identity":"d4bfe19a-8a4e-4bc6-8a69-64986d75125c","order_by":1,"name":"Kentaro Iwata","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAqklEQVRIiWNgGAWjYBACNgYGZiBlY8AgAaQkSNCSRoIWBoiWwwZEK2fgk0h+bPBxx3lj/tnNBxgsdxDjMIk048SZZ26bSdw5lsAgeYYYLdIJxod5227bGEjkGDBIthGlJf3z4b9t50jSkmOczNh2wIwELfJvig1725KNJW6kJRwgyi/yPcc3S/xsszPsn5F88LEkMSGGAg5LNpCqhfEjyVpGwSgYBaNgJAAA9mEw+1k5hFMAAAAASUVORK5CYII=","orcid":"","institution":"Kobe City Medical Center General Hospital","correspondingAuthor":true,"prefix":"","firstName":"Kentaro","middleName":"","lastName":"Iwata","suffix":""},{"id":436022032,"identity":"346926b3-57bc-4e20-8717-d731041d12f5","order_by":2,"name":"Kanji Yamada","email":"","orcid":"","institution":"Kobe City Medical Center General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Kanji","middleName":"","lastName":"Yamada","suffix":""},{"id":436022033,"identity":"a793d94c-d277-4332-9c49-cc77cc7adda7","order_by":3,"name":"Yoshihiro Yoshimura","email":"","orcid":"","institution":"Kumamoto Rehabilitation Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yoshihiro","middleName":"","lastName":"Yoshimura","suffix":""},{"id":436022034,"identity":"8031c469-d1c1-4962-b8f8-91fe19526fca","order_by":4,"name":"Atsuki Nozaki","email":"","orcid":"","institution":"Kobe City Medical Center General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Atsuki","middleName":"","lastName":"Nozaki","suffix":""},{"id":436022035,"identity":"2ff123f9-8f10-415e-96a9-373363508c58","order_by":5,"name":"Akio Yamamoto","email":"","orcid":"","institution":"Kobe University Graduate School of Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Akio","middleName":"","lastName":"Yamamoto","suffix":""},{"id":436022036,"identity":"05de0761-b8eb-4ad1-830b-eb0642c0ceb4","order_by":6,"name":"Kumiko Ono","email":"","orcid":"","institution":"Kobe University Graduate School of Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Kumiko","middleName":"","lastName":"Ono","suffix":""},{"id":436022039,"identity":"0bdb1c4a-0add-4ac8-a752-e4f9afeca1e0","order_by":7,"name":"Takeshi Kitai","email":"","orcid":"","institution":"Kobe City Medical Center General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Takeshi","middleName":"","lastName":"Kitai","suffix":""},{"id":436022041,"identity":"fb212fb0-5fd7-4df1-a79c-daaa049b00d5","order_by":8,"name":"Akihiro Yoshimoto","email":"","orcid":"","institution":"Kobe City Medical Center General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Akihiro","middleName":"","lastName":"Yoshimoto","suffix":""},{"id":436022043,"identity":"09d33574-e629-4b47-914d-4f6a484ecfe6","order_by":9,"name":"Nobuo Kohara","email":"","orcid":"","institution":"Kobe City Medical Center General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Nobuo","middleName":"","lastName":"Kohara","suffix":""},{"id":436022045,"identity":"4062a9b9-3754-4e25-9723-c9e213ebd157","order_by":10,"name":"Akira Ishikawa","email":"","orcid":"","institution":"Kobe University Graduate School of Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Akira","middleName":"","lastName":"Ishikawa","suffix":""}],"badges":[],"createdAt":"2025-03-21 07:08:19","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6274942/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6274942/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s11255-025-04721-w","type":"published","date":"2025-08-21T16:29:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":79666009,"identity":"73afc5f9-d249-4533-9e35-5d23d5af970c","added_by":"auto","created_at":"2025-04-01 10:12:06","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":28469,"visible":true,"origin":"","legend":"\u003cp\u003eFlow chart of patient selection\u003c/p\u003e\n\u003cp\u003eAbbreviations: mGPS, modified Glasgow Prognostic Score\u003c/p\u003e","description":"","filename":"Picture1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6274942/v1/256244ae7f9b6fcf9629aab3.jpg"},{"id":79663846,"identity":"ff07a973-2d5a-4caf-b487-d3b3b4fe09c2","added_by":"auto","created_at":"2025-04-01 09:56:06","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":91759,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation between the FIM score at discharge and the mGPS, Alb level, and CRP level; (a) mGPS, (b) Alb, (c) CRP\u003c/p\u003e\n\u003cp\u003eAbbreviations: FIM, Functional Independence Measure; mGPS, modified Glasgow Prognostic Score; Alb, albumin; CRP, C-reactive protein\u003c/p\u003e","description":"","filename":"Picture2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6274942/v1/8b06821de6285228bfd4d1ef.jpg"},{"id":89847175,"identity":"0a35d438-c1ce-4260-8c72-7fc560202a52","added_by":"auto","created_at":"2025-08-25 16:41:39","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":860024,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6274942/v1/5f1b71bd-2dfd-4ab1-b344-9260c75e54aa.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Systemic inflammation is associated with reduced functional recovery in older inpatients with chronic kidney disease","fulltext":[{"header":"Introduction","content":"\u003cp\u003eIn Japan, with an aging population, the number of patients with chronic kidney disease (CKD) has increased to 14.8\u0026nbsp;million, with the mean age also increasing[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. In patients with CKD, physical function and activities of daily living (ADL) are likely to be impaired[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. CKD causes physiological changes\u0026mdash;such as malnutrition and inflammation\u0026mdash;that lead to decreasing physical function[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Furthermore, hospitalization is associated with a decline in physical function among patients on hemodialysis[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Previous studies have shown that decreasing physical function and ADL are associated with subsequent mortality[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Therefore, assessment of physical function and ADL is important to avoid poor outcomes.\u003c/p\u003e \u003cp\u003eIn patients with CKD, systemic inflammation is common, and it is associated with cardiovascular events and mortality[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Therefore, the assessment of systemic inflammation in these patients is important. Moreover, systemic inflammation is one of the factors in the decline of physical function and ADL[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. A study by Matsuo et al. showed that systemic inflammation is negatively associated with improvements in physical function and ADL in patients hospitalized with acute heart failure[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Systemic inflammation can lead to physical dysfunction, which in turn can result in impaired ADL, but the association between systemic inflammation and ADL is unclear among patients with CKD in the acute phase.\u003c/p\u003e \u003cp\u003eThe modified Glasgow Prognostic Score (mGPS), which is calculated using C-reactive protein (CRP) and albumin level, is one of the simple tools used to assess systemic inflammation, and it is the most validated prognostic score[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. In patients with CKD, the mGPS is associated with disease severity[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] and mortality[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]; however, the association between the mGPS and ADL is unclear in this patient population. To assess the association, it is hypothesized that systemic inflammation was assessed using the mGPS associated with impaired ADL among patients with CKD in the acute phase.\u003c/p\u003e \u003cp\u003eThis study aimed to investigate whether the mGPS relates to ADL among hospitalized older patients with CKD in the acute phase. This study may make it possible to predict ADL at discharge from the time of admission and may contribute to the consideration of rehabilitation intervention plans during hospitalization to improve ADL.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and population\u003c/h2\u003e \u003cp\u003eThis observational, retrospective cohort study was conducted from January 2019 to February 2022 at the Kobe City Medical Center General Hospital. We included patients with CKD aged 65 years and older with unscheduled admissions for exacerbation of CKD to the nephrology department. Patients who were undergoing maintenance hemodialysis therapy; died during hospitalization; were treated in other departments; experienced serious events during hospitalization, e.g. bone fracture or stroke; or did not receive rehabilitation during hospitalization were excluded.\u003c/p\u003e \u003cp\u003eThis study was approved by the ethics committee of Kobe City Medical Center General Hospital (approval no. zn220612) and was conducted in accordance with the principles of the Declaration of Helsinki regarding investigations in humans. We applied the opt-out method to obtain participant consent.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eOutcomes and data collection\u003c/h3\u003e\n\u003cp\u003eThe main outcome measure was the Functional Independence Measure (FIM) score at discharge. Data were retrospectively collected from medical records and included age, sex, body mass index, clinical frailty scale (CFS) score[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], CKD stages, laboratory values on admission (albumin, blood urea nitrogen, CRP, creatinine, hemoglobin, total protein, estimated glomerular filtration rate [eGFR], and creatinine clearance), mGPS score on admission, comorbidity defined by the Charlson comorbidity index (CCI)[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], complications of infection on admission, prevalent diseases, renal replacement therapy (RRT) during hospitalization, amount of rehabilitation, length of hospital stay (LOS), discharge destination, and FIM score on admission and at discharge. Amount rehabilitation was defined as the average number of rehabilitation units per day. In Japan, one rehabilitation unit consists of 20 minutes.\u003c/p\u003e\n\u003ch3\u003eActivities of daily living\u003c/h3\u003e\n\u003cp\u003eThe FIM is a measurement tool for ADL that assesses 18 items in two domains\u0026mdash;motor and cognitive[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. The motor domain (FIM\u0026ndash;motor) consists of 13 items\u0026mdash;eating, grooming, bathing, upper body dressing, lower body dressing, toileting, bladder management, bowel management, transfers to the tub/shower, walk/wheelchair, and stairs. The cognitive domain (FIM\u0026ndash;cognitive) consists of five items\u0026mdash;comprehension, expression, social interaction, problem-solving, and memory. The FIM is scored on a 7-point rating scale, with 1 point indicating total assistance and 7 points indicating complete independence in ADL. The FIM score was assessed by a physical therapist at discharge.\u003c/p\u003e\n\u003ch3\u003eSystemic inflammation assessment\u003c/h3\u003e\n\u003cp\u003eSystemic inflammation was assessed using the mGPS[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], which is scored using serum CRP and albumin levels. Patients with a high CRP level (\u0026gt;\u0026thinsp;1.0 mg/dL) and low albumin level (\u0026lt;\u0026thinsp;3.5 mg/dL) were allocated a score of 2; those with a high CRP (\u0026gt;\u0026thinsp;1.0 mg/dL) and albumin level (\u0026ge;\u0026thinsp;3.5 mg/dL) were allocated a score of 1; and those with a CRP level of \u0026le;\u0026thinsp;1.0 mg/dL and any albumin level were allocated a score of 0. The mGPS was assessed on admission.\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eParametric data were expressed as mean (standard deviation), whereas non-parametric data were expressed as median [interquartile range]. The normality of the distribution was assessed using the Shapiro-Wilk test. Qualitative variables are expressed as numbers (%).\u003c/p\u003e \u003cp\u003eMultiple linear regression analysis was used to determine the effect of the mGPS on admission on the FIM score at discharge. Covariates were selected to adjust for bias included age, sex, eGFR on admission, CFS, LOS, and RRT during hospitalization. The variance inflation factor (VIF) was used to check for multicollinearity.\u003c/p\u003e \u003cp\u003eTo determine the association between the mGPS on admission and subitems of the FIM (FIM\u0026ndash;motor and FIM\u0026ndash;cognitive) at discharge, Spearman\u0026rsquo;s rank correlation coefficient was used.\u003c/p\u003e \u003cp\u003eTo examine the association of the mGPS on admission and known inflammation markers (albumin and CRP) on admission with FIM at discharge, Spearman\u0026rsquo;s rank correlation coefficient was used.\u003c/p\u003e \u003cp\u003eAll statistical analyses were performed using EZR ver. 2.7-1 (Saitama Medical Center, Jichi Medical University, Saitama, Japan), which is a graphical user interface for R ver. 4.1.1 (The R Foundation for Statistical Computing, Vienna, Austria)[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. It is a modified version of R commander designed to include statistical functions frequently used in biostatistics. Statistical significance was set at \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eFig. 1 shows a flowchart of the study. A total of 168 patients were initially considered eligible for inclusion. Among them, 79 were excluded because of undergoing maintenance hemodialysis therapy (n = 31), death during hospitalization (n = 5), receiving treatment in other departments (n = 4), experiencing serious events during hospitalization (n = 2), not receiving rehabilitation during hospitalization (n = 25), and missing data (n = 12). A final cohort of 89 patients was included in this study. The demographic data are shown in Table 1. The mean age of the cohort was 79.3 years (standard deviation [SD]: 6.7), 58 patients were men (65.2%), the median eGFR was 7.8 mL/min/1.73 m\u003csup\u003e2\u003c/sup\u003e (interquartile range [IQR]: 5.0\u0026ndash;10.9). Patients were on stages 3b to 5. An mGPS score on admission of 0, 1, and 2 was assigned to 41 (46.1%), 15 (16.9%), and 33 patients (37.1%), respectively. The median LOS was 14.0 days (IQR: 9.0\u0026ndash;21.0). The median FIM score at discharge was 93 points (IQR: 72\u0026ndash;111).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1. Clinical characteristics of the participants\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eOverall\u003c/p\u003e\n \u003cp\u003e(n = 89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003emGPS = 0\u003c/p\u003e\n \u003cp\u003e(n = 41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003emGPS = 1\u003c/p\u003e\n \u003cp\u003e(n = 15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003emGPS = 2\u003c/p\u003e\n \u003cp\u003e(n = 33)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAge (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e79.3 (6.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e78.6 (6.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e81.1 (8.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e79.3 (7.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMen, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e58 (65.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e24 (58.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e11 (73.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e23 (67.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e23.5 (4.64)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e24.1 (4.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e21.9 (4.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e23.4 (5.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCFS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5 [4, 6]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5 [4, 6]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5 [4, 6]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5 [4, 6]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCKD stage, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eStage 3b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1 (1.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1 (2.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eStage 4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7 (7.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3 (7.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1 (6.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3 (9.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eStage 5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e81 (91.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e37 (90.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e14 (93.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e30 (90.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eClinical parameters\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAlbumin (g/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3.2 (0.54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3.4 (0.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3.7 (0.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.9 (0.39)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eBUN (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e88.4 [62.1, 112.9]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e75.6 [59.5, 102.6]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e86.8 [67.4, 114.7]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e104.0 [64.8, 119.5]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCRP (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.2 [0.3, 4.7]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.2 [0.1, 0.4]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.4 [1.5, 5.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5.3 [2.3, 8.8]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCreatinine (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5.9 [4.3, 7.6]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5.7 [4.2, 7.6]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5.9 [4.3, 6.3]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6.4 [4.7, 8.1]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHemoglobin (g/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e9.5 [8.2, 10.5]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e10.0 [8.7, 11.1]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e9.5 [8.7, 10.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e8.9 [7.5, 10.2]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eTotal protein (g/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6.7 (0.77)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6.5 (0.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7.4 (0.64)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6.6 (0.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eeGFR (mL/min/1.73 m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7.8 [5.0, 10.9]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7.5 [5.0, 11.4]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e8.2 [6.5, 11.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7.3 [4.6, 9.3]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCCr (mL/min)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e8.6 [5.0, 12.4]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e8.5 [5.3, 12.7]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e8.6 [5.9, 11.8]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e8.3 [4.8, 12.2]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCCI (points)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6 [5, 7]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6 [5, 7]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6 [5, 7]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6 [5, 7]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eComplications of infection, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e14 (15.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1 (2.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3 (20.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e10 (30.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRRT in hospital, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e61 (68.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e26 (63.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e11 (73.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e24 (72.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePrevalent diseases\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHF, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e57 (64.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e26 (63.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e12 (80.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e19 (57.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDM, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e52 (58.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e25 (61.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e9 (60.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e18 (54.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eStroke, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e29 (32.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e10 (24.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6 (40.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e13 (39.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRRT during hospital, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e61 (68.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e26 (63.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e11 (73.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e24 (72.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAmount of rehabilitation (unit/d)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.1 [0.7, 1.3]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.1 [0.7, 1.4]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.1 [0.7, 1.3]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.1 [0.7, 1.3]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLOS (days)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e14.0 [9.0, 21.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e14.0 [10.0, 17.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e15.0 [9.5, 23.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e13.0 [8.0, 21.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDischarge destination, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHome\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e45 (50.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e20 (48.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e9 (60.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e16 (48.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHospital\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e43 (48.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e21 (51.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6 (40.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e16 (48.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNursing home\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1 (1.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1 (3.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFIM score on admission\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eTotal (points)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e73.0 [53.5, 91.5]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e85.0 [61.5, 96.5]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e69.0 [55.5, 73.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e68.5 [48.0, 88.5]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMotor (points)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e44.0 [27.0, 59.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e54.0 [34.0, 66.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e39.5 [30.3, 47.5]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e37.0 [19.3, 55.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCognitive (points)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e31.0 [24.5, 35.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e34.0 [26.5, 35.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e28.0 [23.0, 31.8]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e30.5 [23.5, 35.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFIM score at discharge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eTotal (points)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e93.0 [72.0, 111.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e104.0 [85.0, 112.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e98.0 [69.5, 101.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e53.0 [59.0, 109.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMotor (points)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e66.0 [46.0, 79.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e71.0 [57.0, 79.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e66.0 [49.5, 75.5]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e54.0 [35.0, 74.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCognitive (points)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e30.0 [25.0, 35.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e35.0 [28.0, 35.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e28.0 [21.5, 32.5]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e30.0 [24.0, 35.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003eData are presented as mean (standard deviation), median [interquartile range], or n (%). mGPS, modified Glasgow Prognostic Score; BMI, body mass index; CFS, clinical frailty scale; BUN, blood urea nitrogen; CRP, C-reactive protein; eGFR, estimated glomerular filtration rate; CCr, creatinine clearance rate; CCI, Charlson comorbidity index, RRT, renal replacement therapy; HF, heart failure; DM, diabetes mellitus; LOS, length of hospital stay; FIM, functional independence measure.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;Table 2 shows the results of the multiple regression analysis. No multicollinearity was found among the included variables. The mGPS (standard error [SE] = 2.16; \u0026beta; = \u0026minus;0.25; \u003cem\u003eP\u003c/em\u003e = 0.001) was independently associated with the FIM score at discharge after adjustment for bias such as age, sex, eGFR on admission, CFS, LOS, and RRT during hospitalization.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2. Multiple regression analysis of the FIM score at discharge\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"549\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 147px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003eB (95%CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003eSE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026beta;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e\u003cem\u003eP\u0026nbsp;\u003c/em\u003evalue\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 147px;\"\u003e\n \u003cp\u003emGPS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026minus;7.22 (\u0026minus;11.5, \u0026minus;2.93)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e2.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026minus;0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 147px;\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026minus;0.40 (\u0026minus;1.02, 0.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026minus;0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e0.195\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 147px;\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026minus;1.17 (\u0026minus;9.76, 7.42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e4.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026minus;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e0.787\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 147px;\"\u003e\n \u003cp\u003eeGFR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026minus;0.07 (\u0026minus;0.93, 0.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026minus;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e0.866\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 147px;\"\u003e\n \u003cp\u003eCFS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026minus;14.8 (\u0026minus;18.3, \u0026minus;11.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e1.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026minus;0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026lt; .001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 147px;\"\u003e\n \u003cp\u003eLOS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e0.09 (\u0026minus;0.32, 0.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e0.648\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 147px;\"\u003e\n \u003cp\u003eRRT during hospital\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026minus;1.16 (\u0026minus;10.9, 8.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e4.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026minus;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e0.812\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"top\" style=\"width: 549px;\"\u003e\n \u003cp\u003eCI, confidence interval; SE, standard error; mGPS, modified Glasgow Prognostic Score; eGFR, estimated glomerular filtration rate; CFS, clinical frailty scale; LOS, length of stay; RRT, renal replacement therapy.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eUpon Spearman\u0026rsquo;s rank correlation coefficient, the mGPS score was significantly correlated with the FIM\u0026ndash;motor score at discharge (\u003cem\u003e\u0026rho;\u003c/em\u003e = \u0026minus;0.226; 95% CI, \u0026minus;0.42 to \u0026minus;0.02; \u003cem\u003eP\u003c/em\u003e = 0.033), but not with the FIM\u0026ndash;cognitive score at discharge (\u003cem\u003e\u0026rho;\u003c/em\u003e = \u0026minus;0.147; 95% CI, \u0026minus;0.34 to 0.06; \u003cem\u003eP\u003c/em\u003e = 0.169).\u003c/p\u003e\n\u003cp\u003eFigure 2 shows the results of the correlation analysis between the FIM score and the mGPS, albumin level, and CRP level. The FIM score at discharge was significantly correlated with the mGPS (\u003cem\u003e\u0026rho;\u003c/em\u003e = \u0026minus;0.226; 95% CI, \u0026minus;0.42 to \u0026minus;0.02; \u003cem\u003eP\u003c/em\u003e = 0.033), but not with albumin (\u003cem\u003e\u0026rho;\u003c/em\u003e = 0.093; 95% CI, \u0026minus;0.12 to 0.30; \u003cem\u003eP\u003c/em\u003e = 0.384) or CRP level (\u003cem\u003e\u0026rho;\u003c/em\u003e = \u0026minus;0.176; 95% CI; \u0026minus;0.37 to 0.03; \u003cem\u003eP\u003c/em\u003e = 0.098).\u003c/p\u003e\n\u003cp\u003eTo rule out the effects of acute inflammation, subgroup analysis was carried out in 75 patients who were not complications of infection. Multiple regression analysis in the subgroup showed that mGPS (SE = 2.29; \u0026beta; = \u0026minus;0.18; \u003cem\u003eP\u003c/em\u003e = 0.023) was independently associated with the FIM score at discharge after adjustment for bias such as age, sex, eGFR on admission, CFS, LOS, and RRT during hospitalization (Table 2).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3.\u003c/strong\u003e \u003cstrong\u003eMultiple regression analysis of the FIM score at discharge in subgroup\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"549\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 147px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003eB (95%CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003eSE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026beta;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e\u003cem\u003eP\u0026nbsp;\u003c/em\u003evalue\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 147px;\"\u003e\n \u003cp\u003emGPS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026minus;5.31 (\u0026minus;9.87, \u0026minus;0.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e2.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026minus;0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e0.023\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 147px;\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026minus;0.68 (\u0026minus;1.30, \u0026minus;0.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026minus;0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e0.031\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 147px;\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026minus;7.63 (\u0026minus;16.7, 1.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e4.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026minus;0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e0.098\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 147px;\"\u003e\n \u003cp\u003eeGFR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026minus;0.07 (\u0026minus;0.97, 0.83)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026minus;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e0.878\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 147px;\"\u003e\n \u003cp\u003eCFS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026minus;15.0 (\u0026minus;18.6, \u0026minus;11.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e1.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026minus;0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026lt; .001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 147px;\"\u003e\n \u003cp\u003eLOS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e0.15 (\u0026minus;0.25, 0.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e0.465\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 147px;\"\u003e\n \u003cp\u003eRRT during hospital\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026minus;0.75 (\u0026minus;10.5, 9.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e4.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026minus;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e0.880\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" style=\"width: 549px;\"\u003e\n \u003cp\u003eCI, confidence interval; SE, standard error; mGPS, modified Glasgow Prognostic Score; eGFR, estimated glomerular filtration rate; CFS, clinical frailty scale; LOS, length of stay; RRT, renal replacement therapy.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe main findings of the present study are that higher degrees of systemic inflammation according to the mGPS obtained on admission was associated with the FIM score at discharge in older patients with CKD with unscheduled hospitalization. Furthermore, the FIM score at discharge was significantly related to the mGPS, but not to albumin and CRP levels, on admission.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Among the patients in this study, the mean age was 79.3 years and the median eGFR, 7.8 mL/min/1.73 m\u003csup\u003e2\u003c/sup\u003e. According to the data of the Japan Chronic Kidney Disease Database (J-CKD-DB), the median age was 71 years and the median eGFR, 51.3 mL/min/1.73 m\u003csup\u003e2\u003c/sup\u003e among CKD outpatients[20]. In comparison, the patients in our study were older and had lower renal function. In this study, the mean albumin level was 3.2 g/dL and the median CRP level was 1.2 mg/dL. In J-CKD-DB, the median albumin level was 4.1 g/dL and median CRP level was 0.1 mg/dL. The patients in our study had low albumin and high CRP levels, meaning that this study population exhibited high systemic inflammation. Studies on hospitalization among patients with CKD are limited; however, these patients’ characteristics may be a clinical feature among older patients with CKD with unscheduled hospitalization. This difference in clinical features from CKD outpatients may be due to the overlap of acute inflammation, such as infection, with chronic inflammation in patients with CKD in the acute phase.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;We found that systemic inflammation assessed using the mGPS on admission was independently associated with the FIM score at discharge in patients with CKD. The mGPS is an assessment tool for systemic inflammation using albumin and CRP levels. Although previous studies reported the association between systemic inflammation and physical function[9, 10, 21], the mechanism of this association remains poorly understood. Chronic inflammation such as shown in CKD can lead to oxidative stress and, in turn, inflammation and oxidative stress can lead to frailty[4]. Moreover, inflammatory cytokines are thought to lead to skeletal muscle dysfunction[22]. Systemic inflammation is associated with loss of skeletal muscle mass[23, 24] and muscle strength[25], finally leading to the loss of physical function and ADL. Therefore, systemic inflammation is thought to play an important role in the decline in physical function. In this study, the mGPS was associated with the FIM–motor score, but not with the FIM–cognitive score. As aforementioned, this study population exhibited high systemic inflammation. The subgroup analysis to rule out the effect of acute inflammation showed similar results. These results suggest that systemic inflammation was associated with physical function and ADL in patients with CKD, similar to previous studies.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Furthermore, the FIM score at discharge was associated with the mGPS but not with albumin and CRP level on admission in this study. Several studies have shown that CRP level, as a marker of inflammation, is associated with physical function[26, 27], whereas one study showed that CRP level is not associated with physical function[28]. The association between CRP level and physical function remains controversial. Moreover, previous studies have shown that albumin is associated with physical function[29–31]; however, in this study, no such association was found. The conflicting results may be because of the presence of high-grade inflammation in our study population. Among the patients in previous studies, the median albumin level ranged from 3.8 g/dL to 4.2 g/dL, whereas in our study the median Alb level was 3.2 g/dL. In the present study, the mGPS—scored using albumin and CRP level—was associated with physical function. These results suggest that among high systemic inflammatory patients with CKD in the acute phase, mGPS, which is assessed by combining albumin and CRP, may be useful for predicting ADL at discharge compared with albumin or CRP levels alone.\u003c/p\u003e\n\u003cp\u003eIn the acute phase, it is often not possible to assess physical function and ADL for reasons such as fatigue or medical treatment such as continuous renal replacement therapy. In this study, the mGPS on admission was associated with the FIM score at discharge among patients with CKD in the acute phase. Thus, the mGPS on admission could possibly predict ADL at discharge. The mGPS is a simple tool using routinely assessed laboratory values, including albumin and CRP. Our study suggests that the mGPS may be a useful predictive tool for ADL compared with albumin or CRP level among older patients with CKD in the acute phase. It may be important to plan rehabilitation programs during hospitalization to improve physical function and ADL based on the mGPS score on admission.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Our study has some limitations. First, there was a risk of sampling bias, and the results cannot be generalized because this retrospective study was conducted at a single center with a small sample size. Second, the adjustment of covariates was limited. Not all covariates associated with the FIM score at discharge were adjusted for, for example, nutritional support and cognitive function. Third, there is no clear distinction between acute and chronic inflammation. Finally, skeletal muscle function, such as muscle strength and skeletal muscle mass, baseline renal function, and cardiac function, such as left ventricular ejection fraction, were difficult to investigate using a retrospective study design.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, our study suggests that systemic inflammation assessed using the mGPS on admission among older patients with CKD in the acute phase was independently associated with the FIM score at discharge. The FIM score was significantly related to the mGPS, but not to albumin or CRP level. These findings indicate that the mGPS may be a useful predictive tool for ADL among older patients with CKD in the acute phase. Further studies are needed to investigate other factors, including muscle strength and muscle mass, and to identify effective interventions that can improve physical function and ADL among high inflammatory patients with CKD in the acute phase.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eADL = activities of daily living, CCI = Charlson comorbidity index, CFS = crinical frailty scale, CKD = chronic kidney disease, CRP = C-reactive protein, eGFR = estimated glomerular filtration rate, FIM = Functional Indepenence Measure, IQR = interquartile range, LOS = length of hospital stay, mGPS = modified Glasgow Prognostic Score, RRT = renal replacement therapy, SD = standard deviation, SE = standard error, VIF = variance inflation factor.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank Chisato Miyakoshi (Department of Research Support, Center for Clinical Research and Innovation, Kobe City Medical Center General Hospital) for statistical consultation. We also thank Editage (www.editage.com) for English language editing.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics declarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eConflict of interest\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eEthical approval\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the ethics committee of Kobe City Medical Center General Hospital (approval no. zn220612)\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eNagai K, Asahi K, Iseki K, Yamagata K (2021) Estimating the prevalence of definitive chronic kidney disease in the Japanese general population. Clin Exp Nephrol 25:885\u0026ndash;892\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRoshanravan B, Robinson-Cohen C, Patel KV, et al (2013) Association between physical performance and all-cause mortality in CKD. J Am Soc Nephrol 24:822\u0026ndash;830\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKurella Tamura M, Covinsky KE, Chertow GM, et al (2009) Functional status of elderly adults before and after initiation of dialysis. N Engl J Med 361:1539\u0026ndash;1547\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWalker SR, Wagner M, Tangri N (2014) Chronic kidney disease, frailty, and unsuccessful aging: a review. J Ren Nutr 24:364\u0026ndash;370\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJohansen KL, Dalrymple LS, Delgado C, et al (2017) Factors Associated with Frailty and Its Trajectory among Patients on Hemodialysis. Clin J Am Soc Nephrol 12:1100\u0026ndash;1108\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eInaguma D, Tanaka A, Shinjo H (2017) Physical function at the time of dialysis initiation is associated with subsequent mortality. Clin Exp Nephrol 21:425\u0026ndash;435\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKato A, Takita T, Maruyama Y, Hishida A (2004) Chlamydial infection and progression of carotid atherosclerosis in patients on regular haemodialysis. Nephrol Dial Transplant 19:2539\u0026ndash;2546\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBazeley J, Bieber B, Li Y, et al (2011) C-reactive protein and prediction of 1-year mortality in prevalent hemodialysis patients. Clin J Am Soc Nephrol 6:2452\u0026ndash;2461\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChang SS, Weiss CO, Xue Q-L, Fried LP (2012) Association between inflammatory-related disease burden and frailty: results from the Women\u0026rsquo;s Health and Aging Studies (WHAS) I and II. Arch Gerontol Geriatr 54:9\u0026ndash;15\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMatsuo H, Yoshimura Y, Fujita S, et al (2021) Role of systemic inflammation in functional recovery, dysphagia, and 1-y mortality in heart failure: A prospective cohort study. Nutrition 91\u0026ndash;92:111465\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcMillan DC (2013) The systemic inflammation-based Glasgow Prognostic Score: a decade of experience in patients with cancer. Cancer Treat Rev 39:534\u0026ndash;540\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcMillan DC, Crozier JEM, Canna K, et al (2007) Evaluation of an inflammation-based prognostic score (GPS) in patients undergoing resection for colon and rectal cancer. Int J Colorectal Dis 22:881\u0026ndash;886\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStefan G, Stancu S, Zugravu A, Capusa C (2022) Inflammation-based modified Glasgow prognostic score and renal outcome in chronic kidney disease patients: is there a relationship? Intern Med J 52:968\u0026ndash;974\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKato A, Tsuji T, Sakao Y, et al (2013) A comparison of systemic inflammation-based prognostic scores in patients on regular hemodialysis. Nephron Extra 3:91\u0026ndash;100\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCai L, Yu J, Yu J, et al (2018) Prognostic value of inflammation-based prognostic scores on outcome in patients undergoing continuous ambulatory peritoneal dialysis. BMC Nephrol 19:297\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRockwood K, Song X, MacKnight C, et al (2005) A global clinical measure of fitness and frailty in elderly people. CMAJ 173:489\u0026ndash;495\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCharlson ME, Pompei P, Ales KL, MacKenzie CR (1987) A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis 40:373\u0026ndash;383\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOttenbacher KJ, Hsu Y, Granger CV, Fiedler RC (1996) The reliability of the functional independence measure: a quantitative review. Arch Phys Med Rehabil 77:1226\u0026ndash;1232\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKanda Y (2013) Investigation of the freely available easy-to-use software \u0026ldquo;EZR\u0026rdquo; for medical statistics. Bone Marrow Transplant 48:452\u0026ndash;458\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNakagawa N, Sofue T, Kanda E, et al (2020) J-CKD-DB: a nationwide multicentre electronic health record-based chronic kidney disease database in Japan. Sci Rep 10:7351\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYoshimura Y, Bise T, Nagano F, et al (2018) Systemic Inflammation in the Recovery Stage of Stroke: Its Association with Sarcopenia and Poor Functional Rehabilitation Outcomes. Prog Rehabil Med 3:20180011\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXia Z, Cholewa J, Zhao Y, et al (2017) Targeting Inflammation and Downstream Protein Metabolism in Sarcopenia: A Brief Up-Dated Description of Concurrent Exercise and Leucine-Based Multimodal Intervention. Front Physiol 8:434\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHida T, Imagama S, Ando K, et al (2018) Sarcopenia and physical function are associated with inflammation and arteriosclerosis in community-dwelling people: The Yakumo study. Mod Rheumatol 28:345\u0026ndash;350\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBano G, Trevisan C, Carraro S, et al (2017) Inflammation and sarcopenia: A systematic review and meta-analysis. Maturitas 96:10\u0026ndash;15\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGranic A, Davies K, Martin-Ruiz C, et al (2017) Grip strength and inflammatory biomarker profiles in very old adults. Age Ageing 46:976\u0026ndash;982\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWalston J, McBurnie MA, Newman A, et al (2002) Frailty and activation of the inflammation and coagulation systems with and without clinical comorbidities: results from the Cardiovascular Health Study. Arch Intern Med 162:2333\u0026ndash;2341\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchaap LA, Pluijm SMF, Deeg DJH, Visser M (2006) Inflammatory markers and loss of muscle mass (sarcopenia) and strength. Am J Med 119:526.e9\u0026ndash;17\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLai H-Y, Chang H-T, Lee YL, Hwang S-J (2014) Association between inflammatory markers and frailty in institutionalized older men. Maturitas 79:329\u0026ndash;333\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHiraki K, Yasuda T, Hotta C, et al (2013) Decreased physical function in pre-dialysis patients with chronic kidney disease. Clin Exp Nephrol 17:225\u0026ndash;231\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOnem Y, Terekeci H, Kucukardali Y, et al (2010) Albumin, hemoglobin, body mass index, cognitive and functional performance in elderly persons living in nursing homes. Arch Gerontol Geriatr 50:56\u0026ndash;59\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJohansen KL, Chertow GM, da Silva M, et al (2001) Determinants of physical performance in ambulatory patients on hemodialysis. Kidney Int 60:1586\u0026ndash;1591\u003c/span\u003e\u003c/li\u003e \u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"activities of daily living, chronic kidney disease, functional independence measure, modified Glasgow Prognostic Score, systemic inflammation","lastPublishedDoi":"10.21203/rs.3.rs-6274942/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6274942/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e \u003cp\u003eTo investigate the association between systemic inflammation and activities of daily living (ADL) in older patients with chronic kidney disease (CKD) in the acute phase.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis observational, retrospective cohort study included patients with CKD aged 65 years and older with unscheduled admissions to the nephrology department between January 2019 and February 2022. Patients who underwent maintenance hemodialysis therapy; died during hospitalization; were treated in other departments; experienced serious events during hospitalization; or did not receive rehabilitation during hospitalization were excluded. Systemic inflammation was assessed by the modified Glasgow Prognostic Score (mGPS) on admission, and ADL was assessed by functional independence measure (FIM) at discharge.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eA total of 89 patients (median age, 80 years [interquartile range, 75\u0026ndash;84 years]) were included in the analysis. Ann mGPS score of 0, 1, and 2 was assigned to 41 (46.1%), 15 (16.9%), and 33 (37.1%) patients, respectively. In multivariable analysis, the mGPS (SE\u0026thinsp;=\u0026thinsp;2.16; β = \u0026minus;0.25; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.001) was significantly associated with the FIM score at discharge. On the other hand, albumin (\u003cem\u003eρ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.093; 95% CI, \u0026minus;\u0026thinsp;0.12 to 0.30; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.384) and CRP level (\u003cem\u003eρ\u003c/em\u003e = \u0026minus;0.176; 95% CI; \u0026minus;0.37 to 0.03; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.098) were not significantly correlated with the FIM score at discharge.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eAmong older patients with CKD in the acute phase, systemic inflammation assessed using the mGPS may be useful for predicting ADL.\u003c/p\u003e","manuscriptTitle":"Systemic inflammation is associated with reduced functional recovery in older inpatients with chronic kidney disease","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-01 09:56:01","doi":"10.21203/rs.3.rs-6274942/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"710c2d2c-17ee-42ec-ac09-116c2cbe1760","owner":[],"postedDate":"April 1st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-08-25T16:32:08+00:00","versionOfRecord":{"articleIdentity":"rs-6274942","link":"https://doi.org/10.1007/s11255-025-04721-w","journal":{"identity":"international-urology-and-nephrology","isVorOnly":false,"title":"International Urology and Nephrology"},"publishedOn":"2025-08-21 16:29:00","publishedOnDateReadable":"August 21st, 2025"},"versionCreatedAt":"2025-04-01 09:56:01","video":"","vorDoi":"10.1007/s11255-025-04721-w","vorDoiUrl":"https://doi.org/10.1007/s11255-025-04721-w","workflowStages":[]},"version":"v1","identity":"rs-6274942","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6274942","identity":"rs-6274942","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}