Financial Toxicity in ICU Survivors: The Mediating Role of Nutritional Status and Implications for Post-Discharge Service Planning

Financial Toxicity in ICU Survivors: The Mediating Role of Nutritional Status and Implications for Post-Discharge Service Planning | 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 Financial Toxicity in ICU Survivors: The Mediating Role of Nutritional Status and Implications for Post-Discharge Service Planning Zhenzhen Huang, Yuhan Chen, Ran Yu, Peiyao Zheng, Yiyu Zhuang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9333777/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Background Understanding which clinically obtainable indicators are associated with financial vulnerability at discharge has implications for post-discharge service planning and resource allocation. This study examined whether nutritional status and multidimensional frailty mediate the relationship between ICU length of stay and financial toxicity in middle-aged and older ICU survivors. Methods In this single-centre cross-sectional study, 422 ICU survivors aged 45 years or older were recruited before hospital discharge. Nutritional status, multidimensional frailty, and financial toxicity were assessed using the Mini Nutritional Assessment–Short Form, Tilburg Frailty Indicator, and Comprehensive Score for Financial Toxicity. Structural equation modelling was used to test a serial mediation model with adjustment for selected demographic and clinical covariates. Results Longer ICU LOS was associated with poorer nutritional status (β = −0.256, p = 0.001), and poorer nutritional status was associated with greater frailty (β = −0.325, p < 0.001). Better nutritional status (β = 0.148, p = 0.003) and lower frailty (β = −0.118, p = 0.014) were associated with higher COST scores, indicating lower financial toxicity. The direct association between ICU LOS and COST score was not significant. The indirect association through nutritional status alone was significant (B = − 0.069, 95% CI − 0.130 to − 0.008, p = 0.027), whereas the frailty-only pathway was not. The sequential pathway through nutritional status and frailty was not significant (B = − 0.018, p = 0.058). Conclusions Longer ICU stay was indirectly associated with greater financial toxicity, primarily through poorer nutritional status. These findings suggest that nutritional screening before discharge may help identify ICU survivors at early risk of financial vulnerability, and that incorporating nutritional status into pre-discharge assessment protocols may support more targeted referral to post-discharge support services. ICU survivors Financial toxicity Nutritional status Frailty Length of stay Health services research Discharge planning Figures Figure 1 Figure 2 Introduction With advances in critical care, in-hospital mortality among intensive care unit (ICU) patients has declined, resulting in a growing population of ICU survivors. As survival has improved, attention has increasingly shifted from short-term mortality to longer-term recovery and quality of life after critical illness. However, many survivors continue to experience substantial physical, psychological, and cognitive problems after discharge, often described within the framework of post-intensive care syndrome (PICS) [ 1 – 3 ]. In addition to these health-related sequelae, the financial burden experienced by ICU survivors and their families has also drawn increasing attention [ 4 ]. Critical care is resource intensive, and ICU treatment is often accompanied by substantial medical expenditure [ 4 , 5 ]. Beyond the acute hospitalization period, survivors may face persistent economic strain related to reduced work capacity, prolonged rehabilitation needs, and ongoing caregiving demands [ 6 ]. These pressures may contribute to financial toxicity, a concept that refers to both the material burden of medical care and the psychological distress arising from financial strain [ 7 ]. Although financial toxicity has been widely studied in oncology, it remains less well understood among survivors of critical illness [ 8 – 10 ]. Existing studies in this area have mainly focused on baseline socioeconomic factors, such as income and insurance coverage, or on the direct costs of hospitalisation [ 11 ]. Less attention has been paid to how clinical recovery characteristics identifiable within the hospital episode may be associated with financial toxicity after critical illness. Understanding whether such factors are involved has direct implications for how discharge planning and post-acute services are organised, particularly given that socioeconomic circumstances are often difficult to modify within the clinical encounter. This question is especially relevant given the substantial healthcare costs associated with post-ICU recovery, including ongoing rehabilitation, community care, and repeated healthcare utilisation, all of which place additional strain on patients and health systems alike. Guided by the conceptual framework of PICS [ 12 ] and the Wilson and Cleary model of health outcomes [ 13 ], this study examined how ICU length of stay (LOS), nutritional status, and multidimensional frailty may be related to financial toxicity. ICU LOS is commonly used as an indicator of cumulative illness burden and treatment intensity during critical illness, and prolonged ICU exposure is often accompanied by metabolic stress and nutritional decline [ 14 ]. Poor nutritional status has been linked to impaired recovery and increased vulnerability, including higher levels of multidimensional frailty [ 15 ]. Among middle-aged and older survivors, frailty reflects deficits across physical, psychological, and social domains and is associated with reduced functional independence and greater care needs [ 16 ]. Together, these factors may contribute to financial strain during recovery. Financial toxicity research in critical illness has largely concentrated on upstream socioeconomic determinants, including income, insurance status, and direct hospitalisation costs, while the contribution of clinical recovery characteristics has received comparatively little attention [ 8 – 11 ]. This gap matters because clinical variables, unlike socioeconomic circumstances, may be more readily detected and acted upon within routine nursing practice. Nutritional status and multidimensional frailty are both routinely assessable before discharge and have established links to functional recovery trajectories after critical illness [ 14 – 16 ], yet whether either is associated with financial toxicity in this population, or whether they help explain how ICU exposure translates into financial strain, remains largely unexplored. Clarifying these relationships may help identify which patients are at elevated financial risk at the point of discharge, informing decisions about resource allocation and referral to post-discharge support services. This study therefore examined whether nutritional status and multidimensional frailty mediate the relationship between ICU LOS and financial toxicity in middle-aged and older ICU survivors, with the aim of identifying routinely obtainable clinical markers that could guide the organisation of post-ICU transitional care and support services. Methods 2.1 Study design and participants This single-centre cross-sectional study was conducted at a tertiary hospital in Zhejiang Province, China, between November 2025 and March 2026. Middle-aged and older adults aged 45 years or above who had survived critical illness were screened for eligibility after transfer from the ICU to general wards. Eligible participants were approached and interviewed within 48 hours before hospital discharge. Participants were eligible if they were aged 45 years or older, had an ICU length of stay of at least 48 hours, and were conscious and cognitively able to complete the survey, defined as a Glasgow Coma Scale score of at least 15 and a negative Confusion Assessment Method for the ICU (CAM-ICU). Patients were excluded if they had neurological or severe physical conditions that could substantially interfere with functional assessment or questionnaire completion. Detailed inclusion and exclusion criteria are presented in Supplementary Table S1. A total of 458 eligible participants were initially enrolled. During retrospective extraction of clinical information from the electronic medical record system, cases with missing data on any study variable or covariate were excluded. The final analytic sample consisted of 422 participants with complete data. Sample size adequacy was evaluated based on the recommendation of 10 observations per free parameter. The structural equation model in this study estimated approximately 20 free parameters, indicating a minimum requirement of around 200 participants. The final sample of 422 participants comfortably exceeded this threshold and was considered sufficient for the planned analyses, including bootstrap-based estimation of indirect effects with 5,000 resamples. 2.2 Data collection Data were collected through face-to-face interviews by trained researchers. Demographic and socioeconomic information was obtained using a structured questionnaire developed specifically for this study. The questionnaire was developed based on a review of relevant literature and expert consultation. The English version of the questionnaire is provided in Supplementary File 1. Clinical data were extracted retrospectively from the electronic medical record using a standardized form. Collected variables included demographic characteristics, lifestyle factors, treatment-related variables, and clinical indicators. Demographic variables included age, sex, marital status, education level, and occupation. Lifestyle-related variables included smoking, alcohol use, exercise, and sleep. Clinical variables included BMI, ICU length of stay, hospital length of stay, Charlson Comorbidity Index, duration of mechanical ventilation, pain score at discharge, Barthel Index, and the use of analgesic and sedative medications during the ICU stay. 2.3 Measures 2.3.1 Nutritional status Nutritional status was assessed using the Mini Nutritional Assessment–Short Form (MNA-SF) [17]. The MNA-SF contains six items with a total score ranging from 0 to 14. Scores of 0–7 indicate malnutrition, 8–11 indicate risk of malnutrition, and ≥12 indicate normal nutritional status. The scale has demonstrated good reliability, with a reported Cronbach’s alpha of 0.832. 2.3.2 Multidimensional frailty Multidimensional frailty was assessed using the Tilburg Frailty Indicator (TFI) [18], a self-reported instrument developed by Gobbens et al. The scale consists of 15 items across three domains: physical (8 items), psychological (4 items), and social (3 items). Each item is scored as 0 or 1, with total scores ranging from 0 to 15. A score ≥5 indicates frailty, with higher scores reflecting greater frailty severity. 2.3.3 Financial toxicity Financial toxicity was measured using the Comprehensive Score for Financial Toxicity (COST) [19], originally developed by de Souza et al. as a patient-reported measure of the financial burden associated with medical care. The scale consists of 11 items assessing both financial well-being and psychological distress related to medical expenses. Items are scored on a five-point Likert scale, yielding a total score ranging from 0 to 44, with lower scores indicating greater financial toxicity. Permission to use the MNA-SF, TFI, and the Chinese version of the FACIT-COST was obtained from the respective copyright holders or authorized sources before data collection. 2.3.4 Covariates To reduce potential confounding, age, sex, marital status, education level, duration of mechanical ventilation, and Barthel Index were included in the model as covariates. These variables were selected a priori based on prior literature and their theoretical relevance to financial toxicity, critical illness recovery, and post-ICU functional status. 2.4 Statistical analysis All analyses were performed in R (version 4.5.2-arm64). Continuous variables were summarized as mean ± standard deviation or median (interquartile range), as appropriate. Categorical variables were summarized as frequency and percentage. Variable distributions were assessed by visual inspection and the Shapiro-Wilk test. Spearman rank correlation was used to examine bivariate associations among ICU length of stay, nutritional status, multidimensional frailty, and financial toxicity. Structural equation modeling was used to test the hypothesized serial mediation model with the lavaan package in R. ICU LOS was entered as the independent variable, nutritional status as the first mediator, multidimensional frailty as the second mediator, and COST score as the dependent variable. Age, sex, marital status, education level, duration of mechanical ventilation, and Barthel Index were included as covariates. Parameters were estimated with robust maximum likelihood estimation. Indirect effects were tested with bootstrap resampling based on 5,000 samples, and 95% confidence intervals were calculated. An indirect effect was considered statistically significant when the confidence interval did not include zero. Both unstandardized coefficients (B) and standardized coefficients (β) were reported. Indirect effects included the path through nutritional status alone (X → M1 → Y), the path through multidimensional frailty alone (X → M2 → Y), the serial path through nutritional status and multidimensional frailty (X → M1 → M2 → Y), and the total indirect effect. Complete-case analysis was used. Patients with missing data on any study variable or covariate were excluded from the model. 2.5 Ethical approval This study was approved by the Ethics Committee of Sir Run Run Shaw Hospital, Zhejiang University School of Medicine (Approval No. 2026.0191, Acceptance No. 2026-2143-01). All procedures were conducted in accordance with the ethical standards of the institutional research committee and the Declaration of Helsinki. Written informed consent was obtained from all participants before participation. Results 3.1 Participant characteristics A flow diagram of participant inclusion and analysis is shown in Figure 1. Of the 458 participants initially enrolled, 36 were excluded because of missing data on study variables or covariates, leaving 422 participants in the final analysis. The mean age was 69.8 years (SD = 10.4), and 266 participants (63.0%) were male. Most participants were married (87.2%), retired (55.7%), and had a primary school education or below (53.8%). The median ICU length of stay was 5 days (IQR 3–9), and the median duration of mechanical ventilation was 24 hours (IQR 8–72). The mean nutritional status score was 10.3 (SD = 3.1), the mean multidimensional frailty score was 8.7 (SD = 2.6), and the mean COST score was 18.6 (SD = 9.7). Participant characteristics are shown in Table 1. Table 1. Characteristics of the study participants (N = 422) Variable No. (%) or Value Age, mean (SD), y 69.8 ± 10.4 Sex Male 266 (63.0) Female 156 (37.0) Education Primary school or below 227 (53.8) Middle school / vocational 166 (39.3) College or above 29 (6.9) Occupation Housewife/Farmer/Worker 152 (36.0) Self-employed/business 24 (5.7) Teacher/Company employee 11 (2.6) Retired 235 (55.7) Marital status Married 368 (87.2) Unmarried 5 (1.2) Divorced 10 (2.4) Widowed 39 (9.2) BMI, mean (SD) 22.9 ± 3.97 Smoking Never 278 (65.9) Quit <2 years 19 (4.5) Quit ≥2 years 46 (10.9) Current smoking 79 (18.7) Alcohol Never 276 (65.4) Quit drinking 62 (14.7) Current drinking 84 (19.9) Exercise Never 117 (27.7) Occasionally 167 (39.6) Frequently 138 (32.7) Sleep < 6 h 187 (44.3) ≥ 6 h 235 (55.7) Sedative use in ICU Yes 269 (63.7) No 153 (36.3) Analgesic use in ICU Yes 332 (78.7) No 90 (21.3) ICU LOS , median (IQR), d 5 (3–9) Hospital length of stay, median (IQR), d 14 (10–20) Charlson Comorbidity Index, mean (SD) 3.2 ± 1.5 Mechanical ventilation duration, median (IQR), h 24 (8–72) Multidimensional frailty score, mean (SD) 8.7 ± 2.6 Barthel Index, mean (SD) 72.4 ± 21.3 Nutritional status score, mean (SD) 10.3 ± 3.1 Financial toxicity score, mean (SD) 18.6 ± 9.7 Note: Values are presented as mean (SD), median (IQR), or n (%) 3.2 Correlations among the core study variables Spearman rank correlations among the core study variables are shown in Table 2. ICU length of stay was negatively correlated with nutritional status (ρ = −0.243, p < 0.001) and positively correlated with multidimensional frailty (ρ = 0.240, p < 0.001). Nutritional status was negatively correlated with multidimensional frailty (ρ = −0.394, p < 0.001). COST score was positively correlated with nutritional status (ρ = 0.139, p = 0.004) and negatively correlated with multidimensional frailty (ρ = −0.146, p = 0.003), indicating lower financial toxicity among participants with better nutritional status and lower frailty. The correlation between ICU length of stay and COST score was not statistically significant (ρ = −0.085, p = 0.082). Table 2. Spearman correlations among the core study variables Variable 1 2 3 4 1.ICU LoS 1 2.Nutritional status −0.243*** 1 3.Frailty score 0.240*** −0.394*** 1 4.Financial toxicity −0.085 0.139** −0.146** 1 Values are Spearman rank correlation coefficients (ρ). * p < 0.05, ** p < 0.01, *** p < 0.001 3.3 Serial mediation analysis The serial mediation model is shown in Figure 2, and the parameter estimates are presented in Table 3. Longer ICU length of stay was associated with poorer nutritional status (β = −0.256, p = 0.001). Poorer nutritional status was associated with greater multidimensional frailty (β = −0.325, p < 0.001). Better nutritional status was associated with higher COST scores (β = 0.148, p = 0.003), indicating lower financial toxicity, whereas greater multidimensional frailty was associated with lower COST scores (β = −0.118, p = 0.014), indicating greater financial toxicity. The direct association between ICU length of stay and multidimensional frailty was not statistically significant (β = 0.077, p = 0.195), and the direct association between ICU length of stay and COST score was also not statistically significant (β = −0.075, p = 0.319). Bootstrap estimates of the indirect effects are shown in Table 3. The indirect effect through nutritional status alone was statistically significant (B = −0.069, β = −0.038, 95% CI −0.130 to −0.008, p = 0.027). The indirect effect through multidimensional frailty alone was not statistically significant (B = −0.016, β = −0.009, 95% CI −0.042 to 0.009, p = 0.213). The serial indirect effect did not meet conventional statistical significance (B = −0.018, β = −0.010, 95% CI −0.036 to 0.001, p = 0.058), although the point estimate was directionally consistent with the hypothesized model. The total indirect effect was statistically significant (B = −0.103, β = −0.057, 95% CI −0.172 to −0.034, p = 0.004), whereas the total effect did not reach statistical significance (B = −0.238, β = −0.131, 95% CI −0.505 to 0.029, p = 0.080). Table 3. Serial mediation model linking ICU length of stay, nutritional status, multidimensional frailty, and financial toxicity Path B Standardized β 95% CI p value ICU LoS → Nutritional status -0.115 −0.256 −0.181 to −0.049 0.001 Nutritional status → Frailty -0.297 −0.325 −0.384 to −0.211 <0.001 ICU LoS → Frailty 0.032 0.077 −0.016 to 0.079 0.195 Nutritional status → Financial toxicity 0.600 0.148 0.201 to 0.999 0.003 Frailty → Financial toxicity -0.520 −0.118 −0.935 to −0.106 0.014 ICU LoS → Financial toxicity -0.135 −0.075 −0.401 to 0.130 0.319 Indirect effects Pathway B β 95% CI p value X → M1 → Y -0.069 −0.038 −0.130 to −0.008 0.027 X → M2 → Y -0.016 −0.009 −0.042 to 0.009 0.213 X → M1 → M2 → Y -0.018 −0.010 −0.036 to 0.001 0.058 total indirect effect -0.103 −0.057 −0.172 to −0.034 0.004 total effect -0.238 -0.131 -0.505 to 0.029 0.080 Note:N = 422. X, ICU LoS; M1,nutritional status; M2 multidimensional frailty; Y,financial toxicity B indicates unstandardized coefficients and β indicates standardized coefficients. The model was adjusted for age, sex, marital status, education level, duration of mechanical ventilation, and Barthel Index. Discussion This study examined how ICU length of stay, nutritional status, multidimensional frailty, and financial toxicity were related in middle-aged and older ICU survivors. After adjustment for selected covariates, ICU length of stay was not directly associated with COST score, but showed a statistically significant indirect association through nutritional status. By contrast, the indirect path through multidimensional frailty alone was not supported, and the serial indirect effect through nutritional status and frailty did not reach conventional statistical significance. Interpreted in light of the PICS framework and the Wilson and Cleary model, this pattern suggests that nutritional status and multidimensional frailty may reflect different levels of vulnerability during recovery after critical illness [12,13]. Nutritional status may represent a more immediate marker of vulnerability at discharge, whereas multidimensional frailty may reflect a broader and more slowly evolving state of risk. The stronger role of nutritional status likely reflects both the timing of measurement and the level of recovery captured by this variable. Prolonged ICU stay often coincides with inflammation, hypercatabolism, reduced intake, immobility, and muscle loss [20,21]. These processes rapidly erode physiological reserve and are reflected relatively directly in nutritional assessment at discharge. At this stage of recovery, nutritional status appears to function as a more proximal marker of compromised recovery than broader and more distal outcomes [22]. In the present study, longer ICU stay was associated with poorer nutritional status, and poorer nutritional status was associated with lower COST scores. Poor nutritional status is also linked to delayed recovery, greater rehabilitation and caregiving needs, and reduced capacity to resume previous social and family roles after discharge [21]. Although causality cannot be inferred from this cross-sectional design, the observed pattern supports the view that nutritional status is an important clinical correlate of early financial vulnerability during the transition from hospital to home. From a nursing perspective, nutritional status may also provide a practical signal of which ICU survivors are likely to need closer assessment and support before discharge. Multidimensional frailty appeared to play a different role in the model. Frailty was significantly associated with COST score, but the indirect path through frailty alone was not statistically significant, and the serial indirect effect was only marginal. This may indicate that multidimensional frailty represents a broader state of vulnerability rather than a direct extension of ICU exposure alone [23]. Because the TFI captures physical, psychological, and social domains, frailty may summarize accumulated deficits that are shaped by nutritional decline, functional limitation, psychological burden, and reduced social participation [18,24]. In that sense, frailty may be more useful as an indicator of overall recovery burden than as a specific explanatory link between ICU length of stay and financial toxicity [25]. This distinction suggests that clinically relevant vulnerabilities may occupy different positions in the recovery process. In ICU survivors, financial toxicity appears to reflect not only socioeconomic disadvantage but also the clinical course of recovery [26]. In the present study, poorer nutritional status was associated with lower COST scores, suggesting greater financial toxicity, whereas the pathway through frailty alone was not supported. One possible explanation is that nutritional deterioration appears to be more directly linked to the practical consequences of recovery after critical illness [22,27]. Patients with poor nutritional status are more likely to experience delayed physical recovery, prolonged dependence on rehabilitation and caregiving, and reduced capacity to resume previous family and social roles, all of which can contribute to early financial strain after discharge [20]. Because COST was assessed shortly before hospital discharge, the findings reflect early perceived financial vulnerability rather than the full long-term economic consequences of critical illness. This timing remains clinically relevant, as hospitalisation costs have already been incurred and concerns about continuing care and rehabilitation are beginning to emerge. Prior research in ICU survivors has documented substantial and persistent economic strain after discharge, including reduced labour market participation and ongoing out-of-pocket expenditure, suggesting that the financial burden identified here may extend well beyond the immediate post-discharge period [6,26,28]. These findings carry implications for how post-ICU care pathways are designed and resourced. The pattern observed here, where nutritional status carried the indirect association with financial toxicity, points to a concrete and actionable signal that could be integrated into pre-discharge assessment protocols. Nutritional screening tools such as the MNA-SF are brief, require no specialised equipment, and are already incorporated into many discharge workflows [17]. The present data suggest that low MNA-SF scores before discharge may serve as an early marker not only of physical recovery risk but also of financial vulnerability in the weeks following hospitalisation. From a health services perspective, this raises the question of whether pre-discharge nutritional screening could be used to stratify patients for differential post-discharge support, for example by prioritising referrals to community dietetic services, social work assessment, or structured transitional care programmes for those identified as nutritionally at risk [28,29]. The findings also point to a broader gap in how post-ICU care transitions are currently structured. In many health systems, discharge planning for ICU survivors remains focused on clinical stabilisation and medication management, with less systematic attention to the economic consequences of recovery [6,26]. The present study suggests that financial vulnerability may begin to accumulate while patients are still hospitalised, and that clinical indicators available before discharge, particularly nutritional status, may signal who is at greatest risk. Embedding structured financial risk assessment alongside existing clinical discharge protocols could enable earlier connection to relevant support services, including community rehabilitation, social welfare referrals, and transitional care coordination, before financial hardship becomes entrenched [28]. Frailty assessment, while less central to the specific pathway identified here, provides complementary information about the broader recovery burden patients are likely to face after leaving hospital [23], and may inform resource allocation decisions for post-acute care services. Limitations Several limitations should be considered. First, the cross-sectional design does not allow conclusions about causality or temporal sequence, and the observed indirect effects should therefore be interpreted as statistical patterns rather than confirmed mechanisms. Second, the study was conducted at a single tertiary hospital, which may limit transferability to other settings and health systems. Third, ICU length of stay was used as a proxy indicator of cumulative illness burden and treatment intensity, and it cannot distinguish among disease severity, complications, and care processes. Fourth, financial toxicity was assessed before discharge and may therefore reflect early perceived financial distress rather than longer-term financial hardship. Finally, although selected demographic and clinical covariates were included, unmeasured socioeconomic confounding could not be excluded. Conclusion Nutritional status was associated with financial toxicity in middle-aged and older ICU survivors and carried a more central role than multidimensional frailty in the pathway examined here. These findings suggest that nutritional screening before discharge may serve as a practical signal for identifying patients at early financial risk, and that nutritional status warrants explicit consideration in discharge assessment alongside functional recovery after critical illness. Declarations Ethics approval and consent to participate This study was approved by the Ethics Committee of Sir Run Run Shaw Hospital, Zhejiang University School of Medicine (Approval No. 2026.0191, Acceptance No. 2026-2143-01). All procedures were conducted in accordance with the ethical standards of the institutional research committee and the Declaration of Helsinki. Written informed consent was obtained from all participants before participation. This was not a clinical trial, so trial registration is not applicable. Consent for publication : Not applicable. Funding This study was supported by the Zhejiang Hospital Association Project, Qilu Research Program for the Development of Medical Consortium Construction (2025KY904). Conflict of interest The authors declare that they have no competing interests. Authors' contributions ZH: Conceptualization, Methodology, Software, Investigation, Writing - original draft. YZ: Resources, Supervision, Funding acquisition, Writing - review & editing. All authors: Read and approved the final manuscript. Acknowledgments We would like to thank all participating patients and hospital staff for their support of this study. References Herridge MS, Azoulay É. Outcomes after critical illness. N Engl J Med. 2023;388(10):913–24. 10.1056/NEJMra2104669 . Butcher BW. Post-intensive care syndrome. JAMA. 2026;335(6):542–3. 10.1001/jama.2025.23666 . Zare-Kaseb A, Sanaie N, Sarmadi S. 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Frailty in very old critically ill patients in Australia and New Zealand: a population-based cohort study. Med J Aust. 2019;211(7):318–23. 10.5694/mja2.50329 . Khandelwal N, Hough CL, Downey L, et al. Prevalence, risk factors, and outcomes of financial stress in survivors of critical illness. Crit Care Med. 2018;46(6):e530–9. 10.1097/CCM.0000000000003076 . Patel BK, Pohlman AS, Hall JB, Kress JP. Impact of early mobilization on glycemic control and ICU-acquired weakness in critically ill patients who are mechanically ventilated. Chest. 2014;146(3):583–9. 10.1378/chest.13-2046 . Schandl A, Bäckman C, Ehnfors M, et al. The impact of critical illness on patients’ physical function and its recovery 6 months following critical illness. Intensive Crit Care Nurs. 2024;80:103562. 10.1016/j.iccn.2023.103562 . Lasiter S, Oles SK, Mundell J, London S, Khan B. Examining the needs of survivors of critical illness through the lens of ICU recovery programs. Intensive Crit Care Nurs. 2023;74:103321. 10.1016/j.iccn.2022.103321 . Griffiths J, Hatch RA, Bishop J, et al. An exploration of social and economic outcome and associated health-related quality of life after critical illness in general intensive care unit survivors. Crit Care. 2013;17(3):R100. Haines KJ, Hibbert E, Leggett N, et al. Transitions of care after critical illness: challenges to recovery and adaptive problem solving. Crit Care Med. 2021;49(11):1923–31. Altice CK, Banegas MP, Tucker-Seeley RD, Yabroff KR. Financial hardship experienced by cancer survivors: a systematic review. J Natl Cancer Inst. 2017;109(2):djw205. Additional Declarations No competing interests reported. Supplementary Files SupplementaryTableS1.docx SupplementaryFile1.Englishversionofthestudyspecificinterviewquestionnaireusedinthisstudy.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviewers invited by journal 05 May, 2026 Editor assigned by journal 04 May, 2026 Editor invited by journal 13 Apr, 2026 Submission checks completed at journal 12 Apr, 2026 First submitted to journal 12 Apr, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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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-9333777","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":639295148,"identity":"85b11871-4ec5-4122-b73f-774b07338686","order_by":0,"name":"Zhenzhen Huang","email":"","orcid":"","institution":"Sir Run Run Shaw Hospital, Zhejiang University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Zhenzhen","middleName":"","lastName":"Huang","suffix":""},{"id":639295149,"identity":"937db5a3-5bbe-43cb-90fd-3a40792485da","order_by":1,"name":"Yuhan Chen","email":"","orcid":"","institution":"Sir Run Run Shaw Hospital, Zhejiang University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Yuhan","middleName":"","lastName":"Chen","suffix":""},{"id":639295150,"identity":"f240e595-9f15-4b80-a2b7-500dc48e66ee","order_by":2,"name":"Ran Yu","email":"","orcid":"","institution":"Sir Run Run Shaw Hospital, Zhejiang University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Ran","middleName":"","lastName":"Yu","suffix":""},{"id":639295151,"identity":"465c237f-23cb-4f78-aeb2-f6cbe566e378","order_by":3,"name":"Peiyao Zheng","email":"","orcid":"","institution":"Sir Run Run Shaw Hospital, Zhejiang University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Peiyao","middleName":"","lastName":"Zheng","suffix":""},{"id":639295155,"identity":"224ed343-2879-4210-a85d-674d933eb0ea","order_by":4,"name":"Yiyu Zhuang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4klEQVRIiWNgGAWjYDACCSjNz8CQAKSYSdAi2UCyFoMDYIoILfKzeww/F/w6nLj5/IFnEgwV1okN7GcP4NXCOOeMsfTMvsOJ2w4cSJNgOJOe2MCTl4BXC7NEjoE0bw9Qy8GGNAnGtsOJDRI8Bni1sEnkGP8GadnczADU8o8ILTwSOWbSPD8OJ25gA2lpIEKLhERamTVvQ7rxjDMMyRYJx9KN23hy8GuRn5G8+TbPH2vZ/v4ziTc+1AAZ7GfwawEDxrZmxwYGngRwZLIRVg8Cf+rsGRjYDxCneBSMglEwCkYcAACB7EUAsVMsRAAAAABJRU5ErkJggg==","orcid":"","institution":"Sir Run Run Shaw Hospital, Zhejiang University School of Medicine","correspondingAuthor":true,"prefix":"","firstName":"Yiyu","middleName":"","lastName":"Zhuang","suffix":""}],"badges":[],"createdAt":"2026-04-06 12:10:28","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9333777/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9333777/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":109266432,"identity":"ceaf7d4b-95ed-4291-b671-a4bf1e7df7be","added_by":"auto","created_at":"2026-05-14 12:51:58","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":83734,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFlow diagram of participant inclusion and analysis\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-9333777/v1/92518acdd5a576504616c2bb.png"},{"id":109298016,"identity":"c0a23706-9b36-422d-bedf-0805f24d851e","added_by":"auto","created_at":"2026-05-15 09:08:23","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":85169,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSerial mediation model linking ICU length of stay, nutritional status, multidimensional frailty, and financial toxicity.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNote. *P \u0026lt; 0.05, **P \u0026lt; 0.01, ***P \u0026lt; 0.001.\u003c/p\u003e\n\u003cp\u003eValues on arrows represent standardized coefficients (β).\u003c/p\u003e\n\u003cp\u003eSolid lines indicate significant paths and dashed lines indicate non-significant paths.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-9333777/v1/79657432deeeac818ddd6ab6.png"},{"id":109296351,"identity":"c418e3f2-2c33-4f20-af3f-74d948ba7e99","added_by":"auto","created_at":"2026-05-15 08:46:35","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":338379,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9333777/v1/5f1f67ec-f8de-4f19-8b72-10135fc05756.pdf"},{"id":109266431,"identity":"8c564ec7-289e-48c2-a5f1-3680c7fc3b3f","added_by":"auto","created_at":"2026-05-14 12:51:58","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":11772,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTableS1.docx","url":"https://assets-eu.researchsquare.com/files/rs-9333777/v1/bba0c185dedc815050a4a862.docx"},{"id":109266433,"identity":"757ffc8a-a3a5-4fd3-bdb5-a6db34ce1ac7","added_by":"auto","created_at":"2026-05-14 12:51:59","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":12521,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFile1.Englishversionofthestudyspecificinterviewquestionnaireusedinthisstudy.docx","url":"https://assets-eu.researchsquare.com/files/rs-9333777/v1/51e07d970a6ec17578217970.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Financial Toxicity in ICU Survivors: The Mediating Role of Nutritional Status and Implications for Post-Discharge Service Planning","fulltext":[{"header":"Introduction","content":"\u003cp\u003eWith advances in critical care, in-hospital mortality among intensive care unit (ICU) patients has declined, resulting in a growing population of ICU survivors. As survival has improved, attention has increasingly shifted from short-term mortality to longer-term recovery and quality of life after critical illness. However, many survivors continue to experience substantial physical, psychological, and cognitive problems after discharge, often described within the framework of post-intensive care syndrome (PICS) [\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. In addition to these health-related sequelae, the financial burden experienced by ICU survivors and their families has also drawn increasing attention [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eCritical care is resource intensive, and ICU treatment is often accompanied by substantial medical expenditure [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Beyond the acute hospitalization period, survivors may face persistent economic strain related to reduced work capacity, prolonged rehabilitation needs, and ongoing caregiving demands [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. These pressures may contribute to financial toxicity, a concept that refers to both the material burden of medical care and the psychological distress arising from financial strain [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Although financial toxicity has been widely studied in oncology, it remains less well understood among survivors of critical illness [\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eExisting studies in this area have mainly focused on baseline socioeconomic factors, such as income and insurance coverage, or on the direct costs of hospitalisation [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Less attention has been paid to how clinical recovery characteristics identifiable within the hospital episode may be associated with financial toxicity after critical illness. Understanding whether such factors are involved has direct implications for how discharge planning and post-acute services are organised, particularly given that socioeconomic circumstances are often difficult to modify within the clinical encounter. This question is especially relevant given the substantial healthcare costs associated with post-ICU recovery, including ongoing rehabilitation, community care, and repeated healthcare utilisation, all of which place additional strain on patients and health systems alike.\u003c/p\u003e \u003cp\u003eGuided by the conceptual framework of PICS [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] and the Wilson and Cleary model of health outcomes [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], this study examined how ICU length of stay (LOS), nutritional status, and multidimensional frailty may be related to financial toxicity. ICU LOS is commonly used as an indicator of cumulative illness burden and treatment intensity during critical illness, and prolonged ICU exposure is often accompanied by metabolic stress and nutritional decline [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Poor nutritional status has been linked to impaired recovery and increased vulnerability, including higher levels of multidimensional frailty [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Among middle-aged and older survivors, frailty reflects deficits across physical, psychological, and social domains and is associated with reduced functional independence and greater care needs [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Together, these factors may contribute to financial strain during recovery.\u003c/p\u003e \u003cp\u003eFinancial toxicity research in critical illness has largely concentrated on upstream socioeconomic determinants, including income, insurance status, and direct hospitalisation costs, while the contribution of clinical recovery characteristics has received comparatively little attention [\u003cspan additionalcitationids=\"CR9 CR10\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. This gap matters because clinical variables, unlike socioeconomic circumstances, may be more readily detected and acted upon within routine nursing practice. Nutritional status and multidimensional frailty are both routinely assessable before discharge and have established links to functional recovery trajectories after critical illness [\u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], yet whether either is associated with financial toxicity in this population, or whether they help explain how ICU exposure translates into financial strain, remains largely unexplored. Clarifying these relationships may help identify which patients are at elevated financial risk at the point of discharge, informing decisions about resource allocation and referral to post-discharge support services. This study therefore examined whether nutritional status and multidimensional frailty mediate the relationship between ICU LOS and financial toxicity in middle-aged and older ICU survivors, with the aim of identifying routinely obtainable clinical markers that could guide the organisation of post-ICU transitional care and support services.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003e2.1 Study design and participants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis single-centre cross-sectional study was conducted at a tertiary hospital in Zhejiang Province, China, between November 2025 and March 2026. Middle-aged and older adults aged 45 years or above who had survived critical illness were screened for eligibility after transfer from the ICU to general wards. Eligible participants were approached and interviewed within 48 hours before hospital discharge.\u003c/p\u003e\n\u003cp\u003eParticipants were eligible if they were aged 45 years or older, had an ICU length of stay of at least 48 hours, and were conscious and cognitively able to complete the survey, defined as a Glasgow Coma Scale score of at least 15 and a negative Confusion Assessment Method for the ICU (CAM-ICU). Patients were excluded if they had neurological or severe physical conditions that could substantially interfere with functional assessment or questionnaire completion. Detailed inclusion and exclusion criteria are presented in Supplementary Table S1.\u003c/p\u003e\n\u003cp\u003eA total of 458 eligible participants were initially enrolled. During retrospective extraction of clinical information from the electronic medical record system, cases with missing data on any study variable or covariate were excluded. The final analytic sample consisted of 422 participants with complete data.\u003c/p\u003e\n\u003cp\u003eSample size adequacy was evaluated based on the recommendation of 10 observations per free parameter. The structural equation model in this study estimated approximately 20 free parameters, indicating a minimum requirement of around 200 participants. The final sample of 422 participants comfortably exceeded this threshold and was considered sufficient for the planned analyses, including bootstrap-based estimation of indirect effects with 5,000 resamples.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2 Data collection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData were collected through face-to-face interviews by trained researchers. Demographic and socioeconomic information was obtained using a structured questionnaire developed specifically for this study. The questionnaire was developed based on a review of relevant literature and expert consultation. The English version of the questionnaire is provided in Supplementary File 1. Clinical data were extracted retrospectively from the electronic medical record using a standardized form.\u003c/p\u003e\n\u003cp\u003eCollected variables included demographic characteristics, lifestyle factors, treatment-related variables, and clinical indicators. Demographic variables included age, sex, marital status, education level, and occupation. Lifestyle-related variables included smoking, alcohol use, exercise, and sleep. Clinical variables included BMI, ICU length of stay, hospital length of stay, Charlson Comorbidity Index, duration of mechanical ventilation, pain score at discharge, Barthel Index, and the use of analgesic and sedative medications during the ICU stay.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.3 Measures\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.3.1 Nutritional status\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNutritional status was assessed using the Mini Nutritional Assessment\u0026ndash;Short Form (MNA-SF) [17]. The MNA-SF contains six items with a total score ranging from 0 to 14. Scores of 0\u0026ndash;7 indicate malnutrition, 8\u0026ndash;11 indicate risk of malnutrition, and \u0026ge;12 indicate normal nutritional status. The scale has demonstrated good reliability, with a reported Cronbach\u0026rsquo;s alpha of 0.832.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.3.2 Multidimensional frailty\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMultidimensional frailty was assessed using the Tilburg Frailty Indicator (TFI) [18], a self-reported instrument developed by Gobbens et al. The scale consists of 15 items across three domains: physical (8 items), psychological (4 items), and social (3 items). Each item is scored as 0 or 1, with total scores ranging from 0 to 15. A score \u0026ge;5 indicates frailty, with higher scores reflecting greater frailty severity.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.3.3 Financial toxicity\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFinancial toxicity was measured using the Comprehensive Score for Financial Toxicity (COST) [19], originally developed by de Souza et al. as a patient-reported measure of the financial burden associated with medical care. The scale consists of 11 items assessing both financial well-being and psychological distress related to medical expenses. Items are scored on a five-point Likert scale, yielding a total score ranging from 0 to 44, with lower scores indicating greater financial toxicity.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePermission to use the MNA-SF, TFI, and the Chinese version of the FACIT-COST was obtained from the respective copyright holders or authorized sources before data collection.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.3.4 Covariates\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo reduce potential confounding, age, sex, marital status, education level, duration of mechanical ventilation, and Barthel Index were included in the model as covariates. These variables were selected a priori based on prior literature and their theoretical relevance to financial toxicity, critical illness recovery, and post-ICU functional status.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.4 Statistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll analyses were performed in R (version 4.5.2-arm64). Continuous variables were summarized as mean \u0026plusmn; standard deviation or median (interquartile range), as appropriate. Categorical variables were summarized as frequency and percentage. Variable distributions were assessed by visual inspection and the Shapiro-Wilk test. Spearman rank correlation was used to examine bivariate associations among ICU length of stay, nutritional status, multidimensional frailty, and financial toxicity.\u003c/p\u003e\n\u003cp\u003eStructural equation modeling was used to test the hypothesized serial mediation model with the lavaan package in R. ICU LOS was entered as the independent variable, nutritional status as the first mediator, multidimensional frailty as the second mediator, and COST score as the dependent variable. Age, sex, marital status, education level, duration of mechanical ventilation, and Barthel Index were included as covariates.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eParameters were estimated with robust maximum likelihood estimation. Indirect effects were tested with bootstrap resampling based on 5,000 samples, and 95% confidence intervals were calculated. An indirect effect was considered statistically significant when the confidence interval did not include zero. Both unstandardized coefficients (B) and standardized coefficients (\u0026beta;) were reported. Indirect effects included the path through nutritional status alone (X \u0026rarr; M1 \u0026rarr; Y), the path through multidimensional frailty alone (X \u0026rarr; M2 \u0026rarr; Y), the serial path through nutritional status and multidimensional frailty (X \u0026rarr; M1 \u0026rarr; M2 \u0026rarr; Y), and the total indirect effect. Complete-case analysis was used. Patients with missing data on any study variable or covariate were excluded from the model.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.5 Ethical approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Ethics Committee of Sir Run Run Shaw Hospital, Zhejiang University School of Medicine (Approval No. 2026.0191, Acceptance No. 2026-2143-01). All procedures were conducted in accordance with the ethical standards of the institutional research committee and the Declaration of Helsinki. Written informed consent was obtained from all participants before participation.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003e3.1 Participant characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA flow diagram of participant inclusion and analysis is shown in Figure 1. Of the 458 participants initially enrolled, 36 were excluded because of missing data on study variables or covariates, leaving 422 participants in the final analysis. The mean age was 69.8 years (SD = 10.4), and 266 participants (63.0%) were male. Most participants were married (87.2%), retired (55.7%), and had a primary school education or below (53.8%). The median ICU length of stay was 5 days (IQR 3\u0026ndash;9), and the median duration of mechanical ventilation was 24 hours (IQR 8\u0026ndash;72). The mean nutritional status score was 10.3 (SD = 3.1), the mean multidimensional frailty score was 8.7 (SD = 2.6), and the mean COST score was 18.6 (SD = 9.7). Participant characteristics are shown in Table 1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1. Characteristics of the study participants (N = 422)\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo. (%) or Value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eAge, mean (SD), y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003e69.8 \u0026plusmn; 10.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003e266 (63.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003e156 (37.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eEducation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003ePrimary school or below\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003e227 (53.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003eMiddle school / vocational\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003e166 (39.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003eCollege or above\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003e29 (6.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eOccupation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003eHousewife/Farmer/Worker\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003e152 (36.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003eSelf-employed/business\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003e24 (5.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003eTeacher/Company employee\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003e11 (2.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003eRetired\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003e235 (55.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eMarital status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003e368 (87.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003eUnmarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003e5 (1.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003eDivorced\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003e10 (2.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003eWidowed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003e39 (9.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eBMI, mean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003e22.9 \u0026plusmn; 3.97\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eSmoking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003eNever\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003e278 (65.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003eQuit \u0026lt;2 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003e19 (4.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003eQuit \u0026ge;2 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003e46 (10.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003eCurrent smoking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003e79 (18.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eAlcohol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003eNever\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003e276 (65.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003eQuit drinking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003e62 (14.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003eCurrent drinking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003e84 (19.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eExercise\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003eNever\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003e117 (27.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003eOccasionally\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003e167 (39.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003eFrequently\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003e138 (32.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eSleep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003e\u0026lt; 6 h\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003e187 (44.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003e\u0026ge; 6 h\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003e235 (55.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eSedative use in ICU\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003e269 (63.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003e153 (36.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eAnalgesic use in ICU\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003e332 (78.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003e90 (21.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eICU LOS , median (IQR), d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003e5 (3\u0026ndash;9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eHospital length of stay, median (IQR), d\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003e14 (10\u0026ndash;20)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eCharlson Comorbidity Index, mean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003e3.2 \u0026plusmn; 1.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eMechanical ventilation duration, median (IQR), h\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003e24 (8\u0026ndash;72)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eMultidimensional frailty score, mean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003e8.7 \u0026plusmn; 2.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eBarthel Index, mean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003e72.4 \u0026plusmn; 21.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eNutritional status score, mean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003e10.3 \u0026plusmn; 3.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eFinancial toxicity score, mean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003e18.6 \u0026plusmn; 9.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eNote: Values are presented as mean (SD), median (IQR), or n (%)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2 Correlations among the core study variables\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSpearman rank correlations among the core study variables are shown in Table 2. ICU length of stay was negatively correlated with nutritional status (\u0026rho; = \u0026minus;0.243, p \u0026lt; 0.001) and positively correlated with multidimensional frailty (\u0026rho; = 0.240, p \u0026lt; 0.001). Nutritional status was negatively correlated with multidimensional frailty (\u0026rho; = \u0026minus;0.394, p \u0026lt; 0.001). COST score was positively correlated with nutritional status (\u0026rho; = 0.139, p = 0.004) and negatively correlated with multidimensional frailty (\u0026rho; = \u0026minus;0.146, p = 0.003), indicating lower financial toxicity among participants with better nutritional status and lower frailty. The correlation between ICU length of stay and COST score was not statistically significant (\u0026rho; = \u0026minus;0.085, p = 0.082).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2. Spearman correlations among the core study variables\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"440\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003e1.ICU LoS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003e2.Nutritional status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026minus;0.243***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003e3.Frailty score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.240***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026minus;0.394***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003e4.Financial toxicity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026minus;0.085\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e0.139**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026minus;0.146**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eValues are Spearman rank correlation coefficients (\u0026rho;).\u003c/p\u003e\n\u003cp\u003e* p \u0026lt; 0.05, ** p \u0026lt; 0.01, *** p \u0026lt; 0.001\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.3 Serial mediation analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe serial mediation model is shown in Figure 2, and the parameter estimates are presented in Table 3. Longer ICU length of stay was associated with poorer nutritional status (\u0026beta; = \u0026minus;0.256, p = 0.001). Poorer nutritional status was associated with greater multidimensional frailty (\u0026beta; = \u0026minus;0.325, p \u0026lt; 0.001). Better nutritional status was associated with higher COST scores (\u0026beta; = 0.148, p = 0.003), indicating lower financial toxicity, whereas greater multidimensional frailty was associated with lower COST scores (\u0026beta; = \u0026minus;0.118, p = 0.014), indicating greater financial toxicity. The direct association between ICU length of stay and multidimensional frailty was not statistically significant (\u0026beta; = 0.077, p = 0.195), and the direct association between ICU length of stay and COST score was also not statistically significant (\u0026beta; = \u0026minus;0.075, p = 0.319).\u003c/p\u003e\n\u003cp\u003eBootstrap estimates of the indirect effects are shown in Table 3. The indirect effect through nutritional status alone was statistically significant (B = \u0026minus;0.069, \u0026beta; = \u0026minus;0.038, 95% CI \u0026minus;0.130 to \u0026minus;0.008, p = 0.027). The indirect effect through multidimensional frailty alone was not statistically significant (B = \u0026minus;0.016, \u0026beta; = \u0026minus;0.009, 95% CI \u0026minus;0.042 to 0.009, p = 0.213). The serial indirect effect did not meet conventional statistical significance (B = \u0026minus;0.018, \u0026beta; = \u0026minus;0.010, 95% CI \u0026minus;0.036 to 0.001, p = 0.058), although the point estimate was directionally consistent with the hypothesized model. The total indirect effect was statistically significant (B = \u0026minus;0.103, \u0026beta; = \u0026minus;0.057, 95% CI \u0026minus;0.172 to \u0026minus;0.034, p = 0.004), whereas the total effect did not reach statistical significance (B = \u0026minus;0.238, \u0026beta; = \u0026minus;0.131, 95% CI \u0026minus;0.505 to 0.029, p = 0.080).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3. Serial mediation model linking ICU length of stay, nutritional status, multidimensional frailty, and financial toxicity\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePath\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eB\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStandardized \u0026beta;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003eICU LoS \u0026rarr; Nutritional status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e-0.115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026minus;0.256\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026minus;0.181 to \u0026minus;0.049\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003eNutritional status \u0026rarr; Frailty\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e-0.297\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026minus;0.325\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026minus;0.384 to \u0026minus;0.211\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003eICU LoS \u0026rarr; Frailty\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.032\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.077\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026minus;0.016 to 0.079\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e0.195\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003eNutritional status \u0026rarr; Financial toxicity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.600\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.148\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e0.201 to 0.999\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003eFrailty \u0026rarr; Financial toxicity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e-0.520\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026minus;0.118\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026minus;0.935 to \u0026minus;0.106\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003eICU LoS \u0026rarr; Financial toxicity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e-0.135\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026minus;0.075\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026minus;0.401 to 0.130\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e0.319\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eIndirect effects\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 293px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePathway\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eB\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026beta;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 293px;\"\u003e\n \u003cp\u003eX \u0026rarr; M1 \u0026rarr; Y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e-0.069\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026minus;0.038\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e\u0026minus;0.130 to \u0026minus;0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e0.027\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 293px;\"\u003e\n \u003cp\u003eX \u0026rarr; M2 \u0026rarr; Y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e-0.016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026minus;0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e\u0026minus;0.042 to 0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e0.213\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 293px;\"\u003e\n \u003cp\u003eX \u0026rarr; M1 \u0026rarr; M2 \u0026rarr; Y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e-0.018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026minus;0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e\u0026minus;0.036 to 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e0.058\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 293px;\"\u003e\n \u003cp\u003etotal indirect effect\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e-0.103\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026minus;0.057\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e\u0026minus;0.172 to \u0026minus;0.034\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 293px;\"\u003e\n \u003cp\u003etotal effect\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e-0.238\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e-0.131\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e-0.505 to 0.029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e0.080\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eNote:N = 422.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eX, ICU LoS; M1,nutritional status; M2 multidimensional frailty; Y,financial toxicity\u003c/p\u003e\n\u003cp\u003eB indicates unstandardized coefficients and \u0026beta; indicates standardized coefficients. The model was adjusted for age, sex, marital status, education level, duration of mechanical ventilation, and Barthel Index.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study examined how ICU length of stay, nutritional status, multidimensional frailty, and financial toxicity were related in middle-aged and older ICU survivors. After adjustment for selected covariates, ICU length of stay was not directly associated with COST score, but showed a statistically significant indirect association through nutritional status. By contrast, the indirect path through multidimensional frailty alone was not supported, and the serial indirect effect through nutritional status and frailty did not reach conventional statistical significance. Interpreted in light of the PICS framework and the Wilson and Cleary model, this pattern suggests that nutritional status and multidimensional frailty may reflect different levels of vulnerability during recovery after critical illness [12,13]. Nutritional status may represent a more immediate marker of vulnerability at discharge, whereas multidimensional frailty may reflect a broader and more slowly evolving state of risk.\u003c/p\u003e\n\u003cp\u003eThe stronger role of nutritional status likely reflects both the timing of measurement and the level of recovery captured by this variable. Prolonged ICU stay often coincides with inflammation, hypercatabolism, reduced intake, immobility, and muscle loss [20,21]. These processes rapidly erode physiological reserve and are reflected relatively directly in nutritional assessment at discharge. At this stage of recovery, nutritional status appears to function as a more proximal marker of compromised recovery than broader and more distal outcomes [22]. In the present study, longer ICU stay was associated with poorer nutritional status, and poorer nutritional status was associated with lower COST scores. Poor nutritional status is also linked to delayed recovery, greater rehabilitation and caregiving needs, and reduced capacity to resume previous social and family roles after discharge [21]. Although causality cannot be inferred from this cross-sectional design, the observed pattern supports the view that nutritional status is an important clinical correlate of early financial vulnerability during the transition from hospital to home. From a nursing perspective, nutritional status may also provide a practical signal of which ICU survivors are likely to need closer assessment and support before discharge.\u003c/p\u003e\n\u003cp\u003eMultidimensional frailty appeared to play a different role in the model. Frailty was significantly associated with COST score, but the indirect path through frailty alone was not statistically significant, and the serial indirect effect was only marginal. This may indicate that multidimensional frailty represents a broader state of vulnerability rather than a direct extension of ICU exposure alone [23]. Because the TFI captures physical, psychological, and social domains, frailty may summarize accumulated deficits that are shaped by nutritional decline, functional limitation, psychological burden, and reduced social participation [18,24]. In that sense, frailty may be more useful as an indicator of overall recovery burden than as a specific explanatory link between ICU length of stay and financial toxicity [25]. This distinction suggests that clinically relevant vulnerabilities may occupy different positions in the recovery process.\u003c/p\u003e\n\u003cp\u003eIn ICU survivors, financial toxicity appears to reflect not only socioeconomic disadvantage but also the clinical course of recovery [26]. In the present study, poorer nutritional status was associated with lower COST scores, suggesting greater financial toxicity, whereas the pathway through frailty alone was not supported. One possible explanation is that nutritional deterioration appears to be more directly linked to the practical consequences of recovery after critical illness [22,27]. Patients with poor nutritional status are more likely to experience delayed physical recovery, prolonged dependence on rehabilitation and caregiving, and reduced capacity to resume previous family and social roles, all of which can contribute to early financial strain after discharge [20]. Because COST was assessed shortly before hospital discharge, the findings reflect early perceived financial vulnerability rather than the full long-term economic consequences of critical illness. This timing remains clinically relevant, as hospitalisation costs have already been incurred and concerns about continuing care and rehabilitation are beginning to emerge. Prior research in ICU survivors has documented substantial and persistent economic strain after discharge, including reduced labour market participation and ongoing out-of-pocket expenditure, suggesting that the financial burden identified here may extend well beyond the immediate post-discharge period [6,26,28].\u003c/p\u003e\n\u003cp\u003eThese findings carry implications for how post-ICU care pathways are designed and resourced. The pattern observed here, where nutritional status carried the indirect association with financial toxicity, points to a concrete and actionable signal that could be integrated into pre-discharge assessment protocols. Nutritional screening tools such as the MNA-SF are brief, require no specialised equipment, and are already incorporated into many discharge workflows [17]. The present data suggest that low MNA-SF scores before discharge may serve as an early marker not only of physical recovery risk but also of financial vulnerability in the weeks following hospitalisation. From a health services perspective, this raises the question of whether pre-discharge nutritional screening could be used to stratify patients for differential post-discharge support, for example by prioritising referrals to community dietetic services, social work assessment, or structured transitional care programmes for those identified as nutritionally at risk [28,29].\u003c/p\u003e\n\u003cp\u003eThe findings also point to a broader gap in how post-ICU care transitions are currently structured. In many health systems, discharge planning for ICU survivors remains focused on clinical stabilisation and medication management, with less systematic attention to the economic consequences of recovery [6,26]. The present study suggests that financial vulnerability may begin to accumulate while patients are still hospitalised, and that clinical indicators available before discharge, particularly nutritional status, may signal who is at greatest risk. Embedding structured financial risk assessment alongside existing clinical discharge protocols could enable earlier connection to relevant support services, including community rehabilitation, social welfare referrals, and transitional care coordination, before financial hardship becomes entrenched [28]. Frailty assessment, while less central to the specific pathway identified here, provides complementary information about the broader recovery burden patients are likely to face after leaving hospital [23], and may inform resource allocation decisions for post-acute care services.\u003c/p\u003e"},{"header":"Limitations","content":"\u003cp\u003eSeveral limitations should be considered. First, the cross-sectional design does not allow conclusions about causality or temporal sequence, and the observed indirect effects should therefore be interpreted as statistical patterns rather than confirmed mechanisms. Second, the study was conducted at a single tertiary hospital, which may limit transferability to other settings and health systems. Third, ICU length of stay was used as a proxy indicator of cumulative illness burden and treatment intensity, and it cannot distinguish among disease severity, complications, and care processes. Fourth, financial toxicity was assessed before discharge and may therefore reflect early perceived financial distress rather than longer-term financial hardship. Finally, although selected demographic and clinical covariates were included, unmeasured socioeconomic confounding could not be excluded.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eNutritional status was associated with financial toxicity in middle-aged and older ICU survivors and carried a more central role than multidimensional frailty in the pathway examined here. These findings suggest that nutritional screening before discharge may serve as a practical signal for identifying patients at early financial risk, and that nutritional status warrants explicit consideration in discharge assessment alongside functional recovery after critical illness.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Ethics Committee of Sir Run Run Shaw Hospital, Zhejiang University School of Medicine (Approval No. 2026.0191, Acceptance No. 2026-2143-01). All procedures were conducted in accordance with the ethical standards of the institutional research committee and the Declaration of Helsinki. Written informed consent was obtained from all participants before participation.\u003c/p\u003e\n\u003cp\u003eThis was not a clinical trial, so trial registration is not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e: Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by the Zhejiang Hospital Association Project, Qilu Research Program for the Development of Medical Consortium Construction (2025KY904).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eZH: Conceptualization, Methodology, Software, Investigation, Writing - original draft.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eYZ: Resources, Supervision, Funding acquisition, Writing - review \u0026amp; editing.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll authors: Read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to thank all participating patients and hospital staff for their support of this study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eHerridge MS, Azoulay \u0026Eacute;. 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J Natl Cancer Inst. 2017;109(2):djw205.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-health-services-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bhsr","sideBox":"Learn more about [BMC Health Services Research](http://bmchealthservres.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/BHSR/default.aspx","title":"BMC Health Services Research","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"ICU survivors, Financial toxicity, Nutritional status, Frailty, Length of stay, Health services research, Discharge planning","lastPublishedDoi":"10.21203/rs.3.rs-9333777/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9333777/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eUnderstanding which clinically obtainable indicators are associated with financial vulnerability at discharge has implications for post-discharge service planning and resource allocation. This study examined whether nutritional status and multidimensional frailty mediate the relationship between ICU length of stay and financial toxicity in middle-aged and older ICU survivors.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eIn this single-centre cross-sectional study, 422 ICU survivors aged 45 years or older were recruited before hospital discharge. Nutritional status, multidimensional frailty, and financial toxicity were assessed using the Mini Nutritional Assessment\u0026ndash;Short Form, Tilburg Frailty Indicator, and Comprehensive Score for Financial Toxicity. Structural equation modelling was used to test a serial mediation model with adjustment for selected demographic and clinical covariates.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eLonger ICU LOS was associated with poorer nutritional status (β = \u0026minus;0.256, p\u0026thinsp;=\u0026thinsp;0.001), and poorer nutritional status was associated with greater frailty (β = \u0026minus;0.325, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Better nutritional status (β\u0026thinsp;=\u0026thinsp;0.148, p\u0026thinsp;=\u0026thinsp;0.003) and lower frailty (β = \u0026minus;0.118, p\u0026thinsp;=\u0026thinsp;0.014) were associated with higher COST scores, indicating lower financial toxicity. The direct association between ICU LOS and COST score was not significant. The indirect association through nutritional status alone was significant (B\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;0.069, 95% CI\u0026thinsp;\u0026minus;\u0026thinsp;0.130 to \u0026minus;\u0026thinsp;0.008, p\u0026thinsp;=\u0026thinsp;0.027), whereas the frailty-only pathway was not. The sequential pathway through nutritional status and frailty was not significant (B\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;0.018, p\u0026thinsp;=\u0026thinsp;0.058).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eLonger ICU stay was indirectly associated with greater financial toxicity, primarily through poorer nutritional status. These findings suggest that nutritional screening before discharge may help identify ICU survivors at early risk of financial vulnerability, and that incorporating nutritional status into pre-discharge assessment protocols may support more targeted referral to post-discharge support services.\u003c/p\u003e","manuscriptTitle":"Financial Toxicity in ICU Survivors: The Mediating Role of Nutritional Status and Implications for Post-Discharge Service Planning","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-14 12:51:50","doi":"10.21203/rs.3.rs-9333777/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewersInvited","content":"","date":"2026-05-05T14:59:24+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-05-04T10:01:07+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-04-13T10:07:45+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-12T13:16:46+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Health Services Research","date":"2026-04-12T13:11:57+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-health-services-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bhsr","sideBox":"Learn more about [BMC Health Services Research](http://bmchealthservres.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/BHSR/default.aspx","title":"BMC Health Services Research","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"62680f4e-6fa5-409c-a79c-2498498b108d","owner":[],"postedDate":"May 14th, 2026","published":true,"recentEditorialEvents":[{"type":"reviewersInvited","content":"30","date":"2026-05-05T14:59:24+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-05-04T10:01:07+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-14T12:51:50+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-14 12:51:50","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9333777","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9333777","identity":"rs-9333777","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}