Risk Stratification for Delirium After Hip Fracture Surgery: Comparing the Risk Analysis Index and mFI-5

Risk Stratification for Delirium After Hip Fracture Surgery: Comparing the Risk Analysis Index and mFI-5 | 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 Risk Stratification for Delirium After Hip Fracture Surgery: Comparing the Risk Analysis Index and mFI-5 Hikmat Chmait, Omar Sbaih, Hannah Grimmett, Michael DiCosmo, Mitchell Gray, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8643967/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 10 You are reading this latest preprint version Abstract Objectives: Postoperative delirium (POD) is a frequent complication following hip fracture surgery in older adults and contributes to increased morbidity and mortality. Frailty is a known predictor of adverse outcomes, but the optimal index for forecasting POD remains uncertain. This study compared the revised Risk Analysis Index (RAI-rev) and the five-item Modified Frailty Index (mFI-5) in predicting POD and short-term outcomes. Methods: Using the 2021 American College of Surgeons NSQIP database, 13,957 patients aged ≥ 75 years undergoing hip fracture surgery were identified. RAI-rev and mFI-5 scores were calculated, and frailty categories were analyzed against POD, 30-day mortality, extended length of stay (eLOS), non-home discharge (NHD), readmission, reoperation, and major complications. Multivariate logistic regression and receiver operating characteristic (ROC) analyses assessed associations and discriminative performance. Mediation analyses evaluated whether POD mediated frailty’s effects on adverse outcomes. Results: POD occurred in 3,200 patients (22.9%). Higher frailty categories were strongly associated with POD. RAI-rev demonstrated greater predictive accuracy (AUC 0.63) than mFI-5 (AUC 0.55; p < 0.001). POD independently increased the odds of 30-day mortality (OR 3.20), eLOS (OR 2.01), NHD (OR 2.23), and complications (OR 1.32). Mediation analyses showed POD partially mediated frailty’s impact on 30-day outcomes, with indirect effects for mortality (RIT 35.9%), eLOS (21.4%), readmission (15.1%), reoperation (24.5%), and complications (10.4%). Conclusion: The RAI-rev more accurately predicts POD and short-term adverse outcomes than mFI-5 in elderly hip fracture patients. POD significantly mediates frailty’s effect on surgical outcomes, underscoring the importance of frailty assessment and delirium prevention strategies. Hip Fracture Postoperative Delirium Frailty RAI-Rev mFI-5 Figures Figure 1 Figure 2 Figure 3 Introduction With an aging global population, the number of elderly patients requiring surgical management is increasing; as of 2000, there were 600 million people over the age of 60, and this number is expected to increase to 2 billion by 2050. 1 The increasing average population age is also associated with increased rates of osteoporosis, and as a result, hip fractures. 2 In the United States, approximately 90% of hip fractures occur in patients over the age of 65 with the average age being 80. 3 Furthermore, hip fracture patients, compared to their counterparts without hip fractures, are associated with an increased rate of mortality with 7.7% at 30 days, 13.9% at 3 months, and 24.3% at 1 year following a hip fracture. 4 The risk for postoperative complications generally increases with age due to the patient’s comorbidities and frailty status. 5 Frailty can be defined as decreased physiologic reserve resulting in an increase in vulnerability. 6 , 7 Several frailty indices have been developed in an effort for preoperative risk stratification of patients including the 5-item Modified Frailty Index (mFI-5) and the revised Risk Analysis Index (RAI-rev). 8 Within orthopaedics, mFI-5 is more commonly used. Previously adapted from mFI-11, it includes variables such as congestive heart failure, hypertension requiring medication, COPD, diabetes mellitus requiring insulin, and non-independent functional status. 9 – 11 Of note, mFI-5 encompasses variables that are considered comorbidities rather than frailty status. 11 , 12 RAI-rev, a newer index, includes 11 variables: sex, age, cancer diagnosis, weight loss, renal failure, congestive heart failure, poor appetite, shortness of breath at rest, non-independent living, cognitive deterioration, and activities of daily living. 13 Including variables such as weight loss, activities of daily living, and poor appetite allow for a more accurate assessment of a patient’s frailty status, as it provides more insight into their physiological state. 13 , 14 Postoperative delirium (POD) is a relatively common postoperative complication among the elderly, affecting around 15% of patients, and is even more common in hip fracture patients. Increasing age, frailty, and comorbidities all increase the risk for postoperative delirium. 15 – 17 Unfortunately, POD can slow recovery rates, increase the length of hospital stay, and increase the rate of 30-day readmission. 18 This study aims to compare RAI-rev and mFI-5 scores in predicting POD and short-term outcomes among elderly patients undergoing hip fracture surgery. We hypothesize that RAI-rev would be a better predictor of postoperative delirium due to its inclusion of variables more related to physiologic functional status. Methods Data Source The study utilized data from the American College of Surgeons National Surgical Quality Improvement Program (NSQIP) database for the year 2021. NSQIP is a national registry collecting detailed clinical data from over 600 hospitals across the United States. Patients were identified using Current Procedural Terminology (CPT) codes specific to hip fracture management, including 27236 (hemiarthroplasty), 27244 (plate/screw fixation), 27245 (intramedullary fixation), and 27235 (percutaneous fixation). Exclusion criteria included patients who had not been screened for postoperative delirium (POD) or < 75 years of age. Patient Population and Baseline Characteristics Baseline population characteristics, including age, sex, and race, were documented. Comorbidities assessed included functional independence, diabetes mellitus, chronic obstructive pulmonary disease (COPD), congestive heart failure (CHF), smoking status, dyspnea, hypertension, disseminated cancer, chronic steroid use, weight loss, and bleeding disorders. Procedural variables such as hospital length of stay (LOS), operative duration, and discharge disposition were also collected. Frailty Indices 5-Item Modified Frailty Index (mFI-5) The mFI-5, a condensed version of the original 11-variable Modified Frailty Index (mFI-11), was developed following a 2014 update to the ACS NSQIP, which removed six of the original variables. It incorporates the five remaining factors—functional status, diabetes mellitus (DM), chronic obstructive pulmonary disease (COPD), hypertension, and congestive heart failure (CHF)—to assign patients a score ranging from 0 to 5. Based on their score, patients are classified as robust (0), prefrail (1), frail (2), or severely frail (≥ 3). Revised Risk Analysis Index (RAI) Frailty was also measured using the revised Risk Analysis Index (RAI) by Arya and Hall (Arya et al., 2020), a validated tool combining variables such as age, sex, cancer diagnosis (excluding melanoma), unintentional weight loss of ≥ 4.5 kg within 3 months, renal failure, congestive heart failure (CHF), poor appetite, shortness of breath at rest, dependency in daily living activities, cognitive decline, and residential independence. RAI scores were categorized as follows: normal (≤ 30), frail (31–40), and very frail (≥ 41). Outcome Measures Outcome Measures Primary outcomes included POD, 30-day mortality, discharge to a non-home destination (NHD), extended length of stay (eLOS), 30-day unplanned readmission, 30-day unplanned reoperation, functional dependence at discharge, and the occurrence of minor and major complications. POD was evaluated via the ACS-NSQIP variable “DELIRIUM”. Major complications were defined as postoperative events such as prolonged intubation exceeding 48 hours, unplanned reintubation, sepsis, septic shock, pneumonia, deep vein thrombosis or thrombophlebitis, pulmonary embolism, acute cerebrovascular accident or stroke with neurological deficit, acute renal failure, myocardial infarction, cardiac arrest requiring cardiopulmonary resuscitation, superficial surgical site infection (SSI), deep incisional SSI, organ space SSI, or wound disruption. Minor complications included intra- or postoperative blood transfusion, renal insufficiency, or urinary tract infection. eLOS was defined as hospital stays exceeding the 75th percentile of the cohort's length of stay distribution. Statistical Analysis Continuous variables were summarized as medians with interquartile ranges (1st–3rd quartiles), while categorical variables were presented as percentages. To identify independent risk factors for developing postoperative delirium (POD), a forward stepwise logistic regression analysis was conducted, incorporating variables significantly associated with POD in univariate analysis. Additional logistic regression models were constructed to examine the adjusted relationship between POD and major postoperative outcomes, controlling for gender, race, ethnicity, inpatient status, age, and total operation time. Results were reported as unadjusted and adjusted odds ratios (ORs) with 95% confidence intervals (CIs). Receiver operating characteristic (ROC) curve analysis was used to evaluate the ability of the Risk Analysis Index (RAI) and the modified frailty index (mFI-5) to predict POD and other primary outcomes, including 30-day mortality, extended length of stay (eLOS), and discharge to a non-home destination (NHD). The area under the curve (AUC) was reported for each model as a measure of discrimination. To provide additional context, ROC analyses were also conducted for fall history, dementia status, and functional health status to compare their predictive abilities against RAI and mFI-5. Comparisons of AUCs between RAI, mFI-5, and these clinical markers were performed using DeLong’s test (Delong et al., 1988), with a p-value of < 0.05 indicating statistical significance. Mediation analysis was performed to investigate the role of POD as an intermediate variable in the relationship between frailty, as measured by RAI, and postoperative outcomes. Using the Sobel test, this analysis quantified the direct and indirect effects, reporting the ratio of the indirect effect to the total effect (RIT) and to the direct effect (RID). This approach clarified the extent to which POD mediated the impact of frailty on outcomes such as mortality, eLOS, and functional dependence. All statistical analyses were conducted using SPSS software, version 24.0 (IBM, New York, NY). A two-sided p-value of < 0.05 was considered statistically significant for all analyses. Demographic and Clinical Characteristics of Included Cohort There were 13,957 patients undergoing hip fracture surgery included in the ACS-NSQIP database for the year analyzed (Table 1 ). After stratification by postoperative delirium (POD) status, 10,757 patients were identified as not experiencing POD, while 3,200 were identified with POD. The median age of the cohort was 85 years (IQR: 75–90), with a higher median age among those with POD (85.7 years) compared to those without POD (84.3 years). Male patients accounted for 29.6% of the total population, with a slightly higher prevalence in the POD group (31.2% vs. 29.1%). The most common comorbidities included hypertension requiring medication (70.6%), diabetes mellitus (18.3% total: 6.6% insulin, 11.7% non-insulin), and severe COPD (9.8%). Functional dependence was significantly more common among patients with POD, with 33.2% classified as partially dependent and 8.3% as totally dependent, compared to 19.1% and 2.5% in the non-POD group, respectively. Patients were stratified into frailty categories based on RAI score. Among the cohort, 42.3% were categorized as normal, 51.1% as frail, and 6.6% as very frail. Patients with POD were more likely to be in the frail (59.8% vs. 48.6%) or very frail (11.7% vs. 5.1%) categories compared to those without POD. The most frequent complications included intraoperative/postoperative transfusions (11.0%), unplanned readmissions (8.3%), and urinary tract infections (4.0%) (Table 2 ). Transfusions were notably more common in the POD group (12.6% vs. 10.5%). Additionally, POD patients experienced higher rates of adverse postoperative outcomes, including mortality (7.3% vs. 2.4%), eLOS (31.5% vs. 18.6%), and any complication development (37.0% vs. 28.7%) (Table 3 ). Results Multivariate Regression Multivariate analysis identified key preadmission characteristics and major postoperative outcomes associated with an increased risk of POD (Fig. 1 ). Preoperative factors most strongly predictive of POD included a history of dementia or cognitive impairment (OR: 4.33, 95% CI: 3.98–4.70, p < 0.001), total dependence on admission (OR: 4.42, 95% CI: 3.69–5.28, p < 0.001), and prior falls (OR: 1.13, 95% CI: 1.04–1.24, p = 0.007). Patients requiring ventilator support also had increased odds of POD (OR: 3.16, 95% CI: 1.09–9.16, p = 0.034). Frailty, as measured by both RAI-rev and mFI-5, was a significant predictor of POD. Compared to robust patients, those classified as frail (RAI-rev OR: 1.90, 95% CI: 1.74–2.07, p < 0.001; mFI-5 OR: 1.32, 95% CI: 1.17–1.48, p < 0.001) or very frail (RAI-rev OR: 3.44, 95% CI: 2.96–4.006, p < 0.001; mFI-5 OR: 1.71, 95% CI: 1.47–1.98, p < 0.001) were significantly more likely to develop POD. POD was also associated with worse postoperative outcomes, including mortality (OR: 3.20, 95% CI: 2.66–3.85, p < 0.001) and any complication development (OR: 1.32, 95% CI: 1.21–1.43, p < 0.001) (Fig. 2). The odds of postoperative partial or total dependence were markedly higher in the POD cohort, with ORs of 1.97 (95% CI: 1.70–2.29, p < 0.001) and 6.49 (95% CI: 5.46–7.70, p < 0.001), respectively. Additional complications strongly associated with POD included unplanned readmission (OR: 1.69, 95% CI: 1.48–1.92, p < 0.001) and reoperation (OR: 1.48, 95% CI: 1.14–1.91, p = 0.002). ROC Analysis ROC analysis was conducted to evaluate the predictive performance of preoperative characteristics for the development of POD (Fig. 3 ). Among individual predictors, dementia exhibited the highest discriminatory accuracy (AUC: 0.67, 95% CI: 0.62–0.71) followed by history of falls (AUC: 0.51, 95% CI: 0.48–0.55). When comparing overall frailty measures, RAI-rev demonstrated superior predictive capability for POD (AUC: 0.63, 95% CI: 0.60–0.67) compared to mFI-5 (AUC: 0.55, 95% CI: 0.51–0.58). Mediation of the Effect of Frailty by POD on 30-day Outcomes The proportion of frailty’s impact on 30-day outcomes that was mediated by postoperative delirium (POD) was calculated using the ratio of indirect to direct effect (RID) and the ratio of indirect to total effect (RIT) (Table 4 ). For mortality, the mediation effect was higher among frail patients (RID: 56.1%, RIT: 35.9%, p = 0.001) than among very frail patients (RID: 12.6%, RIT: 11.2%, p < 0.001). For NHD, both frail (RID: 9.5%, RIT: 8.7%) and very frail patients (RID: 14.0%, RIT: 12.3%) showed significant mediation effects (p < 0.001 for both). Functional dependence at discharge demonstrated insignificant mediation by POD for either frail (RID: 2.5%, RIT: 2.4%, p = 0.189) or very frail patients (RID: − 5.4%, RIT: − 5.8%, p = 0.188). Significant mediation effects were observed for reoperation, where frail patients showed RID: 32.5%, RIT: 24.5%, and very frail patients RID: 41.2%, RIT: 29.8% (p < 0.001 for both). For readmission, frail patients (RID: 17.7%, RIT: 15.1%) and very frail patients (RID: 24.1%, RIT: 19.4%) both showed significant effects (p < 0.001). eLOS showed significant mediation as well: frail patients had RID: 27.2%, RIT: 21.4%, and very frail patients RID: 32.8%, RIT: 24.7% (p < 0.001). For any complication, frail patients had RID: 11.6%, RIT: 10.4%, and very frail patients RID: 7.8%, RIT: 7.3%, both statistically significant (p < 0.001). Discussion In this nationwide database analysis of patients who underwent surgery to treat a hip fracture we examined the utility of the mFI-5 and RAI-rev frailty assessment tools in predicting postoperative delirium (POD) and short-term surgical outcomes. Our findings demonstrate that both indices are significantly associated with the occurrence of POD, however RAI-rev exhibited greater discriminatory capability than mFI-5. This superior performance may stem from RAI-rev’s inclusion of variables reflecting physiologic functional status such as weight loss, poor appetite, and independence with activities of daily living. Other frailty assessments such as mFI-5 solely rely on comorbidities such as hypertension, diabetes, and COPD. These results align with previous literature indicating that a more robust and nuanced assessment of physiologic reserve yields superior prognostic value in older, vulnerable surgical populations. 8 , 14 , 19 Patients developing POD had markedly higher rates of 30-day mortality, extended length of stay (eLOS), non-home discharge, and major complications. This finding aligns with previously published literature describing delirium’s detrimental effects on clinical outcomes in spine surgery, including prolonged hospitalization and increased in-hospital mortality. 18 Notably, our mediation analysis further highlights the interconnectedness between frailty and POD. In our population a significant proportion of the frailty scores influence on postoperative complications and adverse events is transmitted indirectly through POD, as seen in the mediation analysis. While frail patients are predisposed to worse outcomes, delirium appears to be a key driver exacerbating that risk. 18 , 20 , 21 These results suggest that utilizing a comprehensive frailty risk assessment in the preoperative period in order to properly identify patients who may most benefit from proactive delirium prevention and prehabilitation management strategies (e.g., multimodal analgesia, geriatric co-management, early mobilization) may mitigate the downstream consequences of frailty in post-operative hip fracture care. 22 The differential predictive power of RAI-rev over mFI-5 suggests that not all frailty indices are equally informative for elderly surgical populations. 7 , 23 , 24 While mFI-5 remains valuable for rapidly capturing comorbidities, its narrower clinical scope may overlook aspects of true physiologic decline not fully elucidated in the diagnostic assessment of this index. 25 RAI-rev’s broader parameters, in comparison, encompass both cognitive and functional domains, allowing for a more comprehensive evaluation of overall vulnerability. 13 Geriatric hip fracture patients commonly present with complex needs, making it essential to distinguish between baseline comorbidities and deficits in functional reserve when optimizing perioperative care. 9 , 26 Enhanced recognition of these subtleties may lead to more targeted interventions, such as optimizing nutrition, addressing cognitive deficits, and arranging early rehabilitation services. 27 , 28 Further studies need to elucidate our ability to improve outcomes with such interventions. Despite the strengths of leveraging a robust, multicenter surgical registry, several limitations exist. First, the retrospective nature of using ACS-NSQIP data introduces potential selection bias, and our study only captures 30-day outcomes without providing insights into long-term functional recovery or mortality. Second, POD was not universally screened or diagnosed with standardized criteria across all participating centers, which may underestimate its true prevalence. Although these factors are inherent limitations of large administrative datasets, our findings still provide a valuable and generalizable perspective on frailty, delirium, and outcomes in this vulnerable patient group. Future research should prospectively examine frailty-based interventions such as enhanced prehabilitation programs or dedicated perioperative geriatric consultation. Conclusion In conclusion, RAI-rev more accurately predicts postoperative delirium and short-term outcomes than mFI-5 in elderly patients undergoing hip fracture surgery. This study also highlights delirium’s key mediating role in translating frailty into worse clinical trajectories, reinforcing the importance of early frailty assessment and tailored perioperative management. Prospective, multicenter studies evaluating targeted interventions, such as comprehensive pre-habilitation and delirium prevention protocols, are needed to validate these observations and further enhance care strategies for this growing surgical population. Table 1 Overview of patient characteristics for the entire cohort, stratified by POD status. Variable No POD (N = 10,757) POD (N = 3,200) Overall (N = 13,957) p-value Age (years) 84.3 (75–90) 85.7 (75–90) 85 (75–90) 0.64 BMI 25.0 (16.84–33.16) 24.3 (10.5–64.4) 24.7 (16.2–32.9) 0.83 Male sex 3,132 (29.1%) 998 (31.2%) 4,130 (29.6%) 0.024 Race – White 7,047 (65.5%) 2,045 (63.9%) 9,092 (65.1%) 0.095 – Black or African American 268 (2.5%) 88 (2.8%) 356 (2.6%) 0.407 – Asian 291 (2.7%) 62 (1.9%) 353 (2.5%) 0.015 – Other 3,151 (29.3%) 1,005 (31.4%) 4,156 (29.8%) 0.022 Hispanic Ethnicity 439 (4.1%) 133 (4.2%) 572 (4.1%) 0.839 Diabetes mellitus – Insulin 722 (6.7%) 203 (6.3%) 925 (6.6%) 0.491 – Non-insulin 1,276 (11.9%) 356 (11.1%) 1,632 (11.7%) 0.259 Current smoker 627 (5.8%) 194 (6.1%) 821 (5.9%) 0.638 Functional status – Independent 8,437 (78.4%) 1,873 (58.5%) 10,310 (73.9%) < 0.001 – Partially dependent 2,049 (19.1%) 1,063 (33.2%) 3,112 (22.3%) < 0.001 – Totally dependent 271 (2.5%) 264 (8.3%) 535 (3.8%) < 0.001 Ventilator dependent 6 (0.1%) 9 (0.3%) 15 (0.1%) 0.002 Severe COPD 1,044 (9.7%) 328 (10.3%) 1,372 (9.8%) 0.36 CHF (past 30 days) 1,433 (13.3%) 455 (14.2%) 1,888 (13.5%) 0.19 Hypertension (on meds) 7,620 (70.8%) 2,230 (69.7%) 9,850 (70.6%) 0.21 On dialysis 157 (1.5%) 43 (1.3%) 200 (1.4%) 0.67 Disseminated cancer 207 (1.9%) 41 (1.3%) 248 (1.8%) 0.015 Steroid use 563 (5.2%) 128 (4.0%) 691 (5.0%) 0.005 Bleeding disorder 824 (7.7%) 277 (8.7%) 1,101 (7.9%) 0.067 Oxygen support 1,551 (14.4%) 462 (14.4%) 2,013 (14.4%) 0.97 Fall history 7,210 (67.0%) 2,211 (69.1%) 9,421 (67.5%) 0.028 Dementia or cognitive impairment 2,721 (25.3%) 1,909 (59.7%) 4,630 (33.2%) < 0.001 RAI – ≤30 (Normal) 4,985 (46.3%) 913 (28.5%) 5,898 (42.3%) < 0.001 – 31–40 (Frail) 5,223 (48.6%) 1,914 (59.8%) 7,137 (51.1%) < 0.001 – ≥41 (Very frail) 549 (5.1%) 373 (11.7%) 922 (6.6%) < 0.001 mFI-5 – 0 (Normal) 2,007 (18.7%) 435 (13.6%) 2,442 (17.5%) < 0.001 – 1–2 (Frail) 7,542 (70.1%) 2,257 (70.5%) 9,799 (70.2%) 0.66 – ≥3 (Very frail) 1,208 (11.2%) 508 (15.9%) 1,716 (12.3%) < 0.001 Transfer status – Home/Permanent residence 9,125 (84.8%) 2,531 (79.1%) 11,656 (83.5%) < 0.001 – Acute care hospital 1,201 (11.2%) 410 (12.8%) 1,611 (11.5%) 0.012 – Other facility 423 (3.9%) 248 (7.8%) 671 (4.8%) < 0.001 – Unknown 8 (0.1%) 11 (0.3%) 19 (0.1%) 0.001 Case type – Elective 3,381 (31.4%) 888 (27.8%) 4,269 (30.6%) < 0.001 – Urgent 4,696 (43.7%) 1,536 (48.0%) 6,232 (44.7%) < 0.001 – Emergent 2,680 (24.9%) 776 (24.2%) 3,456 (24.8%) 0.45 Transfusion (preop) 346 (3.2%) 148 (4.6%) 494 (3.5%) < 0.001 ASA class – I 28 (0.3%) 1 (0.03%) 29 (0.2%) 0.007 – II 1,660 (15.4%) 234 (7.3%) 1,894 (13.6%) < 0.001 – III 6,903 (64.2%) 2,080 (65.0%) 8,983 (64.4%) 0.4 – IV 2,126 (19.8%) 865 (27.0%) 2,991 (21.4%) < 0.001 – V 24 (0.2%) 14 (0.4%) 38 (0.3%) 0.052 Inpatient status 10,666 (99.2%) 3,176 (99.3%) 13,842 (99.2%) 0.65 Operation time (min) 58 (25–110) 64.6 (18–108) 60 (23–114) < 0.001 Table 2 Postoperative complications for the entire cohort, stratified by POD status. Complication No POD (N = 10,757) POD (N = 3,200) Overall (N = 13,957) p-value Superficial SSI 115 (1.1%) 45 (1.4%) 160 (1.1%) 0.13 Deep Incisional SSI 9 (0.1%) 5 (0.2%) 14 (0.1%) 0.33 Organ Space SSI 25 (0.2%) 12 (0.4%) 37 (0.3%) 0.17 Wound Disruption 6 (0.1%) 6 (0.2%) 12 (0.1%) 0.037 Pneumonia 266 (2.5%) 176 (5.5%) 442 (3.2%) < 0.001 Unplanned Intubation 36 (0.3%) 27 (0.8%) 63 (0.5%) 48 hrs 16 (0.1%) 13 (0.4%) 29 (0.2%) 0.012 Acute Renal Failure 4 (0.04%) 1 (0.03%) 5 (0.04%) 1 Urinary Tract Infection 364 (3.4%) 200 (6.3%) 564 (4.0%) < 0.001 Stroke / CVA 67 (0.6%) 49 (1.5%) 116 (0.8%) < 0.001 Cardiac Arrest (CPR) 24 (0.2%) 8 (0.3%) 32 (0.2%) 0.83 Myocardial Infarction 179 (1.7%) 102 (3.2%) 281 (2.0%) < 0.001 Transfusions 1,125 (10.5%) 403 (12.6%) 1,528 (11.0%) 0.001 DVT 57 (0.5%) 16 (0.5%) 73 (0.5%) < 0.001 Sepsis 89 (0.8%) 42 (1.3%) 131 (0.9%) 0.016 Septic Shock 36 (0.3%) 32 (1.0%) 68 (0.5%) < 0.001 C. difficile Colitis 42 (0.4%) 15 (0.5%) 57 (0.4%) 0.52 Complication No POD (N = 10,757) POD (N = 3,200) Overall (N = 13,957) p-value Superficial SSI 115 (1.1%) 45 (1.4%) 160 (1.1%) 0.13 Table 3 Postoperative outcomes for the entire cohort, stratified by POD status. Outcome No POD (N = 10,757) POD (N = 3,200) Overall (N = 13,957) p-value Functional Health Status on Discharge – Partially dependent 8,174 (76.0%) 2,187 (68.3%) 10,361 (74.2%) < 0.001 – Totally dependent 886 (8.2%) 792 (24.8%) 1,678 (12.0%) < 0.001 NHD 4,651 (43.2%) 1,497 (46.8%) 6,148 (44.1%) < 0.001 eLOS 1997 (18.6%) 1009 (31.5%) 3,006 (21.5%) < 0.001 Reoperation 195 (1.8%) 92 (2.9%) 287 (2.1%) < 0.001 Readmission 793 (7.4%) 372 (11.6%) 1,165 (8.3%) < 0.001 Mortality 253 (2.4%) 234 (7.3%) 487 (3.5%) < 0.001 Any Complication 3,086 (28.7%) 1,185 (37.0%) 4,271 (30.6%) < 0.001 Table 4 Mediation analysis results illustrating the influence of POD on postoperative outcomes in patients classified as frail or very frail. The RID represents the ratio of the indirect effect (POD) to the direct effect (frailty) on outcomes, while the RIT represents the ratio of the indirect effect (POD) to the total effect (indirect + direct) on postoperative outcomes. Outcome Frailty Status Compared to Normal Ratio of Indirect to Direct Effect Ratio of Indirect to Total Effect p-value Mortality Frail 56.10% 35.90% 0.001 Very Frail 12.60% 11.20% < 0.001 NHD Frail 9.50% 8.70% < 0.001 Very Frail 14.00% 12.30% < 0.001 Functional Status Frail 2.50% 2.40% 0.189 Very Frail -5.40% -5.80% 0.188 Reoperation Frail 17.70% 15.10% < 0.001 Very Frail 24.10% 19.40% < 0.001 Readmission Frail 32.50% 24.50% < 0.001 Very Frail 41.20% 29.80% < 0.001 eLOS Frail 27.20% 21.40% < 0.001 Very Frail 32.80% 24.70% < 0.001 Any Complication Frail 11.60% 10.40% < 0.001 Very Frail 7.80% 7.30% < 0.001 Declarations Ethics Approval: This study used de-identified data obtained from the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP). As all data are fully de-identified and collected for quality improvement purposes, the study was exempt from Institutional Review Board approval, and no ethics committee review was required. No approval number applies. Consent to Participate: Not applicable because this was an ACS-NSQIP study using de-identified data, informed consent to participate was not required. Availability of Data and Materials: Per ACS-NSQIP data-use policies, the dataset is not publicly available and cannot be shared by the authors. Researchers may obtain access to NSQIP data directly through the American College of Surgeons by submitting a formal data request and meeting all program requirements. All analyses in this study were conducted in compliance with NSQIP’s data-use agreement. Competing Interests: The authors declare no conflicts of interest related to the material presented in this manuscript. Funding: The authors received no financial support from any funding agency, commercial entity, or not-for-profit organization for the research, authorship, or publication of this article. Author Contributions: Conceptualization: HRC, MH. Methodology: HRC, OS. Formal Analysis: HRC, OS. Investigation: HG, MD, MG. Resources: MH. Writing – Original Draft: HRC, HG, OS. Writing – Review & Editing: All authors. Supervision: MD, MG, MH Acknowledgements: None to report. Author’s Information: None to report. References Buckinx F, Rolland Y, Reginster JY, Ricour C, Petermans J, Bruyère O. Burden of frailty in the elderly population: perspectives for a public health challenge. Arch Public Health. 2015;73(1):19. 10.1186/s13690-015-0068-x . Baker-LePain JC, Lane NE. Role of bone architecture and anatomy in osteoarthritis. Bone Aug. 2012;51(2):197–203. 10.1016/j.bone.2012.01.008 . Brauer CA, Coca-Perraillon M, Cutler DM, Rosen AB. Incidence and mortality of hip fractures in the United States. Jama Oct. 2009;14(14):1573–9. 10.1001/jama.2009.1462 . von Friesendorff M, McGuigan FE, Wizert A, et al. Hip fracture, mortality risk, and cause of death over two decades. Osteoporos Int Oct. 2016;27(10):2945–53. 10.1007/s00198-016-3616-5 . Clegg A, Young J, Iliffe S, Rikkert MO, Rockwood K. Frailty in elderly people. lancet. 2013;381(9868):752–62. Eeles EM, White SV, O'Mahony SM, Bayer AJ, Hubbard RE. The impact of frailty and delirium on mortality in older inpatients. Age Ageing May. 2012;41(3):412–6. 10.1093/ageing/afs021 . Bowers CA, Varela S, Conlon M et al. Jul. Comparison of the Risk Analysis Index and the modified 5-factor frailty index in predicting 30-day morbidity and mortality after spine surgery. Journal of Neurosurgery: Spine . 01 2023 2023;39(1):136–145. https://doi.org/10.3171/2023.2.SPINE221019 Gupta NK, Dunivin F, Chmait HR, et al. Orthopedic frailty risk stratification (OFRS): a systematic review of the frailty indices predicting adverse outcomes in orthopedics. J Orthop Surg Res Mar. 2025;6(1):247. 10.1186/s13018-025-05609-2 . Traven SA, Reeves RA, Althoff AD, Slone HS, Walton ZJ. New Five-Factor Modified Frailty Index Predicts Morbidity and Mortality in Geriatric Hip Fractures. J Orthop Trauma Jul. 2019;33(7):319–23. 10.1097/bot.0000000000001455 . Erne F, Wallmeier V, Ihle C, et al. The modified 5-item frailty index determines the length of hospital stay and accompanies with mortality rate in patients with bone and implant-associated infections after trauma and orthopedic surgery. Injury Apr. 2023;54(4):1125–31. 10.1016/j.injury.2023.01.042 . Weaver DJ, Malik AT, Jain N, Yu E, Kim J, Khan SN. The Modified 5-Item Frailty Index: A Concise and Useful Tool for Assessing the Impact of Frailty on Postoperative Morbidity Following Elective Posterior Lumbar Fusions. World Neurosurg Apr. 2019;124:e626–32. 10.1016/j.wneu.2018.12.168 . Gijsen R, Hoeymans N, Schellevis FG, Ruwaard D, Satariano WA, van den Bos GA. Causes and consequences of comorbidity: a review. J Clin Epidemiol Jul. 2001;54(7):661–74. 10.1016/s0895-4356(00)00363-2 . Arya S, Varley P, Youk A, et al. Recalibration and External Validation of the Risk Analysis Index: A Surgical Frailty Assessment Tool. Ann Surg. 2020;272(6):996–1005. 10.1097/sla.0000000000003276 . Gupta N, Sasaki J, Koltenyuk V et al. The Risk Analysis Index as a Predictor of 30-Day Mortality for Obese Patients Undergoing Elective Total Joint Arthroplasty. J Orthop. 2025. Gupta NK, Chmait HR, Gill V, et al. Risk Analysis Index for Estimation of 30-Day Postoperative Mortality in Hip Fractures. JAMA Netw Open May. 2025;1(5):e2512689. 10.1001/jamanetworkopen.2025.12689 . Siddiqi N, House AO, Holmes JD. Occurrence and outcome of delirium in medical in-patients: a systematic literature review. Age Ageing Jul. 2006;35(4):350–64. 10.1093/ageing/afl005 . Ansaloni L, Catena F, Chattat R, et al. Risk factors and incidence of postoperative delirium in elderly patients after elective and emergency surgery. Br J Surg Feb. 2010;97(2):273–80. 10.1002/bjs.6843 . Gupta NK, Prvulovic ST, Zoghi S, et al. Complementary Effects of Postoperative Delirium and Frailty on 30-Day Outcomes in Spine Surgery. Spine J Dec. 2024;12. 10.1016/j.spinee.2024.12.017 . Roy JM, Bowers CA, Rumalla K, Covell MM, Kazim SF, Schmidt MH. Frailty Indexes in Metastatic Spine Tumor Surgery: A Narrative Review. World Neurosurg Oct. 2023;178:117–22. 10.1016/j.wneu.2023.07.095 . Parikh SS, Chung F. Postoperative delirium in the elderly. Anesth Analgesia. 1995;80(6):1223–32. Robinson TN, Raeburn CD, Tran ZV, Angles EM, Brenner LA, Moss M. Postoperative delirium in the elderly: risk factors and outcomes. Ann Surg. 2009;249(1):173–8. Hall DE, Youk A, Allsup K, et al. Preoperative Rehabilitation Is Feasible in the Weeks Prior to Surgery and Significantly Improves Functional Performance. J Frailty Aging. 2023;12(4):267–76. 10.14283/jfa.2022.42 . Conlon M, Thommen R, Kazim SF, et al. Risk Analysis Index and Its Recalibrated Version Predict Postoperative Outcomes Better Than 5-Factor Modified Frailty Index in Traumatic Spinal Injury. Neurospine Dec. 2022;19(4):1039–48. 10.14245/ns.2244326.163 . Paiz CC, Owodunni OP, Courville EN, Schmidt M, Alunday R, Bowers CA. Frailty Predicts 30-day mortality following major complications in neurosurgery patients: The risk analysis index has superior discrimination compared to modified frailty index-5 and increasing patient age. World Neurosurgery: X. 2024;23:100286. https://doi.org/10.1016/j.wnsx.2024.100286 . 2024/07/01/. Hall DE, Arya S, Schmid KK, et al. Development and Initial Validation of the Risk Analysis Index for Measuring Frailty in Surgical Populations. JAMA Surg Feb. 2017;1(2):175–82. 10.1001/jamasurg.2016.4202 . Kammerlander C, Gosch M, Kammerlander-Knauer U, Luger TJ, Blauth M, Roth T. Long-term functional outcome in geriatric hip fracture patients. Arch Orthop Trauma Surg Oct. 2011;131(10):1435–44. 10.1007/s00402-011-1313-6 . Whittle J, Wischmeyer PE, Grocott MPW, Miller TE. Surgical Prehabilitation: Nutrition and Exercise. Anesthesiol Clin Dec. 2018;36(4):567–80. 10.1016/j.anclin.2018.07.013 . Lin CQ, Chmait HR, Conroy JP, Nelms NJ, Blankstein M. Can We Empower Patients for Joint Surgery? Assessing the Impact of a Telemedicine Coaching Intervention. Arthroplasty Today. 2025;33:101701. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 23 Feb, 2026 Reviews received at journal 22 Feb, 2026 Reviews received at journal 15 Feb, 2026 Reviewers agreed at journal 08 Feb, 2026 Reviewers agreed at journal 05 Feb, 2026 Reviewers agreed at journal 05 Feb, 2026 Reviewers invited by journal 03 Feb, 2026 Editor assigned by journal 26 Jan, 2026 Submission checks completed at journal 26 Jan, 2026 First submitted to journal 19 Jan, 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. 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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-8643967","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":585330594,"identity":"3e511f1f-7b4d-4490-be5a-d56db2a3a00a","order_by":0,"name":"Hikmat Chmait","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2klEQVRIiWNgGAWjYLACxgYGBjYG5gNApoQMEeqZGRvAWtjYEkBaeIjXwsDGYwDiEtai237++IOfO7bJ88n3fH51o8aCh4H98NEN+LSYnUlmbOw9c9uwjY13m3XOMaDDeNLSbuDVciCZsZmx7TYjSItxDhtQiwSPGX4t5x+Dtdi3sfE8M875R4yWGxBbEoFamB/nthGl5bHhzN6228ltbGlmzLl9EjxsBP1yPvHBh59tt23nNx9+/DnnW50cP/vhY3i1IAM2CTBJrHIQYP5AiupRMApGwSgYOQAAsndIDTN1LcMAAAAASUVORK5CYII=","orcid":"","institution":"University of Vermont","correspondingAuthor":true,"prefix":"","firstName":"Hikmat","middleName":"","lastName":"Chmait","suffix":""},{"id":585330598,"identity":"2be99bac-b74e-400e-b437-a173892f0027","order_by":1,"name":"Omar Sbaih","email":"","orcid":"","institution":"Georgetown University","correspondingAuthor":false,"prefix":"","firstName":"Omar","middleName":"","lastName":"Sbaih","suffix":""},{"id":585330604,"identity":"e74f861e-591f-43db-8416-533b80e92dea","order_by":2,"name":"Hannah Grimmett","email":"","orcid":"","institution":"William Carey University","correspondingAuthor":false,"prefix":"","firstName":"Hannah","middleName":"","lastName":"Grimmett","suffix":""},{"id":585330607,"identity":"273d6aa3-11a7-43e5-b748-8d1cde979c2b","order_by":3,"name":"Michael DiCosmo","email":"","orcid":"","institution":"University of Vermont","correspondingAuthor":false,"prefix":"","firstName":"Michael","middleName":"","lastName":"DiCosmo","suffix":""},{"id":585330610,"identity":"042e7239-fcfe-4037-bcb5-d020e2b6827a","order_by":4,"name":"Mitchell Gray","email":"","orcid":"","institution":"University of Vermont","correspondingAuthor":false,"prefix":"","firstName":"Mitchell","middleName":"","lastName":"Gray","suffix":""},{"id":585330613,"identity":"817189e2-b443-468d-8f9d-d37c1f534dca","order_by":5,"name":"Mark Haimes","email":"","orcid":"","institution":"University of Vermont","correspondingAuthor":false,"prefix":"","firstName":"Mark","middleName":"","lastName":"Haimes","suffix":""}],"badges":[],"createdAt":"2026-01-20 02:23:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8643967/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8643967/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":102180058,"identity":"37928cea-434e-435d-bdf5-73351b9e6da5","added_by":"auto","created_at":"2026-02-09 07:12:07","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":169785,"visible":true,"origin":"","legend":"\u003cp\u003eForest plot illustrating the outcomes of multivariate regression analysis, adjusted for race, ethnicity, inpatient status, length of stay, and total operation time, for the association between POD and pre-admission characteristics.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8643967/v1/00306428b6494f55ef139f0b.png"},{"id":102180158,"identity":"6934c2a6-40f2-4737-bb9e-b76edb27b4dd","added_by":"auto","created_at":"2026-02-09 07:12:27","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":230979,"visible":true,"origin":"","legend":"\u003cp\u003eForest plot illustrating the outcomes of multivariate regression analysis, adjusted for race, ethnicity, inpatient status, length of stay, and total operation time, for the association between POD and post-operative outcomes.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8643967/v1/b8467a16699efcf2c31c3575.png"},{"id":102180061,"identity":"1fa680b5-b2b1-4530-9aec-62d5c8ebfca7","added_by":"auto","created_at":"2026-02-09 07:12:08","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":359565,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eROC curves for predictive performance of preoperative characteristics for development of POD\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8643967/v1/31fa9ef8c4edbb2eaafa30d9.png"},{"id":102180468,"identity":"41d1d1ec-7cb8-4b26-b810-1031e04042bd","added_by":"auto","created_at":"2026-02-09 07:13:09","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2095914,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8643967/v1/67b248ef-502c-4eb4-8947-097c79898bd2.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Risk Stratification for Delirium After Hip Fracture Surgery: Comparing the Risk Analysis Index and mFI-5","fulltext":[{"header":"Introduction","content":"\u003cp\u003eWith an aging global population, the number of elderly patients requiring surgical management is increasing; as of 2000, there were 600\u0026nbsp;million people over the age of 60, and this number is expected to increase to 2\u0026nbsp;billion by 2050.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e The increasing average population age is also associated with increased rates of osteoporosis, and as a result, hip fractures.\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e In the United States, approximately 90% of hip fractures occur in patients over the age of 65 with the average age being 80.\u003csup\u003e3\u003c/sup\u003e Furthermore, hip fracture patients, compared to their counterparts without hip fractures, are associated with an increased rate of mortality with 7.7% at 30 days, 13.9% at 3 months, and 24.3% at 1 year following a hip fracture.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eThe risk for postoperative complications generally increases with age due to the patient\u0026rsquo;s comorbidities and frailty status.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e Frailty can be defined as decreased physiologic reserve resulting in an increase in vulnerability.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e Several frailty indices have been developed in an effort for preoperative risk stratification of patients including the 5-item Modified Frailty Index (mFI-5) and the revised Risk Analysis Index (RAI-rev).\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e Within orthopaedics, mFI-5 is more commonly used. Previously adapted from mFI-11, it includes variables such as congestive heart failure, hypertension requiring medication, COPD, diabetes mellitus requiring insulin, and non-independent functional status.\u003csup\u003e\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e Of note, mFI-5 encompasses variables that are considered comorbidities rather than frailty status.\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e RAI-rev, a newer index, includes 11 variables: sex, age, cancer diagnosis, weight loss, renal failure, congestive heart failure, poor appetite, shortness of breath at rest, non-independent living, cognitive deterioration, and activities of daily living.\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e Including variables such as weight loss, activities of daily living, and poor appetite allow for a more accurate assessment of a patient\u0026rsquo;s frailty status, as it provides more insight into their physiological state.\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003ePostoperative delirium (POD) is a relatively common postoperative complication among the elderly, affecting around 15% of patients, and is even more common in hip fracture patients. Increasing age, frailty, and comorbidities all increase the risk for postoperative delirium.\u003csup\u003e\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e Unfortunately, POD can slow recovery rates, increase the length of hospital stay, and increase the rate of 30-day readmission.\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eThis study aims to compare RAI-rev and mFI-5 scores in predicting POD and short-term outcomes among elderly patients undergoing hip fracture surgery. We hypothesize that RAI-rev would be a better predictor of postoperative delirium due to its inclusion of variables more related to physiologic functional status.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData Source\u003c/h2\u003e \u003cp\u003eThe study utilized data from the American College of Surgeons National Surgical Quality Improvement Program (NSQIP) database for the year 2021. NSQIP is a national registry collecting detailed clinical data from over 600 hospitals across the United States. Patients were identified using Current Procedural Terminology (CPT) codes specific to hip fracture management, including 27236 (hemiarthroplasty), 27244 (plate/screw fixation), 27245 (intramedullary fixation), and 27235 (percutaneous fixation). Exclusion criteria included patients who had not been screened for postoperative delirium (POD) or \u0026lt;\u0026thinsp;75 years of age.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003ePatient Population and Baseline Characteristics\u003c/h3\u003e\n\u003cp\u003eBaseline population characteristics, including age, sex, and race, were documented. Comorbidities assessed included functional independence, diabetes mellitus, chronic obstructive pulmonary disease (COPD), congestive heart failure (CHF), smoking status, dyspnea, hypertension, disseminated cancer, chronic steroid use, weight loss, and bleeding disorders. Procedural variables such as hospital length of stay (LOS), operative duration, and discharge disposition were also collected.\u003c/p\u003e\n\u003ch3\u003eFrailty Indices\u003c/h3\u003e\n\u003cp\u003e \u003cem\u003e5-Item Modified Frailty Index (mFI-5)\u003c/em\u003e \u003c/p\u003e \u003cp\u003eThe mFI-5, a condensed version of the original 11-variable Modified Frailty Index (mFI-11), was developed following a 2014 update to the ACS NSQIP, which removed six of the original variables. It incorporates the five remaining factors\u0026mdash;functional status, diabetes mellitus (DM), chronic obstructive pulmonary disease (COPD), hypertension, and congestive heart failure (CHF)\u0026mdash;to assign patients a score ranging from 0 to 5. Based on their score, patients are classified as robust (0), prefrail (1), frail (2), or severely frail (\u0026ge;\u0026thinsp;3).\u003c/p\u003e\n\u003ch3\u003eRevised Risk Analysis Index (RAI)\u003c/h3\u003e\n\u003cp\u003eFrailty was also measured using the revised Risk Analysis Index (RAI) by Arya and Hall (Arya et al., 2020), a validated tool combining variables such as age, sex, cancer diagnosis (excluding melanoma), unintentional weight loss of \u0026ge;\u0026thinsp;4.5 kg within 3 months, renal failure, congestive heart failure (CHF), poor appetite, shortness of breath at rest, dependency in daily living activities, cognitive decline, and residential independence. RAI scores were categorized as follows: normal (\u0026le;\u0026thinsp;30), frail (31\u0026ndash;40), and very frail (\u0026ge;\u0026thinsp;41).\u003c/p\u003e\n\u003ch3\u003eOutcome Measures\u003c/h3\u003e\n\u003cdiv class=\"Heading\"\u003eOutcome Measures\u003c/div\u003e \u003cp\u003ePrimary outcomes included POD, 30-day mortality, discharge to a non-home destination (NHD), extended length of stay (eLOS), 30-day unplanned readmission, 30-day unplanned reoperation, functional dependence at discharge, and the occurrence of minor and major complications. POD was evaluated via the ACS-NSQIP variable \u0026ldquo;DELIRIUM\u0026rdquo;. Major complications were defined as postoperative events such as prolonged intubation exceeding 48 hours, unplanned reintubation, sepsis, septic shock, pneumonia, deep vein thrombosis or thrombophlebitis, pulmonary embolism, acute cerebrovascular accident or stroke with neurological deficit, acute renal failure, myocardial infarction, cardiac arrest requiring cardiopulmonary resuscitation, superficial surgical site infection (SSI), deep incisional SSI, organ space SSI, or wound disruption. Minor complications included intra- or postoperative blood transfusion, renal insufficiency, or urinary tract infection. eLOS was defined as hospital stays exceeding the 75th percentile of the cohort's length of stay distribution.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eContinuous variables were summarized as medians with interquartile ranges (1st\u0026ndash;3rd quartiles), while categorical variables were presented as percentages.\u003c/p\u003e \u003cp\u003eTo identify independent risk factors for developing postoperative delirium (POD), a forward stepwise logistic regression analysis was conducted, incorporating variables significantly associated with POD in univariate analysis. Additional logistic regression models were constructed to examine the adjusted relationship between POD and major postoperative outcomes, controlling for gender, race, ethnicity, inpatient status, age, and total operation time. Results were reported as unadjusted and adjusted odds ratios (ORs) with 95% confidence intervals (CIs).\u003c/p\u003e \u003cp\u003eReceiver operating characteristic (ROC) curve analysis was used to evaluate the ability of the Risk Analysis Index (RAI) and the modified frailty index (mFI-5) to predict POD and other primary outcomes, including 30-day mortality, extended length of stay (eLOS), and discharge to a non-home destination (NHD). The area under the curve (AUC) was reported for each model as a measure of discrimination. To provide additional context, ROC analyses were also conducted for fall history, dementia status, and functional health status to compare their predictive abilities against RAI and mFI-5. Comparisons of AUCs between RAI, mFI-5, and these clinical markers were performed using DeLong\u0026rsquo;s test (Delong et al., 1988), with a p-value of \u0026lt;\u0026thinsp;0.05 indicating statistical significance.\u003c/p\u003e \u003cp\u003eMediation analysis was performed to investigate the role of POD as an intermediate variable in the relationship between frailty, as measured by RAI, and postoperative outcomes. Using the Sobel test, this analysis quantified the direct and indirect effects, reporting the ratio of the indirect effect to the total effect (RIT) and to the direct effect (RID). This approach clarified the extent to which POD mediated the impact of frailty on outcomes such as mortality, eLOS, and functional dependence.\u003c/p\u003e \u003cp\u003eAll statistical analyses were conducted using SPSS software, version 24.0 (IBM, New York, NY). A two-sided p-value of \u0026lt;\u0026thinsp;0.05 was considered statistically significant for all analyses.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eDemographic and Clinical Characteristics of Included Cohort\u003c/h3\u003e\n\u003cp\u003eThere were 13,957 patients undergoing hip fracture surgery included in the ACS-NSQIP database for the year analyzed (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). After stratification by postoperative delirium (POD) status, 10,757 patients were identified as not experiencing POD, while 3,200 were identified with POD. The median age of the cohort was 85 years (IQR: 75\u0026ndash;90), with a higher median age among those with POD (85.7 years) compared to those without POD (84.3 years). Male patients accounted for 29.6% of the total population, with a slightly higher prevalence in the POD group (31.2% vs. 29.1%). The most common comorbidities included hypertension requiring medication (70.6%), diabetes mellitus (18.3% total: 6.6% insulin, 11.7% non-insulin), and severe COPD (9.8%). Functional dependence was significantly more common among patients with POD, with 33.2% classified as partially dependent and 8.3% as totally dependent, compared to 19.1% and 2.5% in the non-POD group, respectively. Patients were stratified into frailty categories based on RAI score. Among the cohort, 42.3% were categorized as normal, 51.1% as frail, and 6.6% as very frail. Patients with POD were more likely to be in the frail (59.8% vs. 48.6%) or very frail (11.7% vs. 5.1%) categories compared to those without POD.\u003c/p\u003e \u003cp\u003eThe most frequent complications included intraoperative/postoperative transfusions (11.0%), unplanned readmissions (8.3%), and urinary tract infections (4.0%) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Transfusions were notably more common in the POD group (12.6% vs. 10.5%). Additionally, POD patients experienced higher rates of adverse postoperative outcomes, including mortality (7.3% vs. 2.4%), eLOS (31.5% vs. 18.6%), and any complication development (37.0% vs. 28.7%) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eMultivariate Regression\u003c/h2\u003e \u003cp\u003eMultivariate analysis identified key preadmission characteristics and major postoperative outcomes associated with an increased risk of POD (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Preoperative factors most strongly predictive of POD included a history of dementia or cognitive impairment (OR: 4.33, 95% CI: 3.98\u0026ndash;4.70, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), total dependence on admission (OR: 4.42, 95% CI: 3.69\u0026ndash;5.28, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and prior falls (OR: 1.13, 95% CI: 1.04\u0026ndash;1.24, p\u0026thinsp;=\u0026thinsp;0.007). Patients requiring ventilator support also had increased odds of POD (OR: 3.16, 95% CI: 1.09\u0026ndash;9.16, p\u0026thinsp;=\u0026thinsp;0.034).\u003c/p\u003e \u003cp\u003eFrailty, as measured by both RAI-rev and mFI-5, was a significant predictor of POD. Compared to robust patients, those classified as frail (RAI-rev OR: 1.90, 95% CI: 1.74\u0026ndash;2.07, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; mFI-5 OR: 1.32, 95% CI: 1.17\u0026ndash;1.48, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) or very frail (RAI-rev OR: 3.44, 95% CI: 2.96\u0026ndash;4.006, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; mFI-5 OR: 1.71, 95% CI: 1.47\u0026ndash;1.98, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) were significantly more likely to develop POD.\u003c/p\u003e \u003cp\u003ePOD was also associated with worse postoperative outcomes, including mortality (OR: 3.20, 95% CI: 2.66\u0026ndash;3.85, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and any complication development (OR: 1.32, 95% CI: 1.21\u0026ndash;1.43, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;2). The odds of postoperative partial or total dependence were markedly higher in the POD cohort, with ORs of 1.97 (95% CI: 1.70\u0026ndash;2.29, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and 6.49 (95% CI: 5.46\u0026ndash;7.70, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), respectively.\u003c/p\u003e \u003cp\u003eAdditional complications strongly associated with POD included unplanned readmission (OR: 1.69, 95% CI: 1.48\u0026ndash;1.92, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and reoperation (OR: 1.48, 95% CI: 1.14\u0026ndash;1.91, p\u0026thinsp;=\u0026thinsp;0.002).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eROC Analysis\u003c/h2\u003e \u003cp\u003eROC analysis was conducted to evaluate the predictive performance of preoperative characteristics for the development of POD (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Among individual predictors, dementia exhibited the highest discriminatory accuracy (AUC: 0.67, 95% CI: 0.62\u0026ndash;0.71) followed by history of falls (AUC: 0.51, 95% CI: 0.48\u0026ndash;0.55). When comparing overall frailty measures, RAI-rev demonstrated superior predictive capability for POD (AUC: 0.63, 95% CI: 0.60\u0026ndash;0.67) compared to mFI-5 (AUC: 0.55, 95% CI: 0.51\u0026ndash;0.58).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eMediation of the Effect of Frailty by POD on 30-day Outcomes\u003c/h2\u003e \u003cp\u003eThe proportion of frailty\u0026rsquo;s impact on 30-day outcomes that was mediated by postoperative delirium (POD) was calculated using the ratio of indirect to direct effect (RID) and the ratio of indirect to total effect (RIT) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). For mortality, the mediation effect was higher among frail patients (RID: 56.1%, RIT: 35.9%, p\u0026thinsp;=\u0026thinsp;0.001) than among very frail patients (RID: 12.6%, RIT: 11.2%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). For NHD, both frail (RID: 9.5%, RIT: 8.7%) and very frail patients (RID: 14.0%, RIT: 12.3%) showed significant mediation effects (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001 for both). Functional dependence at discharge demonstrated insignificant mediation by POD for either frail (RID: 2.5%, RIT: 2.4%, p\u0026thinsp;=\u0026thinsp;0.189) or very frail patients (RID: \u0026minus;\u0026thinsp;5.4%, RIT: \u0026minus;\u0026thinsp;5.8%, p\u0026thinsp;=\u0026thinsp;0.188). Significant mediation effects were observed for reoperation, where frail patients showed RID: 32.5%, RIT: 24.5%, and very frail patients RID: 41.2%, RIT: 29.8% (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001 for both). For readmission, frail patients (RID: 17.7%, RIT: 15.1%) and very frail patients (RID: 24.1%, RIT: 19.4%) both showed significant effects (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). eLOS showed significant mediation as well: frail patients had RID: 27.2%, RIT: 21.4%, and very frail patients RID: 32.8%, RIT: 24.7% (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). For any complication, frail patients had RID: 11.6%, RIT: 10.4%, and very frail patients RID: 7.8%, RIT: 7.3%, both statistically significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this nationwide database analysis of patients who underwent surgery to treat a hip fracture we examined the utility of the mFI-5 and RAI-rev frailty assessment tools in predicting postoperative delirium (POD) and short-term surgical outcomes. Our findings demonstrate that both indices are significantly associated with the occurrence of POD, however RAI-rev exhibited greater discriminatory capability than mFI-5. This superior performance may stem from RAI-rev\u0026rsquo;s inclusion of variables reflecting physiologic functional status such as weight loss, poor appetite, and independence with activities of daily living. Other frailty assessments such as mFI-5 solely rely on comorbidities such as hypertension, diabetes, and COPD. These results align with previous literature indicating that a more robust and nuanced assessment of physiologic reserve yields superior prognostic value in older, vulnerable surgical populations.\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003ePatients developing POD had markedly higher rates of 30-day mortality, extended length of stay (eLOS), non-home discharge, and major complications. This finding aligns with previously published literature describing delirium\u0026rsquo;s detrimental effects on clinical outcomes in spine surgery, including prolonged hospitalization and increased in-hospital mortality.\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e Notably, our mediation analysis further highlights the interconnectedness between frailty and POD. In our population a significant proportion of the frailty scores influence on postoperative complications and adverse events is transmitted indirectly through POD, as seen in the mediation analysis. While frail patients are predisposed to worse outcomes, delirium appears to be a key driver exacerbating that risk.\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e These results suggest that utilizing a comprehensive frailty risk assessment in the preoperative period in order to properly identify patients who may most benefit from proactive delirium prevention and prehabilitation management strategies (e.g., multimodal analgesia, geriatric co-management, early mobilization) may mitigate the downstream consequences of frailty in post-operative hip fracture care.\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eThe differential predictive power of RAI-rev over mFI-5 suggests that not all frailty indices are equally informative for elderly surgical populations.\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e While mFI-5 remains valuable for rapidly capturing comorbidities, its narrower clinical scope may overlook aspects of true physiologic decline not fully elucidated in the diagnostic assessment of this index.\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e RAI-rev\u0026rsquo;s broader parameters, in comparison, encompass both cognitive and functional domains, allowing for a more comprehensive evaluation of overall vulnerability.\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e Geriatric hip fracture patients commonly present with complex needs, making it essential to distinguish between baseline comorbidities and deficits in functional reserve when optimizing perioperative care.\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e Enhanced recognition of these subtleties may lead to more targeted interventions, such as optimizing nutrition, addressing cognitive deficits, and arranging early rehabilitation services.\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e,\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e Further studies need to elucidate our ability to improve outcomes with such interventions.\u003c/p\u003e \u003cp\u003eDespite the strengths of leveraging a robust, multicenter surgical registry, several limitations exist. First, the retrospective nature of using ACS-NSQIP data introduces potential selection bias, and our study only captures 30-day outcomes without providing insights into long-term functional recovery or mortality. Second, POD was not universally screened or diagnosed with standardized criteria across all participating centers, which may underestimate its true prevalence. Although these factors are inherent limitations of large administrative datasets, our findings still provide a valuable and generalizable perspective on frailty, delirium, and outcomes in this vulnerable patient group. Future research should prospectively examine frailty-based interventions such as enhanced prehabilitation programs or dedicated perioperative geriatric consultation.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, RAI-rev more accurately predicts postoperative delirium and short-term outcomes than mFI-5 in elderly patients undergoing hip fracture surgery. This study also highlights delirium\u0026rsquo;s key mediating role in translating frailty into worse clinical trajectories, reinforcing the importance of early frailty assessment and tailored perioperative management. Prospective, multicenter studies evaluating targeted interventions, such as comprehensive pre-habilitation and delirium prevention protocols, are needed to validate these observations and further enhance care strategies for this growing surgical population.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eOverview of patient characteristics for the entire cohort, stratified by POD status.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo POD (N\u0026thinsp;=\u0026thinsp;10,757)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePOD (N\u0026thinsp;=\u0026thinsp;3,200)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOverall (N\u0026thinsp;=\u0026thinsp;13,957)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge (years)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e84.3 (75\u0026ndash;90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e85.7 (75\u0026ndash;90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e85 (75\u0026ndash;90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.64\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBMI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25.0 (16.84\u0026ndash;33.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24.3 (10.5\u0026ndash;64.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24.7 (16.2\u0026ndash;32.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.83\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMale sex\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,132 (29.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e998 (31.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4,130 (29.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.024\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRace\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ndash; White\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7,047 (65.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2,045 (63.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9,092 (65.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.095\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ndash; Black or African American\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e268 (2.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e88 (2.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e356 (2.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.407\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ndash; Asian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e291 (2.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e62 (1.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e353 (2.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ndash; Other\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,151 (29.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1,005 (31.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4,156 (29.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.022\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHispanic Ethnicity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e439 (4.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e133 (4.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e572 (4.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.839\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDiabetes mellitus\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ndash; Insulin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e722 (6.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e203 (6.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e925 (6.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.491\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ndash; Non-insulin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,276 (11.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e356 (11.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,632 (11.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.259\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCurrent smoker\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e627 (5.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e194 (6.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e821 (5.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.638\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFunctional status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ndash; Independent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8,437 (78.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1,873 (58.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10,310 (73.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ndash; Partially dependent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,049 (19.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1,063 (33.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3,112 (22.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ndash; Totally dependent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e271 (2.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e264 (8.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e535 (3.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVentilator dependent\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (0.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9 (0.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15 (0.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSevere COPD\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,044 (9.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e328 (10.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,372 (9.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.36\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCHF (past 30 days)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,433 (13.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e455 (14.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,888 (13.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHypertension (on meds)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7,620 (70.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2,230 (69.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9,850 (70.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOn dialysis\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e157 (1.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e43 (1.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e200 (1.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDisseminated cancer\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e207 (1.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e41 (1.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e248 (1.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSteroid use\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e563 (5.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e128 (4.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e691 (5.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBleeding disorder\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e824 (7.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e277 (8.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,101 (7.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.067\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOxygen support\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,551 (14.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e462 (14.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,013 (14.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFall history\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7,210 (67.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2,211 (69.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9,421 (67.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.028\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDementia or cognitive impairment\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,721 (25.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1,909 (59.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4,630 (33.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRAI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ndash; \u0026le;30 (Normal)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4,985 (46.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e913 (28.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5,898 (42.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ndash; 31\u0026ndash;40 (Frail)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5,223 (48.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1,914 (59.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7,137 (51.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ndash; \u0026ge;41 (Very frail)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e549 (5.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e373 (11.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e922 (6.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003emFI-5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ndash; 0 (Normal)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,007 (18.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e435 (13.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,442 (17.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ndash; 1\u0026ndash;2 (Frail)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7,542 (70.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2,257 (70.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9,799 (70.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.66\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ndash; \u0026ge;3 (Very frail)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,208 (11.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e508 (15.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,716 (12.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTransfer status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ndash; Home/Permanent residence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9,125 (84.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2,531 (79.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11,656 (83.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ndash; Acute care hospital\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,201 (11.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e410 (12.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,611 (11.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ndash; Other facility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e423 (3.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e248 (7.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e671 (4.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ndash; Unknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (0.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11 (0.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19 (0.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCase type\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ndash; Elective\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,381 (31.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e888 (27.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4,269 (30.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ndash; Urgent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4,696 (43.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1,536 (48.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6,232 (44.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ndash; Emergent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,680 (24.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e776 (24.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3,456 (24.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTransfusion (preop)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e346 (3.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e148 (4.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e494 (3.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eASA class\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ndash; I\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28 (0.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1 (0.03%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29 (0.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ndash; II\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,660 (15.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e234 (7.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,894 (13.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ndash; III\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6,903 (64.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2,080 (65.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8,983 (64.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ndash; IV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,126 (19.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e865 (27.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,991 (21.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ndash; V\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24 (0.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14 (0.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38 (0.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.052\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInpatient status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10,666 (99.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3,176 (99.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13,842 (99.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.65\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOperation time (min)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e58 (25\u0026ndash;110)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e64.6 (18\u0026ndash;108)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e60 (23\u0026ndash;114)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePostoperative complications for the entire cohort, stratified by POD status.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComplication\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo POD (N\u0026thinsp;=\u0026thinsp;10,757)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePOD (N\u0026thinsp;=\u0026thinsp;3,200)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOverall (N\u0026thinsp;=\u0026thinsp;13,957)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSuperficial SSI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e115 (1.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45 (1.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e160 (1.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDeep Incisional SSI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 (0.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (0.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14 (0.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOrgan Space SSI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25 (0.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 (0.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37 (0.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWound Disruption\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (0.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (0.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12 (0.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.037\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePneumonia\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e266 (2.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e176 (5.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e442 (3.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eUnplanned Intubation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36 (0.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27 (0.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e63 (0.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePulmonary Embolism\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e106 (1.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40 (1.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e146 (1.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVent\u0026thinsp;\u0026gt;\u0026thinsp;48 hrs\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16 (0.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (0.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29 (0.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAcute Renal Failure\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (0.04%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (0.03%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (0.04%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eUrinary Tract Infection\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e364 (3.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e200 (6.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e564 (4.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eStroke / CVA\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e67 (0.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49 (1.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e116 (0.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCardiac Arrest (CPR)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24 (0.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (0.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32 (0.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.83\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMyocardial Infarction\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e179 (1.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e102 (3.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e281 (2.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTransfusions\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,125 (10.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e403 (12.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,528 (11.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDVT\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e57 (0.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16 (0.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e73 (0.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSepsis\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e89 (0.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42 (1.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e131 (0.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.016\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSeptic Shock\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36 (0.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32 (1.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e68 (0.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eC. difficile Colitis\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42 (0.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 (0.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e57 (0.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eComplication\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eNo POD (N\u0026thinsp;=\u0026thinsp;10,757)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003ePOD (N\u0026thinsp;=\u0026thinsp;3,200)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eOverall (N\u0026thinsp;=\u0026thinsp;13,957)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003ep-value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSuperficial SSI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e115 (1.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45 (1.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e160 (1.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePostoperative outcomes for the entire cohort, stratified by POD status.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOutcome\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo POD (N\u0026thinsp;=\u0026thinsp;10,757)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePOD (N\u0026thinsp;=\u0026thinsp;3,200)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOverall (N\u0026thinsp;=\u0026thinsp;13,957)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eFunctional Health Status on Discharge\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ndash; Partially dependent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8,174 (76.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2,187 (68.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10,361 (74.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ndash; Totally dependent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e886 (8.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e792 (24.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1,678 (12.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNHD\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4,651 (43.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1,497 (46.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6,148 (44.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eeLOS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1997 (18.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1009 (31.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3,006 (21.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eReoperation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e195 (1.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e92 (2.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e287 (2.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eReadmission\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e793 (7.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e372 (11.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1,165 (8.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMortality\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e253 (2.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e234 (7.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e487 (3.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAny Complication\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3,086 (28.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1,185 (37.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4,271 (30.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMediation analysis results illustrating the influence of POD on postoperative outcomes in patients classified as frail or very frail. The RID represents the ratio of the indirect effect (POD) to the direct effect (frailty) on outcomes, while the RIT represents the ratio of the indirect effect (POD) to the total effect (indirect\u0026thinsp;+\u0026thinsp;direct) on postoperative outcomes.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOutcome\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFrailty Status Compared to Normal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRatio of Indirect to Direct Effect\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRatio of Indirect to Total Effect\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMortality\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFrail\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e56.10%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e35.90%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVery Frail\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12.60%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11.20%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNHD\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFrail\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9.50%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.70%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVery Frail\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12.30%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFunctional Status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFrail\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.50%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.40%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.189\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVery Frail\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-5.40%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-5.80%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.188\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eReoperation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFrail\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17.70%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15.10%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVery Frail\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24.10%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e19.40%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eReadmission\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFrail\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e32.50%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e24.50%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVery Frail\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e41.20%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e29.80%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eeLOS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFrail\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e27.20%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e21.40%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVery Frail\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e32.80%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e24.70%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAny Complication\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFrail\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.60%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10.40%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVery Frail\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7.80%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.30%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eEthics Approval:\u003c/strong\u003e This study used de-identified data obtained from the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP). As all data are fully de-identified and collected for quality improvement purposes, the study was exempt from Institutional Review Board approval, and no ethics committee review was required. No approval number applies.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eConsent to Participate:\u003c/strong\u003e Not applicable because this was an ACS-NSQIP study using de-identified data, informed consent to participate was not required.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eAvailability of Data and Materials:\u003c/strong\u003e Per ACS-NSQIP data-use policies, the dataset is not publicly available and cannot be shared by the authors. Researchers may obtain access to NSQIP data directly through the American College of Surgeons by submitting a formal data request and meeting all program requirements. All analyses in this study were conducted in compliance with NSQIP\u0026rsquo;s data-use agreement.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests:\u0026nbsp;\u003c/strong\u003eThe authors declare no conflicts of interest related to the material presented in this manuscript.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eFunding:\u003c/strong\u003e The authors received no financial support from any funding agency, commercial entity, or not-for-profit organization for the research, authorship, or publication of this article.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eAuthor Contributions:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization: HRC, MH. Methodology: HRC, OS. Formal Analysis: HRC, OS. Investigation: HG, MD, MG. Resources: MH. Writing \u0026ndash; Original Draft: HRC, HG, OS. Writing \u0026ndash; Review \u0026amp; Editing: All authors. Supervision: MD, MG, MH\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eAcknowledgements:\u0026nbsp;\u003c/strong\u003eNone to report.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eAuthor\u0026rsquo;s Information:\u003c/strong\u003e None to report.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBuckinx F, Rolland Y, Reginster JY, Ricour C, Petermans J, Bruy\u0026egrave;re O. Burden of frailty in the elderly population: perspectives for a public health challenge. Arch Public Health. 2015;73(1):19. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s13690-015-0068-x\u003c/span\u003e\u003cspan address=\"10.1186/s13690-015-0068-x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBaker-LePain JC, Lane NE. Role of bone architecture and anatomy in osteoarthritis. 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Arthroplasty Today. 2025;33:101701.\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":"journal-of-orthopaedic-surgery-and-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"josr","sideBox":"Learn more about [Journal of Orthopaedic Surgery and Research](http://josr-online.biomedcentral.com)","snPcode":"13018","submissionUrl":"https://submission.nature.com/new-submission/13018/3","title":"Journal of Orthopaedic Surgery and Research","twitterHandle":"@MSKmedBMC","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Hip Fracture, Postoperative Delirium, Frailty, RAI-Rev, mFI-5","lastPublishedDoi":"10.21203/rs.3.rs-8643967/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8643967/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjectives:\u003c/h2\u003e \u003cp\u003ePostoperative delirium (POD) is a frequent complication following hip fracture surgery in older adults and contributes to increased morbidity and mortality. Frailty is a known predictor of adverse outcomes, but the optimal index for forecasting POD remains uncertain. This study compared the revised Risk Analysis Index (RAI-rev) and the five-item Modified Frailty Index (mFI-5) in predicting POD and short-term outcomes.\u003c/p\u003e\u003ch2\u003eMethods:\u003c/h2\u003e \u003cp\u003eUsing the 2021 American College of Surgeons NSQIP database, 13,957 patients aged\u0026thinsp;\u0026ge;\u0026thinsp;75 years undergoing hip fracture surgery were identified. RAI-rev and mFI-5 scores were calculated, and frailty categories were analyzed against POD, 30-day mortality, extended length of stay (eLOS), non-home discharge (NHD), readmission, reoperation, and major complications. Multivariate logistic regression and receiver operating characteristic (ROC) analyses assessed associations and discriminative performance. Mediation analyses evaluated whether POD mediated frailty\u0026rsquo;s effects on adverse outcomes.\u003c/p\u003e\u003ch2\u003eResults:\u003c/h2\u003e \u003cp\u003ePOD occurred in 3,200 patients (22.9%). Higher frailty categories were strongly associated with POD. RAI-rev demonstrated greater predictive accuracy (AUC 0.63) than mFI-5 (AUC 0.55; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). POD independently increased the odds of 30-day mortality (OR 3.20), eLOS (OR 2.01), NHD (OR 2.23), and complications (OR 1.32). Mediation analyses showed POD partially mediated frailty\u0026rsquo;s impact on 30-day outcomes, with indirect effects for mortality (RIT 35.9%), eLOS (21.4%), readmission (15.1%), reoperation (24.5%), and complications (10.4%).\u003c/p\u003e\u003ch2\u003eConclusion:\u003c/h2\u003e \u003cp\u003eThe RAI-rev more accurately predicts POD and short-term adverse outcomes than mFI-5 in elderly hip fracture patients. POD significantly mediates frailty\u0026rsquo;s effect on surgical outcomes, underscoring the importance of frailty assessment and delirium prevention strategies.\u003c/p\u003e","manuscriptTitle":"Risk Stratification for Delirium After Hip Fracture Surgery: Comparing the Risk Analysis Index and mFI-5","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-09 07:08:50","doi":"10.21203/rs.3.rs-8643967/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-02-23T05:59:12+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-22T22:26:49+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-15T18:11:47+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"16979655801958854730055388573214083568","date":"2026-02-08T10:11:12+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"124716959882316609544758345235822085426","date":"2026-02-05T06:02:50+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"216526528791053111820755386564339095980","date":"2026-02-05T05:49:38+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-03T05:41:12+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-01-26T23:06:59+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-01-26T23:06:22+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Orthopaedic Surgery and Research","date":"2026-01-20T02:07:18+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-orthopaedic-surgery-and-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"josr","sideBox":"Learn more about [Journal of Orthopaedic Surgery and Research](http://josr-online.biomedcentral.com)","snPcode":"13018","submissionUrl":"https://submission.nature.com/new-submission/13018/3","title":"Journal of Orthopaedic Surgery and Research","twitterHandle":"@MSKmedBMC","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"de975467-46da-4177-82ed-20a368e9e9e2","owner":[],"postedDate":"February 9th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[],"tags":[],"updatedAt":"2026-05-14T07:40:22+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-09 07:08:50","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8643967","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8643967","identity":"rs-8643967","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}