{"paper_id":"33ca87b8-d779-4a73-a694-684c2f75b4a6","body_text":"A Novel Composite Frailty Index for Predicting Postoperative Risk Following Femoral Neck Fracture Repair in Men Aged 18–65: Development and Validation | 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 A Novel Composite Frailty Index for Predicting Postoperative Risk Following Femoral Neck Fracture Repair in Men Aged 18–65: Development and Validation Cameron Sabet, Bhav Jain, Perisa Ashar, Jonathan Franco This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6796724/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Purpose: Accurate preoperative risk stratification remains limited for younger adult men undergoing femoral neck fracture repair, particularly given the limitations of existing indices that assess physiologic, frailty, or acute condition domains in isolation. We aimed to develop and validate the Combined ASA–RAI–Preoperative Acute Severe Condition (CARP) score as a novel composite risk model to predict short-term postoperative outcomes in this population. Methods: Using ACS-NSQIP data from 2015–2021, we conducted a retrospective cohort study of 5,961 male patients aged 18–65 who underwent femoral neck fracture surgery. Risk was assessed using the Risk Analysis Index (RAI), modified Frailty Index-5 (mFI-5), Geriatric Nutritional Risk Index (GNRI), ASA classification, and Preoperative Acute Severe Condition (PACS) score. Multivariable logistic regression identified predictors of 30-day outcomes. The CARP score was derived from model coefficients and evaluated against individual indices using AUROC and bootstrap validation. Results: Thirty-day major complications occurred in 4.8% of patients, with mortality at 2.2% and non-home discharge at 45.8%. Multivariable analysis identified PACS (OR 1.79, p<0.001), ASA class (OR 1.44, p=0.011), and RAI (OR 1.04, p=0.009) as independent predictors of major complications. CARP significantly outperformed mFI-5, RAI, PACS, and ASA in predicting adverse outcomes (AUROC 0.713 vs. 0.623–0.661, all p<0.01). Conclusion: The CARP score provides superior risk stratification compared to traditional indices in younger male patients undergoing femoral neck fracture repair. Its integration of frailty, physiological, and acute condition factors enables more precise prediction of perioperative complications and discharge outcomes, supporting personalized surgical planning. Surgical Complications Orthopedics Trauma Femur Fracture Figures Figure 1 INTRODUCTION Femoral neck fractures represent a significant public health burden in the United States and are a significant portion of hip fractures more broadly, with this specific intracapsular hip fracture contributing to the nation’s over 300,000 hip fracture cases occurring annually [ 1 ]. These fractures predominantly affect older adults and are associated with substantial morbidity, mortality, and healthcare costs, with 30-day mortality rates ranging from 4–15% and one-year mortality approaching 25% [ 2 , 3 ]. The complexity of managing these patients extends beyond surgical technique, as older adults often present with multiple comorbidities, functional limitations, and varying degrees of frailty that significantly impact postoperative outcomes [ 4 , 5 ]. Accurate preoperative risk stratification is therefore essential for optimizing surgical decision-making, patient counseling, and resource allocation in this vulnerable population. Current risk assessment tools have demonstrated varying degrees of success in predicting postoperative outcomes following femoral neck fracture repair. The American Society of Anesthesiologists (ASA) physical status classification system provides a standardized assessment of perioperative risk but lacks specificity for frailty-related factors that are particularly relevant in elderly surgical patients [ 5 ]. Frailty assessment tools, including the Clinical Frailty Scale and modified frailty indices, have shown promise in predicting mortality and complications, with studies demonstrating that frail patients have significantly higher rates of morbidity and mortality compared to non-frail counterparts [ 2 , 4 , 6 ]. The Risk Analysis Index (RAI) has emerged as a comprehensive tool that incorporates both physiologic and functional parameters, while nutritional assessment through indices like the Geriatric Nutritional Risk Index (GNRI) has proven valuable in identifying patients at risk for poor outcomes [ 3 ]. However, existing fracture risk assessment tools, including FRAX and Garvan calculators, have shown limited discriminative ability in adults aged 80 and older, highlighting the need for improved prediction models in this high-risk population [ 7 ]. Despite the availability of multiple individual risk assessment tools, no standardized composite scoring system has been developed that combines the strengths of physiologic, functional, and nutritional assessments for surgical risk stratification in femoral neck fracture patients. Current practice relies on fragmented evaluation using separate indices, which may fail to capture the complex interplay between frailty, comorbidity burden, and nutritional status that collectively determine postoperative outcomes [ 8 ]. This gap in comprehensive risk assessment is particularly problematic given the heterogeneity of the elderly population and the need for individualized surgical approaches based on biological rather than chronological age [ 9 ]. Therefore, this study aims to develop and validate a novel Combined ASA-RAI-Preoperative Acute Severe Condition (CARP) scoring system that integrates multiple domains of preoperative assessment to improve prediction of 30-day mortality, complications, and other adverse outcomes following femoral neck fracture repair in adult men aged 18–65 years. We hypothesize that this composite scoring system will demonstrate superior discriminative ability compared to individual risk assessment tools and provide clinicians with a more comprehensive framework for perioperative risk stratification. METHODS Data Source and Study Design This retrospective cohort study utilized data from the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database spanning 2015 to 2021. The ACS-NSQIP database encompasses over 700 participating hospitals and captures more than 200 variables related to preoperative risk factors, intraoperative variables, and 30-day postoperative outcomes. This study was conducted in compliance with HIPAA regulations and was exempt from institutional review board approval due to the retrospective nature and de-identified structure of the database. Informed consent was waived given the publicly available, anonymized data structure. Patient Selection Adult male patients aged 18-65 years undergoing femoral neck fracture repair were identified using Current Procedural Terminology codes for hip fracture procedures. Exclusion criteria included patients with missing data on critical outcomes such as mortality, discharge destination, functional status, or transfer status. Patients aged 90 years and older were top-coded as 90 years in the database. Cases with incomplete frailty assessment variables or missing key covariates required for risk scoring were excluded to maintain data accuracy and analytical consistency. The final cohort consisted of 5,961 patients after applying these selection criteria. Risk Indices Assessment The Risk Analysis Index was calculated using age, sex, renal impairment, dyspnea, cancer status, weight loss, and functional status (independent, partially dependent, totally dependent). Patients were categorized into frailty tiers as robust (RAI ≤20), normal (RAI 21-30), frail (RAI 31-40), and severely frail (RAI ≥41). The Modified Frailty Index-5 incorporated five comorbidity components including functional dependence, diabetes mellitus, chronic obstructive pulmonary disease, congestive heart failure, and hypertension requiring medication. American Society of Anesthesiologists classification stratified patients across five categories (ASA I through ASA V) based on overall health status. The Preoperative Acute Severe Condition score quantified acute illness burden using Present at Time of Surgery variables from NSQIP. Outcomes and Statistical Analysis Primary outcomes included 30-day mortality and major complications, with secondary outcomes encompassing minor complications, unplanned readmission, unplanned reoperation, extended length of stay (defined as >75th percentile), and non-home discharge. Major complications included myocardial infarction, pulmonary embolism, sepsis, deep vein thrombosis, stroke, and prolonged mechanical ventilation. Continuous variables were presented as mean ± standard deviation or median with interquartile range depending on distribution normality assessed using Kolmogorov-Smirnov testing. Multivariable logistic regression models identified independent predictors of adverse outcomes, with results reported as adjusted odds ratios and 95% confidence intervals. The Combined ASA-RAI-Preoperative Acute Severe Condition score was derived using regression coefficients from multivariable modeling. Model discrimination was assessed using receiver operating characteristic curve analysis with area under the curve calculations, and DeLong testing compared predictive performances between indices. Internal validation utilized 100 bootstrap replications to evaluate model stability and calculate bias-corrected performance estimates. Statistical significance was defined as p<0.05, with all analyses performed using Stata MP Version 18 in the Redivis computing environment. RESULTS Patient Characteristics The final cohort included 5,961 adult men aged 18-65 years undergoing femoral neck fracture repair after excluding 2,863 patients for missing key variables, invalid values, or incomplete data. The mean age was 53.9 ± 11.4 years, with the majority being White (83.8%, n=4,998), followed by Black or African American (12.0%, n=717), Asian/Pacific Islander (3.0%, n=176), and American Indian/Alaska Native (1.2%, n=70). All patients were functionally independent preoperatively (87.8%, n=5,198), with 10.0% (n=589) partially dependent and 2.2% (n=131) totally dependent. The mean body mass index was 26.5 ± 6.7 kg/m², mean total hospital length of stay was 5.9 ± 5.5 days, and mean operative time was 84.0 ± 53.4 minutes. Comorbidity prevalence included hypertension requiring medication (43.6%, n=2,600), diabetes mellitus (21.4%, n=1,275), chronic obstructive pulmonary disease (9.4%, n=560), bleeding disorders (11.1%, n=659), steroid use (6.4%, n=380), dyspnea (6.0%, n=357), disseminated cancer (5.6%, n=333), and congestive heart failure (1.9%, n=116). ASA classification distribution was 6.2% ASA I (n=368), 27.5% ASA II (n=1,640), 53.1% ASA III (n=3,164), and 13.2% ASA IV (n=789). Univariate Analysis Risk stratification using the Risk Analysis Index (RAI) revealed 76.5% (n=4,559) classified as robust (RAI ≤20), 20.6% (n=1,226) as normal (RAI 21-30), 2.8% (n=166) as frail (RAI 31-40), and 0.2% (n=10) as severely frail (RAI ≥41). Modified Frailty Index-5 (mFI-5) distribution showed 44.2% (n=2,635) not frail (score 0), 34.9% (n=2,080) prefrail (score 1), 15.9% (n=948) frail (score 2), and 5.0% (n=298) severely frail (score ≥3). Geriatric Nutritional Risk Index (GNRI) categorization demonstrated 54.9% (n=3,270) at no risk (GNRI ≥99), 19.3% (n=1,148) at low risk (GNRI 92-98), 16.1% (n=960) at moderate risk (GNRI 82-91), and 9.8% (n=583) at major risk (GNRI <82). Preoperative Acute Severe Condition (PACS) scores were available for 4,511 patients, with mean score 0.30 ± 0.58. All individual risk indices demonstrated significant associations with major complications: RAI (OR 1.09, 95% CI 1.07-1.11, p<0.001), mFI-5 (OR 1.64, 95% CI 1.46-1.85, p<0.001), PACS (OR 2.43, 95% CI 2.00-2.95, p<0.001), and ASA class (OR 2.45, 95% CI 2.05-2.93, p<0.001). Multivariable Analysis In adjusted analysis controlling for competing risk factors, the Combined ASA-RAI-Preoperative Acute Severe Condition (CARP) model incorporated significant predictors with respective coefficients: RAI score (β=0.041, OR 1.04, 95% CI 1.01-1.07, p=0.009), PACS score (β=0.582, OR 1.79, 95% CI 1.41-2.26, p<0.001), and ASA class (β=0.362, OR 1.44, 95% CI 1.08-1.90, p=0.011). The CARP scoring algorithm was calculated as: CARP = (0.041 × RAI score) + (0.582 × PACS score) + (0.362 × ASA class). For major complications specifically, significant independent predictors in the complete multivariable model (n=2,854) included PACS score (OR 1.51, 95% CI 1.15-1.98, p=0.003) and GNRI score (OR 0.97, 95% CI 0.95-0.99, p=0.001), while mFI-5 score (OR 1.15, 95% CI 0.92-1.43, p=0.219) and RAI score (OR 1.03, 95% CI 0.99-1.06, p=0.167) were not independently significant when controlling for other factors. For unplanned readmission, both mFI-5 score (OR 1.30, 95% CI 1.10-1.53, p=0.002) and RAI score (OR 1.04, 95% CI 1.02-1.07, p=0.002) remained independently predictive. Major Postoperative Outcomes The overall 30-day mortality rate was 2.2% (n=132). Major complications occurred in 4.8% of patients (n=284), including myocardial infarction (0.6%, n=38), pulmonary embolism (0.7%, n=46), deep vein thrombosis (0.2%, n=13), sepsis (0.8%, n=46), deep incisional surgical site infection (0.4%, n=25), prolonged mechanical ventilation (1.1%, n=65), unplanned reintubation (1.1%, n=65), stroke (0.3%, n=17), and postoperative dialysis (0.4%, n=21) (Figure 1a). Minor complications affected 1.3% (n=76), primarily urinary tract infections (1.5%, n=88), superficial surgical site infections (0.2%, n=13), and blood transfusions (17.5%, n=1,007) (Figure 1b). Thirty-day unplanned readmission occurred in 7.4% (n=438) (Figure 1c) and unplanned reoperation in 2.4% (n=142) (Figure 1d). Extended length of stay (>75th percentile of 7 days) affected 21.6% (n=1,290) (Figure 1e), and non-home discharge occurred in 45.8% (n=2,703) of patients (Figure 1f). Figure 1e : 30-day extended length of stay for men ages 18-65 undergoing femoral fracture repair analyzing the modified frailty index-5 (mFI-5), Risk Analysis Index (RAI), Geriatric Nutritional Risk Index (GNRI), Preoperative Acute Severe Condition (PACS), Combined ASA-RAI-PACS (CARP), and American Society of Anesthesiology (ASA) scores. Figure 1f : 30-day non-home discharge destination for men ages 18-65 undergoing femoral fracture repair analyzing the modified frailty index-5 (mFI-5), Risk Analysis Index (RAI), Geriatric Nutritional Risk Index (GNRI), Preoperative Acute Severe Condition (PACS), Combined ASA-RAI-PACS (CARP), and American Society of Anesthesiology (ASA) scores. Mortality rates increased significantly across RAI tiers: robust 1.1%, normal 4.8%, frail 11.4%, and severely frail 30.0% (p<0.001). Similarly, major complications increased by RAI tier: robust 3.6%, normal 7.3%, frail 15.1%, and severely frail 30.0% (p<0.001). Novel Score Development and Performance The CARP composite score demonstrated superior discriminative ability compared to individual indices across multiple outcomes. For major complications, CARP achieved an area under the receiver operating characteristic curve (AUROC) of 0.713 (95% CI 0.664-0.748), significantly outperforming mFI-5 (AUROC 0.623, 95% CI 0.580-0.654, p<0.001), RAI (AUROC 0.657, 95% CI 0.617-0.683, p=0.004), PACS (AUROC 0.656, 95% CI 0.608-0.692, p=0.008), and ASA class (AUROC 0.661, 95% CI 0.627-0.681, p=0.005) when compared using DeLong tests. For unplanned readmission, CARP demonstrated AUROC 0.691 (95% CI 0.653-0.716), superior to ASA class (AUROC 0.637, p<0.001), mFI-5 (AUROC 0.640, p<0.001), and PACS (AUROC 0.610, p<0.001), with marginal superiority over RAI (AUROC 0.664, p=0.059). CARP performance for extended length of stay showed AUROC 0.664 (95% CI 0.639-0.677), significantly better than RAI (AUROC 0.633, p<0.001), PACS (AUROC 0.571, p<0.001), and mFI-5 (AUROC 0.603, p<0.001). For non-home discharge, both CARP (AUROC 0.737, 95% CI 0.707-0.766) and RAI (AUROC 0.740, 95% CI 0.716-0.764) demonstrated similar excellent performance. Internal Validation Bootstrap validation with 100 replications confirmed robust performance of all risk indices with minimal optimism bias. For CARP, bias-corrected AUROCs were: major complications 0.706 (95% CI 0.664-0.748), minor complications 0.683 (95% CI 0.618-0.748), unplanned readmission 0.684 (95% CI 0.653-0.716), unplanned reoperation 0.611 (95% CI 0.554-0.668), and extended length of stay 0.658 (95% CI 0.639-0.677). The optimism-corrected estimates demonstrated excellent calibration with estimated optimism ranging from 0.6% to 0.7% across outcomes. RAI demonstrated bias-corrected performance of: major complications 0.650 (95% CI 0.617-0.683), unplanned readmission 0.657 (95% CI 0.633-0.682), and extended length of stay 0.627 (95% CI 0.609-0.644). mFI-5 bias-corrected AUROCs were: major complications 0.617 (95% CI 0.580-0.654), minor complications 0.649 (95% CI 0.593-0.706), and unplanned readmission 0.633 (95% CI 0.607-0.659). PACS demonstrated bias-corrected AUROCs of: major complications 0.650 (95% CI 0.608-0.692), unplanned readmission 0.604 (95% CI 0.573-0.634), and extended length of stay 0.565 (95% CI 0.548-0.582). ASA class showed bias-corrected performance of: major complications 0.654 (95% CI 0.627-0.681), unplanned readmission 0.631 (95% CI 0.606-0.655), and extended length of stay 0.654 (95% CI 0.641-0.666). Main Results The CARP composite score represents the first validated tool combining frailty assessment (RAI), acute illness severity (PACS), and perioperative risk stratification (ASA) specifically for femoral neck fracture repair in adult men. CARP consistently outperformed individual risk indices with statistical significance across major surgical outcomes, demonstrating clinical utility for preoperative risk stratification. The score showed particular strength in identifying patients at risk for major complications (C-statistic 0.713), substantially exceeding the performance of traditional ASA classification alone (C-statistic 0.661, p=0.005). Risk stratification using RAI tiers revealed dramatic outcome gradients: mortality increased 27-fold from robust to severely frail patients (1.1% vs 30.0%), major complications increased 8-fold (3.6% vs 30.0%), and extended length of stay increased 4-fold (18.1% vs 70.0%). GNRI demonstrated independent predictive value with clear dose-response relationships: patients with major nutritional risk (GNRI <82) experienced 12.2% major complications compared to 2.8% in patients with no nutritional risk (GNRI ≥99), representing a 4-fold increase in risk (p<0.001). The multivariable analysis confirmed that PACS score remained the strongest independent predictor of major complications (OR 1.79, p<0.001), while GNRI provided additional prognostic information (OR 0.97 per point increase, p=0.001). DISCUSSION Purpose and Clinical Need This study was conducted to address a critical gap in preoperative risk stratification for adult men undergoing femoral neck fracture repair, where existing individual risk indices provide inadequate discrimination for postoperative complications and mortality. The increasing incidence of geriatric hip fractures has become a major public health concern globally, with patients presenting complex medical comorbidities that challenge traditional risk assessment approaches [10]. While frailty assessment tools like the Risk Analysis Index and nutritional screening methods have shown promise individually, no validated composite scoring system has been developed specifically for this vulnerable population undergoing high-risk orthopedic procedures [11]. The development of the Combined ASA-RAI-Preoperative Acute Severe Condition (CARP) score represents the first systematic attempt to integrate multiple validated risk domains into a single, clinically applicable tool for femoral neck fracture repair outcomes prediction. Summary of Key Findings The CARP composite score demonstrated superior discriminative ability compared to individual risk indices across all major surgical outcomes, achieving an area under the receiver operating characteristic curve of 0.713 for major complications, significantly outperforming traditional ASA classification (0.661, p=0.005), RAI (0.657, p=0.004), and Modified Frailty Index-5 (0.623, p<0.001). Risk stratification using RAI tiers revealed dramatic outcome gradients, with mortality increasing 27-fold from robust to severely frail patients (1.1% vs 30.0%), major complications increasing 8-fold (3.6% vs 30.0%), and extended length of stay increasing 4-fold (18.1% vs 70.0%). The multivariable analysis confirmed that PACS score remained the strongest independent predictor of major complications (OR 1.79, p<0.001), while maintaining excellent calibration through bootstrap validation with minimal optimism bias. These findings demonstrate that composite risk assessment provides clinically meaningful improvements in outcome prediction compared to traditional single-parameter approaches used in current surgical practice. Context Within Existing Literature Our findings align with previous research demonstrating the prognostic value of frailty assessment in orthopedic surgery, while extending these concepts through novel composite scoring methodology. Shinall and colleagues (2020) demonstrated that frail patients had mortality rates exceeding 1% even after low-stress procedures, with very frail patients experiencing 10.34% mortality after minimal interventions, supporting our observation of dramatically increased risk in higher RAI tiers [11]. The nutritional component of risk assessment, though not directly incorporated into CARP, has been validated in joint arthroplasty populations where Fang et al. (2022) found malnutrition prevalence of 15.83% using GNRI criteria, with severe malnutrition associated with pneumonia, surgical site infection, and revision surgery [12]. Studies of geriatric femur fracture populations have consistently demonstrated the importance of multifactorial risk assessment, with Joseph et al. (2023) finding that age, length of hospital stay, and readmission were primary predictors of one-year mortality regardless of surgical technique [13]. The Clinical Frailty Scale literature supports our findings, with Jones et al. (2024) reporting 41.7% one-year mortality for patients with CFS ≥7 following proximal femur fractures, emphasizing the critical importance of frailty recognition in surgical decision-making [14]. Comparison with Contemporary Studies Our mortality rates and complication patterns closely align with recent literature examining similar populations and procedures. Vargas et al. (2024) reported 30-day mortality rates of 1.9% in patients aged 60-79 years versus 6.2% in octogenarians following distal femur fixation, comparable to our age-stratified findings though our population was restricted to younger adults [15]. The importance of composite risk assessment is further supported by Boddapati et al. (2021), who found 13.93% total complication rates and 3.29% mortality in pathological fracture populations, emphasizing the need for comprehensive preoperative evaluation in high-risk surgical candidates [16]. Wong et al. (2022) demonstrated that Age-adjusted Charlson Comorbidity Index scores ≥6 were associated with 4.27-fold increased complications in neck of femur fractures, supporting our finding that multifactorial scoring provides superior risk stratification [10]. Notably, our study differs from previous work by focusing specifically on adult men aged 18-65, avoiding the confounding effects of extreme age and sex-related physiological differences that have limited the generalizability of previous frailty research in orthopedic populations. Clinical Relevance and Implementation The CARP score addresses a fundamental clinical need for standardized, objective risk stratification in femoral neck fracture repair, enabling surgeons to provide evidence-based counseling and optimize perioperative management strategies. Unlike previous risk assessment tools that relied on single domains, CARP integrates frailty assessment (RAI), acute illness severity (PACS), and perioperative risk classification (ASA) into a mathematically validated composite score that can be calculated using readily available preoperative data. This approach is particularly relevant given findings by Patel et al. (2021) demonstrating that social deprivation independently predicts adverse outcomes after hip fracture, suggesting that comprehensive risk assessment must account for multiple, interacting patient factors [17]. The superior discriminative ability of CARP for predicting non-home discharge (AUROC 0.737) has immediate practical implications for discharge planning and resource allocation, potentially reducing unexpected extended hospitalizations and improving care coordination. Implementation of CARP scoring could facilitate risk-stratified care pathways, enabling selective application of enhanced recovery protocols, nutritional optimization strategies, and postoperative monitoring intensity based on individual patient risk profiles. Study Limitations This study has several important limitations that must be considered when interpreting results and planning implementation. The retrospective design using NSQIP data inherently limits the granularity of clinical information available, potentially missing important nuances in patient presentation, surgical technique variations, and postoperative care protocols that could influence outcomes. The restriction to adult men aged 18-65 years, while providing population homogeneity, limits generalizability to women, elderly patients, and pediatric populations where different physiological considerations may alter risk relationships. Missing data for certain variables, particularly nutritional markers like albumin levels (33.5% missing), may have introduced selection bias and limited our ability to incorporate validated nutritional risk assessment directly into the composite score. The database lacks information on important prognostic factors including cognitive function, social support systems, and detailed fracture morphology characteristics that have been shown to influence outcomes in orthopedic trauma populations. Additionally, the 30-day follow-up period may not capture longer-term complications, functional outcomes, or quality of life measures that are increasingly recognized as important endpoints in geriatric fracture care. Future Directions Future research should focus on prospective validation of the CARP score in diverse populations and clinical settings to confirm its predictive accuracy and clinical utility across different patient demographics and healthcare systems. External validation studies incorporating women, elderly patients, and different fracture patterns will be essential to establish the broader applicability of composite risk assessment in orthopedic trauma. Integration of additional validated risk domains, including comprehensive nutritional assessment using GNRI methodology and cognitive evaluation tools, could further enhance the discriminative ability of composite scoring approaches. The development of real-time risk calculators and electronic health record integration tools will be crucial for clinical implementation, requiring user-friendly interfaces that provide immediate risk stratification at the point of care. Longer-term outcomes studies examining functional recovery, quality of life measures, and healthcare utilization patterns will provide important insights into the full spectrum of CARP score utility for patient counseling and care planning. Investigation of risk-stratified intervention protocols, including targeted preoperative optimization strategies for high-risk patients identified through composite scoring, represents a critical next step in translating risk prediction into improved patient outcomes. CONCLUSION The Combined ASA-RAI-Preoperative Acute Severe Condition score represents a significant advancement in preoperative risk stratification for adult men undergoing femoral neck fracture repair, demonstrating superior discriminative ability compared to individual risk indices across multiple surgical outcomes. This novel composite scoring system provides clinically meaningful risk stratification that can enhance surgical decision-making, patient counseling, and perioperative care optimization in this vulnerable population. Declarations Author Contribution C.S. conceived the study, conducted the data analysis, developed the CARP model, and drafted the manuscript. B.J. contributed to data acquisition, participated in the analysis, and co-developed the risk model. P.A. assisted with the literature review, interpretation of findings, and manuscript drafting and editing. J.F. provided clinical oversight, supervised the project, and critically revised the manuscript. All authors reviewed and approved the final manuscript. Data Availability The data that support the findings of this study are available from the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP), but restrictions apply to their availability. Access to the dataset requires a data use agreement with the ACS and is not publicly available. Researchers interested in replicating the analysis or learning more about the methodology are welcome to contact the authors for additional details.ACS-NSQIP access details: https://www.facs.org/quality-programs/data-and-registries/acs-nsqip/ References Kazley J, Bagchi K. Femoral Neck Fractures. StatPearls, Treasure Island (FL): StatPearls Publishing; 2025. Ikram A, Norrish AR, Marson BA, Craxford S, Gladman JRF, Ollivere BJ. 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Jones HG, Hathaway I, Glossop S, Bhachoo H, Hoade L, Froud J, et al. The clinical frailty scale as a predictor of orthopaedic outcomes: a narrative review. Injury 2024;55:111450. https://doi.org/10.1016/j.injury.2024.111450. Vargas J, Plantz MA, Gerlach EB, Compton T, Dooley J, Welsh C, et al. Short‐Term Morbidity and Mortality after Distal Femur Open Reduction Internal Fixation in the Geriatric Population. Orthop Surg 2024;16:1665–72. https://doi.org/10.1111/os.14124. Boddapati V, Held MB, Levitsky M, Charette RS, Neuwirth AL, Geller JA. Risks and Complications After Arthroplasty for Pathological or Impending Pathological Fracture of the Hip. J Arthroplasty 2021;36:2049-2054.e5. https://doi.org/10.1016/j.arth.2021.02.004. Patel R, Bhimjiyani A, Ben-Shlomo Y, Gregson CL. Social deprivation predicts adverse health outcomes after hospital admission with hip fracture in England. Osteoporos Int 2021;32:1129–41. https://doi.org/10.1007/s00198-020-05768-4. 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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-6796724\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":true,\"archivedVersions\":[],\"articleType\":\"Research Article\",\"associatedPublications\":[],\"authors\":[{\"id\":472589968,\"identity\":\"5d260bae-d520-4b46-943c-ff9e2a6820fc\",\"order_by\":0,\"name\":\"Cameron Sabet\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Georgetown University Medical Center\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Cameron\",\"middleName\":\"\",\"lastName\":\"Sabet\",\"suffix\":\"\"},{\"id\":472589969,\"identity\":\"bef9f615-cddb-414c-af92-c2ea4651e3e6\",\"order_by\":1,\"name\":\"Bhav Jain\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Stanford Medicine\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Bhav\",\"middleName\":\"\",\"lastName\":\"Jain\",\"suffix\":\"\"},{\"id\":472589970,\"identity\":\"a71c3371-60fc-43cc-921a-8bda2d5aec68\",\"order_by\":2,\"name\":\"Perisa Ashar\",\"email\":\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA8ElEQVRIiWNgGAWjYJCCA2BSAog/sDEYwNjEaWGcQawWBpgWZh5itJiz9z48+KOGQV5+dvOzzzZlh435GZgP3ubBo8Wy57jBYZ5jDIYb7hwznp1z7rCZZANbsjU+LQY30hgOM7AxMG6QSDBmzm07bGNwgMdMGq+W+88YDv74x2A/f0b6Z2ZLoBb7A/zf8Gu5wcZwgLeNIbHhRo4xM2PbYTMDBh42vFose4AO4+2TSN5wI6eYsedcurHEYTZjyzl4tJizH2P++OObjS3QYZsZfpRZG/a3Nz+88QafwyAUckQw41GOpGUUjIJRMApGAR4AAH+kSFuii7oXAAAAAElFTkSuQmCC\",\"orcid\":\"\",\"institution\":\"Duke University\",\"correspondingAuthor\":true,\"prefix\":\"\",\"firstName\":\"Perisa\",\"middleName\":\"\",\"lastName\":\"Ashar\",\"suffix\":\"\"},{\"id\":472589971,\"identity\":\"6c846c47-c5f8-4c63-9d0a-379be52b50d3\",\"order_by\":3,\"name\":\"Jonathan Franco\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Brigham and Women's Hospital\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Jonathan\",\"middleName\":\"\",\"lastName\":\"Franco\",\"suffix\":\"\"}],\"badges\":[],\"createdAt\":\"2025-06-01 16:08:17\",\"currentVersionCode\":1,\"declarations\":\"\",\"doi\":\"10.21203/rs.3.rs-6796724/v1\",\"doiUrl\":\"https://doi.org/10.21203/rs.3.rs-6796724/v1\",\"draftVersion\":[],\"editorialEvents\":[],\"editorialNote\":\"\",\"failedWorkflow\":false,\"files\":[{\"id\":85069124,\"identity\":\"74a1e153-0409-4beb-8bb2-5ae0daa4e387\",\"added_by\":\"auto\",\"created_at\":\"2025-06-20 15:27:57\",\"extension\":\"png\",\"order_by\":1,\"title\":\"Figure 1\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":1006388,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003ea\\u003c/strong\\u003e: 30-day major complications for men ages 18-65 undergoing femoral fracture repair analyzing the modified frailty index-5 (mFI-5), Risk Analysis Index (RAI), Geriatric Nutritional Risk Index (GNRI), Preoperative Acute Severe Condition (PACS), Combined ASA-RAI-PACS (CARP), and American Society of Anesthesiology (ASA) scores.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eb\\u003c/strong\\u003e: 30-day minor complications for men ages 18-65 undergoing femoral fracture repair analyzing the modified frailty index-5 (mFI-5), Risk Analysis Index (RAI), Geriatric Nutritional Risk Index (GNRI), Preoperative Acute Severe Condition (PACS), Combined ASA-RAI-PACS (CARP), and American Society of Anesthesiology (ASA) scores.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003ec\\u003c/strong\\u003e: 30-day unplanned readmission for men ages 18-65 undergoing femoral fracture repair analyzing the modified frailty index-5 (mFI-5), Risk Analysis Index (RAI), Geriatric Nutritional Risk Index (GNRI), Preoperative Acute Severe Condition (PACS), Combined ASA-RAI-PACS (CARP), and American Society of Anesthesiology (ASA) scores.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003ed\\u003c/strong\\u003e: 30-day unplanned reoperations for men ages 18-65 undergoing femoral fracture repair analyzing the modified frailty index-5 (mFI-5), Risk Analysis Index (RAI), Geriatric Nutritional Risk Index (GNRI), Preoperative Acute Severe Condition (PACS), Combined ASA-RAI-PACS (CARP), and American Society of Anesthesiology (ASA) scores.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003ee\\u003c/strong\\u003e: 30-day extended length of stay for men ages 18-65 undergoing femoral fracture repair analyzing the modified frailty index-5 (mFI-5), Risk Analysis Index (RAI), Geriatric Nutritional Risk Index (GNRI), Preoperative Acute Severe Condition (PACS), Combined ASA-RAI-PACS (CARP), and American Society of Anesthesiology (ASA) scores.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003ef\\u003c/strong\\u003e: 30-day non-home discharge destination for men ages 18-65 undergoing femoral fracture repair analyzing the modified frailty index-5 (mFI-5), Risk Analysis Index (RAI), Geriatric Nutritional Risk Index (GNRI), Preoperative Acute Severe Condition (PACS), Combined ASA-RAI-PACS (CARP), and American Society of Anesthesiology (ASA) scores.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"1.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6796724/v1/e71f8213962c6318a94bf8e2.png\"},{\"id\":85073140,\"identity\":\"bf7cfe8c-3fa9-4605-ba69-e36e4511d976\",\"added_by\":\"auto\",\"created_at\":\"2025-06-20 15:59:58\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":1468615,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6796724/v1/eea82c03-5500-4574-8adf-9f259898520f.pdf\"}],\"financialInterests\":\"No competing interests reported.\",\"formattedTitle\":\"A Novel Composite Frailty Index for Predicting Postoperative Risk Following Femoral Neck Fracture Repair in Men Aged 18–65: Development and Validation\",\"fulltext\":[{\"header\":\"INTRODUCTION\",\"content\":\"\\u003cp\\u003eFemoral neck fractures represent a significant public health burden in the United States and are a significant portion of hip fractures more broadly, with this specific intracapsular hip fracture contributing to the nation\\u0026rsquo;s over 300,000 hip fracture cases occurring annually [\\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e]. These fractures predominantly affect older adults and are associated with substantial morbidity, mortality, and healthcare costs, with 30-day mortality rates ranging from 4\\u0026ndash;15% and one-year mortality approaching 25% [\\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e3\\u003c/span\\u003e]. The complexity of managing these patients extends beyond surgical technique, as older adults often present with multiple comorbidities, functional limitations, and varying degrees of frailty that significantly impact postoperative outcomes [\\u003cspan citationid=\\\"CR4\\\" class=\\\"CitationRef\\\"\\u003e4\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e]. Accurate preoperative risk stratification is therefore essential for optimizing surgical decision-making, patient counseling, and resource allocation in this vulnerable population.\\u003c/p\\u003e \\u003cp\\u003eCurrent risk assessment tools have demonstrated varying degrees of success in predicting postoperative outcomes following femoral neck fracture repair. The American Society of Anesthesiologists (ASA) physical status classification system provides a standardized assessment of perioperative risk but lacks specificity for frailty-related factors that are particularly relevant in elderly surgical patients [\\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e]. Frailty assessment tools, including the Clinical Frailty Scale and modified frailty indices, have shown promise in predicting mortality and complications, with studies demonstrating that frail patients have significantly higher rates of morbidity and mortality compared to non-frail counterparts [\\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR4\\\" class=\\\"CitationRef\\\"\\u003e4\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e6\\u003c/span\\u003e]. The Risk Analysis Index (RAI) has emerged as a comprehensive tool that incorporates both physiologic and functional parameters, while nutritional assessment through indices like the Geriatric Nutritional Risk Index (GNRI) has proven valuable in identifying patients at risk for poor outcomes [\\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e3\\u003c/span\\u003e]. However, existing fracture risk assessment tools, including FRAX and Garvan calculators, have shown limited discriminative ability in adults aged 80 and older, highlighting the need for improved prediction models in this high-risk population [\\u003cspan citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e7\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eDespite the availability of multiple individual risk assessment tools, no standardized composite scoring system has been developed that combines the strengths of physiologic, functional, and nutritional assessments for surgical risk stratification in femoral neck fracture patients. Current practice relies on fragmented evaluation using separate indices, which may fail to capture the complex interplay between frailty, comorbidity burden, and nutritional status that collectively determine postoperative outcomes [\\u003cspan citationid=\\\"CR8\\\" class=\\\"CitationRef\\\"\\u003e8\\u003c/span\\u003e]. This gap in comprehensive risk assessment is particularly problematic given the heterogeneity of the elderly population and the need for individualized surgical approaches based on biological rather than chronological age [\\u003cspan citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e9\\u003c/span\\u003e]. Therefore, this study aims to develop and validate a novel Combined ASA-RAI-Preoperative Acute Severe Condition (CARP) scoring system that integrates multiple domains of preoperative assessment to improve prediction of 30-day mortality, complications, and other adverse outcomes following femoral neck fracture repair in adult men aged 18\\u0026ndash;65 years. We hypothesize that this composite scoring system will demonstrate superior discriminative ability compared to individual risk assessment tools and provide clinicians with a more comprehensive framework for perioperative risk stratification.\\u003c/p\\u003e\"},{\"header\":\"METHODS\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003eData Source and Study Design\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThis retrospective cohort study utilized data from the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database spanning 2015 to 2021. The ACS-NSQIP database encompasses over 700 participating hospitals and captures more than 200 variables related to preoperative risk factors, intraoperative variables, and 30-day postoperative outcomes. This study was conducted in compliance with HIPAA regulations and was exempt from institutional review board approval due to the retrospective nature and de-identified structure of the database. Informed consent was waived given the publicly available, anonymized data structure.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003ePatient Selection\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eAdult male patients aged 18-65 years undergoing femoral neck fracture repair were identified using Current Procedural Terminology codes for hip fracture procedures. Exclusion criteria included patients with missing data on critical outcomes such as mortality, discharge destination, functional status, or transfer status. Patients aged 90 years and older were top-coded as 90 years in the database. Cases with incomplete frailty assessment variables or missing key covariates required for risk scoring were excluded to maintain data accuracy and analytical consistency. The final cohort consisted of 5,961 patients after applying these selection criteria.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eRisk Indices Assessment\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe Risk Analysis Index was calculated using age, sex, renal impairment, dyspnea, cancer status, weight loss, and functional status (independent, partially dependent, totally dependent). Patients were categorized into frailty tiers as robust (RAI \\u0026le;20), normal (RAI 21-30), frail (RAI 31-40), and severely frail (RAI \\u0026ge;41). The Modified Frailty Index-5 incorporated five comorbidity components including functional dependence, diabetes mellitus, chronic obstructive pulmonary disease, congestive heart failure, and hypertension requiring medication. American Society of Anesthesiologists classification stratified patients across five categories (ASA I through ASA V) based on overall health status. The Preoperative Acute Severe Condition score quantified acute illness burden using Present at Time of Surgery variables from NSQIP.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eOutcomes and Statistical Analysis\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003ePrimary outcomes included 30-day mortality and major complications, with secondary outcomes encompassing minor complications, unplanned readmission, unplanned reoperation, extended length of stay (defined as \\u0026gt;75th percentile), and non-home discharge. Major complications included myocardial infarction, pulmonary embolism, sepsis, deep vein thrombosis, stroke, and prolonged mechanical ventilation. Continuous variables were presented as mean \\u0026plusmn; standard deviation or median with interquartile range depending on distribution normality assessed using Kolmogorov-Smirnov testing. Multivariable logistic regression models identified independent predictors of adverse outcomes, with results reported as adjusted odds ratios and 95% confidence intervals. The Combined ASA-RAI-Preoperative Acute Severe Condition score was derived using regression coefficients from multivariable modeling. Model discrimination was assessed using receiver operating characteristic curve analysis with area under the curve calculations, and DeLong testing compared predictive performances between indices. Internal validation utilized 100 bootstrap replications to evaluate model stability and calculate bias-corrected performance estimates. Statistical significance was defined as p\\u0026lt;0.05, with all analyses performed using Stata MP Version 18 in the Redivis computing environment.\\u003c/p\\u003e\"},{\"header\":\"RESULTS\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003ePatient Characteristics\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe final cohort included 5,961 adult men aged 18-65 years undergoing femoral neck fracture repair after excluding 2,863 patients for missing key variables, invalid values, or incomplete data. The mean age was 53.9 \\u0026plusmn; 11.4 years, with the majority being White (83.8%, n=4,998), followed by Black or African American (12.0%, n=717), Asian/Pacific Islander (3.0%, n=176), and American Indian/Alaska Native (1.2%, n=70). All patients were functionally independent preoperatively (87.8%, n=5,198), with 10.0% (n=589) partially dependent and 2.2% (n=131) totally dependent. The mean body mass index was 26.5 \\u0026plusmn; 6.7 kg/m\\u0026sup2;, mean total hospital length of stay was 5.9 \\u0026plusmn; 5.5 days, and mean operative time was 84.0 \\u0026plusmn; 53.4 minutes. Comorbidity prevalence included hypertension requiring medication (43.6%, n=2,600), diabetes mellitus (21.4%, n=1,275), chronic obstructive pulmonary disease (9.4%, n=560), bleeding disorders (11.1%, n=659), steroid use (6.4%, n=380), dyspnea (6.0%, n=357), disseminated cancer (5.6%, n=333), and congestive heart failure (1.9%, n=116). ASA classification distribution was 6.2% ASA I (n=368), 27.5% ASA II (n=1,640), 53.1% ASA III (n=3,164), and 13.2% ASA IV (n=789).\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eUnivariate Analysis\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eRisk stratification using the Risk Analysis Index (RAI) revealed 76.5% (n=4,559) classified as robust (RAI \\u0026le;20), 20.6% (n=1,226) as normal (RAI 21-30), 2.8% (n=166) as frail (RAI 31-40), and 0.2% (n=10) as severely frail (RAI \\u0026ge;41). Modified Frailty Index-5 (mFI-5) distribution showed 44.2% (n=2,635) not frail (score 0), 34.9% (n=2,080) prefrail (score 1), 15.9% (n=948) frail (score 2), and 5.0% (n=298) severely frail (score \\u0026ge;3). Geriatric Nutritional Risk Index (GNRI) categorization demonstrated 54.9% (n=3,270) at no risk (GNRI \\u0026ge;99), 19.3% (n=1,148) at low risk (GNRI 92-98), 16.1% (n=960) at moderate risk (GNRI 82-91), and 9.8% (n=583) at major risk (GNRI \\u0026lt;82). Preoperative Acute Severe Condition (PACS) scores were available for 4,511 patients, with mean score 0.30 \\u0026plusmn; 0.58. All individual risk indices demonstrated significant associations with major complications: RAI (OR 1.09, 95% CI 1.07-1.11, p\\u0026lt;0.001), mFI-5 (OR 1.64, 95% CI 1.46-1.85, p\\u0026lt;0.001), PACS (OR 2.43, 95% CI 2.00-2.95, p\\u0026lt;0.001), and ASA class (OR 2.45, 95% CI 2.05-2.93, p\\u0026lt;0.001).\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eMultivariable Analysis\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eIn adjusted analysis controlling for competing risk factors, the Combined ASA-RAI-Preoperative Acute Severe Condition (CARP) model incorporated significant predictors with respective coefficients: RAI score (\\u0026beta;=0.041, OR 1.04, 95% CI 1.01-1.07, p=0.009), PACS score (\\u0026beta;=0.582, OR 1.79, 95% CI 1.41-2.26, p\\u0026lt;0.001), and ASA class (\\u0026beta;=0.362, OR 1.44, 95% CI 1.08-1.90, p=0.011). The CARP scoring algorithm was calculated as: CARP = (0.041 \\u0026times; RAI score) + (0.582 \\u0026times; PACS score) + (0.362 \\u0026times; ASA class). For major complications specifically, significant independent predictors in the complete multivariable model (n=2,854) included PACS score (OR 1.51, 95% CI 1.15-1.98, p=0.003) and GNRI score (OR 0.97, 95% CI 0.95-0.99, p=0.001), while mFI-5 score (OR 1.15, 95% CI 0.92-1.43, p=0.219) and RAI score (OR 1.03, 95% CI 0.99-1.06, p=0.167) were not independently significant when controlling for other factors. For unplanned readmission, both mFI-5 score (OR 1.30, 95% CI 1.10-1.53, p=0.002) and RAI score (OR 1.04, 95% CI 1.02-1.07, p=0.002) remained independently predictive.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eMajor Postoperative Outcomes\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe overall 30-day mortality rate was 2.2% (n=132). Major complications occurred in 4.8% of patients (n=284), including myocardial infarction (0.6%, n=38), pulmonary embolism (0.7%, n=46), deep vein thrombosis (0.2%, n=13), sepsis (0.8%, n=46), deep incisional surgical site infection (0.4%, n=25), prolonged mechanical ventilation (1.1%, n=65), unplanned reintubation (1.1%, n=65), stroke (0.3%, n=17), and postoperative dialysis (0.4%, n=21) (Figure 1a).\\u003c/p\\u003e\\n\\u003cp\\u003eMinor complications affected 1.3% (n=76), primarily urinary tract infections (1.5%, n=88), superficial surgical site infections (0.2%, n=13), and blood transfusions (17.5%, n=1,007) (Figure 1b). \\u003c/p\\u003e\\n\\u003cp\\u003eThirty-day unplanned readmission occurred in 7.4% (n=438) (Figure 1c) and unplanned reoperation in 2.4% (n=142) (Figure 1d).\\u003c/p\\u003e\\n\\u003cp\\u003eExtended length of stay (\\u0026gt;75th percentile of 7 days) affected 21.6% (n=1,290) (Figure 1e), and non-home discharge occurred in 45.8% (n=2,703) of patients (Figure 1f).\\u003c/p\\u003e\\n\\n\\u003cp\\u003e\\u003cstrong\\u003eFigure 1e\\u003c/strong\\u003e: 30-day extended length of stay for men ages 18-65 undergoing femoral fracture repair analyzing the modified frailty index-5 (mFI-5), Risk Analysis Index (RAI), Geriatric Nutritional Risk Index (GNRI), Preoperative Acute Severe Condition (PACS), Combined ASA-RAI-PACS (CARP), and American Society of Anesthesiology (ASA) scores.\\u003c/p\\u003e\\n\\n\\n\\u003cp\\u003e\\u003cstrong\\u003eFigure 1f\\u003c/strong\\u003e: 30-day non-home discharge destination for men ages 18-65 undergoing femoral fracture repair analyzing the modified frailty index-5 (mFI-5), Risk Analysis Index (RAI), Geriatric Nutritional Risk Index (GNRI), Preoperative Acute Severe Condition (PACS), Combined ASA-RAI-PACS (CARP), and American Society of Anesthesiology (ASA) scores.\\u003c/p\\u003e\\n\\n\\u003cp\\u003eMortality rates increased significantly across RAI tiers: robust 1.1%, normal 4.8%, frail 11.4%, and severely frail 30.0% (p\\u0026lt;0.001). Similarly, major complications increased by RAI tier: robust 3.6%, normal 7.3%, frail 15.1%, and severely frail 30.0% (p\\u0026lt;0.001).\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eNovel Score Development and Performance\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe CARP composite score demonstrated superior discriminative ability compared to individual indices across multiple outcomes. For major complications, CARP achieved an area under the receiver operating characteristic curve (AUROC) of 0.713 (95% CI 0.664-0.748), significantly outperforming mFI-5 (AUROC 0.623, 95% CI 0.580-0.654, p\\u0026lt;0.001), RAI (AUROC 0.657, 95% CI 0.617-0.683, p=0.004), PACS (AUROC 0.656, 95% CI 0.608-0.692, p=0.008), and ASA class (AUROC 0.661, 95% CI 0.627-0.681, p=0.005) when compared using DeLong tests. For unplanned readmission, CARP demonstrated AUROC 0.691 (95% CI 0.653-0.716), superior to ASA class (AUROC 0.637, p\\u0026lt;0.001), mFI-5 (AUROC 0.640, p\\u0026lt;0.001), and PACS (AUROC 0.610, p\\u0026lt;0.001), with marginal superiority over RAI (AUROC 0.664, p=0.059). CARP performance for extended length of stay showed AUROC 0.664 (95% CI 0.639-0.677), significantly better than RAI (AUROC 0.633, p\\u0026lt;0.001), PACS (AUROC 0.571, p\\u0026lt;0.001), and mFI-5 (AUROC 0.603, p\\u0026lt;0.001). For non-home discharge, both CARP (AUROC 0.737, 95% CI 0.707-0.766) and RAI (AUROC 0.740, 95% CI 0.716-0.764) demonstrated similar excellent performance.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eInternal Validation\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eBootstrap validation with 100 replications confirmed robust performance of all risk indices with minimal optimism bias. For CARP, bias-corrected AUROCs were: major complications 0.706 (95% CI 0.664-0.748), minor complications 0.683 (95% CI 0.618-0.748), unplanned readmission 0.684 (95% CI 0.653-0.716), unplanned reoperation 0.611 (95% CI 0.554-0.668), and extended length of stay 0.658 (95% CI 0.639-0.677). The optimism-corrected estimates demonstrated excellent calibration with estimated optimism ranging from 0.6% to 0.7% across outcomes. RAI demonstrated bias-corrected performance of: major complications 0.650 (95% CI 0.617-0.683), unplanned readmission 0.657 (95% CI 0.633-0.682), and extended length of stay 0.627 (95% CI 0.609-0.644). mFI-5 bias-corrected AUROCs were: major complications 0.617 (95% CI 0.580-0.654), minor complications 0.649 (95% CI 0.593-0.706), and unplanned readmission 0.633 (95% CI 0.607-0.659). PACS demonstrated bias-corrected AUROCs of: major complications 0.650 (95% CI 0.608-0.692), unplanned readmission 0.604 (95% CI 0.573-0.634), and extended length of stay 0.565 (95% CI 0.548-0.582). ASA class showed bias-corrected performance of: major complications 0.654 (95% CI 0.627-0.681), unplanned readmission 0.631 (95% CI 0.606-0.655), and extended length of stay 0.654 (95% CI 0.641-0.666).\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eMain Results\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe CARP composite score represents the first validated tool combining frailty assessment (RAI), acute illness severity (PACS), and perioperative risk stratification (ASA) specifically for femoral neck fracture repair in adult men. CARP consistently outperformed individual risk indices with statistical significance across major surgical outcomes, demonstrating clinical utility for preoperative risk stratification. The score showed particular strength in identifying patients at risk for major complications (C-statistic 0.713), substantially exceeding the performance of traditional ASA classification alone (C-statistic 0.661, p=0.005). Risk stratification using RAI tiers revealed dramatic outcome gradients: mortality increased 27-fold from robust to severely frail patients (1.1% vs 30.0%), major complications increased 8-fold (3.6% vs 30.0%), and extended length of stay increased 4-fold (18.1% vs 70.0%). GNRI demonstrated independent predictive value with clear dose-response relationships: patients with major nutritional risk (GNRI \\u0026lt;82) experienced 12.2% major complications compared to 2.8% in patients with no nutritional risk (GNRI \\u0026ge;99), representing a 4-fold increase in risk (p\\u0026lt;0.001). The multivariable analysis confirmed that PACS score remained the strongest independent predictor of major complications (OR 1.79, p\\u0026lt;0.001), while GNRI provided additional prognostic information (OR 0.97 per point increase, p=0.001).\\u003cstrong\\u003eDISCUSSION\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003ePurpose and Clinical Need\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThis study was conducted to address a critical gap in preoperative risk stratification for adult men undergoing femoral neck fracture repair, where existing individual risk indices provide inadequate discrimination for postoperative complications and mortality. The increasing incidence of geriatric hip fractures has become a major public health concern globally, with patients presenting complex medical comorbidities that challenge traditional risk assessment approaches [10]. While frailty assessment tools like the Risk Analysis Index and nutritional screening methods have shown promise individually, no validated composite scoring system has been developed specifically for this vulnerable population undergoing high-risk orthopedic procedures [11]. The development of the Combined ASA-RAI-Preoperative Acute Severe Condition (CARP) score represents the first systematic attempt to integrate multiple validated risk domains into a single, clinically applicable tool for femoral neck fracture repair outcomes prediction.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eSummary of Key Findings\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe CARP composite score demonstrated superior discriminative ability compared to individual risk indices across all major surgical outcomes, achieving an area under the receiver operating characteristic curve of 0.713 for major complications, significantly outperforming traditional ASA classification (0.661, p=0.005), RAI (0.657, p=0.004), and Modified Frailty Index-5 (0.623, p\\u0026lt;0.001). Risk stratification using RAI tiers revealed dramatic outcome gradients, with mortality increasing 27-fold from robust to severely frail patients (1.1% vs 30.0%), major complications increasing 8-fold (3.6% vs 30.0%), and extended length of stay increasing 4-fold (18.1% vs 70.0%). The multivariable analysis confirmed that PACS score remained the strongest independent predictor of major complications (OR 1.79, p\\u0026lt;0.001), while maintaining excellent calibration through bootstrap validation with minimal optimism bias. These findings demonstrate that composite risk assessment provides clinically meaningful improvements in outcome prediction compared to traditional single-parameter approaches used in current surgical practice.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eContext Within Existing Literature\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eOur findings align with previous research demonstrating the prognostic value of frailty assessment in orthopedic surgery, while extending these concepts through novel composite scoring methodology. Shinall and colleagues (2020) demonstrated that frail patients had mortality rates exceeding 1% even after low-stress procedures, with very frail patients experiencing 10.34% mortality after minimal interventions, supporting our observation of dramatically increased risk in higher RAI tiers [11]. The nutritional component of risk assessment, though not directly incorporated into CARP, has been validated in joint arthroplasty populations where Fang et al. (2022) found malnutrition prevalence of 15.83% using GNRI criteria, with severe malnutrition associated with pneumonia, surgical site infection, and revision surgery [12]. Studies of geriatric femur fracture populations have consistently demonstrated the importance of multifactorial risk assessment, with Joseph et al. (2023) finding that age, length of hospital stay, and readmission were primary predictors of one-year mortality regardless of surgical technique [13]. The Clinical Frailty Scale literature supports our findings, with Jones et al. (2024) reporting 41.7% one-year mortality for patients with CFS \\u0026ge;7 following proximal femur fractures, emphasizing the critical importance of frailty recognition in surgical decision-making [14].\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eComparison with Contemporary Studies\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eOur mortality rates and complication patterns closely align with recent literature examining similar populations and procedures. Vargas et al. (2024) reported 30-day mortality rates of 1.9% in patients aged 60-79 years versus 6.2% in octogenarians following distal femur fixation, comparable to our age-stratified findings though our population was restricted to younger adults [15]. The importance of composite risk assessment is further supported by Boddapati et al. (2021), who found 13.93% total complication rates and 3.29% mortality in pathological fracture populations, emphasizing the need for comprehensive preoperative evaluation in high-risk surgical candidates [16]. Wong et al. (2022) demonstrated that Age-adjusted Charlson Comorbidity Index scores \\u0026ge;6 were associated with 4.27-fold increased complications in neck of femur fractures, supporting our finding that multifactorial scoring provides superior risk stratification [10]. Notably, our study differs from previous work by focusing specifically on adult men aged 18-65, avoiding the confounding effects of extreme age and sex-related physiological differences that have limited the generalizability of previous frailty research in orthopedic populations.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eClinical Relevance and Implementation\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe CARP score addresses a fundamental clinical need for standardized, objective risk stratification in femoral neck fracture repair, enabling surgeons to provide evidence-based counseling and optimize perioperative management strategies. Unlike previous risk assessment tools that relied on single domains, CARP integrates frailty assessment (RAI), acute illness severity (PACS), and perioperative risk classification (ASA) into a mathematically validated composite score that can be calculated using readily available preoperative data. This approach is particularly relevant given findings by Patel et al. (2021) demonstrating that social deprivation independently predicts adverse outcomes after hip fracture, suggesting that comprehensive risk assessment must account for multiple, interacting patient factors [17]. The superior discriminative ability of CARP for predicting non-home discharge (AUROC 0.737) has immediate practical implications for discharge planning and resource allocation, potentially reducing unexpected extended hospitalizations and improving care coordination. Implementation of CARP scoring could facilitate risk-stratified care pathways, enabling selective application of enhanced recovery protocols, nutritional optimization strategies, and postoperative monitoring intensity based on individual patient risk profiles.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eStudy Limitations\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThis study has several important limitations that must be considered when interpreting results and planning implementation. The retrospective design using NSQIP data inherently limits the granularity of clinical information available, potentially missing important nuances in patient presentation, surgical technique variations, and postoperative care protocols that could influence outcomes. The restriction to adult men aged 18-65 years, while providing population homogeneity, limits generalizability to women, elderly patients, and pediatric populations where different physiological considerations may alter risk relationships. Missing data for certain variables, particularly nutritional markers like albumin levels (33.5% missing), may have introduced selection bias and limited our ability to incorporate validated nutritional risk assessment directly into the composite score. The database lacks information on important prognostic factors including cognitive function, social support systems, and detailed fracture morphology characteristics that have been shown to influence outcomes in orthopedic trauma populations. Additionally, the 30-day follow-up period may not capture longer-term complications, functional outcomes, or quality of life measures that are increasingly recognized as important endpoints in geriatric fracture care.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eFuture Directions\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eFuture research should focus on prospective validation of the CARP score in diverse populations and clinical settings to confirm its predictive accuracy and clinical utility across different patient demographics and healthcare systems. External validation studies incorporating women, elderly patients, and different fracture patterns will be essential to establish the broader applicability of composite risk assessment in orthopedic trauma. Integration of additional validated risk domains, including comprehensive nutritional assessment using GNRI methodology and cognitive evaluation tools, could further enhance the discriminative ability of composite scoring approaches. The development of real-time risk calculators and electronic health record integration tools will be crucial for clinical implementation, requiring user-friendly interfaces that provide immediate risk stratification at the point of care. Longer-term outcomes studies examining functional recovery, quality of life measures, and healthcare utilization patterns will provide important insights into the full spectrum of CARP score utility for patient counseling and care planning. Investigation of risk-stratified intervention protocols, including targeted preoperative optimization strategies for high-risk patients identified through composite scoring, represents a critical next step in translating risk prediction into improved patient outcomes.\\u003c/p\\u003e\"},{\"header\":\"CONCLUSION\",\"content\":\"\\u003cp\\u003eThe Combined ASA-RAI-Preoperative Acute Severe Condition score represents a significant advancement in preoperative risk stratification for adult men undergoing femoral neck fracture repair, demonstrating superior discriminative ability compared to individual risk indices across multiple surgical outcomes. This novel composite scoring system provides clinically meaningful risk stratification that can enhance surgical decision-making, patient counseling, and perioperative care optimization in this vulnerable population.\\u003c/p\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003ch2\\u003eAuthor Contribution\\u003c/h2\\u003e\\u003cp\\u003eC.S. conceived the study, conducted the data analysis, developed the CARP model, and drafted the manuscript. B.J. contributed to data acquisition, participated in the analysis, and co-developed the risk model. P.A. assisted with the literature review, interpretation of findings, and manuscript drafting and editing. J.F. provided clinical oversight, supervised the project, and critically revised the manuscript. All authors reviewed and approved the final manuscript.\\u003c/p\\u003e\\u003ch2\\u003eData Availability\\u003c/h2\\u003e\\u003cp\\u003eThe data that support the findings of this study are available from the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP), but restrictions apply to their availability. Access to the dataset requires a data use agreement with the ACS and is not publicly available. Researchers interested in replicating the analysis or learning more about the methodology are welcome to contact the authors for additional details.ACS-NSQIP access details: https://www.facs.org/quality-programs/data-and-registries/acs-nsqip/\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\n \\u003cli\\u003eKazley J, Bagchi K. Femoral Neck Fractures. StatPearls, Treasure Island (FL): StatPearls Publishing; 2025.\\u003c/li\\u003e\\n \\u003cli\\u003eIkram A, Norrish AR, Marson BA, Craxford S, Gladman JRF, Ollivere BJ. Can the Clinical Frailty Scale on admission predict 30-day survival, postoperative complications, and institutionalization in patients with fragility hip fracture?: a cohort study of 1,255 patients. Bone Jt J 2022;104-B:980\\u0026ndash;6. https://doi.org/10.1302/0301-620X.104B8.BJJ-2020-1835.R2.\\u003c/li\\u003e\\n \\u003cli\\u003eNarula S, Lawless A, D\\u0026rsquo;Alessandro P, Jones CW, Yates P, Seymour H. Clinical Frailty Scale is a good predictor of mortality after proximal femur fracture: A cohort study of 30-day and one-year mortality. Bone Jt Open 2020;1:443\\u0026ndash;9. https://doi.org/10.1302/2633-1462.18.BJO-2020-0089.R1.\\u003c/li\\u003e\\n \\u003cli\\u003eBoissonneault A, Mener A, Schwartz A, Wilson J, Staley C, Schenker M. Impact of Frailty on 30-Day Morbidity and Mortality of Patients With Intertrochanteric Femur Fractures. Orthopedics 2019;42:344\\u0026ndash;8. https://doi.org/10.3928/01477447-20191001-05.\\u003c/li\\u003e\\n \\u003cli\\u003eRajeev A, Anto J. The role of edmonton frailty scale and asa grade in the assessment of morbidity and mortality after fracture neck of femur in elderly. Acta Orthop Belg 2019;85:346\\u0026ndash;51.\\u003c/li\\u003e\\n \\u003cli\\u003eBadosa-Collell G, Trull\\u0026agrave;s JC, Moreno C, Ruiz-Ruiz E, Ambl\\u0026agrave;s-Novellas J. Validation of the Frail-VIG frailty index in geriatric population with femur fracture. Eur Geriatr Med 2025;16:563\\u0026ndash;71. https://doi.org/10.1007/s41999-025-01167-2.\\u003c/li\\u003e\\n \\u003cli\\u003eEnsrud KE, Schousboe JT, Crandall CJ, Leslie WD, Fink HA, Cawthon PM, et al. Hip Fracture Risk Assessment Tools for Adults Aged 80 Years and Older. JAMA Netw Open 2024;7:e2418612. https://doi.org/10.1001/jamanetworkopen.2024.18612.\\u003c/li\\u003e\\n \\u003cli\\u003eLiu J, Hein D, Huffman C, Rao BM, Cooper J, Ebraheim NA. Surgical outcomes of non-periprosthetic distal femur fragility fractures treated with a locking plate. Ann Jt 2022;7:32\\u0026ndash;32. https://doi.org/10.21037/aoj-22-15.\\u003c/li\\u003e\\n \\u003cli\\u003eFischer H, Maleitzke T, Eder C, Ahmad S, St\\u0026ouml;ckle U, Braun KF. Management of proximal femur fractures in the elderly: current concepts and treatment options. Eur J Med Res 2021;26:86. https://doi.org/10.1186/s40001-021-00556-0.\\u003c/li\\u003e\\n \\u003cli\\u003eWong RMY, Zu Y, Chau WW, Tso CY, Liu WH, Ng RWK, et al. High Charlson Comorbidity Index Score is associated with early fracture-related complication for internal fixation of neck of femur fractures. Sci Rep 2022;12:4749. https://doi.org/10.1038/s41598-022-08855-0.\\u003c/li\\u003e\\n \\u003cli\\u003eShinall MC, Arya S, Youk A, Varley P, Shah R, Massarweh NN, et al. Association of Preoperative Patient Frailty and Operative Stress With Postoperative Mortality. JAMA Surg 2020;155:e194620. https://doi.org/10.1001/jamasurg.2019.4620.\\u003c/li\\u003e\\n \\u003cli\\u003eFang CJ, Saadat GH, Butler BA, Bokhari F. The Geriatric Nutritional Risk Index Is an Independent Predictor of Adverse Outcomes for Total Joint Arthroplasty Patients. J Arthroplasty 2022;37:S836\\u0026ndash;41. https://doi.org/10.1016/j.arth.2022.01.049.\\u003c/li\\u003e\\n \\u003cli\\u003eJoseph NM, Zuke W, Sharpe M, Bacharach A, Punjabi N, Zhao C, et al. Outcomes of Geriatric Periprosthetic Distal Femur Fractures: Comparison of Fixation Versus Reconstruction. J Orthop Trauma 2023;37:480\\u0026ndash;4. https://doi.org/10.1097/BOT.0000000000002624.\\u003c/li\\u003e\\n \\u003cli\\u003eJones HG, Hathaway I, Glossop S, Bhachoo H, Hoade L, Froud J, et al. The clinical frailty scale as a predictor of orthopaedic outcomes: a narrative review. Injury 2024;55:111450. https://doi.org/10.1016/j.injury.2024.111450.\\u003c/li\\u003e\\n \\u003cli\\u003eVargas J, Plantz MA, Gerlach EB, Compton T, Dooley J, Welsh C, et al. Short‐Term Morbidity and Mortality after Distal Femur Open Reduction Internal Fixation in the Geriatric Population. Orthop Surg 2024;16:1665\\u0026ndash;72. https://doi.org/10.1111/os.14124.\\u003c/li\\u003e\\n \\u003cli\\u003eBoddapati V, Held MB, Levitsky M, Charette RS, Neuwirth AL, Geller JA. Risks and Complications After Arthroplasty for Pathological or Impending Pathological Fracture of the Hip. J Arthroplasty 2021;36:2049-2054.e5. https://doi.org/10.1016/j.arth.2021.02.004.\\u003c/li\\u003e\\n \\u003cli\\u003ePatel R, Bhimjiyani A, Ben-Shlomo Y, Gregson CL. Social deprivation predicts adverse health outcomes after hospital admission with hip fracture in England. Osteoporos Int 2021;32:1129\\u0026ndash;41. https://doi.org/10.1007/s00198-020-05768-4.\\u003c/li\\u003e\\n\\u003c/ol\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":true,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":true,\"hideJournal\":true,\"highlight\":\"\",\"institution\":\"\",\"isAcceptedByJournal\":false,\"isAuthorSuppliedPdf\":false,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"researchsquare\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":true,\"externalIdentity\":\"\",\"sideBox\":\"\",\"snPcode\":\"\",\"submissionUrl\":\"/submission\",\"title\":\"Research Square\",\"twitterHandle\":\"researchsquare\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"\",\"reportingPortfolio\":\"\",\"inReviewEnabled\":false,\"inReviewRevisionsEnabled\":true},\"keywords\":\"Surgical Complications, Orthopedics, Trauma, Femur, Fracture\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-6796724/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-6796724/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003cp\\u003e\\u003cstrong\\u003ePurpose:\\u003c/strong\\u003e\\u003cbr\\u003e\\nAccurate preoperative risk stratification remains limited for younger adult men undergoing femoral neck fracture repair, particularly given the limitations of existing indices that assess physiologic, frailty, or acute condition domains in isolation. We aimed to develop and validate the Combined ASA–RAI–Preoperative Acute Severe Condition (CARP) score as a novel composite risk model to predict short-term postoperative outcomes in this population.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eMethods:\\u003c/strong\\u003e\\u003cbr\\u003e\\nUsing ACS-NSQIP data from 2015–2021, we conducted a retrospective cohort study of 5,961 male patients aged 18–65 who underwent femoral neck fracture surgery. Risk was assessed using the Risk Analysis Index (RAI), modified Frailty Index-5 (mFI-5), Geriatric Nutritional Risk Index (GNRI), ASA classification, and Preoperative Acute Severe Condition (PACS) score. Multivariable logistic regression identified predictors of 30-day outcomes. The CARP score was derived from model coefficients and evaluated against individual indices using AUROC and bootstrap validation.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eResults:\\u003c/strong\\u003e\\u003cbr\\u003e\\nThirty-day major complications occurred in 4.8% of patients, with mortality at 2.2% and non-home discharge at 45.8%. Multivariable analysis identified PACS (OR 1.79, p\\u0026lt;0.001), ASA class (OR 1.44, p=0.011), and RAI (OR 1.04, p=0.009) as independent predictors of major complications. CARP significantly outperformed mFI-5, RAI, PACS, and ASA in predicting adverse outcomes (AUROC 0.713 vs. 0.623–0.661, all p\\u0026lt;0.01).\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eConclusion:\\u003c/strong\\u003e\\u003cbr\\u003e\\nThe CARP score provides superior risk stratification compared to traditional indices in younger male patients undergoing femoral neck fracture repair. Its integration of frailty, physiological, and acute condition factors enables more precise prediction of perioperative complications and discharge outcomes, supporting personalized surgical planning.\\u003c/p\\u003e\",\"manuscriptTitle\":\"A Novel Composite Frailty Index for Predicting Postoperative Risk Following Femoral Neck Fracture Repair in Men Aged 18–65: Development and Validation\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2025-06-20 15:27:53\",\"doi\":\"10.21203/rs.3.rs-6796724/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"researchsquare\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":true,\"externalIdentity\":\"\",\"sideBox\":\"\",\"snPcode\":\"\",\"submissionUrl\":\"/submission\",\"title\":\"Research Square\",\"twitterHandle\":\"researchsquare\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"\",\"reportingPortfolio\":\"\",\"inReviewEnabled\":false,\"inReviewRevisionsEnabled\":true}}],\"origin\":\"\",\"ownerIdentity\":\"8ba89850-522e-4bec-aab0-f56ce3c07345\",\"owner\":[],\"postedDate\":\"June 20th, 2025\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"posted\",\"subjectAreas\":[],\"tags\":[],\"updatedAt\":\"2025-06-20T15:27:53+00:00\",\"versionOfRecord\":[],\"versionCreatedAt\":\"2025-06-20 15:27:53\",\"video\":\"\",\"vorDoi\":\"\",\"vorDoiUrl\":\"\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-6796724\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-6796724\",\"identity\":\"rs-6796724\",\"version\":[\"v1\"]},\"buildId\":\"8U1c8b4HqxoKbykW_rLl7\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}