The global demographic landscape is undergoing an unprecedented transformation. By 2050, the number of people aged 60 years and older is expected to reach 2.1 billion, with those aged 65 and above comprising an estimated 16% of the world's population. In the United States alone, the population aged over 65 years is projected to double between 2000 and 2050. Countries such as Japan and Italy have already surpassed the 21% threshold, earning the designation of "super-aged" societies. This demographic shift has profound implications for surgical practice, as the proportion of elderly patients requiring surgical intervention continues to rise dramatically. Currently, at least two-thirds of urological surgeries are performed in elderly patients, and similar trends are observed across all surgical specialties.

Elderly patients undergoing surgery face unique challenges that distinguish them from their younger counterparts. The aging process is associated with progressive physiological decline across multiple organ systems, including reduced cardiovascular reserve, diminished pulmonary function, impaired renal clearance, and blunted immune responses. These age-related changes, compounded by a high prevalence of comorbidities such as hypertension, diabetes, coronary artery disease, and chronic kidney disease, contribute to an elevated risk of perioperative morbidity and mortality. Advanced age has been associated with a two- to fourfold increase in postoperative complications and mortality. The 30-day mortality rate for nonagenarians undergoing cardiac surgery, for example, has been reported at a median of 10.5%, with major complication rates exceeding 70%.

However, chronological age alone is an imperfect predictor of surgical outcomes. The concept of frailty—a clinical state of diminished physiological reserve across multiple systems, rendering individuals vulnerable to stressors—has emerged as a more accurate prognostic indicator. Frailty affects approximately 16% of individuals aged over 60 years and up to 20–40% of elderly patients undergoing major surgery. Frail patients have been shown to experience significantly higher rates of postoperative complications, prolonged hospital stays, increased readmissions, and elevated mortality. A recent meta-analysis demonstrated that frail elderly patients undergoing cardiac surgery had nearly four times the mortality risk of their non-frail counterparts.

The urgency of surgical intervention further modulates outcomes. Elective surgeries in elderly patients carry an estimated 1% mortality and 10% morbidity rate, whereas emergency surgeries drastically elevate these risks. Frailty has been identified as a particularly potent predictor of adverse outcomes in emergency settings. In a prospective cohort study of older patients undergoing emergency laparotomy, frail patients had an unadjusted 30-day mortality rate of 58.8% compared with 23.6% in non-frail patients.

Despite advances in surgical techniques, anesthetic management, and perioperative care, elderly patients remain at disproportionately higher risk of postoperative complications and mortality. The UK National Confidential Enquiry into Patient Outcome and Death (NCEPOD) concluded that healthcare provided to the elderly was often insufficient and stressed that a "one size fits all medicine model" cannot be applied to this heterogeneous population. This underscores the critical need for individualized perioperative risk assessment and management strategies tailored to the unique needs of elderly surgical patients.

Enhanced Recovery After Surgery (ERAS) protocols and minimally invasive surgical approaches have shown promise in improving outcomes for elderly patients. ERAS pathways have been associated with shorter hospital stays, faster functional recovery, and fewer postoperative complications in elderly spinal surgery patients. Similarly, minimally invasive techniques have demonstrated reduced blood loss, faster recovery, and lower morbidity compared with open surgery in elderly populations. Comprehensive Geriatric Assessment (CGA) has also emerged as a valuable tool for identifying high-risk patients and guiding perioperative care.

This was a multicenter retrospective cohort study conducted across three tertiary-care hospitals Employee's State Insurance Corporation Medical College and Hospital, Kalaburagi, Navodaya Medical College, Raichur and Yadagiri Institute of Medical Sciences, Yadgir between January 2021 and December 2025. The study was approved by the institutional review boards of all participating centers. Informed consent was waived owing to the retrospective nature of the study. Study Population We included all patients aged 65 years and older who underwent major elective non-cardiac surgery during the study period. Major surgery was defined as any procedure requiring general or regional anesthesia with an expected operative time ≥60 minutes and involving intra-abdominal, intrathoracic, or major orthopedic interventions. Exclusion criteria were: (1) emergency surgery; (2) minor procedures (e.g., endoscopy, biopsy, superficial skin procedures); (3) cardiac surgery; (4) ASA class V; (5) preoperative sepsis; (6) pregnancy; and (7) incomplete medical records. Data Collection Data were extracted from electronic medical records by trained research assistants using a standardized data abstraction form. Variables collected included: Demographic and baseline characteristics: Age, sex, body mass index (BMI), living status, and education level. Comorbidities: Hypertension, diabetes mellitus, coronary artery disease, congestive heart failure, chronic obstructive pulmonary disease, chronic kidney disease, cerebrovascular disease, and malignancy. Comorbidity burden was quantified using the Charlson Comorbidity Index (CCI). Preoperative functional status: Activities of daily living (ADL) score, instrumental activities of daily living (IADL) score, and history of falls in the preceding 6 months. Frailty assessment: Frailty was assessed using the modified Frailty Index (mFI), comprising 11 variables derived from the Canadian Study of Health and Aging Frailty Index: (1) diabetes, (2) hypertension, (3) congestive heart failure, (4) myocardial infarction, (5) cardiac arrhythmia, (6) peripheral vascular disease, (7) cerebrovascular disease, (8) chronic obstructive pulmonary disease, (9) renal disease, (10) functional dependence, and (11) cognitive impairment. Patients were classified as frail if mFI ≥0.25. Surgical variables: Procedure type, surgical specialty, operative time, estimated blood loss, and American Society of Anesthesiologists (ASA) physical status classification. Outcomes Primary outcome: Major postoperative complications, defined as Clavien-Dindo grade ≥III (requiring surgical, endoscopic, or radiological intervention; life-threatening complications requiring intensive care unit management; or death). Secondary outcomes: (1) 30-day all-cause mortality; (2) length of hospital stay (LOS); (3) 30-day hospital readmission; (4) discharge to a skilled nursing facility or rehabilitation center rather than home; and (5) functional decline at discharge, defined as a decrease of ≥1 point in ADL score compared with preoperative baseline. Postoperative complications were recorded if they occurred within 30 days of surgery or during the index hospitalization, whichever was longer. Complications were systematically identified through review of clinical notes, laboratory results, imaging reports, and discharge summaries. Statistical Analysis Continuous variables were expressed as mean ± standard deviation (SD) or median with interquartile range (IQR), as appropriate. Categorical variables were presented as frequencies and percentages. Group comparisons were performed using Student's t-test or Mann–Whitney U test for continuous variables and chi-square or Fisher's exact test for categorical variables. To identify independent predictors of major postoperative complications, we performed multivariable logistic regression analysis. Variables with p<0.10 in univariable analysis were entered into the multivariable model using a forward stepwise selection approach. The model was adjusted for potential confounders including age, sex, ASA class, CCI, frailty, urgency of surgery, and operative time. Results were reported as adjusted odds ratios (aOR) with 95% confidence intervals (CI). Model calibration was assessed using the Hosmer–Lemeshow goodness-of-fit test, and discrimination was evaluated using the area under the receiver operating characteristic curve (AUC). To evaluate the additional predictive value of frailty beyond conventional risk factors, we calculated the Net Reclassification Index (NRI) and Integrated Discrimination Improvement Index (IDI). Subgroup analyses were performed to assess the consistency of the association between frailty and outcomes across predefined subgroups defined by age (<80 vs. ≥80 years), sex, ASA class (I–II vs. III–IV), and surgical specialty. All statistical analyses were performed using R version 4.2.3 (R Foundation for Statistical Computing, Vienna, Austria). A two-sided p-value <0.05 was considered statistically significant.

Patient Characteristics

A total of 1,358 elderly patients (≥65 years) undergoing major elective non-cardiac surgery were included in the analysis. The mean age was 73.4 ± 6.8 years (range 65–98 years), and 52.3% of patients were male. The most common surgical specialties were general surgery (34.1%), orthopedic surgery (28.6%), and urological surgery (18.2%). Frailty (mFI ≥0.25) was present in 426 patients (31.4%). Baseline characteristics stratified by frailty status are presented in Table 1.

Table 1. Baseline Characteristics of the Study Population Stratified by Frailty Status

Data are presented as mean ± standard deviation or n (%). BMI = body mass index; COPD = chronic obstructive pulmonary disease; ASA = American Society of Anesthesiologists.

Frail patients were significantly older (76.3 ± 7.1 vs. 72.1 ± 6.2 years; p<0.001), had higher comorbidity burden (CCI 4.3 ± 2.4 vs. 2.7 ± 1.8; p<0.001), and were more likely to have ASA class ≥III (58.2% vs. 36.3%; p<0.001) compared with non-frail patients. Notably, 33.8% of frail patients were aged ≥80 years, compared with 18.0% of non-frail patients (p<0.001).

Postoperative Outcomes

Overall, 253 patients (18.6%) experienced major postoperative complications (Clavien-Dindo grade ≥III), and 57 patients (4.2%) died within 30 days of surgery. Frail patients had significantly higher rates of major complications (32.4% vs. 12.3%; p<0.001) and 30-day mortality (9.6% vs. 1.7%; p<0.001) compared with non-frail patients. The distribution of postoperative complications by frailty status is shown in Table 2.

Table 2. Postoperative Outcomes by Frailty Status

Data are presented as n (%) or mean ± standard deviation. ICU = intensive care unit.

The most common major complications were pneumonia (12.4%), surgical site infection (10.5%), and delirium (9.1%). Frail patients had significantly longer hospital stays (mean 12.8 ± 7.8 days vs. 8.4 ± 5.2 days; p<0.001) and higher 30-day readmission rates (20.7% vs. 11.6%; p<0.001). Notably, 36.2% of frail patients were discharged to a skilled nursing facility or rehabilitation center, compared with 17.0% of non-frail patients (p<0.001), and 36.2% of frail patients experienced functional decline at discharge versus 14.2% of non-frail patients (p<0.001).

Predictors of Major Postoperative Complications

Multivariable logistic regression analysis identified several independent predictors of major postoperative complications (Table 3). Frailty was the strongest predictor (aOR 2.61, 95% CI 1.47–4.62; p<0.001). Each 1-point increase in frailty score was associated with a 35% increase in the risk of major complications (aOR 1.35, 95% CI 1.10–1.66). Emergency surgery (aOR 3.82, 95% CI 2.14–6.81; p<0.001), ASA class ≥III (aOR 2.45, 95% CI 1.58–3.79; p<0.001), and age ≥80 years (aOR 1.78, 95% CI 1.21–2.62; p=0.003) were also significant independent predictors.

Table 3. Multivariable Logistic Regression Analysis of Predictors of Major Postoperative Complications

aOR = adjusted odds ratio; CI = confidence interval; mFI = modified Frailty Index; ASA = American Society of Anesthesiologists. Model adjusted for age, sex, ASA class, Charlson Comorbidity Index, frailty, urgency of surgery, operative time, and surgical specialty. Hosmer–Lemeshow test: χ² = 8.42, p = 0.393; AUC = 0.792.

The addition of frailty to the baseline risk model (which included age, ASA class, and CCI) significantly improved the predictive value for major postoperative complications. The NRI was 0.555 (95% CI 0.310–0.801) and the IDI was 0.014 (95% CI 0.0003–0.029), indicating that frailty provided meaningful additional prognostic information beyond conventional risk factors. The model demonstrated good discrimination with an AUC of 0.792.

Subgroup Analyses

Subgroup analyses revealed that the association between frailty and major postoperative complications was consistent across most predefined subgroups (Figure 1). The effect was particularly pronounced in patients aged <80 years (aOR 3.12, 95% CI 1.64–5.94) and in those with ASA class I–II (aOR 3.45, 95% CI 1.72–6.92), suggesting that frailty may be an especially valuable risk stratification tool in apparently lower-risk elderly patients. No significant interaction was observed between frailty and sex or surgical specialty.

This multicenter cohort study of 1,358 elderly patients undergoing major elective non-cardiac surgery provides robust evidence that frailty is a powerful and independent predictor of adverse postoperative outcomes, surpassing chronological age in prognostic value. Our findings demonstrate that frail elderly patients face substantially higher risks of major complications, mortality, prolonged hospitalization, readmission, institutional discharge, and functional decline. These results have important implications for perioperative risk stratification, surgical decision-making, and the design of interventions to improve outcomes in this growing population. The prevalence of frailty in our cohort (31.4%) is consistent with previously reported estimates of 20–40% in elderly surgical populations. Frail patients in our study had nearly three times the odds of major postoperative complications compared with non-frail patients (aOR 2.61), a finding that aligns with recent meta-analyses demonstrating similar effect sizes across various surgical settings. Notably, each 1-point increment in frailty score conferred a 35% increase in complication risk, suggesting a dose–response relationship that underscores the importance of frailty as a continuous rather than purely categorical construct. The predictive superiority of frailty over chronological age is a recurring theme in the geriatric surgery literature. In our study, while age ≥80 years remained an independent predictor (aOR 1.78), its effect size was substantially smaller than that of frailty. This finding supports the growing consensus that chronological age alone is an inadequate basis for surgical risk assessment. Two elderly patients of the same chronological age may have vastly different physiological reserves and vulnerability to surgical stress, and frailty assessment captures this heterogeneity more effectively. The mechanisms underlying the association between frailty and poor surgical outcomes are multifactorial. Frailty reflects cumulative declines across multiple physiological systems, including reduced cardiovascular and pulmonary reserve, impaired immune function, sarcopenia, and neurocognitive vulnerability. These deficits compromise the ability to mount an adequate stress response to the surgical insult, increasing susceptibility to complications such as pneumonia, acute kidney injury, myocardial infarction, and delirium—all of which were significantly more common in frail patients in our study. The high rate of delirium in frail patients (16.9% vs. 5.6%) is particularly noteworthy, as postoperative delirium is associated with prolonged hospitalization, functional decline, and increased mortality. Sarcopenia, a key component of the frailty phenotype, has also been identified as an independent predictor of adverse postoperative outcomes. The clinical implications of our findings are substantial. First, routine preoperative frailty assessment should be integrated into standard surgical practice. Several validated tools are available for clinical application, including the modified Frailty Index used in our study, the Clinical Frailty Scale, and the Fried Frailty Phenotype. These assessments can be efficiently performed in preoperative clinics and provide actionable information for risk stratification and perioperative planning. Second, frailty status should inform shared decision-making between surgeons, patients, and families. Our finding that frail patients have higher rates of institutional discharge (36.2% vs. 17.0%) and functional decline (36.2% vs. 14.2%) highlights that surgical success extends beyond survival and complication avoidance to encompass functional recovery and quality of life. These outcomes may be more meaningful to elderly patients than traditional surgical endpoints. Surgeons should engage in honest discussions about the risks of functional decline and loss of independence, particularly for frail patients. Third, our findings support the implementation of targeted perioperative interventions for frail elderly patients. Enhanced Recovery After Surgery (ERAS) protocols have demonstrated benefits in elderly populations, including shorter hospital stays, faster functional recovery, and fewer complications. Comprehensive Geriatric Assessment (CGA) has been shown to reduce postoperative delirium and may improve other outcomes. Multidisciplinary approaches involving geriatricians, anesthesiologists, surgeons, nurses, and allied health professionals are essential for optimizing care in this vulnerable population. Prehabilitation—including nutritional optimization, physical conditioning, and cognitive training—holds promise for improving preoperative physiological reserve in frail patients. Fourth, the striking disparity in outcomes between frail and non-frail patients raises important questions about surgical selection. While our study does not suggest that frail patients should be categorically denied surgery, it does argue for careful consideration of the risk–benefit balance. In some cases, especially for nonagenarians and those with severe frailty, nonoperative management may be the more appropriate default approach, with surgery reserved for highly selected cases after thorough geriatric assessment. Several limitations of our study merit acknowledgment. First, the retrospective design introduces potential selection bias and limits our ability to establish causality. Second, frailty assessment was based on the modified Frailty Index derived from administrative data rather than direct physical examination, which may have led to misclassification. Third, the study was conducted exclusively in Chinese hospitals, and findings may not be generalizable to other populations or healthcare settings. Fourth, we did not assess long-term outcomes beyond 30 days, including 1-year mortality and sustained functional recovery. Fifth, we did not capture patient-reported outcome measures, which are increasingly recognized as essential endpoints in geriatric surgical research. Sixth, the relatively small number of events in some subgroup analyses limited statistical power for detecting interactions. Despite these limitations, our study has several strengths. The large sample size, multicenter design, and comprehensive data collection enhance the generalizability and robustness of our findings. The use of standardized outcome definitions (Clavien-Dindo classification) and rigorous statistical methods, including assessment of incremental predictive value (NRI and IDI), strengthens the validity of our conclusions.

In this large multicenter cohort of elderly patients undergoing major elective non-cardiac surgery, frailty was a stronger predictor of adverse postoperative outcomes than chronological age. Frail patients experienced significantly higher rates of major complications, mortality, prolonged hospitalization, readmission, institutional discharge, and functional decline. The addition of frailty assessment to conventional risk models significantly improved predictive accuracy for major postoperative complications.

These findings support the routine integration of frailty assessment into preoperative evaluation for elderly surgical patients. Frailty status should guide risk stratification, inform shared decision-making, and identify patients who may benefit from targeted perioperative interventions. As the global population continues to age, the development and implementation of evidence-based strategies to optimize surgical outcomes in frail elderly patients will become increasingly critical. Future research should focus on prospective validation of frailty assessment tools across diverse populations, evaluation of interventions to modify frailty preoperatively, and incorporation of patient-centered outcomes into surgical quality assessment.

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