A predictive tool incorporating frailty scores for perioperative risk assessment in patients with spinal metastasis: a national retrospective cohort study.

Frailty and an Inflammation-Nutrition Composite for Predicting Postoperative Outcomes in Older Patients Undergoing Endometrial Cancer Surgery

Background Frailty and systemic inflammation/immune–protein reserve may drive adverse outcomes after endometrial cancer (EC) surgery in older patients, but their incremental predictive value is unclear. Methods We analyzed a retrospective cohort of women ≥65 years undergoing primary EC surgery between January 2016 and December 2024. Frailty was assessed using mFI‑5. Inflammation–nutrition status (INS) was derived from routine preoperative laboratory tests as exploratory composite. The primary endpoint was 30‑day severe complications (Clavien–Dindo III–V), and the secondary endpoint was 90‑day unplanned readmission to the index hospital. One‑year non–endometrial cancer (non‑EC) death was exploratory with EC death as a competing event. Logistic regression and Fine–Gray models were fitted. Incremental prediction versus a prespecified baseline perioperative clinical model was evaluated with bootstrap optimism‑corrected discrimination, calibration, and decision‑curve analysis. Results Severe complications occurred in 62 (7.1%) and readmission in 71 (8.1%). One‑year non‑EC and EC deaths were 28 (3.2%) and 19 (2.2%), respectively. mFI‑5 and INS predicted severe complications (OR per 1‑point mFI‑5 1.43 [95% CI 1.22–1.67]; OR per 1‑SD INS 1.34 [1.15–1.55]) and readmission (OR 1.28 [1.10–1.50]; OR 1.22 [1.05–1.41]). For non‑EC death, mFI‑5 (SHR 1.52 [1.23–1.88]) and INS (SHR 1.37 [1.11–1.69]) were significant. Adding mFI‑5+INS improved discrimination (AUC 0.69 to 0.77 for complications; 0.63 to 0.70 for readmission) and the time-dependent C-index for the exploratory competing-risk endpoint (0.66 to 0.73), with acceptable calibration. Decision-curve findings were descriptive rather than definitive. Conclusion Combining frailty with an objective inflammation–nutrition risk composite modestly improved internal model performance for 30-day severe complications and 90-day readmission in older EC patients, and 1-year non-EC death analysis remains exploratory. These findings should be interpreted as perioperative rather than purely preoperative prediction, and decision thresholds require external validation before protocolized use.

Benchmarking risk prediction tools in spine surgery: a national registry analysis of albumin, frailty, and surgical calculators.

OBJECTIVE Preoperative risk-stratification tools, including frailty, nutritional, and surgical risk metrics, are used to predict complications after spine surgery. The relative performance of these tools across complication types and surgical subgroups is not well characterized. This study aimed to compare the predictive performance of 5 risk metrics, American College of Surgeons Surgical Risk Calculator (ACS SRC), serum albumin, Risk Analysis Index (RAI), modified 5-item frailty index (mFI-5), and Geriatric Nutritional Risk Index (GNRI), for perioperative complications. METHODS The authors analyzed 362,145 adult spine surgery patients from the American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) from 2017 to 2022. Adjusted odds ratios were estimated via multivariable logistic regression, controlling for age, sex, urgency, and procedure type (defined by Current Procedural Terminology [CPT] codes). Subgroup analyses were stratified by ICD-10 diagnosis category, including degenerative disease, tumor, trauma, infection, and spinal deformity. Discrimination for predicting complications was assessed using C-statistics and DeLong's test. RESULTS Across all endpoints, ACS SRC had the best predictive accuracy: mortality C-statistic (95% CI) 0.908 (0.900-0.916), Clavien-Dindo grade IV (CD-IV) 0.823 (0.816-0.830), and major complications 0.749 (0.745-0.752). Serum albumin, despite being a single laboratory value, ranked second with mortality C-statistic (95% CI) 0.820 (0.807-0.833), CD-IV 0.734, and major complications 0.682 and showed strong discrimination for infectious complications (e.g., sepsis, septic shock, surgical site infection, and urinary tract infection), as well as for hospital length of stay and nonhome discharge. Compared to frailty-based metrics, albumin showed significantly better predictive value (p < 0.001 for pairwise comparisons) and maintained its advantages across all subgroups, including high-risk groups such as infection, trauma, and tumor cases. RAI provided moderate mortality prediction (C-statistic 0.807) and was most effective for predicting cardiovascular events, while both GNRI (0.753) and mFI-5 (0.647) were less consistent and demonstrated weaker associations with adverse outcomes. Multivariable regression confirmed that lower preoperative albumin and higher ACS SRC predictions were robust, independent predictors of increased risk for major complications, CD-IV events, and mortality. These performance patterns remained stable across surgical indications and in subgroup analyses. CONCLUSIONS ACS SRC remains among the comprehensive tools for risk stratification in spine surgery. Serum albumin offers strong, consistent predictive value, especially for infectious, respiratory, and life-threatening complications, and may be a valuable alternative when calculator inputs are incomplete.

Modified 5-Item Frailty Index Is Associated with Postoperative Delirium but Not Survival in Patients Undergoing Surgery for Oral Squamous Cell Carcinoma

Background/Objectives: Frailty is increasingly recognized as a clinically relevant marker of reduced physiological reserve in surgical oncology. The modified 5-item frailty index (mFI-5) is simple and practical, but its clinical significance in oral squamous cell carcinoma (OSCC) remains incompletely defined. This study evaluated the association between mFI-5-defined frailty and postoperative complications, especially postoperative delirium, as well as survival outcomes in patients undergoing surgery for OSCC. Methods: We retrospectively analyzed 127 patients who underwent surgical resection for OSCC with postoperative high care unit (HCU) management between 2013 and 2021. Frailty was defined as an mFI-5 score of ≥2. Clinical characteristics, postoperative outcomes, HCU stay, length of hospital stay, overall survival (OS), and disease-free survival (DFS) were compared between frail and non-frail groups. Univariable logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for postoperative complications. An exploratory multivariable logistic regression analysis for postoperative delirium was performed using age ≥65 years and sex as covariates. Delirium was retrospectively assessed from clinical documentation considered consistent with DSM-5 criteria. Results: Twenty-one patients (16.5%) were classified as frail. Postoperative delirium occurred more frequently in frail patients than in non-frail patients (42.9% vs. 19.8%; p = 0.023). In a multivariable logistic regression model adjusted for age ≥65 years and sex, mFI-5-defined frailty was significantly associated with postoperative delirium (adjusted OR, 3.07; 95% CI, 1.08–8.60; p = 0.035). No significant association was observed for pneumonia, surgical site infection, or free-flap reoperation. Frailty was not significantly associated with HCU stay, length of hospital stay, OS, or DFS. Conclusions: mFI-5-defined frailty was associated with postoperative delirium but not with survival outcomes in this OSCC cohort. Because this retrospective study was limited by sample size, comorbidity-driven mFI-5 scoring, non-standardized delirium screening, and potential residual confounding, mFI-5 should be interpreted as a convenient screening marker rather than a stand-alone predictor. Comprehensive perioperative assessment incorporating frailty, nutrition, sarcopenia, cognition, tumor burden, and treatment-related factors may better identify patients at risk.

Machine learning-based prediction of perioperative complications in spine surgery: a large-scale model development and validation study.

Evaluating the impact of frailty in older adults on functional outcomes post-mechanical thrombectomy: a multicentre study incorporating traditional and machine learning methods.

Prognostic value of the 5-Item Modified Frailty Index in elderly patients undergoing free flap reconstruction for head and neck cancer.

OBJECTIVE Frailty is a recognized risk factor for poor surgical outcomes, particularly in the elderly. This study evaluates the predictive value of the 5-item Modified Frailty Index in patients aged 70 and older undergoing head and neck cancer resection with microvascular free flap reconstruction. STUDY DESIGN Retrospective cohort study. SETTING Tertiary academic medical center. METHODS Patients aged ≥ 70 years old who underwent oncologic resection and free flap reconstruction from 2014 to 2022 were included. Patients were stratified by 5-item Modified Frailty Index score into non-frail (0), mildly frail (1), and moderately to severely frail (≥2). Primary outcomes included 90-day mortality, 30-day complications, readmission, and return to the operating room. Multivariable logistic regression was used to control potential confounders. RESULTS A total of 211 patients were included. Patients with 5-item Modified Frailty Index scores ≥ 2 had significantly higher 90-day mortality compared to less frail patients (p = 0.031), and they were more frequently discharged to a facility rather than home. While not statistically significant, complication and readmission rates were higher in frail patients. Multivariable analysis showed that patients with 5-item Modified Frailty Index ≥ 2 had increased odds of experiencing complications (OR 2.44, 95 % CI 1.06-5.91)and mortality (OR 1.17, 95 % CI 0.36-4.59). CONCLUSION The 5-item Modified Frailty Index is a simple and clinically useful tool for identifying older head and neck cancer patients at increased risk of adverse outcomes following major surgery. Its incorporation into preoperative risk assessment may improve surgical decision-making and perioperative planning by better stratifying risk and guiding resource allocation.