Background: Frailty is increasingly being recognized as a risk factor for adverse outcomes in older surgical patients undergoing surgery. We investigated the association between frailty and intraoperative complications using multiple frailty assessment tools in older patients undergoing elective intermediate- to high-risk non-cardiac surgery. Methods: This retrospective cohort study included 637 older patients scheduled for elective non-cardiac surgery. Frailty was assessed using the Clinical Frailty Scale (CFS), FRAIL scale, and modified Frailty Index-11 (mFI-11). The predictive ability of frailty tools was analyzed and compared using the area under the receiver operating characteristic curve (AUC). Results: Frailty was significantly associated with higher intraoperative complication rates (FRAIL scale: p = 0.01; mFI-11: p = 0.046). Patients considered frail using the mFI-11 were more likely to have unplanned intensive care unit admissions (p < 0.001). Those classified as frail by the FRAIL scale and mFI-11 had significantly higher rates of vasopressor/inotrope use (p = 0.001 and p = 0.005, respectively) and mechanical ventilation (p = 0.033 and p = 0.007, respectively). In the univariate analysis, frailty measured using the FRAIL scale was significantly associated with intraoperative complications (odds ratio [OR], 2.41; 95% confidence interval [CI]: 1.33–4.38; p = 0.004); this association was not significant in the multivariate analysis (adjusted OR, 1.69; 95% CI: 0.83–3.43; p = 0.148; AUC = 0.550). Atrial fibrillation, hemoglobin levels, anesthesia type, and surgical subspecialty were stronger predictors of intraoperative complications. Conclusions: Frailty assessments demonstrate the limited predictive ability for intraoperative complications. Specific comorbidities, surgical techniques, and anesthesia types play more critical roles. Comprehensive preoperative evaluations integrating frailty with broader risk stratification methods are necessary to enhance patient outcomes and ensure safety.

Background: Frailty is a significant predictor of adverse outcomes in older surgical patients. this study, we aimed to evaluate the feasibility and predictive ability of the Clinical Frailty Scale (CFS), Modified Frailty Index-11 (mFI-11), and FRAIL scale for postoperative complications in older Thai patients who underwent intermediate- to high-risk non-cardiac surgery. Methods: This prospective cohort study included 637 older patients (aged ≥ 60 years) scheduled for intermediate- to high-risk elective non-cardiac surgery. Frailty was assessed preoperatively using the CFS, mFI-11, and FRAIL scale. Postoperative complications were defined as Clavien–Dindo classification ≥ 2. Predictive performance was analyzed using logistic regression and the area under the receiver operating characteristic curve (AUC). Results: The mean age of participants was 70.5 years (standard deviation 7.68), and 48% were male. Frailty was significantly associated with higher rates of postoperative complications across all tools: CFS (44.9% vs. 22.2%), mFI-11 (57.8% vs. 26.9%), and FRAIL scale (56.3% vs. 26.0%) (all p < 0.001). In multivariable logistic regression, the CFS was the only independent predictor (odds ratio 2.39, 95% confidence interval [CI]: 1.42–4.00, p < 0.001). Area under the curve (AUC) values were 0.635 (95% CI: 0.5902–0.6794) (mFI-11), 0.632 (95% CI: 0.5881–0.6756) (FRAIL scale), and 0.619 (95% CI: 0.5742–0.6637) (CFS), compared with 0.657 (95% CI: 0.6152–0.6988) of the American Society of Anesthesiologists (ASA) classification. Combining frailty tools with ASA improved predictive accuracy, with CFS + ASA exhibiting the highest AUC (0.704, 95% CI: 0.660–0.748). Conclusion: Frailty assessed with the CFS, mFI-11, and FRAIL scale was associated with postoperative complications, with the CFS demonstrating the strongest independent predictive value. Incorporating frailty screening into preoperative evaluation, especially combined with ASA classification, can improve risk stratification and perioperative care. Trial registration: TCTR20210706002.

Background: To highlight the risk assessment tool associated with postoperative cardiopulmonary complications of Clavien–Dindo (CD) ≥ II in elderly patients who underwent lung cancer surgery. Methods: In patients ≥ 60 years admitted during 2020–2023 and having undergone lung cancer surgery, postoperative cardiopulmonary complications were examined using the CD classification as groups (CD grade I versus ≥ II), and the risk factors were analyzed using logistic regression and receiver operating characteristic (ROC) curves. Results: Of the 239 elderly patients, 29.3% had postoperative complications (CD ≥ II). Subgroup analysis revealed that patients aged ≥70 years had a higher rate of postoperative complications compared to those aged 60–69 years, however, this relationship was not statistically significant in the multivariable model (OR: 2.03, 95% CI: 0.95–4.36, p = 0.068). The CD grade ≥ II group had longer surgical time (p = 0.002), greater postoperative pulmonary complications (p < 0.001), and longer length of hospital stay (p < 0.001); CD grade ≥ II was more likely in patients with older age (odds ratio [OR]: 1.08, 95% confidence interval [CI]: 1.02–1.15, p = 0.011), COPD (OR: 4.41, 95% CI: 1.55–13.44, p = 0.005) and smoking history (OR: 2.85, 95% CI: 1.12–7.24, p = 0.028), having undergone pneumonectomy (OR: 14.89, 95% CI: 1.71–334.9, p = 0.045), and who converted to open thoracotomy (OR: 16.33, 95% CI: 2.13–169.71, p = 0.007). The area under the ROC curve was 0.81. Conclusions: Older age (≥70 years) is associated with higher rates of postoperative complications (CD classification ≥ II) but is not an independent predictor when adjusting for other factors. Comorbidities such as COPD and surgical factors, including pneumonectomy and conversion to thoracotomy, are significant contributors. These findings emphasize the need for comprehensive, multifactorial risk assessments to guide perioperative management and improve outcomes in elderly lung cancer patients.

Background: to examine factors associated with cardiac evaluation and associations between cardiac test abnormalities and clinical outcomes in patients with acute brain injury (ABI) due to acute ischemic stroke (AIS), spontaneous subarachnoid hemorrhage (SAH), spontaneous intracerebral hemorrhage (sICH), and traumatic brain injury (TBI) requiring neurocritical care. Methods: In a cohort of patients ≥18 years, we examined the utilization of electrocardiography (ECG), beta-natriuretic peptide (BNP), cardiac troponin (cTnI), and transthoracic echocardiography (TTE). We investigated the association between cTnI, BNP, sex-adjusted prolonged QTc interval, low ejection fraction (EF < 40%), all-cause mortality, death by neurologic criteria (DNC), transition to comfort measures only (CMO), and hospital discharge to home using univariable and multivariable analysis (adjusted for age, sex, race/ethnicity, insurance carrier, pre-admission cardiac disorder, ABI type, admission Glasgow Coma Scale Score, mechanical ventilation, and intracranial pressure [ICP] monitoring). Results: The final sample comprised 11,822 patients: AIS (46.7%), sICH (18.5%), SAH (14.8%), and TBI (20.0%). A total of 63% (n = 7472) received cardiac workup, which increased over nine years (p < 0.001). A cardiac investigation was associated with increased age, male sex (aOR 1.16 [1.07, 1.27]), non-white ethnicity (aOR), non-commercial insurance (aOR 1.21 [1.09, 1.33]), pre-admission cardiac disorder (aOR 1.21 [1.09, 1.34]), mechanical ventilation (aOR1.78 [1.57, 2.02]) and ICP monitoring (aOR1.68 [1.49, 1.89]). Compared to AIS, sICH (aOR 0.25 [0.22, 0.29]), SAH (aOR 0.36 [0.30, 0.43]), and TBI (aOR 0.19 [0.17, 0.24]) patients were less likely to receive cardiac investigation. Patients with troponin 25th–50th quartile (aOR 1.65 [1.10–2.47]), troponin 50th–75th quartile (aOR 1.79 [1.22–2.63]), troponin >75th quartile (aOR 2.18 [1.49–3.17]), BNP 50th-75th quartile (aOR 2.86 [1.28–6.40]), BNP >75th quartile (aOR 4.54 [2.09–9.85]), prolonged QTc (aOR 3.41 [2.28; 5.30]), and EF < 40% (aOR 2.47 [1.07; 5.14]) were more likely to be DNC. Patients with troponin 50th–75th quartile (aOR 1.77 [1.14–2.73]), troponin >75th quartile (aOR 1.81 [1.18–2.78]), and prolonged QTc (aOR 1.71 [1.39; 2.12]) were more likely to be associated with a transition to CMO. Patients with prolonged QTc (aOR 0.66 [0.58; 0.76]) were less likely to be discharged home. Conclusions: This large, single-center study demonstrates low rates of cardiac evaluations in TBI, SAH, and sICH compared to AIS. However, there are strong associations between electrocardiography, biomarkers of cardiac injury and heart failure, and echocardiography findings on clinical outcomes in patients with ABI. Findings need validation in a multicenter cohort.

Introduction: Thirty-day mortality remains a critical indicator of perioperative safety and quality of care in patients undergoing non-cardiac surgery. Identifying predictive factors for 30-day mortality is critical for crisis mitigation and improving patient outcomes. This study aimed to identify key predictors of 30-day mortality in non-cardiac surgery patients and develop a predictive model to aid clinical decision-making. Methods: This retrospective observational study analyzed data from patients aged ≥18 years who underwent non-cardiac surgery at a tertiary care hospital between January and August 2022. Data on demographics, comorbidities, intraoperative variables, and postoperative complications were collected. Multivariate logistic regression identified independent predictors of 30-day mortality, and a nomogram was constructed to facilitate individualized risk assessment. Results: Among 7,528 patients, 76 (1.0%) died within 30 days. Independent predictors of mortality included preoperative ventilatory support (odds ratio [OR] 8.76; 95% confidence interval [CI]: 3.58–21.42; p < 0.001), postoperative sepsis (OR 5.86; 95% CI: 2.23–15.37; p < 0.001), coma (OR 18.56; 95% CI: 6.81–50.55; p < 0.001), myocardial infarction (OR 26.35; 95% CI: 4.46–155.63; p < 0.001), and cardiac arrest (OR 57.9; 95% CI: 18.22–184.05; p < 0.001). The nomogram demonstrated good calibration at lower risk levels, with slight overestimation at higher probabilities. The area under the receiver operating characteristic curve indicated excellent discrimination. Discussion: The developed nomogram serves as a useful tool for perioperative risk stratification in non-cardiac surgery. Incorporating both preoperative and postoperative factors, aids in early identification of high-risk patients and supports targeted clinical interventions. External validation and refinement of the model are recommended for broader applicability.