Key result
Clinical Frailty Scale predicts serious in-hospital complications as accurately as ACS NSQIP but is faster.
Why the study?
With major lower limb orthopaedic surgery increasingly performed in older, comorbid patients, accurate risk prediction is needed to guide perioperative management and shared decision-making.
How do the Clinical Frailty Scale, Charlson Comorbidity Index, and ACS NSQIP Surgical Risk Calculator compare in predicting complications following major lower limb orthopaedic surgery?
Observational (n=302)
No
How do the Clinical Frailty Scale, Charlson Comorbidity Index, and ACS NSQIP Surgical Risk Calculator compare in predicting complications following major lower limb orthopaedic surgery?
Effect estimate: AUC 0.77 (95% CI 0.71-0.83)
The Clinical Frailty Scale and ACS NSQIP Calculator demonstrated similar predictive performance for serious complications following major lower limb orthopaedic surgery, but the CFS was significantly faster to administer.
Supports rapid frailty screening in surgical patients; leaves open prospective validation for outcome impact.
BACKGROUND: With major lower limb orthopaedic surgery performed in increasingly older and comorbid patients, accurate risk prediction is essential to guide perioperative management and shared decision-making. AIMS: To compare the Clinical Frailty Scale (CFS), Charlson Comorbidity Index (CCI) and the American College of Surgeons National Surgical Quality Improvement Program Surgical Risk Calculator (ACS NSQIP Calculator) in predicting complications following major lower limb orthopaedic surgery. METHODS: We conducted an audit assessing the clinical utility of the CFS, CCI and ACS NSQIP Calculator at an Australian tertiary hospital (2023-2024). Scores were calculated retrospectively using admission documentation, and complications were identified prospectively. RESULTS: We recruited 302 patients with a mean age of 75.1 ± 12.7 years. Patients underwent surgery for hip fracture (n = 100), elective total knee (n = 103) and hip (n = 69) arthroplasty and other indications (n = 30). During index hospitalisation, 27.5% (n = 83) experienced a serious complication (Clavien-Dindo Grade ≥ II). All tools demonstrated moderate discrimination for serious in-hospital complications; the CFS, CCI and ACS NSQIP Calculator had area under the receiver operating characteristic curves of 0.77 (95% confidence interval (CI) 0.71-0.83), 0.71 (95% CI 0.64-0.77) and 0.76 (95% CI 0.70-0.82) respectively. The CFS was the fastest tool to administer, and the ACS NSQIP Calculator was the most time-consuming (median time 9.5 s (interquartile range (IQR) 7-13) vs 98.5 s (IQR 73-165), P < 0.001). CONCLUSION: The CFS and ACS NSQIP Calculator demonstrated similar predictive performance in this cohort. Given its faster administration, the CFS may represent a practical tool for routine perioperative risk stratification, though prospective validation is required to confirm performance in real-time clinical workflows.
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Yao et al. (2026) conducted an observational in Major lower limb orthopaedic surgery (n=302). Clinical Frailty Scale (CFS) vs. Charlson Comorbidity Index (CCI) and ACS NSQIP Calculator was evaluated on Serious in-hospital complications (Clavien-Dindo Grade ≥ II) (AUC 0.77, 95% CI 0.71-0.83). The Clinical Frailty Scale predicted serious in-hospital complications with moderate discrimination (AUC 0.77; 95% CI 0.71-0.83), similar to the ACS NSQIP Calculator, but was faster to administer.
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