Aims. To develop prediction models using machine-learning (ML) algorithms for 90-day and one-year mortality prediction in femoral neck fracture (FNF) patients aged 50 years or older based on the Hip fracture Evaluation with Alternatives of Total Hip arthroplasty versus Hemiarthroplasty (HEALTH) and Fixation using Alternative Implants for the Treatment of Hip fractures (FAITH) trials. Methods. This study included 2,388 patients from the HEALTH and FAITH trials, with 90-day and one-year mortality proportions of 3.0% (71/2,388) and 6.4% (153/2,388), respectively. The mean age was 75.9 years (SD 10.8) and 65.9% of patients (1,574/2,388) were female. The algorithms included patient and injury characteristics. Six algorithms were developed, internally validated and evaluated across discrimination (c-statistic; discriminative ability between those with risk of mortality and those without), calibration (observed outcome compared to the predicted probability), and the Brier score (composite of discrimination and calibration). Results. The developed algorithms distinguished between patients at high and low risk for 90-day and one-year mortality. The penalized logistic regression algorithm had the best performance metrics for both 90-day (c-statistic 0.80, calibration slope 0.95, calibration intercept -0.06, and Brier score 0.039) and one-year (c-statistic 0.76, calibration slope 0.86, calibration intercept -0.20, and Brier score 0.074) mortality prediction in the hold-out set. Conclusion. Using high-quality data, the ML-based prediction models accurately predicted 90-day and one-year mortality in patients aged 50 years or older with a FNF. The final models must be externally validated to assess generalizability to other populations, and prospectively evaluated in the process of shared decision-making. Cite this article: Bone Jt Open 2023;4(3):168–181

Aims. There are reports of a marked increase in perioperative mortality in patients admitted to hospital with a fractured hip during the COVID-19 pandemic in the UK, USA, Spain, and Italy. Our study aims to describe the risk of mortality among patients with a fractured neck of femur in England during the early stages of the COVID-19 pandemic. Methods. We completed a multicentre cohort study across ten hospitals in England. Data were collected from 1 March 2020 to 6 April 2020, during which period the World Health Organization (WHO) declared COVID-19 to be a pandemic. Patients ≥ 60 years of age admitted with hip fracture and a minimum follow-up of 30 days were included for analysis. Primary outcome of interest was mortality at 30 days post-surgery or postadmission in nonoperative patients. Secondary outcomes included length of hospital stay and discharge destination. Results. In total, 404 patients were included for final analysis with a COVID-19 diagnosis being made in 114 (28.2%) patients. Overall, 30-day mortality stood at 14.4% (n = 58). The COVID-19 cohort experienced a mortality rate of 32.5% (37/114) compared to 7.2% (21/290) in the non-COVID cohort (p < 0.001). In adjusted analysis, 30-day mortality was greatest in patients who were confirmed to have COVID-19 (odds ratio (OR) 5.64, 95% confidence interval (CI) 2.95 to 10.80; p < 0.001) with an adjusted excess risk of 20%, male sex (OR 2.69, 95% CI 1.37 to 5.29; p = 0.004) and in patients with ≥ two comorbidities (OR 4.68, CI 1.5 to 14.61; p = 0.008). Length of stay was also extended in the COVID-19 cohort, on average spending 17.6 days as an inpatient versus 12.04 days in the non-COVID-19 group (p < 0.001). Conclusion. This study demonstrates that patients who sustain a neck of femur fracture in combination with COVID-19 diagnosis have a significantly higher risk of mortality than would be normally expected. Cite this article: Bone Joint Open 2020;1-11:697–705