Hip fracture is a significant public health problem, with associated high morbidity and mortality. Orthopedic surgeons are concerned to improve prognosis and stratify mortality risk after hip fracture surgery. This study established a nomogram that combines the Charlson Comorbidity Index (CCI) with specific laboratory parameters to predict mortality risk after hip fracture surgery in geriatrics. Methods: The records of consecutive patients who underwent hip fracture surgery from January 2015 through May 2020 at one medical center were reviewed for perioperative factors and mortality. Patients with age ≥ 70 years who were diagnosed with intertrochanteric or femoral neck fractures were included. Patients who were diagnosed with pathological fracture, received only conservative treatment or lost to follow-up were excluded. A multivariate Cox proportional hazards regression model was used to identify risk factors. A nomogram was established with R software and evaluated using concordance (C)-index, area under receiver operating characteristic (AUC), calibration curves, and decision curve analysis (DCA). Results: In total, 454 patients were included with a mean age of 81.6 years. The mean follow-up and oneyear mortality rate were 37.2 months and 10.4%, respectively. Five identified risk variables for mortality after hip fracture surgery in geriatrics comprised age (HR 1.05, 95% CI 1.01-1.08; P = 0.003), CCI (HR 1.38, 95% CI 1.24-1.54; P = 0.0 0 0), albumin (HR 1.78, 95% CI 1.31-2.43; P = 0.0 0 0), sodium (HR 1.59, 95% CI 1.18-2.15; P = 0.002) and hemoglobin (HR 1.46, 95% CI 1.07-2.00; P = 0.02). A nomogram was proposed and evaluated, showing a C-index of 0.76 ± 0.02. The AUCs for 6-month, 1-year, and 3-year mortality predictions were 0.83, 0.79, and 0.77, respectively. The calibration curve and DCA showed good discrimination and clinical usefulness. Conclusion: This novel nomogram for stratifying the mortality risk after hip fracture surgery in geriatrics incorporated age, CCI, serum albumin, sodium, and hemoglobin. Internal validation indicated that the model has good accuracy and usefulness. This nomogram had improved convenience and precision compared with other models. External validation is warranted to confirm its performance.

Objective: Although several prognostic models have been developed for patients who underwent hip fracture surgery, their preoperative performance was insufficiently validated. We aimed to verify the effectiveness of the Nottingham Hip Fracture Score (NHFS) for predicting postoperative outcomes following hip fracture surgery. Methods:This was a single-center and retrospective analysis. A total of 702 elderly patients with hip fractures (age ≥ 65 years old) who received treatment in our hospital from June 2020 to August 2021 were selected as the research participants. They were divided into the survival group and the death group based on their survival 30 days after surgery. The multivariate logistic regression model was used to identify the independent risk factors for the 30-day mortality after surgery. The NHFS and American Society of Anaesthesiologists (ASA) grades were used to construct these models, and a receiver operating characteristic curve was plotted to assess their diagnostic significance. A correlation analysis was performed between NHFS and length of hospitalization and mobility 3 months after surgery.Results: There were significant differences in the age, albumin level, NHFS, and ASA grade between both groups (p < 0.05). The length of hospitalization in the death group was longer than the survival group (p < 0.05). The perioperative blood transfusion and postoperative ICU transfer rates in the death group were higher than in the survival group (p < 0.05). The death group's incidence of pulmonary infections, urinary tract infections, cardiovascular events, pressure ulcers, stress ulcers with bleeding, and intestinal obstruction was higher than the survival group (p < 0.05). The NHFS and ASA III were independent risk factors for the 30-day mortality after surgery, regardless of age and albumin level (p < 0.05). The area under the curve (AUC) of the NHFS and ASA grade for predicting the 30-day mortality after surgery was 0.791 (95% confidence interval [CI] 0.709-0.873, p < 0.05) and 0.621 (95% CI 0.477-0.764, p > 0.05), respectively. The NHFS positively correlated with hospitalization length and mobility grade 3 months after surgery (p < 0.05). Conclusion:The NHFS demonstrated a better predictive performance than the ASA score for the 30-day mortality after surgery and positively correlated with the hospitalization length and postoperative activity limitation in elderly patients with hip fractures.

Background: Acute kidney injury (AKI), characterized by sudden impairment of kidney function, is an uncommon complication following hip fracture surgery that is associated with increased morbidity and mortality. We constructed a nomogram to stratify patients according to risk of AKI after hip fracture surgery to guide clinicians in the implementation of timely interventions. Methods: Patients who received hip fracture surgery from January 2015 to December 2021 were retrospectively identified and divided into a training set (n=448, surgery from January 2015 to December 2019) and a validation set (n=200, surgery from January 2020 to December 2021). Univariate and multivariate logistic regression were used to identify risk factors for AKI after surgery in the training set. A nomogram was constructed based the risk factors for AKI, and was evaluated by receiver operating characteristic (ROC) analysis, calibration curves, and decision curve analysis (DCA). Results: The mean age was 82.0±6.22 years-old and the prevalence of post-surgical AKI was 13.3%. Age, American Society of Anesthesiologists (ASA) score, the preexistence of chronic kidney disease (CKD), cemented surgery and the decrease of hemoglobin on the first day after surgery were identified as independent risk factors of AKI after hip fracture surgery, and a predictive nomogram was established based on the multivariable model. The predictive nomogram had good discrimination ability (training set: AUC: 0.784, 95% CI: 0.720-0.848; validation set: AUC: 0.804, 95% CI: 0.704-0.903), and showed good validation ability and clinical usefulness based on a calibration plot and decision curve analysis. Conclusion: A nomogram that incorporated five risk factors including age, ASA score, preexisting CKD, cemented surgery and the decrease of hemoglobin on the first day after surgery had good predictive performance and discrimination. Use of our results for early stratification and intervention has the potential to improve the outcomes of patients receiving hip fracture surgery. Future large, multicenter cohorts are needed to verify the model's performance.

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