ArticleFrontiers in surgery2022
Derivation and validation of a prediction score for postoperative delirium in geriatric patients undergoing hip fracture surgery or hip arthroplasty.
Article in Frontiers in surgery, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The role of diabetes mellitus on delirium onset: a systematic review and meta-analysis.Cardiovascular diabetology · 2025 · on this mapPooled it
- Establishment of a postoperative delirium risk prediction model for elderly hip fracture patients based on machine learning algorithms.BMC geriatrics · 2025Article
- Delirium after Hemiarthroplasty for Neglected Hip Fracture.Hip & pelvis · 2025Article
- Determining the ground truth for the prediction of delirium in adult patients in acute care: a scoping review.JAMIA open · 2025Review
- Delirium on presentation with a hip fracture is associated with adverse outcomes : a multicentre observational study of 18,040 patients using national clinical registry data.The bone & joint journal · 2025Observational
- The Role of Stress Hyperglycemia on Delirium Onset.Journal of clinical medicine · 2025Review
- Validation of the Charlson Comorbidity Index for the prediction of 30-day and 1-year mortality among patients who underwent hip fracture surgery.Perioperative medicine (London, England) · 2024Article
- Prediction models for postoperative delirium in elderly patients with machine-learning algorithms and SHapley Additive exPlanations.Translational psychiatry · 2024Article
- Postoperative delirium in geriatric patients with hip fractures.Frontiers in aging neuroscience · 2022Review
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4 authors.
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Abstract
Introduction: Postoperative delirium is a common complication of patients undergoing hip fracture surgery or arthroplasty and is related to decreased survival time and physical function. In this study, we aim to build and validate a prediction score of postoperative delirium in geriatric patients undergoing hip fracture surgery or hip arthroplasty. Methods: A retrospective cohort of geriatric patients undergoing hip fracture surgery or hip arthroplasty was established. Variables of included patients were collected as candidate predictors of postoperative delirium. The least absolute shrinkage and selection operator (LASSO) regression and logistic regression were used to derive a predictive score for postoperative delirium. The accuracy of the score was evaluated by the area under the curve (AUC) of the receiver operating curve (ROC). We used bootstrapping resamples for model calibration. The prediction score was validated in an extra cohort. Results: There were 1,312 patients in the derivation cohort, and the incidence of postoperative delirium was 14.33%. Of 40 variables, 9 were identified as predictors, including preoperative delirium, cerebrovascular accident (CVA) with the modified Rankin scale, diabetes with a random glucose level, Charlson comorbidity index (CCI), age, application of benzodiazepines in surgery, surgical delay ≥2 days, creatine ≥90 μmol/L, and active smoker. The prediction score achieved a mean AUC of 0.848 in the derivation cohort. In the validation cohort, the mean AUC was 0.833. The prediction model was well-calibrated in the two cohorts. Conclusion: Based on retrospective data, a prediction score for postoperative delirium in geriatric patients undergoing hip fracture surgery or hip arthroplasty was derived and validated. The performance of the scoring system outperformed the models from previous studies. Although the generalization ability of the score needs to be tested in similar populations, the scoring system will enable delirium risk stratification for hip fracture patients and facilitate the development of strategies for delirium prevention.
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