ArticleArthroplasty today2020
Risk Factors for Readmission After Knee Arthroplasty Based on Predictive Models: A Systematic Review.
Article in Arthroplasty today, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 15 citations in OpenAlex.
- Increased 30-Day Readmission Rates in Total Knee Arthroplasty Patients Using Hypoallergenic Implants.Journal of the American Academy of Orthopaedic Surgeons. Global research & reviews · 2026Article
- Comparing prediction accuracy for 30-day readmission following primary total knee arthroplasty: the ACS-NSQIP risk calculator versus a novel artificial neural network model.Knee surgery & related research · 2025Article
- Predicting 30-day unplanned hospital readmission after revision total knee arthroplasty: machine learning model analysis of a national patient cohort.Medical & biological engineering & computing · 2024Article
- Delta hemoglobin cutoffs do not predict readmission in patients undergoing primary simultaneous bilateral total hip or knee arthroplasty: A retrospective cohort study.Journal of clinical orthopaedics and trauma · 2024Article
- Predicting 30-day readmission following total knee arthroplasty using machine learning and clinical expertise applied to clinical administrative and research registry data in an Australian cohort.Arthroplasty (London, England) · 2023Article
- Established and Novel Risk Factors for 30-Day Readmission Following Total Knee Arthroplasty: A Modified Delphi and Focus Group Study to Identify Clinically Important Predictors.Journal of clinical medicine · 2023Article
- Predictive Models for Clinical Outcomes in Total Knee Arthroplasty: A Systematic Analysis.Arthroplasty today · 2021Article
Corrections and comments
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Authors and funding
6 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAn increase in the aging yet active US population will continue to make total knee arthroplasty (TKA) procedures routine in the coming decades. For such joint procedures, the Centers for Medicare and Medicaid Services introduced programs such as the Comprehensive Care for Joint Replacement to emphasize accountable and efficient transitions of care. Accordingly, many studies have proposed models using risk factors for predicting readmissions after the procedure. We performed a systematic review of TKA literature to identify such models and risk factors therein using a reliable appraisal tool for their quality assessment.
methodsFive databases were searched to identify studies that examined correlations between post-TKA readmission and risk factors using multivariate models. We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analysis methodology and Transparent Reporting of a multivariate prediction model for Individual Prognosis Or Diagnosis criteria established for quality assessment of prognostic studies.
resultsOf 29 models in the final selection, 6 models reported performance using a C-statistic, ranging from 0.51 to 0.76, and 2 studies used a validation cohort for assessment. The average 30-day and 90-day readmission rates across the studies were 5.33% and 7.12%, respectively. Three new significant risk factors were discovered.
conclusionsCurrent models for TKA readmissions lack in performance measurement and reporting when assessed with established criteria. In addition to using new techniques for better performance, work is needed to build models that follow the systematic process of calibration, external validation, and reporting for pursuing their deployment in clinical settings.
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