دورية أكاديمية
Machine Learning to Predict Discharge Destination After Total Knee Arthroplasty and Total Hip Arthroplasty.
| العنوان: | Machine Learning to Predict Discharge Destination After Total Knee Arthroplasty and Total Hip Arthroplasty. |
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| المؤلفون: | Booth GJ; Department of Anesthesiology and Pain Medicine, Naval Medical Center Portsmouth, Portsmouth, Virginia; Naval Biotechnology Group, Naval Medical Center Portsmouth, Portsmouth, Virginia; Uniformed Services University of Health Sciences, Bethesda, Maryland., Cole J; Department of Anesthesiology and Pain Medicine, Naval Medical Center Portsmouth, Portsmouth, Virginia; Naval Biotechnology Group, Naval Medical Center Portsmouth, Portsmouth, Virginia; Uniformed Services University of Health Sciences, Bethesda, Maryland., Geiger P; Department of Anesthesiology and Pain Medicine, Naval Medical Center Portsmouth, Portsmouth, Virginia; Naval Biotechnology Group, Naval Medical Center Portsmouth, Portsmouth, Virginia; Uniformed Services University of Health Sciences, Bethesda, Maryland., Balazs GC; Uniformed Services University of Health Sciences, Bethesda, Maryland; Department of Orthopedic Surgery, Naval Medical Center Portsmouth, Portsmouth, Virginia., Hughey S; Department of Anesthesiology and Pain Medicine, Naval Medical Center Portsmouth, Portsmouth, Virginia; Naval Biotechnology Group, Naval Medical Center Portsmouth, Portsmouth, Virginia; Uniformed Services University of Health Sciences, Bethesda, Maryland., Nepa N; Uniformed Services University of Health Sciences, Bethesda, Maryland., Goldman A; Uniformed Services University of Health Sciences, Bethesda, Maryland; Department of Orthopedic Surgery, Naval Medical Center Portsmouth, Portsmouth, Virginia. |
| المصدر: | Journal of surgical orthopaedic advances [J Surg Orthop Adv] 2023 Winter; Vol. 32 (4), pp. 252-258. |
| نوع المنشور: | Journal Article |
| اللغة: | English |
| بيانات الدورية: | Publisher: Data Trace Pub. Co Country of Publication: United States NLM ID: 101197881 Publication Model: Print Cited Medium: Print ISSN: 1548-825X (Print) Linking ISSN: 1548825X NLM ISO Abbreviation: J Surg Orthop Adv Subsets: MEDLINE |
| أسماء مطبوعة: | Original Publication: Towson, MD : Data Trace Pub. Co., c2003- |
| مواضيع طبية MeSH: | Arthroplasty, Replacement, Knee* , Arthroplasty, Replacement, Hip*, Humans ; Patient Discharge ; Postoperative Complications ; Machine Learning |
| مستخلص: | Discharge destination impacts costs and perioperative planning for primary total knee (TKA) or hip arthroplasty (THA). The purpose of this study was to create a tool to predict discharge destination in contemporary patients. Models were developed using more than 400,000 patients from the National Surgical Quality Improvement Program database. Models were compared with a previously published model using area under the receiver operating characteristic curve (AUC) and decision curve analysis (DCA). AUC on patients with TKA was 0.729 (95% confidence interval [CI]: 0.719 to 0.738) and 0.688 (95% CI: 0.678 to 0.697) using the new and previous models, respectively. AUC on patients with THA was 0.768 (95% CI: 0.758 to 0.778) and 0.726 (95% CI: 0.714 to 0.737) using the new and previous models, respectively. DCA showed substantially improved net clinical benefit. The new models were integrated into a web-based application. This tool enhances clinical decision making for predicting discharge destination following primary TKA and THA. (Journal of Surgical Orthopaedic Advances 32(4):252-258, 2023). |
| تواريخ الأحداث: | Date Created: 20240329 Date Completed: 20240401 Latest Revision: 20240401 |
| رمز التحديث: | 20240401 |
| PMID: | 38551234 |
| قاعدة البيانات: | MEDLINE |
| تدمد: | 1548-825X |
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