Literature DB >> 30930154

Predicting Inpatient Status After Primary Total Knee Arthroplasty in Medicare-Aged Patients.

Christian Gronbeck1, Mark P Cote2, Mohamad J Halawi2.   

Abstract

BACKGROUND: The Centers for Medicare and Medicaid Services (CMS) removed total knee arthroplasty (TKA) from its inpatient only (IPO) list as of January 1, 2018. The purpose of this study was to establish a risk-stratifying nomogram to aid in determining the need for inpatient admission among Medicare-aged patients undergoing primary TKA.
METHODS: The American College of Surgeons National Surgical Quality Improvement Program database was queried to identify all patients aged ≥65 years who underwent primary TKA between 2006 and 2015. The primary outcome measure was inpatient admission, as defined by hospital length of stay longer than 2 days. Multiple demographic, comorbid, and perioperative variables were incorporated in a multivariate logistic regression model to yield a risk stratification nomogram.
RESULTS: Sixty-one thousand two hundred eighty-four inpatient and 26,066 outpatient admissions were analyzed. Age >80 years (odds ratio [OR] = 2.27, P < .0001, 95% confidence interval [CI] = 2.13-2.42), simultaneous bilateral TKA (OR = 2.02, P < .0001, 95% CI = 1.77-2.30), dependent functional status (OR = 1.95, P < .0001, 95% CI = 1.62-2.35), metastatic cancer (OR = 1.91, P = .055, 95% CI = 0.99-3.73), and female gender (OR = 1.76, P < .0001, 95% CI = 1.70-1.82) were the greatest determinants of inpatient stay. The resulting predictive model demonstrated acceptable discrimination and excellent calibration.
CONCLUSION: Our model enabled a reliable and straightforward identification of the most suitable candidates for inpatient admission in Medicare aged-patients undergoing primary TKA. Larger multicenter studies are necessary to externally validate the proposed predictive nomogram.
Copyright © 2019 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Medicare; admission status; inpatient; outpatient; predictive nomogram; total knee arthroplasty

Mesh:

Year:  2019        PMID: 30930154     DOI: 10.1016/j.arth.2019.03.009

Source DB:  PubMed          Journal:  J Arthroplasty        ISSN: 0883-5403            Impact factor:   4.757


  8 in total

1.  A clinical model for predicting knee replacement in early-stage knee osteoarthritis: data from osteoarthritis initiative.

Authors:  Rongjie Wu; Yuanchen Ma; Yuhui Yang; Mengyuan Li; Qiujian Zheng; Guangtao Fu
Journal:  Clin Rheumatol       Date:  2021-11-21       Impact factor: 2.980

2.  Financial impact of removal of total knee arthroplasty from the inpatient-only list for a physician-owned BPCI program.

Authors:  James M Rizkalla; Aamir A Bhimani; Kurt J Kitziger; Paul C Peters; Richard D Schubert; Brian P Gladnick
Journal:  J Orthop       Date:  2020-01-30

3.  Factors associated with the length of stay in total knee arthroplasty patients with the enhanced recovery after surgery model.

Authors:  Guoqing Li; Jian Weng; Chang Xu; Deli Wang; Ao Xiong; Hui Zeng
Journal:  J Orthop Surg Res       Date:  2019-11-06       Impact factor: 2.359

4.  Preoperative Predictors of Same-Day Discharge After Total Knee Arthroplasty.

Authors:  Justin J Turcotte; Nandakumar Menon; McKayla E Kelly; Jennifer J Grover; Paul J King; James H MacDonald
Journal:  Arthroplast Today       Date:  2021-02-01

Review 5.  Artificial intelligence in knee arthroplasty: current concept of the available clinical applications.

Authors:  Cécile Batailler; Jobe Shatrov; Elliot Sappey-Marinier; Elvire Servien; Sébastien Parratte; Sébastien Lustig
Journal:  Arthroplasty       Date:  2022-05-02

6.  Predictors of extended length of stay after unicompartmental knee arthroplasty.

Authors:  B M Sephton; P Bakhshayesh; T C Edwards; A Ali; V Kumar Singh; D Nathwani
Journal:  J Clin Orthop Trauma       Date:  2019-09-11

7.  Medicare coverage is an independent predictor of prolonged hospitalization after primary total joint arthroplasty.

Authors:  Mohamad J Halawi; Andrew D Stone; Christian Gronbeck; Lawrence Savoy; Mark P Cote
Journal:  Arthroplast Today       Date:  2019-10-18

8.  A Novel Machine Learning Predictive Tool Assessing Outpatient or Inpatient Designation for Medicare Patients Undergoing Total Knee Arthroplasty.

Authors:  David Kugelman; Shengnan Huang; Greg Teo; Michael Doran; Vivek Singh; Daniel Buchalter; William J Long
Journal:  Arthroplast Today       Date:  2022-01-18
  8 in total

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