A validated preoperative risk prediction tool for extended inpatient length of stay following anatomic or reverse total shoulder arthroplasty.

Autor: Goltz DE; Department of Orthopaedic Surgery, Duke University Medical Center, Durham, NC, USA. Electronic address: daniel.goltz@duke.edu., Burnett RA; Department of Orthopaedic Surgery, Rush University Medical Center, Chicago, IL, USA., Levin JM; Department of Orthopaedic Surgery, Duke University Medical Center, Durham, NC, USA., Helmkamp JK; Department of Orthopaedic Surgery, Duke University Medical Center, Durham, NC, USA., Wickman JR; Department of Orthopaedic Surgery, Duke University Medical Center, Durham, NC, USA., Hinton ZW; Department of Orthopaedic Surgery, Duke University Medical Center, Durham, NC, USA., Howell CB; Performance Services, Duke University Medical Center, Durham, NC, USA., Green CL; Department of Biostatistics & Bioinformatics, Duke University, Durham, NC, USA., Simmons JA; Rush Research Core, Rush University Medical Center, Chicago, IL, USA., Nicholson GP; Department of Orthopaedic Surgery, Rush University Medical Center, Chicago, IL, USA., Verma NN; Department of Orthopaedic Surgery, Rush University Medical Center, Chicago, IL, USA., Lassiter TE Jr; Department of Orthopaedic Surgery, Duke University Medical Center, Durham, NC, USA., Anakwenze OA; Department of Orthopaedic Surgery, Duke University Medical Center, Durham, NC, USA., Garrigues GE; Department of Orthopaedic Surgery, Rush University Medical Center, Chicago, IL, USA., Klifto CS; Department of Orthopaedic Surgery, Duke University Medical Center, Durham, NC, USA.
Jazyk: angličtina
Zdroj: Journal of shoulder and elbow surgery [J Shoulder Elbow Surg] 2023 May; Vol. 32 (5), pp. 1032-1042. Date of Electronic Publication: 2022 Nov 16.
DOI: 10.1016/j.jse.2022.10.016
Abstrakt: Background: Recent work has shown inpatient length of stay (LOS) following shoulder arthroplasty to hold the second strongest association with overall cost (after implant cost itself). In particular, a preoperative understanding for the patients at risk of extended inpatient stays (≥3 days) can allow for counseling, optimization, and anticipating postoperative adverse events.
Methods: A multicenter retrospective review was performed of 5410 anatomic (52%) and reverse (48%) total shoulder arthroplasties done at 2 large, tertiary referral health systems. The primary outcome was extended inpatient LOS of at least 3 days, and over 40 preoperative sociodemographic and comorbidity factors were tested for their predictive ability in a multivariable logistic regression model based on the patient cohort from institution 1 (derivation, N = 1773). External validation was performed using the patient cohort from institution 2 (validation, N = 3637), including area under the receiver operator characteristic curve (AUC), sensitivity, specificity, and positive and negative predictive values.
Results: A total of 814 patients, including 318 patients (18%) in the derivation cohort and 496 patients (14%) in the validation cohort, experienced an extended inpatient LOS of at least 3 days. Four hundred forty-five (55%) were discharged to a skilled nursing or rehabilitation facility. Following parameter selection, a multivariable logistic regression model based on the derivation cohort (institution 1) demonstrated excellent preliminary accuracy (AUC: 0.826), with minimal decrease in accuracy under external validation when tested against the patients from institution 2 (AUC: 0.816). The predictive model was composed of only preoperative factors, in descending predictive importance as follows: age, marital status, fracture case, ASA (American Society of Anesthesiologists) score, paralysis, electrolyte disorder, body mass index, gender, neurologic disease, coagulation deficiency, diabetes, chronic pulmonary disease, peripheral vascular disease, alcohol dependence, psychoses, smoking status, and revision case.
Conclusion: A freely-available, preoperative online clinical decision tool for extended inpatient LOS (≥ 3 days) after shoulder arthroplasty reaches excellent predictive accuracy under external validation. As a result, this tool merits consideration for clinical implementation, as many risk factors are potentially modifiable as part of a preoperative optimization strategy.
(Copyright © 2022 Journal of Shoulder and Elbow Surgery Board of Trustees. Published by Elsevier Inc. All rights reserved.)
Databáze: MEDLINE
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