Patient-related Sociodemographic Predictive Factors for Length of Hospital Stay following Primary Total Knee Replacement in a Total joint Replacement Centre

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Abstract Description
Submission ID :
HAC90
Submission Type
Authors (including presenting author) :
NG HL (1) , POON LY (1), CHUI TC (1), CHIN YM (1), LAU WL (1)
Affiliation :
(1) Occupational Therapy Department, Pamela Youde Nethersole Eastern Hospital
Introduction :
The demand for total knee replacement (TKR) places a heavy economic burden on the healthcare system in Hong Kong . While shortening length of hospital stay (LOS) reduces the associated cost, the association between preoperative patient-related sociodemographic factors and prolonged LOS remains unknown.
Objectives :
To identify preoperative patient-related sociodemographic predictors of LOS following primary TKR performed at Pamela Youde Nethersole Eastern Hospital (PYNEH).
Methodology :
We retrospectively reviewed patients undergoing primary TKR performed at PYNEH from July 2021 to October 2023. 15 preoperative patient-related sociodemographic factors that might influence LOS were recorded. They were age, gender, Body Mass Index (BMI), availability of caregivers, public or private housing, accessibility of direct lift landing, availability of toilet handrail,  availability of bathroom handrail, bathtub or shower cubicle, preoperative home visits by Occupational Therapists (OT), premorbid Modified Barthel Index (MBI), Short-Fall Efficacy Scale (S-FES), DASS Depression, Anxiety and Stress scores and preoperative knee pain level.  
Result & Outcome :
A total of 484 patients were identified. The mean LOS was 8.09 days (SD= 4.16). Logistic regression was used to predict length of stay from 15 preoperative patient-related sociodemographic factors.
The result of regression indicated that only age, availability of caregivers, direct lift landing flat, Preoperative home visit by OT, premorbid MBI , DASS-Depression and DASS- Anxiety could significantly predict the length of stay (B= -1.226 to 0.765, standard error (SE)=0.027 to 0.492, t= -3.081 to 3.530 , p<0.696). All those factors accounted for 10.1% of the total variance in the LOS. The final regression equation to predict the LOS was devised as: LOS = 0.096 (Age) – 1.226 (Availability of caregivers) + 0.193 (Accessibility of Direct Lift Landing) + 0.765 (Preoperative Home visit by OT) -0.139 (Premorbid MBI) + 0.385 (DASS-Depression) -0.100 (DASS-Anxiety) + 14.479.
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