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Predicting Length of Stay after nephrectomy

Krom, Rogier (2024) Predicting Length of Stay after nephrectomy.

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Abstract:The study aimed to analyze preoperative patient characteristics, operation procedures, and lesion variables within the Enhanced Recovery After Surgery (ERAS) program to predict the length of stay (LOS) after nephrectomy or nephroureterectomy in renal patients. Conducted at Medisch Spectrum Twente, the retrospective study included 210 ERAS patients between April 2021 and March 2023. Short LOS was defined as one night or less, and long LOS as more than one night. Data analysis involved T-tests, Chi-squared tests, multivariate logistic regression, and imputation techniques. Six variables, including procedure & lesion size, pulmonary disease, dyspnea, GFR, smoking, and MET-score, were identified as predictors of LOS. The predictive model exhibited strong discriminative power (AUC = 0.79) and adequate fit (p-value = 0.96). Cross-validation indicated fair agreement (accuracy = 67.8%, Cohen’s kappa = 0.34), while the calibration plot showed excellent calibration. The study suggests that integrating predictive models can aid in personalized care planning, offering patients insights into LOS factors for better preoperative preparation and postoperative recovery. Additionally, policymakers and planners could utilize these models to optimize healthcare resource allocation.
Item Type:Essay (Master)
Faculty:TNW: Science and Technology
Subject:44 medicine
Programme:Health Sciences MSc (66851)
Link to this item:https://purl.utwente.nl/essays/98590
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