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Preoperative and Perioperative Predictors of Length of Hospital Stay after Primary Total Hip Arthroplasty—Our Experience on 743 Cases

The aim of this retrospective investigation is to evaluate the correlation between several preoperative and perioperative factors and the length of hospital stay in patients that underwent elective total hip arthroplasty with overnight admission. Medical records of patients that underwent THA from t...

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Autores principales: Papalia, Rocco, Zampogna, Biagio, Torre, Guglielmo, Papalia, Giuseppe Francesco, Vorini, Ferruccio, Bravi, Marco, Albo, Erika, De Vincentis, Antonio, Denaro, Vincenzo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8584853/
https://www.ncbi.nlm.nih.gov/pubmed/34768573
http://dx.doi.org/10.3390/jcm10215053
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author Papalia, Rocco
Zampogna, Biagio
Torre, Guglielmo
Papalia, Giuseppe Francesco
Vorini, Ferruccio
Bravi, Marco
Albo, Erika
De Vincentis, Antonio
Denaro, Vincenzo
author_facet Papalia, Rocco
Zampogna, Biagio
Torre, Guglielmo
Papalia, Giuseppe Francesco
Vorini, Ferruccio
Bravi, Marco
Albo, Erika
De Vincentis, Antonio
Denaro, Vincenzo
author_sort Papalia, Rocco
collection PubMed
description The aim of this retrospective investigation is to evaluate the correlation between several preoperative and perioperative factors and the length of hospital stay in patients that underwent elective total hip arthroplasty with overnight admission. Medical records of patients that underwent THA from the beginning of 2016 to the end of 2018 were retrospectively screened. Demographics, comorbidities, whole blood count, intraoperative details, and length of postoperative stay were retrieved. The association between clinical, laboratory and surgical factors and the length of hospital stay was explored by means of negative binomial and logistic regression models. The median length of postoperative hospital stay was four days (Inter Quartile Range, IQR 3, 5). After univariate regression a stepwise multivariate regression showed that operative time (p = 0.001), the preoperative serum creatinine (p < 0.001), the intraoperative blood loss (p = 0.04) and the use of an anterolateral approach (p < 0.001) were found to correlate significantly with the increase of the hospitalization length, while no significant correlation was found for all the other features. Multivariable model fitted through logistic regression (LOS below or over the median value of four days) had an Area Under the Curve (AUC) of 0.748. Our analysis suggests a significant role played by different preoperative and perioperative variables in influencing the length of hospital stay.
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spelling pubmed-85848532021-11-12 Preoperative and Perioperative Predictors of Length of Hospital Stay after Primary Total Hip Arthroplasty—Our Experience on 743 Cases Papalia, Rocco Zampogna, Biagio Torre, Guglielmo Papalia, Giuseppe Francesco Vorini, Ferruccio Bravi, Marco Albo, Erika De Vincentis, Antonio Denaro, Vincenzo J Clin Med Article The aim of this retrospective investigation is to evaluate the correlation between several preoperative and perioperative factors and the length of hospital stay in patients that underwent elective total hip arthroplasty with overnight admission. Medical records of patients that underwent THA from the beginning of 2016 to the end of 2018 were retrospectively screened. Demographics, comorbidities, whole blood count, intraoperative details, and length of postoperative stay were retrieved. The association between clinical, laboratory and surgical factors and the length of hospital stay was explored by means of negative binomial and logistic regression models. The median length of postoperative hospital stay was four days (Inter Quartile Range, IQR 3, 5). After univariate regression a stepwise multivariate regression showed that operative time (p = 0.001), the preoperative serum creatinine (p < 0.001), the intraoperative blood loss (p = 0.04) and the use of an anterolateral approach (p < 0.001) were found to correlate significantly with the increase of the hospitalization length, while no significant correlation was found for all the other features. Multivariable model fitted through logistic regression (LOS below or over the median value of four days) had an Area Under the Curve (AUC) of 0.748. Our analysis suggests a significant role played by different preoperative and perioperative variables in influencing the length of hospital stay. MDPI 2021-10-28 /pmc/articles/PMC8584853/ /pubmed/34768573 http://dx.doi.org/10.3390/jcm10215053 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Papalia, Rocco
Zampogna, Biagio
Torre, Guglielmo
Papalia, Giuseppe Francesco
Vorini, Ferruccio
Bravi, Marco
Albo, Erika
De Vincentis, Antonio
Denaro, Vincenzo
Preoperative and Perioperative Predictors of Length of Hospital Stay after Primary Total Hip Arthroplasty—Our Experience on 743 Cases
title Preoperative and Perioperative Predictors of Length of Hospital Stay after Primary Total Hip Arthroplasty—Our Experience on 743 Cases
title_full Preoperative and Perioperative Predictors of Length of Hospital Stay after Primary Total Hip Arthroplasty—Our Experience on 743 Cases
title_fullStr Preoperative and Perioperative Predictors of Length of Hospital Stay after Primary Total Hip Arthroplasty—Our Experience on 743 Cases
title_full_unstemmed Preoperative and Perioperative Predictors of Length of Hospital Stay after Primary Total Hip Arthroplasty—Our Experience on 743 Cases
title_short Preoperative and Perioperative Predictors of Length of Hospital Stay after Primary Total Hip Arthroplasty—Our Experience on 743 Cases
title_sort preoperative and perioperative predictors of length of hospital stay after primary total hip arthroplasty—our experience on 743 cases
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8584853/
https://www.ncbi.nlm.nih.gov/pubmed/34768573
http://dx.doi.org/10.3390/jcm10215053
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