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Readmission After Elective Ileostomy in Colorectal Surgery Is Predictable

BACKGROUND AND OBJECTIVES: Patients who undergo colorectal surgery have high postoperative morbidity, with ileostomates being the most disadvantaged. Recent studies assessing readmission risk factors do not provide a specific prediction model and, if so, do not focus on patients who have had colorec...

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Autores principales: Iqbal, Atif, Sakharuk, Ilya, Goldstein, Lindsey, Tan, Sanda A., Qiu, Peihua, Li, Zhaomian, Hughes, Steven J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Society of Laparoendoscopic Surgeons 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6158969/
https://www.ncbi.nlm.nih.gov/pubmed/30275672
http://dx.doi.org/10.4293/JSLS.2018.00008
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author Iqbal, Atif
Sakharuk, Ilya
Goldstein, Lindsey
Tan, Sanda A.
Qiu, Peihua
Li, Zhaomian
Hughes, Steven J.
author_facet Iqbal, Atif
Sakharuk, Ilya
Goldstein, Lindsey
Tan, Sanda A.
Qiu, Peihua
Li, Zhaomian
Hughes, Steven J.
author_sort Iqbal, Atif
collection PubMed
description BACKGROUND AND OBJECTIVES: Patients who undergo colorectal surgery have high postoperative morbidity, with ileostomates being the most disadvantaged. Recent studies assessing readmission risk factors do not provide a specific prediction model and, if so, do not focus on patients who have had colorectal surgery; thus, the results of these studies have limited applicability to our specialized practice. We wanted to develop a prediction model for readmission within 30 days of discharge after ileostomy creation. METHODS: Patients who underwent elective ileostomy creation from 2013 to 2016 at the University of Florida were included in this retrospective study. Factors significantly associated with readmission within 30 days after discharge were identified by comparing a cohort that was readmitted within 30 days with one that was not. A practical, predictive model that stratified a patient's risk of readmission after the index procedure was developed. RESULTS: A total of 86 iliostomates were included; of those, 22 (26%) were readmitted within 30 days. Factors significantly associated with readmission included preoperative steroid use, history of diabetes, history of depression, lack of a hospital social worker or postoperative ostomy education, and the presence of complications after the index procedure. A model predicting readmission within 30 days of discharge that comprised the first 4 factors was developed, with a sensitivity of 73% and a specificity of 77%. CONCLUSION: Prediction of readmission in patients who undergo ileostomy creation is possible, suggesting interventions addressing predictive factors that may help decrease the readmission rate. Prospective validation of the model in a larger cohort is needed.
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spelling pubmed-61589692018-10-01 Readmission After Elective Ileostomy in Colorectal Surgery Is Predictable Iqbal, Atif Sakharuk, Ilya Goldstein, Lindsey Tan, Sanda A. Qiu, Peihua Li, Zhaomian Hughes, Steven J. JSLS Scientific Paper BACKGROUND AND OBJECTIVES: Patients who undergo colorectal surgery have high postoperative morbidity, with ileostomates being the most disadvantaged. Recent studies assessing readmission risk factors do not provide a specific prediction model and, if so, do not focus on patients who have had colorectal surgery; thus, the results of these studies have limited applicability to our specialized practice. We wanted to develop a prediction model for readmission within 30 days of discharge after ileostomy creation. METHODS: Patients who underwent elective ileostomy creation from 2013 to 2016 at the University of Florida were included in this retrospective study. Factors significantly associated with readmission within 30 days after discharge were identified by comparing a cohort that was readmitted within 30 days with one that was not. A practical, predictive model that stratified a patient's risk of readmission after the index procedure was developed. RESULTS: A total of 86 iliostomates were included; of those, 22 (26%) were readmitted within 30 days. Factors significantly associated with readmission included preoperative steroid use, history of diabetes, history of depression, lack of a hospital social worker or postoperative ostomy education, and the presence of complications after the index procedure. A model predicting readmission within 30 days of discharge that comprised the first 4 factors was developed, with a sensitivity of 73% and a specificity of 77%. CONCLUSION: Prediction of readmission in patients who undergo ileostomy creation is possible, suggesting interventions addressing predictive factors that may help decrease the readmission rate. Prospective validation of the model in a larger cohort is needed. Society of Laparoendoscopic Surgeons 2018 /pmc/articles/PMC6158969/ /pubmed/30275672 http://dx.doi.org/10.4293/JSLS.2018.00008 Text en © 2018 by JSLS, Journal of the Society of Laparoendoscopic Surgeons. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial No Derivatives License (http://creativecommons.org/licenses/by-nc-nd/3.0/us/), which permits for noncommercial use, distribution, and reproduction in any medium, provided the original work is properly cited and is not altered in any way.
spellingShingle Scientific Paper
Iqbal, Atif
Sakharuk, Ilya
Goldstein, Lindsey
Tan, Sanda A.
Qiu, Peihua
Li, Zhaomian
Hughes, Steven J.
Readmission After Elective Ileostomy in Colorectal Surgery Is Predictable
title Readmission After Elective Ileostomy in Colorectal Surgery Is Predictable
title_full Readmission After Elective Ileostomy in Colorectal Surgery Is Predictable
title_fullStr Readmission After Elective Ileostomy in Colorectal Surgery Is Predictable
title_full_unstemmed Readmission After Elective Ileostomy in Colorectal Surgery Is Predictable
title_short Readmission After Elective Ileostomy in Colorectal Surgery Is Predictable
title_sort readmission after elective ileostomy in colorectal surgery is predictable
topic Scientific Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6158969/
https://www.ncbi.nlm.nih.gov/pubmed/30275672
http://dx.doi.org/10.4293/JSLS.2018.00008
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