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Time to development of surgical site infection and its predictors among general surgery patients admitted at specialized hospitals in Amhara region, northwest Ethiopia: a prospective follow-up study

BACKGROUND: Surgical site infection is an infection occurring within 30 days after surgery. It is recently reported that evidence-based information on the specific time when the majority of surgical site infections would develop is a key to early detect the infection as well as to preventing and ear...

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Autores principales: Alemayehu, Meron Asmamaw, Azene, Abebaw Gedef, Mihretie, Kebadnew Mulatu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10193810/
https://www.ncbi.nlm.nih.gov/pubmed/37198551
http://dx.doi.org/10.1186/s12879-023-08301-0
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author Alemayehu, Meron Asmamaw
Azene, Abebaw Gedef
Mihretie, Kebadnew Mulatu
author_facet Alemayehu, Meron Asmamaw
Azene, Abebaw Gedef
Mihretie, Kebadnew Mulatu
author_sort Alemayehu, Meron Asmamaw
collection PubMed
description BACKGROUND: Surgical site infection is an infection occurring within 30 days after surgery. It is recently reported that evidence-based information on the specific time when the majority of surgical site infections would develop is a key to early detect the infection as well as to preventing and early intervene against their pressing and fatal complications. Therefore, the current study aimed to determine the incidence, predictors, and time to development of surgical site infection among general surgery patients at specialized hospitals in the Amhara region. METHOD: An institution-based prospective follow-up study was conducted. The two-stage cluster sampling procedure was used. A systematic sampling technique with a K interval of 2 was applied to prospectively recruit 454 surgical patients. Patients were followed up for 30 days. Data were collected using Epicollect5 v 3.0.5 software. Post-discharge follow-up and diagnosis were done by telephone call follow-up. Data were analyzed using STATA™ version 14.0. Kaplan–Meier curve was used to estimate survival time. Cox proportional regression model was used to determine significant predictors. Variables with a P-value less than 0.05 in the multiple Cox regression models were independent predictors. RESULT: The incidence density was 17.59 per 1000 person-day-observation. The incidence of post-discharge Surgical site infection was 70.3%. The majority of surgical site infections were discovered after discharge between postoperative days 9 to 16. Being male (AHR: 1.98, 95% CI: 1.201 – 3.277, diabetes Mellitus (AHR: 1.819, 95% CI: 1.097 – 3.016), surgical history (AHR: 2.078, 95% CI: 1.345, 3.211), early antimicrobial prophylaxis (AHR: 2.60, 95% CI: 1.676, 4.039), American Society of Anesthesiologists score ≥ III AHR: 6.710, 95% CI: 4.108, 10.960), duration of the surgery (AHR: 1.035 95% CI: 1.001, 1.070), Age (AHR: 1.022 95% CI: 1.000, 1.043), and the number of professionals in the Operation Room (AHR: 1.085 95% CI: 1.037, 1.134) were found to be the predictors of time to development of Surgical site infection. CONCLUSION: The incidence of surgical site infection was higher than the acceptable international range. The majority of infections were detected after hospital discharge between 9 to 16 postoperative days. The main predictors of Surgical site infection were Age, Sex, Diabetes Mellitus, previous surgical history, the timing of Antimicrobial prophylaxis, American Society of Anesthesiologists score, pre-operative hospital stay, duration of surgery, and the number of professionals in the operation room. Hence, hospitals should give great emphasis on pre-operative preparation, post-discharge surveillance, modifiable predictors, and high-risk patients, as they found in this study.
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spelling pubmed-101938102023-05-19 Time to development of surgical site infection and its predictors among general surgery patients admitted at specialized hospitals in Amhara region, northwest Ethiopia: a prospective follow-up study Alemayehu, Meron Asmamaw Azene, Abebaw Gedef Mihretie, Kebadnew Mulatu BMC Infect Dis Research BACKGROUND: Surgical site infection is an infection occurring within 30 days after surgery. It is recently reported that evidence-based information on the specific time when the majority of surgical site infections would develop is a key to early detect the infection as well as to preventing and early intervene against their pressing and fatal complications. Therefore, the current study aimed to determine the incidence, predictors, and time to development of surgical site infection among general surgery patients at specialized hospitals in the Amhara region. METHOD: An institution-based prospective follow-up study was conducted. The two-stage cluster sampling procedure was used. A systematic sampling technique with a K interval of 2 was applied to prospectively recruit 454 surgical patients. Patients were followed up for 30 days. Data were collected using Epicollect5 v 3.0.5 software. Post-discharge follow-up and diagnosis were done by telephone call follow-up. Data were analyzed using STATA™ version 14.0. Kaplan–Meier curve was used to estimate survival time. Cox proportional regression model was used to determine significant predictors. Variables with a P-value less than 0.05 in the multiple Cox regression models were independent predictors. RESULT: The incidence density was 17.59 per 1000 person-day-observation. The incidence of post-discharge Surgical site infection was 70.3%. The majority of surgical site infections were discovered after discharge between postoperative days 9 to 16. Being male (AHR: 1.98, 95% CI: 1.201 – 3.277, diabetes Mellitus (AHR: 1.819, 95% CI: 1.097 – 3.016), surgical history (AHR: 2.078, 95% CI: 1.345, 3.211), early antimicrobial prophylaxis (AHR: 2.60, 95% CI: 1.676, 4.039), American Society of Anesthesiologists score ≥ III AHR: 6.710, 95% CI: 4.108, 10.960), duration of the surgery (AHR: 1.035 95% CI: 1.001, 1.070), Age (AHR: 1.022 95% CI: 1.000, 1.043), and the number of professionals in the Operation Room (AHR: 1.085 95% CI: 1.037, 1.134) were found to be the predictors of time to development of Surgical site infection. CONCLUSION: The incidence of surgical site infection was higher than the acceptable international range. The majority of infections were detected after hospital discharge between 9 to 16 postoperative days. The main predictors of Surgical site infection were Age, Sex, Diabetes Mellitus, previous surgical history, the timing of Antimicrobial prophylaxis, American Society of Anesthesiologists score, pre-operative hospital stay, duration of surgery, and the number of professionals in the operation room. Hence, hospitals should give great emphasis on pre-operative preparation, post-discharge surveillance, modifiable predictors, and high-risk patients, as they found in this study. BioMed Central 2023-05-17 /pmc/articles/PMC10193810/ /pubmed/37198551 http://dx.doi.org/10.1186/s12879-023-08301-0 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Alemayehu, Meron Asmamaw
Azene, Abebaw Gedef
Mihretie, Kebadnew Mulatu
Time to development of surgical site infection and its predictors among general surgery patients admitted at specialized hospitals in Amhara region, northwest Ethiopia: a prospective follow-up study
title Time to development of surgical site infection and its predictors among general surgery patients admitted at specialized hospitals in Amhara region, northwest Ethiopia: a prospective follow-up study
title_full Time to development of surgical site infection and its predictors among general surgery patients admitted at specialized hospitals in Amhara region, northwest Ethiopia: a prospective follow-up study
title_fullStr Time to development of surgical site infection and its predictors among general surgery patients admitted at specialized hospitals in Amhara region, northwest Ethiopia: a prospective follow-up study
title_full_unstemmed Time to development of surgical site infection and its predictors among general surgery patients admitted at specialized hospitals in Amhara region, northwest Ethiopia: a prospective follow-up study
title_short Time to development of surgical site infection and its predictors among general surgery patients admitted at specialized hospitals in Amhara region, northwest Ethiopia: a prospective follow-up study
title_sort time to development of surgical site infection and its predictors among general surgery patients admitted at specialized hospitals in amhara region, northwest ethiopia: a prospective follow-up study
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10193810/
https://www.ncbi.nlm.nih.gov/pubmed/37198551
http://dx.doi.org/10.1186/s12879-023-08301-0
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