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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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Detalles Bibliográficos
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
Descripción
Sumario: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.