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Factors predicting the anastomotic leakage in small bowel anastomoses

International Journal of Surgery Science · 2021 · Vol. 5(4) · pp. 34–38
Arounkumar NagalingamK SelvakumarRavisankar Palaniappan

Abstract

Aim: This is a prospective study that studies the various factors predicting the anastomotic leakage in small bowel anastomoses Patients with suture line disruption were compared with patients whose anastomoses did not leak.Materials and Methods: All patients above the age of 18 years undergoing surgical closure of a full thickness small intestinal breach, were analyzed and followed up until their discharge from hospital or death.Type of study: Prospective, analytical studyPlace of study: Department of General Surgery, Sri Venkateshwaraa Medical College Hospital and Research Centre, Ariyur, PuducherryDuration: April 2018 to March 2020Methodology: Detection of suture line disruptionResult: ASA grade and leak, Biochemical Parameters and leak, Parameters associated with mortality, Anastomotic procedure and leak, Intraoperative factors and leak rate, Typhoid perforations (Widal positive) and leak all the parameters were tabulated conducted to clarify issues relating to factors causing small bowel anastomotic leakage with specific reference to emergency surgeries. Logistic regression and multivariate analysis were used to identify independent predictors of anastomotic leak.Conclusion: Factors found to have a significant association with suture line disruption by univariate analysis included ASA grade of 3 or above, low hemoglobin, low serum albumin, low preoperative serum sodium, higher mean duration of surgery, presence of gross peritoneal contamination, use of drains in primary anastomoses, higher mean amount of fluids infused intraoperatively, intraoperative hypotension and postoperative ventilatory support.

Colorectal Cancer Surgical TreatmentsCardiac, Anesthesia and Surgical OutcomesAnorectal Disease Treatments and OutcomesMedicineAnastomosisLeakDehiscenceSurgeryUnivariate analysisProspective cohort studyFibrous jointLogistic regressionMultivariate analysis
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