CROSS-SECTIONAL STUDY OF FACTORS PREDICTING CONVERSION FROM LAPAROSCOPIC TO OPEN CHOLECYSTECTOMY.

Abstract

Background

Laparoscopic cholecystectomy (LC) has become the gold standard procedure for the surgical management of gallstone disease due to its minimally invasive nature and faster recovery. However, conversion to open cholecystectomy (OC) is occasionally required in technically difficult cases, “potentially leading to increased morbidity, prolonged hospitalization, and higher healthcare costs. Identifying the factors associated with such conversions is essential for optimizing surgical outcomes and patient safety.

Objective

This study aims to determine the demographic, clinical, sonographic, and intraoperative factors that predict conversion from laparoscopic to open cholecystectomy in patients undergoing elective surgery for gallbladder disease.

Methods

The General Surgery Department of Rajendra Institute of Medical Sciences (RIMS), Ranchi, undertook this cross-sectional observational study.  Based on inclusion and exclusion criteria, 100 elective laparoscopic cholecystectomy patients were included.  Age, sex, BMI, clinical history, ultrasonographic findings, and intraoperative observations were gathered using a structured proforma.  Conversion to open cholecystectomy was the main result.  Statistical analysis used chi-square, t-tests, and multivariate logistic regression with a significance level of p < 0.05.

Results

Total conversion was 18%.  In particular, 30% of patients over 50, 40.9% of those with BMI >30, and 27.8% of those with acute cholecystitis converted.  Sonography showed conversion in 36.7% with gallbladder wall thickness >3 mm and 38.9% with pericholecystic fluid.  Distorted Calot's triangle converted 50% and dense adhesions 42.9% intraoperatively.  Significant predictors include age >50 (p=0.01), BMI >30 (p=0.002), acute cholecystitis history (p=0.006), gallbladder wall thickness >3 mm (p=0.001), and extensive intraoperative adhesions (p<0.001).  These findings indicate that preoperative and intraoperative factors greatly influence conversion.

Conclusion

Identification of high-risk patients through thorough preoperative evaluation can facilitate surgical planning and improve outcomes. Incorporating predictive models into routine clinical practice may help reduce unnecessary conversions and associated complications.