Clinical & Ultrasonography Based Scoring to Predict Pre-Operatively the Conversionof Laparoscopic to Open Cholecystectomy - A Prospective Observational Study
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Abstract
Introduction: Laparoscopic cholecystectomy (LC) is the standard procedure for gallbladder removal due to its minimally invasive nature and better postoperative outcomes. However, conversion to open cholecystectomy (OC) may be required in certain high-risk cases, leading to longer operative times and increased morbidity. Early identification of factors predictive of conversion is essential to improve surgical preparedness and patient counseling.
Materials & Methods: This prospective observational study was conducted at the Department of General Surgery, J.A. Group of Hospitals, Gwalior, over 18 months. A total of 330 patients diagnosed with cholelithiasis and planned for LC were evaluated preoperatively using a clinical and ultrasonographic scoring system. Parameters included gallbladder morphology, wall thickness, stone size and location, number of attacks, duration of complaints, and comorbidities. Standard laparoscopic cholecystectomy was performed, and intraoperative conversion rates were recorded. Statistical analysis was done using SPSS-25, with ROC curve analysis used to identify predictive cutoff scores.
Results: Out of 330 patients, 38 (11.5%) required conversion to OC. The conversion rate was significantly higher in patients aged 51–60 years (29.6%), those with multiple prior attacks (up to 83.3%), and those with complaints longer than 12 months (60.5%). Ultrasonographic factors such as gallbladder wall thickness >3 mm, stone at the neck, stone size ≥2 cm, and pericholecystic collection were significantly associated with conversion. A USG score cutoff of >8.5 predicted conversion with moderate sensitivity and specificity.
Conclusion: Clinical and ultrasonographic parameters effectively predict the likelihood of conversion from LC to OC. The scoring system aids in risk stratification, surgical planning, and informed consent, ensuring better outcomes and resource optimization.