Development of a Predictive Model for Common Bile Duct Stones in Patients With Clinical Suspicion of Choledocholithiasis: A Cohort Study

Tunruttanakul, Suppadech; Verasmith, Kotchakorn; Patumanond, Jayanton; Mingmalairak, Chatchai

doi:10.14740/gr1560

Cited by 4 publications

(3 citation statements)

References 46 publications

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“…Other algorithms for predicting choledocholithiasis do exist [23][24][25] ; however, much like the ASGE, they incorporate cutoff points for age or clinical variables such as bilirubin levels. The cutoff points, for instance, for bilirubin may vary depending on age or other variables, a nuance our model addresses by considering continuous variables.…”

Section: Discussionmentioning

confidence: 99%

Development and validation of a predictive model for choledocholithiasis

Huerta‐Reyna,

Guevara‐Torres,

Martínez‐Jiménez

et al. 2024

World j. surg.

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BackgroundGallstone‐related conditions affect a significant portion of the population, with varying prevalence among different ethnic groups. Complications such as pancreatitis and cholangitis are associated with the presence of common bile duct (CBD) stones. Existing guidelines for diagnosing choledocholithiasis lack precision, leading to excessive use of invasive procedures like endoscopic retrograde cholangiopancreatography (ERCP).MethodsA prospective study was conducted at Hospital Central “Dr. Ignacio Morones Prieto,” involving 374 patients in the development cohort and 154 patients in the validation cohort. Patients meeting inclusion criteria underwent biochemical testing and ultrasonography. A predictive scoring system was developed using logistic regression and validated in an independent cohort. Clinical and laboratory variables were collected, and model performance was assessed using receiver‐operator characteristic (ROC) curves.ResultsThe predictive model incorporated variables such as age, pancreatitis, cholangitis, bilirubin levels, and CBD stone presence on ultrasound. The model demonstrated an area under the ROC curve (AUC) of 93.81% in the validation dataset. By adjusting the threshold defining high‐risk probability to 40%, the model improved specificity and sensitivity compared to existing guidelines. Notably, the model reclassified patients, leading to a more accurate risk assessment.ConclusionsThe developed algorithm accurately predicts choledocholithiasis non‐invasively in patients with symptomatic gallstones. This tool has the potential to reduce reliance on costly or invasive procedures like magnetic resonance cholangiopancreatography and ERCP, offering a more efficient and cost‐effective approach to patient management. The user‐friendly calculator developed in this study could streamline diagnostic procedures, particularly in resource‐limited healthcare settings, ultimately improving patient care.

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Section: Discussionmentioning

confidence: 99%

Development and validation of a predictive model for choledocholithiasis

Huerta‐Reyna,

Guevara‐Torres,

Martínez‐Jiménez

et al. 2024

World j. surg.

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“…Both alkaline phosphatase and GGT had been studied for predicting the presence of CBD stones, with conflicting results for GGT. Alkaline phosphatase was already reported widely and commonly used in this context, for instance, developing predictive models for clinical suspicion of CBD stones 28 . However, we only focused on GGT elevation in the light of detecting CBD stones, unlike another cohort study which determined the accuracy of these markers in the earliest stages of acute biliary pancreatitis 29 .…”

Section: Discussionmentioning

confidence: 99%

Normal preoperative levels of gamma-glutamyltransferase predict the absence of common bile duct stones in patients scheduled for laparoscopic cholecystectomy: a retrospective cohort study

Khan

Siraj

Rajput

et al. 2023

Annals of Medicine &Amp; Surgery

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Objective: Laparoscopic cholecystectomy, nowadays, is considered the gold standard option for management in patients diagnosed with symptomatic cholelithiasis. Nevertheless, some patients may have coexisting choledocholithiasis, which manifests later in life with grave complications such as cholangitis and pancreatitis. The objective of this study is to evaluate the role of preoperative gamma-glutamyltransferase (GGT) in predicting choledocholithiasis in patients undergoing laparoscopic cholecystectomy. Method: A total of 360 patients with symptomatic cholelithiasis based on diagnosis aided with abdominal ultrasound were included in the study. The study design was a retrospective cohort. Patients were evaluated based on a comparison between findings of per-operative cholangiogram and laboratory measure of GGT. Result: The mean age of study participants was 47.22 (±28.41) years. Mean GGT levels were 121.54 (±87.91) U/l. One hundred (27.7%) participants had raised GGT. But only 19.4% had been diagnosed with filling defect positive on cholangiogram. The predictability of GGT for positive cholangiogram is statistically significant at less than 0.001 with an area under the curve of 0.922 (0.887–0.957), sensitivity of 95.7%, specificity of 88.6%, and accuracy of 90%. The standard error reported (0.018) was found to be relatively low. Conclusion: Based on the provided information, it is concluded that GGT plays an important role in predicting the coexistence of choledocholithiasis in symptomatic cholelithiasis and can be used in the setting where the facility of per-operative cholangiogram is not available.

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“…Similarly, Kadah et al [ 17 ] proposed that dilated CBD on ultrasound, increased age, and GGT were independent predictors of CBD stone and also developed a model using these scores, which had an AUROC of 0.73. Tunruttanakul et al [ 18 ] proposed a model for predicting CL, comprising advanced age, dilated CBD on percutaneous ultrasound, higher serum bilirubin, and ALP levels with an AUROC of 0.80. However, in our study, serum tests that included parameters of liver function such as total bilirubin and ALP, along with dilated CBD (>6 mm) on percutaneous ultrasound, were independent predictors of CL.…”

Section: Discussionmentioning

confidence: 99%

Utility of the “BATS” Score in Predicting Choledocholithiasis in Patients With Gall Bladder Stones

Ali¹,

Yaseen²,

Khan³

et al. 2023

Cureus

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Background and aim The role of expensive, risky, and unnecessary endoscopic interventions can be avoided by the use of non-invasive tests to predict common bile duct (CBD) stones. Therefore, our aim was to identify non-invasive predictors of choledocholithiasis (CL) in patients and further to predict a model and assess its diagnostic accuracy in predicting CL. Methods This cross-sectional study was carried out from June 1, 2020, to December 31, 2021. Patients having gall bladder stones on percutaneous transabdominal sonography and fulfilling intermediate probability criteria of CL were enrolled. These patients then underwent radial endoscopic ultrasound (EUS) followed by endoscopic retrograde cholangiopancreatography (ERCP) for detecting CBD stones. Univariate logistic regression analysis, followed by multivariate logistic regression analysis, was performed to ascertain the independent predictors of CBD stone in patients with intermediate probability. A model was proposed, and the diagnostic accuracy was calculated at an optimal cutoff. The model was then internally validated in the patients with intermediate probability and was also compared with the pre-existing score. Results Out of 131 patients included in the study, CBD stone was noted in 85 (66%) and 88 (67.2%) patients on EUS and ERCP, respectively. On multivariate analysis, high serum bilirubin (>2 mg/dL) and alkaline phosphatase (200 IU) and dilated CBD (>6 mm) on transabdominal sonography at baseline were significant predictors of CBD stone in these patients. Using these variables, a scoring system (BATS score) was developed, which had an area under the receiver operating curve (AUROC) of 0.98 in predicting the presence of CBD stone with a sensitivity of 93.18%, a specificity of 76.74%, and a diagnostic accuracy of 87.79%. In the validation cohort, a BATS score of ≥5 had a diagnostic accuracy of 95.91% in predicting CL. Conclusion The BATS score showed excellent sensitivity and good diagnostic accuracy in predicting the CBD stone with excellent results on internal validation. However, external validation of our results is required to recommend this model on a larger scale.

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Development of a Predictive Model for Common Bile Duct Stones in Patients With Clinical Suspicion of Choledocholithiasis: A Cohort Study

Cited by 4 publications

References 46 publications

Development and validation of a predictive model for choledocholithiasis

Development and validation of a predictive model for choledocholithiasis

Normal preoperative levels of gamma-glutamyltransferase predict the absence of common bile duct stones in patients scheduled for laparoscopic cholecystectomy: a retrospective cohort study

Utility of the “BATS” Score in Predicting Choledocholithiasis in Patients With Gall Bladder Stones

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