Background: Techniques for diagnosing choledocholithiasis pose significant morbidity and mortality risks.
Objectives: We aimed to develop and validate a clinical scoring system for predicting choledocholithiasis.
Design: Data from a prospectively maintained database of all patients with gallstones.
Setting: Patients were admitted to the general surgery department of a military hospital.
Patients And Methods: We enrolled consecutive patients with symptomatic gallstones, biliary pancreatitis, obstructive jaundice, or cholangitis, who subsequently underwent biochemical testing and ultrasonography. A predictive model was developed from a scoring system using their imaging and laboratory data. Endoscopic retrograde cholangiopancreatography (ERCP) or intraoperative cholangiography were used for confirmatory diagnoses. The predictive efficacy of the scoring system was validated using a retrospective cohort of 272 patients.
Main Outcome Measures: Predictive accuracy of the scoring system.
Results: We enrolled 155 patients in the development group. The common bile duct diameter, alkaline phosphatase of >=200 IU, elevated bilirubin levels, alanine transaminase of >=220 IU, and male age of >=50 years were significantly associated with choledocholithiasis and were included in the scoring system. Ninety-six patients (35%) had scores of >=8 (high risk), 86 patients (32%) had scores of 4-7 (intermediate risk), and 27 patients (10%) had scores of 1-3 (low risk). In the validation cohort, the positive predictive value for a score of >=8 was 91.7%, and the scoring system had an area under the curve of 0.896.
Conclusion: Scores of >=8 were strongly correlated with choledocholithiasis in the developmental and validation groups, which indicates that our scoring system may be useful for predicting the need for therapeutic ERCP. However, prospective validation in a large multicenter cohort is needed to fully understand the benefits of the system.
Limitations: The retrospective validation cohort might have introduced selection and observational biases. The study may have been underpowered because of the sample size of the developmental cohort. The delay between admission and the time of ERCP theoretically may have increased the number of negative ERCP results, but our false negative rate for ERCP was consistent with the previously reported rates.
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http://dx.doi.org/10.5144/0256-4947.2016.57 | DOI Listing |
Curr Med Chem
January 2025
Cukurova University, Faculty of Medicine, Division of Endocrinology, Adana, Turkey.
Introduction: Diabetes mellitus is associated with an increased risk of atherosclerosis related to dyslipidemia. Although the terms hyperlipidemia and Diabetes Mellitus [DM] or diabetic dyslipidemia are interrelated to each other, these two conditions have some differences.
Aim: This study aimed to highlight possible mechanisms of hyperlipidemia and/or dyslipidemia in diabetic patients, which can be treated with available and newer hypolipidemic drugs.
J Antimicrob Chemother
January 2025
Department of Infectious Diseases and Clinical Microbiology, Hacettepe University Faculty of Medicine, Ankara, Turkey.
Objectives: To develop a scoring system to predict resistance to ceftolozane/tazobactam in Pseudomonas aeruginosa strains isolated from respiratory specimens.
Methods: A case-control study was conducted to evaluate the risk factors associated with resistance to ceftolozane/tazobactam. Patients with P.
JACC Adv
January 2025
Department of Cardiology, The Third-Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China.
Background: Previous studies on the prevalence and prognosis of nutritional status in valvular heart disease (VHD) were primarily limited to aortic stenosis. The nutritional status of other types of VHDs remained an underexplored area.
Objectives: This study aimed to evaluate the prevalence of malnutrition risk in different types of VHD and investigate the association between malnutrition risk and adverse clinical events.
iScience
January 2025
School of Mathematics and Statistics, Zhengzhou University, Zhengzhou 450001, China.
This study introduces a hybrid network model for phase classification, integrating quantum networks and complex-valued neural networks. This architecture uses elemental composition as its only input, eliminating complex feature engineering. Parameterized quantum networks handle sparse elemental data and convert data from real to complex domains, increasing information dimensionality.
View Article and Find Full Text PDFHealth disparities in patients with pulmonary arterial hypertension (PAH) have not been extensively reported in the United States. The aim of this project was to characterize the extent of demographic and socioeconomic disparities in clinical outcomes within a large, diverse PAH patient population. A retrospective, population-based study of electronic health record data from the OneFlorida Data Trust was completed.
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