The goal of this study is to present the multiple institutions experience comparing the outcome of management between initial laparoscopic cholecystectomy (LC) surgeon and specialist as well as the outcome of different operative procedures to major bile duct injury (BDI) after LC. We have retrospectively collected data of 77 cases of perioperatively detected major BDI in LC at 15 general surgical institutions from 1997 to 2007. We classified 42 cases treated by an experienced biliary surgeon as Group A and 35 cases treated by the initial LC surgeon as Group B. Forty-eight cases were treated with duct-to-duct anastomosis as Group C and 29 cases were treated with Roux-en-Y choledochojejunostomy as Group D. The median duration of follow-up was 62 months. The outcome of groups was compared. In Group A, 7 of 42 (16.7%) patients developed a failure. Two of seven (28.6%) patients were treated by a secondary operation. In Group B, 24 of 35 (68.6%) patients developed a failure. Seventeen of 24 (70.8%) patients were treated by a secondary operation. One of 35 (2.85%) patients died. The significant differences were observed in failure and secondary operations (16.7 vs 68.6%, P < 0.01 and 28.6 vs 70.8%, P < 0.01). There is no significant difference Group C and Group D in failure rate (28.5 vs 11.7%, P > 0.05). A multiple institutional cooperative methodology between the local surgical institution and tertiary care centers provided a good way to limit further operations, failure. The reconstructive strategy is important and should be selected according to the type of injury and the diagnosed status of major BDI.
Download full-text PDF |
Source |
---|
Afr J Reprod Health
December 2024
Department of Gynecology and Obstetrics, Affiliated Hospital of Nantong University, Medical School of Nantong University, Nantong 226001, Jiangsu, China.
Through implementing a bidirectional Mendelian randomization (MR) study, the causal effects between gut microbiome and polycystic ovary syndrome (PCOS) were analyzed. Summary statistics for PCOS were acquired from the FinnGen consortium R8 release data, which included 27,943 cases and 162,936 controls. The inverse-variance weighting (IVW) method was adopted for analysis.
View Article and Find Full Text PDFRestor Dent Endod
January 2025
School of Dentistry, IMU University, Kuala Lumpur, Malaysia.
Objectives: This study evaluated the number and quality of working length (WL) and master cone (MC) radiographs taken during root canal treatment by dental undergraduates, and their associations with the technical quality of root canal fillings (TQRCF) and endodontic outcomes (EO).
Methods: A retrospective evaluation of radiographs from 303 root canal-treated teeth in 231 patients was conducted, with 72 patients attending recall visits to assess EO. The chi-square and one-way analysis of variance tests were performed.
Viruses
December 2024
Carson Valley Large Animal Clinic, Gardnerville, NV 89460, USA.
The objective of this study was to describe an outbreak of equine herpesvirus-1 myeloencephalopathy (EHM) in a population of aged equids. The outbreak was linked to the introduction of five healthy non-resident horses 15 days prior to the first case of acute recumbency. This fulminant EHM outbreak was predisposed by the grouping of the 33 unvaccinated animals in two large pens with shared water and feed troughs.
View Article and Find Full Text PDFViruses
December 2024
Institute of Chemical Biology and Fundamental Medicine, Siberian Branch of Russian Academy of Sciences, Prosp. Lavrentieva 8, Novosibirsk 630090, Russia.
Anti-phage defense systems are widespread in bacteria due to the latter continuous adaptation to infection by bacteriophages (phages). has a high degree of intrinsic antibiotic resistance, which makes phage therapy relevant for the treatment of infections caused by this species. Studying the array of anti-phage defense systems that could be found in helps in better adapting the phages to the systems present in the pathogenic bacteria.
View Article and Find Full Text PDFViruses
November 2024
Faculty of Medical and Health Sciences, Tel Aviv University, Tel Aviv 6997801, Israel.
In this study, we introduce a novel approach that integrates interpretability techniques from both traditional machine learning (ML) and deep neural networks (DNN) to quantify feature importance using global and local interpretation methods. Our method bridges the gap between interpretable ML models and powerful deep learning (DL) architectures, providing comprehensive insights into the key drivers behind model predictions, especially in detecting outliers within medical data. We applied this method to analyze COVID-19 pandemic data from 2020, yielding intriguing insights.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!