Results 181 to 190 of about 803,878 (345)

Annual Report of the 2022 National Clinical Database: Decade‐Long Trends and Current Status of Gastroenterological Surgery in Japan

open access: yesAnnals of Gastroenterological Surgery, EarlyView.
ABSTRACT Aim The National Clinical Database (NCD) of Japan is the largest nationwide registry, covering over 95% of surgeries in the country. This 2022 annual report summarizes the short‐term outcomes of gastroenterological surgeries and discusses trends and insights over the past decade.
Koshi Kumagai   +19 more
wiley   +1 more source

Impact of Prophylactic Cefepime on Surgical Site Infection and Severe Morbidity in Patients Who Underwent Pancreaticoduodenectomy With Preoperative Biliary Drainage

open access: yesAnnals of Gastroenterological Surgery, EarlyView.
ABSTRACT Background Although prophylactic broad‐spectrum antibiotics can reduce postoperative complications after pancreaticoduodenectomy (PD), the optimal regimen remains uncertain. This study evaluated the impact of prophylactic cefepime (CFPM) on surgical site infection (SSI) and severe morbidity after PD with preoperative biliary drainage.
Genki Watanabe   +8 more
wiley   +1 more source

Surgical Outcomes of Sequential Robot‐Assisted Hepatobiliary–Pancreatic Surgery in a Single Operating Room: A Single‐Center Retrospective Analysis of a High‐Volume Center in Japan (TAKUMI‐6)

open access: yesAnnals of Gastroenterological Surgery, EarlyView.
This study investigated the surgical outcomes of sequential robot‐assisted hepatobiliary–pancreatic (HBP) in a single operating room. The outcomes and operating room timelines were comparable between the first and second cases. The median turnover time was 49 min, and the day‐shift completion success rate was 34.4%.
Tomokazu Fuji   +7 more
wiley   +1 more source

Can Machine Learning Reduce Unnecessary Surgeries? A Retrospective Analysis Using Threshold Optimization to Prevent Negative Appendectomies in Adults

open access: yesAnnals of Gastroenterological Surgery, EarlyView.
Threshold‐optimized machine learning models using routine clinical and laboratory data in 623 adults undergoing appendectomy. Logistic regression (AUC = 0.765) and random forest (AUC = 0.785) were the best‐performing models for appendicitis detection and complicated appendicitis prediction, respectively.
Ivan Males   +8 more
wiley   +1 more source

Home - About - Disclaimer - Privacy