Browsing by Author "Karabulut, Ali"

Filter results by typing the first few letters
Now showing 1 - 1 of 1
  • Thumbnail Image
    Article
    Citation - WoS: 2
    Citation - Scopus: 3
    Assessing the Effectiveness of Acs Surgical Risk Calculator Versus P-Possum in Predicting Mortality and Morbidity for Major Hepatobiliary Surgery: an Observational Study
    (Lippincott williams & wilkins, 2024) Karabulut, Ali; Umman, Veysel; Oral, Güneş; Erginoz, Ergin; Çarkman, Mehmet Sinan
    Risk assessment is difficult yet would provide valuable data for both the surgeons and the patients in major hepatobiliary surgeries. An ideal risk calculator should improve workflow through efficient, timely, and accurate risk stratification. The American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) surgical risk calculator (SRC) and Portsmouth Physiological and Operative Severity Score for the enUmeration of Mortality and Morbidity (P-POSSUM) are surgical risk stratification tools used to assess postoperative morbidity. In this study, preoperative data from 300 patients undergoing major hepatobiliary surgeries performed at a single tertiary university hospital were retrospectively collected from electronic patient records and entered into the ACS-SRC and P-POSSUM systems, and the resulting risk scores were calculated and recorded accordingly. The ACS-NSQIP-M1 (C-statistics = 0.725) and M2 (C-statistics = 0.791) models showed better morbidity discrimination ability than P-POSSUM-M1 (C-statistics = 0.672) model. The P-POSSUM-M2 (C-statistics = 0.806) model showed better differentiation success in morbidity than other models. The ACS-NSQIP-M1 (C-statistics = 0.888) and M2 (C-statistics = 0.956) models showed better mortality discrimination than P-POSSUM-M1 (C-statistics = 0.776) model. The P-POSSUM-M2 (C-statistics = 0.948) model showed better mortality differentiation success than the ACS-NSQIP-M1 and P-POSSUM-M1 models. The use of ACS-SRC and P-POSSUM calculators for major hepatobiliary surgeries offers quantitative data to assess risks for both the surgeon and the patient. Integrating these calculators into preoperative evaluation practices can enhance decision-making processes for patients. The results of the statistical analyses indicated that the P-POSSUM-M2 model for morbidity and the ACS-NSQIP-M2 model for mortality exhibited superior overall performance.