{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,16]],"date-time":"2026-09-16T01:28:13Z","timestamp":1789522093992,"version":"build-2803163510"},"reference-count":24,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2022,11,28]],"date-time":"2022-11-28T00:00:00Z","timestamp":1669593600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2022,11,28]],"date-time":"2022-11-28T00:00:00Z","timestamp":1669593600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Gastroenterol"],"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Background<\/jats:title><jats:p>Preoperative prediction of severe cholecystitis (SC), including acute gangrenous cholecystitis (AGC) and acute purulent cholecystitis (APC), as opposed to acute exacerbation of chronic cholecystitis (ACC), is of great significance, as SC is associated with high mortality rate.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>In this study, we retrospectively investigated medical records of 114 cholecystitis patients, treated in Shanghai No. 6 People\u2019s Hospital from February 2009 to July 2020. Gallbladder wall thickness (GBWT), indexes of blood routine examination, including white blood cell (WBC), alkaline phosphatase (ALP), the percentage of neutrophil, alanine transaminase (ALT), aspartate aminotransferase (AST), fibrinogen (FIB), gamma-glutamyl transferase, prothrombin time and total bilirubin were evaluated. One-way analysis of variance (ANOVA) was used to evaluate significant differences between a certain kind of SC and ACC to select a prediction index for each kind of SC. Receiver operating characteristic (ROC) curve analysis was conducted to identify the prediction effectiveness of these indexes and their optimal cut-off values.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Higher WBC and lower ALP were associated with AGC diagnosis (<jats:italic>P<\/jats:italic>\u2009&lt;\u20090.05). Higher percentage of neutrophils was indicative of APC and AGC, while higher GBWT was significantly associated with APC diagnosis (<jats:italic>P<\/jats:italic>\u2009&lt;\u20090.05) The optimal cut-off values for these indexes were established at 11.1*10<jats:sup>9<\/jats:sup>\/L (OR: 5.333, 95% CI 2.576\u201310.68,<jats:italic>P<\/jats:italic>\u2009&lt;\u20090.0001, sensitivity: 72.73%, specificity: 66.67%), 79.75% (OR: 5.735, 95% CI 2.749\u201312.05,<jats:italic>P<\/jats:italic>\u2009&lt;\u20090.0001, sensitivity: 77.92%, specificity: 61.9%) and 5.5\u00a0mm (OR: 22, 95% CI 4.757\u201383.42,<jats:italic>P<\/jats:italic>\u2009&lt;\u20090.0001, sensitivity: 78.57%, specificity: 85.71%), respectively.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>We established a predictive model for the differentiations of APC and AGC from ACC using clinical indexes, such as GBWT, the percentage of neutrophil and WBC, and determined cut-off values for these indexes based on ROC curves. Index values exceeding these cut-off values will allow to diagnose patients as APC and AGC, as opposed to a diagnosis of ACC.<\/jats:p><\/jats:sec>","DOI":"10.1186\/s12876-022-02582-6","type":"journal-article","created":{"date-parts":[[2022,11,28]],"date-time":"2022-11-28T04:30:16Z","timestamp":1669609816000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Prognostic clinical indexes for prediction of acute gangrenous cholecystitis and acute purulent cholecystitis"],"prefix":"10.1186","volume":"22","author":[{"given":"Jie","family":"Chen","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qi","family":"Gao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xinyu","family":"Huang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yingqi","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2022,11,28]]},"reference":[{"key":"2582_CR1","doi-asserted-by":"publisher","first-page":"1479","DOI":"10.1007\/s11605-020-04707-2","volume":"25","author":"M Bouassida","year":"2021","unstructured":"Bouassida M, Madhioub M, Kallel Y, Zribi S, Slama H, Mighri MM, et al. 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