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PloS one · 2019

Diagnostic utility of CT for small bowel obstruction: Systematic review and meta-analysis.

СтатьяМетаанализСистематический обзорНазвание и аннотация: Перевод пока не подготовлен
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Li Zhengyan, Zhang Ling, Liu Xijiao, Yuan Fang, Song Bin

Аннотация

BACKGROUND: To perform a systematic review and meta-analysis evaluating the diagnostic performance of computed tomography (CT) for small bowel obstruction (SBO), including diagnostic accuracy, ischemia, predicting surgical intervention, etiology and transition point.

METHODS: PubMed/MEDLINE and related databases were searched for research articles published from their inception through August 2018. Findings were pooled using bivariate random-effects and summary receiver operating characteristic curve models. Meta-regression and subgroup analyses were performed to evaluate whether publication year, patient age, enhanced CT, slice thickness and pathogenesis affected classification accuracy.

RESULTS: In total, 45 studies with a total of 4004 patients were included in the analysis. The pooled sensitivity and specificity of CT for SBO were 91% (95% confidence interval [CI]: 84%, 95%) and 89% (95% CI: 81%, 94%), respectively, and there were no differences in the subgroup analyses of age, publication year, enhanced CT and slice thickness. For ischemia, the pooled sensitivity and specificity was 82% (95% CI: 67%, 91%) and 92% (95% CI: 86%, 95%), respectively. No difference was found between enhanced and unenhanced CT based on subgroup analysis; however, high sensitivity was found in adhesive SBO compared with routine causes (96% vs. 78%, P = 0.03). The pooled sensitivity and specificity for predicting surgical intervention were 87% and 73%, respectively. The accuracy for etiology of adhesions, hernia and tumor was 95%, 70% and 82%, respectively. In addition, the pooled sensitivity and specificity for transition point was 92% and 77%, respectively.

CONCLUSIONS: CT has considerable accuracy in diagnosis of SBO, ischemia, predicting surgical intervention, etiology and transition point.

Предметные рубрики MeSH

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

Реквизиты и контакты