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Background <p>Acute pancreatitis (AP) necessitates accurate severity and prognosis assessment. While the Computed Tomography Severity Index (CTSI) is widely used, its time-dependent predictive value remains unclarified. This meta-analysis compares the predictive efficacy of CTSI across assessment times for AP outcomes.</p> Methods <p>Systematic searches were performed in PubMed, Cochrane, Embase, and Web of Science. Literature was collated by using EndNote 20. Methodological quality was assessed using QUADAS-2. Bivariate meta-analyses were conducted with Stata 16 and Meta-Disc 1.4.</p> Results <p>Analysis of 28 studies (<i>n</i> = 5,419) revealed significant time-dependent variations: CTSI achieved optimal sensitivity for severity prediction at ≤ 48&#xa0;h (0.84, 95%CI 0.78–0.89) with specificity 0.79 (0.76–0.82), and peak sensitivity for organ failure at ≤ 48&#xa0;h (0.90, 0.82–0.95) though with moderate specificity (0.52, 0.48–0.57). Mortality prediction showed the highest sensitivity at ≤ 72&#xa0;h (0.89, 0.74–0.97), despite suboptimal specificity (0.65, 0.61–0.68). Pancreatic necrosis detection demonstrated superior accuracy at &gt; 72&#xa0;h (sensitivity 0.91, 0.84–0.95; specificity 0.82, 0.79–0.85). The pooled area under the receiver operating characteristic curve values with 95% CI for overall predictive performance were: severity, 0.85 (0.82–0.88); organ failure, 0.86 (0.82–0.88); mortality, 0.85 (0.81–0.88); and pancreatic necrosis, 0.94 (0.99 − 0.96).</p> Conclusion <p>CTSI exhibits distinct temporal predictive patterns: ≤48&#xa0;h assessments optimise early evaluation of severity/organ failure, ≤ 72&#xa0;h scans best predict mortality, while delayed imaging (&gt; 72&#xa0;h) maximises pancreatic necrosis accuracy at the expense of clinical timeliness. Future research must standardise imaging timepoints, integrate CTSI with physiological biomarkers, and develop dynamic assessment models to resolve discrepancies in anatomical-pathophysiological prognostic factors in AP management.</p>

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Comparison of the predictive value of different assessment times in the severity and prognostic outcomes of CTSI in patients with acute pancreatitis: a systematic review and meta-analysis

  • 期刊论文

  • 发表日期：

    2025年11月20日

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  • Shan Huang,
  • Xinwei Liu,
  • Longyan Zhu,
  • Kun Ai

摘要

Background

Acute pancreatitis (AP) necessitates accurate severity and prognosis assessment. While the Computed Tomography Severity Index (CTSI) is widely used, its time-dependent predictive value remains unclarified. This meta-analysis compares the predictive efficacy of CTSI across assessment times for AP outcomes.

Methods

Systematic searches were performed in PubMed, Cochrane, Embase, and Web of Science. Literature was collated by using EndNote 20. Methodological quality was assessed using QUADAS-2. Bivariate meta-analyses were conducted with Stata 16 and Meta-Disc 1.4.

Results

Analysis of 28 studies (n = 5,419) revealed significant time-dependent variations: CTSI achieved optimal sensitivity for severity prediction at ≤ 48 h (0.84, 95%CI 0.78–0.89) with specificity 0.79 (0.76–0.82), and peak sensitivity for organ failure at ≤ 48 h (0.90, 0.82–0.95) though with moderate specificity (0.52, 0.48–0.57). Mortality prediction showed the highest sensitivity at ≤ 72 h (0.89, 0.74–0.97), despite suboptimal specificity (0.65, 0.61–0.68). Pancreatic necrosis detection demonstrated superior accuracy at > 72 h (sensitivity 0.91, 0.84–0.95; specificity 0.82, 0.79–0.85). The pooled area under the receiver operating characteristic curve values with 95% CI for overall predictive performance were: severity, 0.85 (0.82–0.88); organ failure, 0.86 (0.82–0.88); mortality, 0.85 (0.81–0.88); and pancreatic necrosis, 0.94 (0.99 − 0.96).

Conclusion

CTSI exhibits distinct temporal predictive patterns: ≤48 h assessments optimise early evaluation of severity/organ failure, ≤ 72 h scans best predict mortality, while delayed imaging (> 72 h) maximises pancreatic necrosis accuracy at the expense of clinical timeliness. Future research must standardise imaging timepoints, integrate CTSI with physiological biomarkers, and develop dynamic assessment models to resolve discrepancies in anatomical-pathophysiological prognostic factors in AP management.