Lipids in Health and Disease (Apr 2024)

Novel anthropometric indicators of visceral obesity predict the severity of hyperlipidemic acute pancreatitis

  • Yi Zhu,
  • Yingbao Huang,
  • Houzhang Sun,
  • Lifang Chen,
  • Huajun Yu,
  • Liuzhi Shi,
  • Weizhi Xia,
  • Xuecheng Sun,
  • Yunjun Yang,
  • Hang Huang

DOI
https://doi.org/10.1186/s12944-024-02112-1
Journal volume & issue
Vol. 23, no. 1
pp. 1 – 10

Abstract

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Abstract Background Obesity substantially contributes to the onset of acute pancreatitis (AP) and influences its progression to severe AP. Although body mass index (BMI) is a widely used anthropometric parameter, it fails to delineate the distribution pattern of adipose tissue. To circumvent this shortcoming, the predictive efficacies of novel anthropometric indicators of visceral obesity, such as lipid accumulation products (LAP), cardiometabolic index (CMI), body roundness index (BRI), visceral adiposity index (VAI), A Body Shape Index (ABSI), and Chinese visceral adiposity index (CVAI) were examined to assess the severity of AP. Method The body parameters and laboratory indices of 283 patients with hyperlipidemic acute pancreatitis (HLAP) were retrospectively analysed, and the six novel anthropometric indicators of visceral obesity were calculated. The severity of HLAP was determined using the revised Atlanta classification. The correlation between the six indicators and HLAP severity was evaluated, and the predictive efficacy of the indicators was assessed using area under the curve (AUC). The differences in diagnostic values of the six indicators were also compared using the DeLong test. Results Patients with moderate to severe AP had higher VAI, CMI, and LAP than patients with mild AP (all P < 0.001). The highest AUC in predicting HLAP severity was observed for VAI, with a value of 0.733 and 95% confidence interval of 0.678–0.784. Conclusions This study demonstrated significant correlations between HLAP severity and VAI, CMI, and LAP indicators. These indicators, particularly VAI, which displayed the highest predictive power, were instrumental in forecasting and evaluating the severity of HLAP.