A Clinical and Imaging-based Model for Distinguishing Mild From Moderately Severe/Severe Hypertriglyceridemic Acute Pancreatitis: Development and Validation.

IF 1.3 4区 医学 Q4 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
Yixiu Hao, Jiajun Feng, Wenjuan He, Yongshun Wu, Ying Ma, Honggang Xu
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引用次数: 0

Abstract

Background: Hypertriglyceridemic acute pancreatitis (HTG-AP) is a distinct subtype of acute pancreatitis with a wide spectrum of clinical severity, ranging from mild to moderately severe or severe disease. Timely identification of patients at higher risk is essential for informing early clinical decisions and improving outcomes. However, reliable tools specifically designed to stratify HTG-AP severity remain limited.

Objective: To develop and validate a predictive model for distinguishing mild from moderately severe/severe hypertriglyceridemic acute pancreatitis (HTG-AP) using routine clinical and imaging parameters.

Methods: This retrospective study included 106 patients diagnosed with HTG-AP at Guangzhou First People's Hospital from January 2018 to April 2023. Patients were categorized into mild (HTG-MAP) and moderately severe/severe (HTG-MSAP/SAP) groups based on the revised Atlanta classification. Clinical data, laboratory results, and imaging findings, including peak C-reactive protein (CRP), serum calcium levels, and Modified CT Severity Index (MCTSI) scores, were analyzed. Univariate and multivariate logistic regression analyses were performed to identify independent predictors of disease severity. Model performance was assessed through 10-fold cross-validation and bootstrap calibration.

Results: Among the 106 patients (median age: 38 y; 82.1% male), 46 had HTG-MAP and 60 had HTG-MSAP/SAP. Multivariate analysis identified peak CRP (OR: 1.0082, P=0.011), serum calcium (OR: 0.05, P=0.014), and MCTSI score ≥6 (OR: 4.91, P=0.008) as independent predictors of severe disease. The final logistic regression model demonstrated excellent discrimination, with an AUC of 0.900 in the overall cohort and a mean cross-validated AUC of 0.87. Calibration was satisfactory (Hosmer-Lemeshow P=0.774), and overall diagnostic accuracy reached 84.91%.

Conclusions: The proposed model, incorporating peak CRP, serum calcium, and MCTSI score, effectively distinguishes between HTG-MAP and HTG-MSAP/SAP. Compared with conventional scoring systems such as Bedside Index for Severity in Acute Pancreatitis (BISAP), it demonstrates superior specificity and overall diagnostic accuracy, providing clinicians with a practical tool for risk stratification and clinical decision-making in HTG-AP.

区分轻度和中重度/重度高甘油三酯血症急性胰腺炎的临床和影像学模型:发展和验证。
背景:高甘油三酯血症急性胰腺炎(HTG-AP)是一种独特的急性胰腺炎亚型,具有广泛的临床严重程度,从轻度到中重度或重度疾病不等。及时识别高风险患者对于告知早期临床决策和改善结果至关重要。然而,专门设计用于HTG-AP严重程度分层的可靠工具仍然有限。目的:建立并验证一种利用常规临床和影像学参数区分轻、中重度/重度高甘油三酯血症急性胰腺炎(HTG-AP)的预测模型。方法:回顾性研究广州市第一人民医院2018年1月至2023年4月诊断为HTG-AP的106例患者。根据修订后的亚特兰大分级将患者分为轻度(HTG-MAP)和中重度/重度(HTG-MSAP/SAP)组。分析临床资料、实验室结果和影像学表现,包括c反应蛋白(CRP)峰值、血清钙水平和改良CT严重程度指数(MCTSI)评分。进行单因素和多因素logistic回归分析,以确定疾病严重程度的独立预测因子。通过10倍交叉验证和自举校准评估模型性能。结果:106例患者(中位年龄:38岁;男性占82.1%),HTG-MAP 46例,HTG-MSAP/SAP 60例。多因素分析发现CRP峰值(OR: 1.0082, P=0.011)、血清钙(OR: 0.05, P=0.014)和MCTSI评分≥6 (OR: 4.91, P=0.008)是严重疾病的独立预测因子。最终的逻辑回归模型表现出良好的辨别能力,整个队列的AUC为0.900,平均交叉验证的AUC为0.87。校正结果令人满意(Hosmer-Lemeshow P=0.774),总体诊断准确率达到84.91%。结论:该模型结合CRP峰值、血清钙和MCTSI评分,可有效区分HTG-MAP和HTG-MSAP/SAP。与传统的评分系统如BISAP(床边严重程度指数)相比,它具有更高的特异性和总体诊断准确性,为临床医生提供了HTG-AP风险分层和临床决策的实用工具。
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来源期刊
CiteScore
2.50
自引率
0.00%
发文量
230
审稿时长
4-8 weeks
期刊介绍: The mission of Journal of Computer Assisted Tomography is to showcase the latest clinical and research developments in CT, MR, and closely related diagnostic techniques. We encourage submission of both original research and review articles that have immediate or promissory clinical applications. Topics of special interest include: 1) functional MR and CT of the brain and body; 2) advanced/innovative MRI techniques (diffusion, perfusion, rapid scanning); and 3) advanced/innovative CT techniques (perfusion, multi-energy, dose-reduction, and processing).
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