Development and Validation of a Clinical Predictive Nomogram for Assessing the Risk of Recurrence of Acute Pancreatitis in Combined Hypertriglyceridemia
Shuaiyong Wen, Yu Zhang, Guijie Zhao, Kun Zhang, Yunfeng Cui
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引用次数: 0
Abstract
Background
The objective of this study is to develop and validate a new nomogram-based scoring system for anticipating the recurrence of acute pancreatitis (AP) in combined hypertriglyceridemia (HTG).
Methods
A total of 292 patients diagnosed with AP combined with HTG participated in this research. Among them, 201 patients meeting the inclusion criteria were randomly divided into training and validation sets at a ratio of 7:3. Clinical data were collected for all patients. In the training set, predictive indicators were chosen through backward stepwise multivariable logistic regression analysis. Subsequently, a nomogram was developed based on the selected indicators. Finally, the model’s performance was validated in both the training and validation sets.
Results
By employing backward stepwise multivariable logistic regression analysis, we identified diabetes, gallstones, alcohol consumption, and triglyceride levels as predictive indicators. Subsequently, a clinical nomogram that incorporates these four independent risk factors was constructed. Model validation demonstrated an AUC of 0.726 (95% CI 0.644–0.809) in the training set and an AUC of 0.712 (95% CI 0.583–0.842) in the validation set, indicating a good discriminative ability. The Hosmer–Lemeshow test yielded P-values of 0.882 and 0.536 in the training and validation sets, respectively, suggesting good calibration. Calibration curves further confirmed good agreement. Ultimately, decision curve analysis (DCA) emphasized the clinical utility of our model.
Conclusion
We have developed a nomogram for predicting the recurrence of AP combined with HTG in patients, and this nomogram demonstrates good discriminative ability, calibration, and clinical utility. This tool holds the potential to assist clinicians in offering more personalized treatment strategies for AP combined with HTG.
背景本研究旨在开发和验证一种新的基于提名图的评分系统,用于预测合并高甘油三酯血症(HTG)的急性胰腺炎(AP)的复发。其中,符合纳入标准的 201 例患者按 7:3 的比例随机分为训练集和验证集。研究人员收集了所有患者的临床数据。在训练集中,通过逆向逐步多变量逻辑回归分析选出了预测指标。随后,根据所选指标建立了一个提名图。结果 通过后向逐步多变量逻辑回归分析,我们确定了糖尿病、胆结石、饮酒和甘油三酯水平作为预测指标。随后,我们构建了包含这四个独立风险因素的临床提名图。模型验证表明,训练集的AUC为0.726(95% CI 0.644-0.809),验证集的AUC为0.712(95% CI 0.583-0.842),显示出良好的判别能力。通过 Hosmer-Lemeshow 检验,训练集和验证集的 P 值分别为 0.882 和 0.536,表明校准效果良好。校准曲线进一步证实了良好的一致性。最终,决策曲线分析(DCA)强调了我们模型的临床实用性。结论我们开发了一种预测 AP 合并 HTG 患者复发的提名图,该提名图显示了良好的鉴别能力、校准性和临床实用性。该工具有望帮助临床医生为 AP 合并 HTG 患者提供更加个性化的治疗策略。
期刊介绍:
Digestive Diseases and Sciences publishes high-quality, peer-reviewed, original papers addressing aspects of basic/translational and clinical research in gastroenterology, hepatology, and related fields. This well-illustrated journal features comprehensive coverage of basic pathophysiology, new technological advances, and clinical breakthroughs; insights from prominent academicians and practitioners concerning new scientific developments and practical medical issues; and discussions focusing on the latest changes in local and worldwide social, economic, and governmental policies that affect the delivery of care within the disciplines of gastroenterology and hepatology.