Department of Gastroenterology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China.
Department of Gastroenterology and Hepatology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China.
Biomed Res Int. 2017;2017:1648385. doi: 10.1155/2017/1648385. Epub 2017 Aug 22.
Early prediction of disease severity of acute pancreatitis (AP) would be helpful for triaging patients to the appropriate level of care and intervention. The aim of the study was to develop a model able to predict Severe Acute Pancreatitis (SAP).
A total of 647 patients with AP were enrolled. The demographic data, hematocrit, High-Density Lipoprotein Cholesterol (HDL-C) determinant at time of admission, Blood Urea Nitrogen (BUN), and serum creatinine (Scr) determinant at time of admission and 24 hrs after hospitalization were collected and analyzed statistically.
Multivariate logistic regression indicated that HDL-C at admission and BUN and Scr at 24 hours (hrs) were independently associated with SAP. A logistic regression function (LR model) was developed to predict SAP as follows: -2.25-0.06 HDL-C (mg/dl) at admission + 0.06 BUN (mg/dl) at 24 hours + 0.66 Scr (mg/dl) at 24 hours. The optimism-corrected c-index for LR model was 0.832 after bootstrap validation. The area under the receiver operating characteristic curve for LR model for the prediction of SAP was 0.84.
The LR model consists of HDL-C at admission and BUN and Scr at 24 hours, representing an additional tool to stratify patients at risk of SAP.
急性胰腺炎（AP）严重程度的早期预测有助于将患者分诊到适当级别的治疗和干预。本研究的目的是开发一种能够预测重症急性胰腺炎（SAP）的模型。
共纳入 647 例 AP 患者。收集并统计分析患者入院时的人口统计学数据、红细胞压积、高密度脂蛋白胆固醇（HDL-C）、入院时和住院 24 小时后的血尿素氮（BUN）和血清肌酐（Scr）。
多变量逻辑回归表明，入院时的 HDL-C 以及入院 24 小时时的 BUN 和 Scr 与 SAP 独立相关。建立了一个逻辑回归函数（LR 模型）来预测 SAP，如下所示：入院时-2.25-0.06 HDL-C（mg/dl）+入院 24 小时时 0.06 BUN（mg/dl）+入院 24 小时时 0.66 Scr（mg/dl）。经 bootstrap 验证后，LR 模型的校正后 optimism-corrected c-index 为 0.832。LR 模型预测 SAP 的受试者工作特征曲线下面积为 0.84。
LR 模型由入院时的 HDL-C 和入院 24 小时时的 BUN 和 Scr 组成，是一种能够对 SAP 风险患者进行分层的附加工具。
