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鉴定急性胰腺炎感染性坏死的早期预测因子。

Identification of early predictors for infected necrosis in acute pancreatitis.

机构信息

Department of Medicine A, University Medicine Greifswald, Ferdinand-Sauerbruch-Straße, 17475, Greifswald, Germany.

Institute of Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, Greifswald, Germany.

出版信息

BMC Gastroenterol. 2022 Sep 3;22(1):405. doi: 10.1186/s12876-022-02490-9.

Abstract

BACKGROUND

In acute pancreatitis, secondary infection of pancreatic necrosis is a complication that mostly necessitates interventional therapy. A reliable prediction of infected necrotizing pancreatitis would enable an early identification of patients at risk, which however, is not possible yet.

METHODS

This study aims to identify parameters that are useful for the prediction of infected necrosis and to develop a prediction model for early detection. We conducted a retrospective analysis from the hospital information and reimbursement data system and screened 705 patients hospitalized with diagnosis of acute pancreatitis who underwent contrast-enhanced computed tomography and additional diagnostic puncture or drainage of necrotic collections. Both clinical and laboratory parameters were analyzed for an association with a microbiologically confirmed infected pancreatic necrosis. A prediction model was developed using a logistic regression analysis with stepwise inclusion of significant variables. The model quality was tested by receiver operating characteristics analysis and compared to single parameters and APACHE II score.

RESULTS

We identified a total of 89 patients with necrotizing pancreatitis, diagnosed by computed tomography, who additionally received biopsy or drainage. Out of these, 59 individuals had an infected necrosis. Eleven parameters showed a significant association with an infection including C-reactive protein, albumin, creatinine, and alcoholic etiology, which were independent variables in a predictive model. This model showed an area under the curve of 0.819, a sensitivity of 0.692 (95%-CI [0.547-0.809]), and a specificity of 0.840 (95%-CI [0.631-0.947]), outperforming single laboratory markers and APACHE II score. Even in cases of missing values predictability was reliable.

CONCLUSION

A model consisting of a few single blood parameters and etiology of pancreatitis might help for differentiation between infected and non-infected pancreatic necrosis and assist medical therapy in acute necrotizing pancreatitis.

摘要

背景

在急性胰腺炎中,胰腺坏死的继发感染是一种需要介入治疗的并发症。然而,目前还无法可靠地预测感染性坏死性胰腺炎,因此无法早期识别高危患者。

方法

本研究旨在确定有助于预测感染性坏死的参数,并开发早期检测的预测模型。我们从医院信息和报销数据系统中进行回顾性分析,筛选了 705 名因急性胰腺炎住院且接受过增强 CT 检查和胰腺坏死区额外诊断性穿刺或引流的患者。分析了临床和实验室参数与微生物学证实的感染性胰腺坏死的相关性。使用逐步纳入有意义变量的逻辑回归分析来建立预测模型。通过接受者操作特征分析来测试模型质量,并与单个参数和 APACHE II 评分进行比较。

结果

我们总共确定了 89 名经 CT 诊断为坏死性胰腺炎且接受了活检或引流的患者,其中 59 名患者患有感染性坏死。11 个参数与感染有显著相关性,包括 C 反应蛋白、白蛋白、肌酐和酒精性病因,这些参数是预测模型中的独立变量。该模型的曲线下面积为 0.819,敏感性为 0.692(95%CI [0.547-0.809]),特异性为 0.840(95%CI [0.631-0.947]),优于单个实验室标志物和 APACHE II 评分。即使在缺失值的情况下,预测能力也是可靠的。

结论

由几个单一的血液参数和胰腺炎病因组成的模型可能有助于区分感染性和非感染性胰腺坏死,并有助于急性坏死性胰腺炎的治疗。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/22f2/9440524/43a8d5695497/12876_2022_2490_Fig1_HTML.jpg

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