数字连续肠音对危重急性胃肠损伤患者的诊断价值:一项前瞻性观察研究。

IF 1.8 4区 医学 Q3 GASTROENTEROLOGY & HEPATOLOGY
Yuan-Hui Sun, Yun-Yun Song, Sha Sha, Qi Sun, Deng-Chao Huang, Lan Gao, Hao Li, Qin-Dong Shi
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引用次数: 0

摘要

背景:急性胃肠道损伤(AGI)在重症监护病房(ICU)常见,严重影响重症患者的预后。欧洲重症监护医学学会提出的四级评分系统是主观的,缺乏特异性。因此,需要一种更客观的方法来评估和确定该患者群体的胃肠功能障碍等级。数字连续监测肠道声音和一些生物标志物可以改变胃肠道损伤。我们的目标是通过连续监测肠道声音和生物标志物来开发AGI模型。目的:建立一种通过监测肠道声音和生物标志物来鉴别AGI的模型。方法:我们对某三级医院ICU的75例患者进行了前瞻性观察研究,以建立AGI的诊断模型。我们记录了他们的肠道声音,评估了AGI分级,收集了临床数据,并测量了生物标志物。我们使用误判概率和留一交叉验证来评估模型。结果:平均肠音率和瓜氨酸水平是AGI的独立危险因素。胃泌素被认为是AGI严重程度的一个危险因素。与AGI相关的其他因素包括平均肠音率、振幅、间隔时间、序期器官衰竭评估评分、急性生理和慢性健康评估II评分、血小板计数、总蛋白水平、血气氢电位(pH)和碳酸氢盐(HCO3 -)水平。构建了两个判别模型,错分类概率均< 0.1。留一交叉验证正确分类69.8%的病例。结论:我们的AGI诊断模型代表了一种潜在的有效的临床AGI分级方法,有望成为AGI的客观诊断标准。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Diagnostic value of digital continuous bowel sounds in critically ill patients with acute gastrointestinal injury: A prospective observational study.

Background: Acute gastrointestinal injury (AGI) is common in intensive care unit (ICU) and worsens the prognosis of critically ill patients. The four-point grading system proposed by the European Society of Intensive Care Medicine is subjective and lacks specificity. Therefore, a more objective method is required to evaluate and determine the grade of gastrointestinal dysfunction in this patient population. Digital continuous monitoring of bowel sounds and some biomarkers can change in gastrointestinal injuries. We aimed to develop a model of AGI using continuous monitoring of bowel sounds and biomarkers.

Aim: To develop a model to discriminate AGI by monitoring bowel sounds and biomarker indicators.

Methods: We conducted a prospective observational study with 75 patients in an ICU of a tertiary-care hospital to create a diagnostic model for AGI. We recorded their bowel sounds, assessed AGI grading, collected clinical data, and measured biomarkers. We evaluated the model using misjudgment probability and leave-one-out cross-validation.

Results: Mean bowel sound rate and citrulline level are independent risk factors for AGI. Gastrin was identified as a risk factor for the severity of AGI. Other factors that correlated with AGI include mean bowel sound rate, amplitude, interval time, Sequential Organ Failure Assessment score, Acute Physiology and Chronic Health Evaluation II score, platelet count, total protein level, blood gas potential of hydrogen (pH), and bicarbonate (HCO3 -) level. Two discriminant models were constructed with a misclassification probability of < 0.1. Leave-one-out cross-validation correctly classified 69.8% of the cases.

Conclusion: Our AGI diagnostic model represents a potentially effective approach for clinical AGI grading and holds promise as an objective diagnostic standard for AGI.

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