与临床特征相结合的C-反应蛋白与淋巴细胞比率,构建了一个预测模型,用于预测由于胃的上部胃肠道出血
Hong Song1, Juan Yang2, Jiao Li3
1Department of Gerontology, Taiyuan Central Hospital, Taiyuan City, Shanxi Province, China.
Clinics (Sao Paulo, Brazil)
|April 24, 2025
概括
使用C-反应对淋巴细胞比率 (CLR) 和临床因素的新预测模型准确地预测了胃潰瘍引起的上胃肠道出血 (UGIB). 该工具有助于预防UGIB,并指导治疗计划.
科学领域:
- 胃肠病学 胃肠病学
- 内部医学 内部医学
- 医学诊断 医学诊断 医学诊断
背景情况:
- 胃潰瘍疾病 (PUD) 是一種常見的疾病.
- 上部胃肠道出血 (UGIB) 是PUD的一个重要并发症.
- 准确预测UGIB风险对于患者管理至关重要.
研究的目的:
- 开发和验证在患有胃潰瘍的患者中UGIB的预测模型.
- 评估使用C-反应对淋巴细胞比率 (CLR) 和临床特征用于UGIB预测的可行性和准确性.
- 在胃潰瘍疾病的背景下,找出UGIB的獨立風險因素.
主要方法:
- 来自146名胃患者的临床数据的前性收集.
- 多因素后勤回归和对线性分析,以确定风险因素.
- 使用ROC曲线,AUC,校准曲线和决策曲线分析构建和验证预测模型.
主要成果:
- 杆菌感染,阶段,NSAID使用,中性粒细胞与淋巴细胞比率 (NLR) 和CLR被确定为UGIB的独立风险因素.
- 开发的预测模型显示出高预测值,曲线下的面积 (AUC) 为0.921.
- 该模型显示了良好的准确性,与匹配的校准曲线和显著的临床应用价值.
结论:
- 结合CLR和临床特征的预测模型是有效的,用于识别患有胃引起的UGIB风险的患者.
- 这个模型可以帮助临床医生制定积极的治疗策略,以预防UGIB.
- 这些发现强调了随时可用的临床参数和炎症标记在预测胃病的严重并发症的有用性.
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