预测患者退学:Helicobacter pylori根除疗法后的随访损失的名图
Xiao Zhao1, Xiao She1, Haiyan Yang1
1Department of Gastroenterology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China.
一个新的诺米图预测了Helicobacter pylori根除过程中患者的随访损失 (LTFU). 该工具识别高风险个体,旨在提高这一全球健康问题的治疗成功率.
科学领域:
- 胃肠病学 胃肠病学
- 公共卫生 公共卫生
- 医疗信息学 医疗信息学
背景情况:
- 杆菌感染是全球重要的健康问题,特别是在发展中国家.
- 消灭H. pylori对于预防胃癌至关重要,但面临着抗生素耐药性和患者随访损失 (LTFU) 等挑战.
- LTFU严重破坏了H. pylori根除疗法的成功.
研究的目的:
- 为了确定与H. pylori根除后的LTFU相关的风险因素.
- 开发一种可预测的诺姆图,用于评估在接受H. pylori根除的患者中LTFU风险.
主要方法:
- 一项前性队列研究招募了以前没有接受过治疗的患者.
- 使用LASSO回归和后勤回归来开发LTFU的预测名录.
- 使用AUC,校准和决策曲线分析 (DCA) 验证了模型性能.
主要成果:
- 确定了六个LTFU的独立预测因素:BMI>30 kg/m2,是政府雇员,离医院的距离>10公里,酒精消耗,更长的门诊等待时间,以及缺乏随访意识.
- 诺米图实现了高预测准确性,在训练组中AUC为0.885在测试组中为0.862.
- 决策曲线分析表明,名图作为预测LTFU风险的辅助工具具有良好的临床效用.
结论:
- 一个经过验证的诺姆图有效地预测了在接受H. pylori根除的患者中LTFU风险.
- 这种预测工具可以帮助改善H. pylori感染的治疗管理和治疗结果.
- 解决已识别的风险因素可能有助于减轻LTFU并提高根除成功率.
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