一个预测模型,用于识别患有肝硬化患者中药物坚持率低的预测模型
Na Wang1, Pei Li1, Dandan Suo1
1Department of Infectious Diseases, Tangdu Hospital, Air Force Medical University, Xi'an, People's Republic of China.
这项研究确定了肝硬化患者药物坚持度较低的关键预测因素,开发了一个名谱,以帮助临床医生有效预测和管理不坚持的风险.
科学领域:
- 肝病学和胃肠道学
- 临床药房 临床药房
- 在医疗保健中的预测建模.
背景情况:
- 药物坚持对于治疗肝硬化至关重要,但预测不坚持仍然具有挑战性.
- 识别新的风险因素和开发预测工具可以改善患者的治疗结果.
研究的目的:
- 在一大批肝硬化患者中确定低药物坚持的新风险预测因子.
- 为个性化风险评估构建一个适用的预测模型.
主要方法:
- 分析了460名肝硬化患者的队列,使用问卷收集有关人口统计,疾病严重程度,知识,社会支持,自我照顾和药物负担的数据.
- 单变量和多变量逻辑回归确定了预测因素,从而构建了一个名ogram.
- 模型性能使用决策曲线分析,ROC曲线,Brier分数和平均平方误差进行评估,并用于内部验证.
主要成果:
- 74.78%的患者表现出良好的或中度的药物坚持.
- 不遵守的关键风险因素包括年轻 (≤50),教育/收入低,疾病持续时间短 (<10年),Child-Pugh类低,疾病知识差,社会支持低,自我护理机构低,药物负担高.
- 诺米图表表现出良好的校准和区分 (AUC = 0.938),Brier分数为0.14和MSE为0.03,表明没有过度拟合.
结论:
- 这项研究成功地确定了肝硬化患者药物坚持率低的预测因素.
- 一个经过验证的名图为临床医生提供了一种简单,精确的工具来识别高风险患者.
- 早期识别允许及时干预,以改善药物坚持和患者管理.
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