一种新的交替联合纵向模型用于ICU后血红蛋白的预测
A Novel Alternating Joint Longitudinal Model for Post-ICU Hemoglobin Prediction
摘要：
贫血在ICU出院后的患者中很常见。然而，哪些患者会发展或从贫血中恢复仍不清楚。该人群中贫血的预测因再次入院而变得复杂，由于手术，输血或作为严重疾病的代表，再次入院可能对血红蛋白水平产生重大影响。因此，我们引入了一种新的贝叶斯联合纵向模型血红蛋白随着时间的推移，其中包括特定的参数影响入院和出院。这些影响本身取决于患者住院时的血红蛋白;因此，给定时间的血红蛋白是该患者在该时间之前的完整入院和出院史的函数。然而，由于入院或出院的影响并不取决于自身，该模型仍然是明确的。我们使用交叉验证对来自罗切斯特流行病学项目的6，876例患者的回顾性队列进行了验证，发现它准确地估计了血红蛋白，并预测了出院后30天内的贫血状态和再次入院，AUC分别为0.82和0.72。
英文摘要：
Anemia is common in patients post-ICU discharge. However, which patients will develop or recover from anemia remains unclear. Prediction of anemia in this population is complicated by hospital readmissions, which can have substantial impacts on hemoglobin levels due to surgery, blood transfusions, or being a proxy for severe illness. We therefore introduce a novel Bayesian joint longitudinal model for hemoglobin over time, which includes specific parametric effects for hospital admission and discharge. These effects themselves depend on a patient's hemoglobin at time of hospitalization; therefore hemoglobin at a given time is a function of that patient's complete history of admissions and discharges up until that time. However, because the effects of an admission or discharge do not depend on themselves, the model remains well defined. We validate our model on a retrospective cohort of 6,876 patients from the Rochester Epidemiology Project using cross-validation, and find it accurately estimates hemoglobin and predicts anemic status and hospital readmission in the 30 days post-discharge with AUCs of .82 and .72, respectively.
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