Lapidus Nathanael, Zhou Xianlong, Carrat Fabrice, Riou Bruno, Zhao Yan, Hejblum Gilles
Sorbonne Université, INSERM, Institut Pierre Louis D'Épidémiologie Et de Santé Publique, AP-HP, Hôpital Saint-Antoine, Unité de Santé Publique, 27 Rue Chaligny, 75571, Paris Cedex 12, France.
Emergency Center, Zhongnan Hospital of Wuhan University, 169 Donghu Road, Wuhan, 430071, Hubei, China.
Ann Intensive Care. 2020 Oct 16;10(1):135. doi: 10.1186/s13613-020-00749-6.
The average length of stay (LOS) in the intensive care unit (ICU_ALOS) is a helpful parameter summarizing critical bed occupancy. During the outbreak of a novel virus, estimating early a reliable ICU_ALOS estimate of infected patients is critical to accurately parameterize models examining mitigation and preparedness scenarios.
Two estimation methods of ICU_ALOS were compared: the average LOS of already discharged patients at the date of estimation (DPE), and a standard parametric method used for analyzing time-to-event data which fits a given distribution to observed data and includes the censored stays of patients still treated in the ICU at the date of estimation (CPE). Methods were compared on a series of all COVID-19 consecutive cases (n = 59) admitted in an ICU devoted to such patients. At the last follow-up date, 99 days after the first admission, all patients but one had been discharged. A simulation study investigated the generalizability of the methods' patterns. CPE and DPE estimates were also compared to COVID-19 estimates reported to date.
LOS ≥ 30 days concerned 14 out of the 59 patients (24%), including 8 of the 21 deaths observed. Two months after the first admission, 38 (64%) patients had been discharged, with corresponding DPE and CPE estimates of ICU_ALOS (95% CI) at 13.0 days (10.4-15.6) and 23.1 days (18.1-29.7), respectively. Series' true ICU_ALOS was greater than 21 days, well above reported estimates to date.
Discharges of short stays are more likely observed earlier during the course of an outbreak. Cautious unbiased ICU_ALOS estimates suggest parameterizing a higher burden of ICU bed occupancy than that adopted to date in COVID-19 forecasting models.
Support by the National Natural Science Foundation of China (81900097 to Dr. Zhou) and the Emergency Response Project of Hubei Science and Technology Department (2020FCA023 to Pr. Zhao).
重症监护病房的平均住院时间（ICU_ALOS）是一个有助于总结重症病床占用情况的参数。在新型病毒爆发期间，尽早估计感染患者可靠的ICU_ALOS对于准确参数化研究缓解措施和应对预案的模型至关重要。
比较了两种ICU_ALOS估计方法：估计日期（DPE）时已出院患者的平均住院时间，以及一种用于分析事件发生时间数据的标准参数方法，该方法将给定分布拟合到观察数据中，并包括估计日期时仍在ICU接受治疗患者的截尾住院时间（CPE）。在专门收治此类患者的ICU中，对一系列连续的所有COVID-19病例（n = 59）进行了方法比较。在首次入院99天后的最后随访日期，除1例患者外，所有患者均已出院。一项模拟研究调查了这些方法模式的普遍性。还将CPE和DPE估计值与迄今为止报告的COVID-19估计值进行了比较。
59例患者中有14例（24%）的住院时间≥30天，包括观察到的21例死亡患者中的8例。首次入院两个月后，38例（64%）患者已出院，相应的ICU_ALOS的DPE和CPE估计值（95%CI）分别为13.0天（10.4 - 15.6）和23.1天（18.1 - 29.7）。该系列病例的真实ICU_ALOS大于21天，远高于迄今为止报告的估计值。
在疫情爆发过程中，更有可能较早观察到短期住院患者的出院情况。谨慎且无偏倚的ICU_ALOS估计表明，与COVID-19预测模型迄今采用的参数相比，ICU床位占用负担更高。
中国国家自然科学基金（周博士，81900097）和湖北省科技厅应急响应项目（赵教授，2020FCA023）的支持。
