Department of Statistics and Operations Research, Universidad de Valladolid, Valladolid, Spain.
MRC-Biostatistics Unit, University of Cambridge, Cambridge, United Kingdom.
PLoS One. 2021 Sep 20;16(9):e0257613. doi: 10.1371/journal.pone.0257613. eCollection 2021.
This paper analyses COVID-19 patients' dynamics during the first wave in the region of Castilla y León (Spain) with around 2.4 million inhabitants using multi-state competing risk survival models. From the date registered as the start of the clinical process, it is assumed that a patient can progress through three intermediate states until reaching an absorbing state of recovery or death. Demographic characteristics, epidemiological factors such as the time of infection and previous vaccinations, clinical history, complications during the course of the disease and drug therapy for hospitalised patients are considered as candidate predictors. Regarding risk factors associated with mortality and severity, consistent results with many other studies have been found, such as older age, being male, and chronic diseases. Specifically, the hospitalisation (death) rate for those over 69 is 27.2% (19.8%) versus 5.3% (0.7%) for those under 70, and for males is 14.5%(7%) versus 8.3%(4.6%)for females. Among patients with chronic diseases the highest rates of hospitalisation are 26.1% for diabetes and 26.3% for kidney disease, while the highest death rate is 21.9% for cerebrovascular disease. Moreover, specific predictors for different transitions are given, and estimates of the probability of recovery and death for each patient are provided by the model. Some interesting results obtained are that for patients infected at the end of the period the hazard of transition from hospitalisation to ICU is significatively lower (p < 0.001) and the hazard of transition from hospitalisation to recovery is higher (p < 0.001). For patients previously vaccinated against pneumococcus the hazard of transition to recovery is higher (p < 0.001). Finally, internal validation and calibration of the model are also performed.
本文使用多状态竞争风险生存模型分析了西班牙卡斯蒂利亚-莱昂地区（约 240 万居民）第一波 COVID-19 患者的动态。从登记为临床过程开始的日期起，假设患者可以通过三个中间状态进展，直到达到恢复或死亡的吸收状态。人口统计学特征、感染时间和先前接种疫苗等流行病学因素、临床病史、疾病过程中的并发症以及住院患者的药物治疗被认为是候选预测因素。关于与死亡率和严重程度相关的危险因素，与许多其他研究一致的结果已经发现，例如年龄较大、男性和慢性疾病。具体而言，69 岁以上患者的住院（死亡）率为 27.2%（19.8%），而 70 岁以下患者的住院（死亡）率为 5.3%（0.7%），男性的住院（死亡）率为 14.5%（7%），而女性的住院（死亡）率为 8.3%（4.6%）。在患有慢性疾病的患者中，住院率最高的是糖尿病，为 26.1%，其次是肾脏疾病，为 26.3%，而脑血管疾病的死亡率最高，为 21.9%。此外，还给出了不同转移的特定预测因子，并通过模型提供了每位患者康复和死亡的概率估计。获得的一些有趣结果是，对于在该时期末感染的患者，从住院到 ICU 的转移风险显著降低（p<0.001），从住院到康复的转移风险更高（p<0.001）。对于先前接种过肺炎球菌疫苗的患者，康复的转移风险更高（p<0.001）。最后，还对模型进行了内部验证和校准。
