Calonico Sebastian, Del Valle Juan Cruz Lopez, Di Tella Rafael
Department of Health Policy and Management, Mailman School of Public Health, ColumbiaUniversity, NYC, New York, United States of America.
Boston University, Boston, Massachusetts, United States of America.
PLOS Glob Public Health. 2024 Jan 5;4(1):e0000816. doi: 10.1371/journal.pgph.0000816. eCollection 2024.
COVID-19 poses dire threats for low and middle-income countries (LMICs). Yet, there remains limited rigorous evidence describing the characteristics and outcomes of hospitalized patients for LMICs, and often the evidence was based on small samples and/or unicentric. The objective of this study was to examine risk factors of COVID-19 mortality in Argentina, a hard-hit middle-income Latin American country. We analyze data on 5,146 COVID-19 patients from 11 centers across 10 cities in Argentina, making this one of the largest multi-centric retrospective observational descriptive studies in the LMICs. Information on demographics and co-morbidities was extracted from medical records. Outcomes of relevance consisted of whether the patient was discharged or deceased (as established in medical records), along with date of each event. We use survival models that account for competing risks. Median age was 60 years (IQR: 48-72), there were fewer women (40.8%) hospitalized than men (59.2%), and the most prevalent comorbidities were hypertension (40.9%), diabetes (20.0%) and obesity (19.1%). Patients were hospitalized for a median duration of 8 days (IQR: 5-13), and in-hospital mortality was 18.1%, though it varied substantially across health centers (95%CI: 17.1%-19.2%). Baseline characteristics most associated with in-hospital mortality were respiratory rate (adjusted HR = 3.6, 95%CI: 2.5-5.4 for ≥ 26 breathes/min), older age (adjusted HR = 2.5, 95%CI: 2.0-3.3 for the 80+ age group), and chronic kidney disease (adjusted HR = 2.2, 95%CI: 1.8-2.8). Associations were attenuated when survival models did not account for the competing risk of being discharged. We document lower mortality rates than those in prior studies, likely due to a lower prevalence of comorbidities amongst patients in our sample. Compared with standard Cox models, we find that, when using competing risk models, risk factors have a larger role in explaining COVID-19 mortality. Overall, we provide rigorous evidence describing the characteristics and outcomes of hospitalized patients for LMICs. Thus, our findings are useful to conduct a more accurate in-hospital monitoring of patient subgroups who may be at greater risk. They also provide valuable guidance for public health and policy efforts in Argentina and other developing countries.
新冠疫情给低收入和中等收入国家(LMICs)带来了严峻威胁。然而,关于这些国家住院患者特征和治疗结果的严格证据仍然有限,而且这些证据往往基于小样本和/或单中心研究。本研究的目的是调查在受疫情重创的拉丁美洲中等收入国家阿根廷,新冠病毒感染死亡的风险因素。我们分析了来自阿根廷10个城市11个中心的5146例新冠患者的数据,这使其成为低收入和中等收入国家中规模最大的多中心回顾性观察描述性研究之一。人口统计学和合并症信息从病历中提取。相关结果包括患者是否出院或死亡(根据病历确定)以及每个事件的日期。我们使用了考虑竞争风险的生存模型。中位年龄为60岁(四分位间距:48 - 72岁),住院女性(40.8%)少于男性(59.2%),最常见的合并症是高血压(40.9%)、糖尿病(20.0%)和肥胖(19.1%)。患者住院中位时长为8天(四分位间距:5 - 13天),院内死亡率为18.1%,不过在各医疗中心差异很大(95%置信区间:17.1% - 19.2%)。与院内死亡率最相关的基线特征是呼吸频率(呼吸频率≥26次/分钟时,校正风险比 = 3.6,95%置信区间:2.5 - 5.4)、高龄(80岁及以上年龄组校正风险比 = 2.5,95%置信区间:2.0 - 3.3)和慢性肾病(校正风险比 = 2.2,95%置信区间:1.8 - 2.8)。当生存模型未考虑出院的竞争风险时,这些关联减弱。我们记录的死亡率低于先前研究,这可能是因为我们样本中患者的合并症患病率较低。与标准Cox模型相比,我们发现,使用竞争风险模型时,风险因素在解释新冠病毒感染死亡方面作用更大。总体而言,我们提供了关于低收入和中等收入国家住院患者特征和治疗结果的严格证据。因此,我们的研究结果有助于对可能风险更高的患者亚组进行更准确的院内监测。它们也为阿根廷和其他发展中国家的公共卫生和政策努力提供了有价值的指导。