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葡萄牙两波 COVID-19 住院患者 ICU 入院和死亡的决定因素差异:医疗负担和病床占用对临床管理和结局的可能影响,2020 年 3 月至 12 月。

Difference in determinants of ICU admission and death among COVID-19 hospitalized patients in two epidemic waves in Portugal: possible impact of healthcare burden and hospital bed occupancy on clinical management and outcomes, March-December 2020.

机构信息

NOVA National School of Public Health, Public Health Research Centre, Comprehensive Health Research Center, CHRC, NOVA University Lisbon, Lisbon, Portugal.

Unit for Multidisciplinary Research in Biomedicine (UMIB), School of Medicine and Biomedical Sciences (ICBAS), University of Porto, Porto, Portugal.

出版信息

Front Public Health. 2023 Jun 29;11:1215833. doi: 10.3389/fpubh.2023.1215833. eCollection 2023.

Abstract

AIM

Identify factors associated with COVID-19 intensive care unit (ICU) admission and death among hospitalized cases in Portugal, and variations from the first to the second wave in Portugal, March-December 2020.

INTRODUCTION

Determinants of ICU admission and death for COVID-19 need further understanding and may change over time. We used hospital discharge data (ICD-10 diagnosis-related groups) to identify factors associated with COVID-19 outcomes in two epidemic periods with different hospital burdens to inform policy and practice.

METHODS

We conducted a retrospective cohort study including all hospitalized cases of laboratory-confirmed COVID-19 in the Portuguese NHS hospitals, discharged from March to December 2020. We calculated sex, age, comorbidities, attack rates by period, and calculated adjusted relative risks (aRR) for the outcomes of admission to ICU and death, using Poisson regressions. We tested effect modification between two distinct pandemic periods (March-September/October-December) with lower and higher hospital burden, in other determinants.

RESULTS

Of 18,105 COVID-19 hospitalized cases, 10.22% were admitted to the ICU and 20.28% died in hospital before discharge. Being aged 60-69 years (when compared with those aged 0-49) was the strongest independent risk factor for ICU admission (aRR 1.91, 95%CI 1.62-2.26). Unlike ICU admission, risk of death increased continuously with age and in the presence of specific comorbidities. Overall, the probability of ICU admission was reduced in the second period but the risk of death did not change. Risk factors for ICU admission and death differed by epidemic period. Testing interactions, in the period with high hospital burden, those aged 80-89, women, and those with specific comorbidities had a significantly lower aRR for ICU admission. Risk of death increased in the second period for those with dementia and diabetes.

DISCUSSION AND CONCLUSIONS

The probability of ICU admission was reduced in the second period. Different patient profiles were identified for ICU and deaths among COVID-19-hospitalized patients in different pandemic periods with lower and higher hospital burden, possibly implying changes in clinical practice, priority setting, or clinical presentation that should be further investigated and discussed considering impacts of higher burden on services in health outcomes, to inform preparedness, healthcare workforce planning, and pandemic prevention measures.

摘要

目的

确定与葡萄牙住院患者 COVID-19 重症监护病房(ICU)入院和死亡相关的因素,并分析 2020 年 3 月至 12 月葡萄牙第一波和第二波疫情之间的差异。

简介

需要进一步了解 COVID-19 患者 ICU 入院和死亡的决定因素,并且这些因素可能会随时间而变化。我们使用医院出院数据(ICD-10 诊断相关组)来确定与 COVID-19 两种不同流行期住院患者结局相关的因素,这两种流行期的医院负担不同,可为政策和实践提供信息。

方法

我们进行了一项回顾性队列研究,纳入了葡萄牙国民保健系统医院所有经实验室确诊的 COVID-19 住院患者,这些患者的出院时间为 2020 年 3 月至 12 月。我们计算了不同时期的性别、年龄、合并症、发病率,并使用泊松回归计算了 ICU 入院和死亡结局的校正相对风险(aRR)。我们在两个具有不同医院负担(低负担和高负担)的不同大流行时期之间测试了效应修饰,以确定其他决定因素之间的差异。

结果

在 18105 例 COVID-19 住院患者中,有 10.22%的患者被收入 ICU,20.28%的患者在出院前死亡。与 0-49 岁年龄组相比,60-69 岁(aRR 1.91,95%CI 1.62-2.26)是 ICU 入院的最强独立危险因素。与 ICU 入院不同,死亡风险随着年龄的增长和特定合并症的存在而持续增加。总体而言,第二阶段 ICU 入院的概率降低,但死亡风险没有变化。ICU 入院和死亡的危险因素因流行期而异。在高医院负担时期进行交互测试时,年龄在 80-89 岁之间、女性以及具有特定合并症的患者 ICU 入院的 aRR 显著降低。第二阶段痴呆和糖尿病患者的死亡风险增加。

讨论与结论

第二阶段 ICU 入院的概率降低。在低负担和高负担的不同大流行时期,COVID-19 住院患者的 ICU 和死亡的患者特征不同,这可能暗示临床实践、优先事项或临床表现发生了变化,应进一步调查和讨论,考虑到更高的负担对服务健康结果的影响,以为准备工作、医疗保健劳动力规划和大流行预防措施提供信息。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3957/10370276/f3a252b24abc/fpubh-11-1215833-g001.jpg

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