ICES, Toronto, Ontario, Canada.
MAP Centre for Urban Health Solutions, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health Toronto, Toronto, Ontario, Canada.
Influenza Other Respir Viruses. 2022 Nov;16(6):1072-1081. doi: 10.1111/irv.13004. Epub 2022 May 24.
Shared and divergent predictors of clinical severity across respiratory viruses may support clinical and community responses in the context of a novel respiratory pathogen.
We conducted a retrospective cohort study to identify predictors of 30-day all-cause mortality following hospitalization with influenza (N = 45,749; 2010-09 to 2019-05), respiratory syncytial virus (RSV; N = 24 345; 2010-09 to 2019-04), or severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2; N = 8988; 2020-03 to 2020-12; pre-vaccine) using population-based health administrative data from Ontario, Canada. Multivariable modified Poisson regression was used to assess associations between potential predictors and mortality. We compared the direction, magnitude, and confidence intervals of risk ratios to identify shared and divergent predictors of mortality.
A total of 3186 (7.0%), 697 (2.9%), and 1880 (20.9%) patients died within 30 days of hospital admission with influenza, RSV, and SARS-CoV-2, respectively. Shared predictors of increased mortality included older age, male sex, residence in a long-term care home, and chronic kidney disease. Positive associations between age and mortality were largest for patients with SARS-CoV-2. Few comorbidities were associated with mortality among patients with SARS-CoV-2 as compared with those with influenza or RSV.
Our findings may help identify patients at greatest risk of illness secondary to a respiratory virus, anticipate hospital resource needs, and prioritize local prevention and therapeutic strategies to communities with higher prevalence of risk factors.
呼吸道病毒临床严重程度的共同和不同预测因素可能支持在新型呼吸道病原体背景下的临床和社区应对。
我们进行了一项回顾性队列研究,以确定流感(N=45749;2010 年 9 月至 2019 年 5 月)、呼吸道合胞病毒(RSV;N=24345;2010 年 9 月至 2019 年 4 月)或严重急性呼吸综合征冠状病毒 2(SARS-CoV-2;N=8988;2020 年 3 月至 2020 年 12 月;疫苗接种前)住院后 30 天内全因死亡率的预测因素。使用来自加拿大安大略省的基于人群的健康管理数据,采用多变量修正泊松回归评估潜在预测因素与死亡率之间的关联。我们比较了风险比的方向、大小和置信区间,以确定死亡率的共同和不同预测因素。
流感、RSV 和 SARS-CoV-2 住院患者分别有 3186 例(7.0%)、697 例(2.9%)和 1880 例(20.9%)在入院后 30 天内死亡。死亡率增加的共同预测因素包括年龄较大、男性、居住在长期护理院和慢性肾脏病。SARS-CoV-2 患者的年龄与死亡率之间呈正相关,且相关性最大。与流感或 RSV 患者相比,SARS-CoV-2 患者的几种合并症与死亡率相关。
我们的发现可能有助于确定因呼吸道病毒而导致疾病风险最大的患者,预测医院资源需求,并为风险因素患病率较高的社区确定优先预防和治疗策略。