Clinic of Infectious Diseases, San Gerardo Hospital, School of Medicine and Surgery, University of Milano - Bicocca, Monza, Italy.
Bicocca Bioinformatics, Biostatistics and Bioimaging Center B4, School of Medicine and Surgery, University of Milano - Bicocca, Monza, Italy.
PLoS One. 2021 Jan 28;16(1):e0246170. doi: 10.1371/journal.pone.0246170. eCollection 2021.
During the Coronavirus disease 2019 (COVID-19) pandemic, advanced health systems have come under pressure by the unprecedented high volume of patients needing urgent care. The impact on mortality of this "patients' burden" has not been determined.
Through retrieval of administrative data from a large referral hospital of Northern Italy, we determined Aalen-Johansen cumulative incidence curves to describe the in-hospital mortality, stratified by fixed covariates. Age- and sex-adjusted Cox models were used to quantify the effect on mortality of variables deemed to reflect the stress on the hospital system, namely the time-dependent number of daily admissions and of total hospitalized patients, and the calendar period. Of the 1225 subjects hospitalized for COVID-19 between February 20 and May 13, 283 died (30-day mortality rate 24%) after a median follow-up of 14 days (interquartile range 5-19). Hospitalizations increased progressively until a peak of 465 subjects on March 26, then declined. The risk of death, adjusted for age and sex, increased for a higher number of daily admissions (adjusted hazard ratio [AHR] per an incremental daily admission of 10 patients: 1.13, 95% Confidence Intervals [CI] 1.05-1.22, p = 0.0014), and for a higher total number of hospitalized patients (AHR per an increase of 50 patients in the total number of hospitalized subjects: 1.11, 95%CI 1.04-1.17, p = 0.0004), while was lower for the calendar period after the peak (AHR 0.56, 95%CI 0.43-0.72, p<0.0001). A validation was conducted on a dataset from another hospital where 500 subjects were hospitalized for COVID-19 in the same period. Figures were consistent in terms of impact of daily admissions, daily census, and calendar period on in-hospital mortality.
The pressure of a high volume of severely ill patients suffering from COVID-19 has a measurable independent impact on in-hospital mortality.
在 2019 年冠状病毒病（COVID-19）大流行期间，由于需要紧急护理的患者数量空前增加，先进的卫生系统面临压力。这种“患者负担”对死亡率的影响尚未确定。
通过从意大利北部一家大型转诊医院检索行政数据，我们使用 Aalen-Johansen 累积发生率曲线来描述按固定协变量分层的住院死亡率。使用年龄和性别调整的 Cox 模型来量化死亡率变量的影响，这些变量被认为反映了医院系统的压力，即每日入院人数和住院患者总数的时间依赖性以及日历期。在 2 月 20 日至 5 月 13 日期间，因 COVID-19 住院的 1225 名患者中，283 名患者在中位随访 14 天后死亡（30 天死亡率为 24%）。住院人数逐渐增加，直到 3 月 26 日达到高峰 465 人，然后下降。死亡风险，按年龄和性别调整后，与每日入院人数增加相关（每增加 10 名患者的每日入院人数的调整后危害比[AHR]：1.13，95%置信区间[CI]1.05-1.22，p=0.0014），与住院患者总数增加相关（每增加 50 名住院患者的住院患者总数的 AHR：1.11，95%CI1.04-1.17，p=0.0004），而在高峰期过后的日历期较低（AHR0.56，95%CI0.43-0.72，p<0.0001）。在同一时期因 COVID-19 住院的 500 名患者的另一家医院数据集上进行了验证。在每日入院人数、每日普查和日历期对住院死亡率的影响方面，结果是一致的。
大量患有 COVID-19 的重病患者的压力对住院死亡率有可衡量的独立影响。
