Conway Richard, Cournane Sean, Byrne Declan, O'Riordan Deirdre, Silke Bernard
Department of Internal Medicine, St. James's Hospital, Dublin 8, Ireland.
Medical Physics and Bioengineering Department, St. James's Hospital, Dublin 8, Ireland.
Eur J Intern Med. 2016 Dec;36:44-49. doi: 10.1016/j.ejim.2016.08.010. Epub 2016 Aug 18.
The aim of this study was to detail the time profile and frequency distribution of mortality following an emergency admission and to compare these for weekday and weekend admissions.
We profiled in-hospital deaths following emergency medical admission between 2002 and 2014. We determined the frequency distribution, time pattern, causality and influence of day of admission on mortality out to 120days. We utilized a multivariable regression model (logistic for in-hospital mortality and truncated Poisson for count data) to adjust for major predictor variables.
There were 82,368 admissions in 44,628 patients with 4587 in-hospital deaths. The 30-day in-hospital mortality declined from 8.2% in 2002 to 3.7% in 2014. The mortality pattern showed an exponential decay over time; the time to death was best described by the three-parameter Weibull model. The calculated time to death for the 5th, 10th, 25th, 50th, 75th, and 90th centiles were 0.5, 1.2, 3.8, 11.1, 26.3 and 49.3days. Acute Illness Severity Score, Chronic Disabling Disease Score, Charlson Co-Morbidity Index and Sepsis status were associated with mortality. The risk of death was initially high, lower by day 3, and showed a cumulative increase over time. The mortality pattern was very similar between a weekday or weekend admission; however, the risk of death was greater at all time points between 0 and 120days for patients admitted at a weekend OR 1.08 (95% CI 1.01-1.15).
We have demonstrated the pattern of mortality following an emergency admission. The underlying pattern is similar between weekday and weekend admissions.
本研究旨在详细描述急诊入院后的死亡时间分布和频率,并比较工作日和周末入院情况。
我们对2002年至2014年间急诊入院后的院内死亡情况进行了分析。我们确定了120天内的频率分布、时间模式、因果关系以及入院日期对死亡率的影响。我们使用多变量回归模型(用于院内死亡率的逻辑回归模型和用于计数数据的截断泊松回归模型)来调整主要预测变量。
44628例患者中有82368次入院,其中4587例院内死亡。30天院内死亡率从2002年的8.2%降至2014年的3.7%。死亡模式随时间呈指数衰减;死亡时间最好用三参数威布尔模型描述。计算得出第5、10、25、50、75和90百分位数的死亡时间分别为0.5、1.2、3.8、11.1、26.3和49.3天。急性疾病严重程度评分、慢性致残疾病评分、查尔森合并症指数和脓毒症状态与死亡率相关。死亡风险最初较高,到第3天降低,并随时间呈累积增加。工作日或周末入院的死亡模式非常相似;然而,周末入院患者在0至120天内所有时间点的死亡风险更高,比值比为1.08(95%可信区间1.01 - 1.15)。
我们展示了急诊入院后的死亡模式。工作日和周末入院的基本模式相似。