van Kleef E, Green N, Goldenberg S D, Robotham J V, Cookson B, Jit M, Edmunds W J, Deeny S R
London School of Hygiene and Tropical Medicine, London, UK; Public Health England, Colindale, London, UK.
Public Health England, Colindale, London, UK; Imperial College London, London, UK.
J Hosp Infect. 2014 Dec;88(4):213-7. doi: 10.1016/j.jhin.2014.08.008. Epub 2014 Sep 18.
The burden of healthcare-associated infections, such as healthcare-acquired Clostridium difficile (HA-CDI), can be expressed in terms of additional length of stay (LOS) and mortality. However, previous estimates have varied widely. Although some have considered time of infection onset (time-dependent bias), none considered the impact of severity of HA-CDI; this was the primary aim of this study.
The daily risk of in-hospital death or discharge was modelled using a Cox proportional hazards model, fitted to data on patients discharged in 2012 from a large English teaching hospital. We treated HA-CDI status as a time-dependent variable and adjusted for confounders. In addition, a multi-state model was developed to provide a clinically intuitive metric of delayed discharge associated with non-severe and severe HA-CDI respectively.
Data comprised 157 (including 48 severe) HA-CDI cases among 42,618 patients. HA-CDI reduced the daily discharge rate by nearly one-quarter [hazard ratio (HR): 0.72; 95% confidence interval (CI): 0.61-0.84] and increased the in-hospital death rate by 75% compared with non-HA-CDI patients (HR: 1.75; 95% CI: 1.16-2.62). Whereas overall HA-CDI resulted in a mean excess LOS of about seven days (95% CI: 3.5-10.9), severe cases had an average excess LOS which was twice (∼11.6 days; 95% CI: 3.6-19.6) that of the non-severe cases (about five days; 95% CI: 1.1-9.5).
HA-CDI contributes to patients' expected LOS and risk of mortality. However, when quantifying the health and economic burden of hospital-onset of HA-CDI, the heterogeneity in the impact of HA-CDI should be accounted for.
医疗保健相关感染的负担,如医疗保健获得性艰难梭菌感染(HA-CDI),可以用额外住院时间(LOS)和死亡率来表示。然而,先前的估计差异很大。尽管一些研究考虑了感染发生时间(时间依赖性偏倚),但没有一项研究考虑HA-CDI严重程度的影响;这是本研究的主要目的。
使用Cox比例风险模型对住院死亡或出院的每日风险进行建模,该模型适用于2012年从一家大型英国教学医院出院的患者数据。我们将HA-CDI状态视为时间依赖性变量,并对混杂因素进行了调整。此外,还开发了一个多状态模型,以分别提供与非严重和严重HA-CDI相关的延迟出院的临床直观指标。
数据包括42618名患者中的157例(包括48例严重)HA-CDI病例。与非HA-CDI患者相比,HA-CDI使每日出院率降低了近四分之一[风险比(HR):0.72;95%置信区间(CI):0.61-0.84],并使住院死亡率增加了75%(HR:1.75;95%CI:1.16-2.62)。总体而言,HA-CDI导致平均额外住院时间约为7天(95%CI:3.5-10.9),而严重病例的平均额外住院时间是非严重病例的两倍(约11.6天;95%CI:3.6-19.6)(约5天;95%CI:1.1-9.5)。
HA-CDI会增加患者的预期住院时间和死亡风险。然而,在量化医院内HA-CDI发病的健康和经济负担时,应考虑HA-CDI影响的异质性。