Abstract
BackgroundThe effectiveness of emergency medical interventions can be best evaluated using time-to-event statistical methods with time-varying covariates (TVC), but this approach is complicated by uncertainty about the actual times of death. We therefore sought to evaluate the effect of hospital intervention on mortality after penetrating trauma using a method that allowed for interval censoring of the precise times of death.MethodsData on persons with penetrating trauma due to interpersonal assault were combined from the 2008 to 2010 National Trauma Data Bank (NTDB) and the 2004 to 2010 National Violent Death Reporting System (NVDRS). Cox and Weibull proportional hazards models for survival time (tSURV) were estimated, with TVC assumed to have constant effects for specified time intervals following hospital arrival. The Weibull model was repeated with tSURV interval-censored to reflect uncertainty about the precise times of death, using an imputation method to accommodate interval censoring along with TVC.ResultsAll models showed that mortality was increased by older age, female sex, firearm mechanism, and injuries involving the head/neck or trunk. Uncensored models showed a paradoxical increase in mortality associated with the first hour in a hospital. The interval-censored model showed that mortality was markedly reduced after admission to a hospital, with a hazard ratio (HR) of 0.68 (95% CI 0.63, 0.73) during the first 30 min declining to a HR of 0.01 after 120 min. Admission to a verified level I trauma center (compared to other hospitals in the NTDB) was associated with a further reduction in mortality, with a HR of 0.93 (95% CI 0.82, 0.97).ConclusionsTime-to-event models with TVC and interval censoring can be used to estimate the effect of hospital care on early mortality after penetrating trauma or other acute medical conditions and could potentially be used for interhospital comparisons.Electronic supplementary materialThe online version of this article (doi:10.1186/s40621-014-0024-1) contains supplementary material, which is available to authorized users.
Highlights
Introduction of interval censoringIn the present study, non-parametric and Weibull models were estimated using tSURV calculated first as the difference between the recorded injury time and declared death time
For 2004 to 2010, National Violent Death Reporting System (NVDRS) contained records for 64,936 persons in 18 states who died after penetrating trauma, of whom 24,619 (37.9%) died as a result of interpersonal violence; 13,955 (56.7%) of the latter group died without transportation to a hospital
The nonhospitalized NVDRS subjects were included in the subsequent analysis; among these, only 4,824 (34.6%) had valid and non-missing data for outcome and time to death; NVDRS contained only fatal cases and did not record any injury severity scores
Summary
Introduction of interval censoringIn the present study, non-parametric and Weibull models were estimated using tSURV calculated first as the difference between the recorded injury time and declared death time. The precise time may be unobserved if it occurs before Emergency Medical Services (EMS) personnel have arrived; declaration of death in the hospital (even for those ‘Dead on Arrival’ (DOA)) may be delayed until after resuscitative efforts have been judged futile This inexactness creates a distribution of recorded survival times with an anomalous secondary mode (Clark et al 2012a). It may be preferable to consider these early deaths as having occurred at some unspecified point during a defined interval, assuming only that the subject was alive at the beginning of the interval and dead at the end of the interval Such ‘interval censoring’ can be incorporated within the framework of time-to-event analysis (Lindsey and Ryan 1998; Zhang and Sun 2010), but the combination of time-varying covariates (TVC) and an intervalcensored outcome is not routinely handled by standard statistical software
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