4.5 Article

The Distribution of Survival Times after Injury

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WORLD JOURNAL OF SURGERY
卷 36, 期 7, 页码 1562-1570

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SPRINGER
DOI: 10.1007/s00268-012-1549-5

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  1. National Center for Injury Prevention and Control [R01CE001594]

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The distribution of survival times after injury has been described as trimodal, but several studies have not confirmed this. The purpose of this study was to clarify the distribution of survival times after injury. We defined survival time (t(s)) as the interval between injury time and declared death time. We constructed histograms for t(s) a parts per thousand currency sign 150 min from the 2004-2007 Fatality Analysis Reporting System (FARS, for traffic crashes) and National Violent Death Reporting System (NVDRS, for homicides). We estimated statistical models in which death times known only within intervals were treated as interval-censored. For confirmation, we also obtained EMS response times (t(r)), prehospital times (t(p)), and hospital times (t(h)) for decedents in the 2008 National Trauma Data Bank (NTDB) with t(s) = t(p) + t(h) a parts per thousand currency sign 150. We approximated times until circulatory arrest (t(x)) as t(r) for patients pulseless at the injury scene, t(p) for other patients pulseless at hospital admission, and t(s) for the rest; for any declared t(s), we calculated mean t(x)/t(s). We used this ratio to estimate t(x) for hospital deaths in FARS or NVDRS and provide independent support for using interval-censored methods. FARS and NVDRS deaths were most frequent in the first few minutes. Both showed a second peak at 35-40 min after injury, corresponding to peaks in hospital deaths. Third peaks were not present. Estimated t(x) in FARS and NVDRS did not show second peaks and were similar to estimates treating some death times as interval-censored. Increases in frequency of survival times at 35-40 min are primarily artifacts created because declaration of death in hospitals is delayed until completing resuscitative attempts. By avoiding these artifacts, interval censoring methods are useful for analysis of injury survival times.

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