BACKGROUND: Mortality from firearms among US schoolchildren is an increasingly major clinical and public health crisis. We explored temporal trends in mortality from firearms among US schoolchildren from 1999 to 2017 by age and race. METHODS: We used the Multiple Cause of Death Files of the United States National Center for Health Statistics; PubMed searches, and joinpoint regressions for trend analyses and calculated mortality rates and 95% confidence limits. RESULTS: From 1999 to 2017, the 38,942 deaths due to firearms in school-age children ranged from 340 per year at ages 5-14 to 2050 at 15-18 years. One epidemic among 5-to 14-year-olds began in 2009 and another among 15-to 18-yearolds began in 2014. The listed intents were 61% assault, 32% suicide, 5% accidental, and 2% undetermined. Blacks accounted for 41% of overall deaths, but only 17% of the school-age deaths. 86% of all deaths were boys. CONCLUSIONS: Mortality from firearms in US schoolchildren is increasing at alarming rates, especially among blacks and those aged 15-18 years. To the best of our knowledge, this is the first report to quantify these recent epidemics. Although federal laws prohibited them until recently, analytic studies designed a priori to do so are necessary to test the hypotheses generated by these descriptive data. We believe that combatting the epidemic of mortality from firearms among US schoolchildren without addressing firearms is analogous to combatting the epidemic of mortality from lung cancer from cigarettes without addressing cigarettes.
Introduction:
Brain death occurs in 10-15% of successfully resuscitated out-of-hospital cardiac arrest (OHCA) patients. Early identification of potential organ donors is critical to prevent withdrawal of life sustaining therapy (WLST) and ensure adequate organ perfusion. To predict brain death after OHCA, we developed a novel brain death risk (BDR) score.
Methods:
The BDR score was developed from a retrospective, single center cohort of OHCA patients admitted from 2011-2020. After excluding patients with early WLST (defined as < 72 hours from OHCA), univariate regression models identified independent predictors of brain death, which were used to build the BDR score. We included the following variables: non-shockable rhythm (1 point), drug overdose as etiology of arrest (1 point), evidence of grey-white differentiation loss or sulcal effacement on head computed tomography (CT) within 24 hours of arrest (2 points), Full-Outline-Of-UnResponsiveness (FOUR) score of 0 (2 points), FOUR score 1-5 (1 point), and age < 45 years (1 point). Head CT findings were based on neuroradiology reports. We validated the BDR score in an independent single center OHCA cohort. The primary outcome was occurrence of brain death. Using the area under the receiving operator characteristic curve (AUC), we assessed the score’s prediction of brain death.
Results:
The development cohort included 256 OHCA patients; 15.6% (40/256) experienced brain death. The AUC (95% CI) of the BDR score was 0.921 (0.870-0.971). In the validation cohort, 24.4% (21/86) experienced brain death. The AUC (95% CI) of the BDR score was 0.830 (0.7266-0.9335). Table 1 shows the rate of brain death at each BDR score. In both cohorts, a BDR score ≥ 5 was the optimal cut off (sensitivity 0.9 and 0.714, specificity 0.843 and 0.831, respectively).
Conclusion:
Early scoring systems may be able to identify those at highest risk for brain death after OHCA. Our data suggest that a BDR score ≥ 5 could help predict progression to brain death.
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