Setting and Design:A hospital-based retrospective study of firecracker-related injuries was carried out at a government sponsored hospital in Delhi.Materials and Methods:1373 patients attended the emergency burn care out-patients clinic during 2002–2010 pre-Diwali, Diwali and post-Diwali days. Every year, a disaster management protocol is revoked during these 3 days under the direct supervision of the Ministry of Health and Family Welfare, Government of India.Results:There was an increase in the number of patients of firecracker-related injuries in Delhi national capital region from the year 2002 to 2010, based on the hospital statistics. During the study period, the hospital received approximately one patient with firecracker-related injury per 100,000 population of the city. 73.02% of the victims were 5–30 years old. Majority (90.87%) of them sustained <5% total body surface area burn.Conclusions:In spite of legislations and court orders, the number of patients is on the rise. The implementation agencies have to analyse the situation to find a way to control this preventable manmade accident. Websites, emails, SMS, social sites, etc. should be used for public education, apart from conventional methods of public awareness.

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Background Prediction of outcome for burn patients allows appropriate allocation of resources and prognostication. There is a paucity of simple to use burn-specific mortality prediction models which consider both endogenous and exogenous factors. Our objective was to create such a model. Methods A prospective observational study was performed on consecutive eligible consenting burns patients. Demographic data, total burn surface area (TBSA), results of complete blood count, kidney function test, and arterial blood gas analysis were collected. The quantitative variables were compared using the unpaired student t-test/nonparametric Mann Whitney U-test. Qualitative variables were compared using the ⊠2-test/Fischer exact test. Binary logistic regression analysis was done and a logit score was derived and simplified. The discrimination of these models was tested using the receiver operating characteristic curve; calibration was checked using the Hosmer—Lemeshow goodness of fit statistic, and the probability of death calculated. Validation was done using the bootstrapping technique in 5,000 samples. A p-value of <0.05 was considered significant. Results On univariate analysis TBSA (p <0.001) and Acute Physiology and Chronic Health Evaluation II (APACHE II) score (p = 0.004) were found to be independent predictors of mortality. TBSA (odds ratio [OR] 1.094, 95% confidence interval [CI] 1.037–1.155, p = 0.001) and APACHE II (OR 1.166, 95% CI 1.034–1.313, p = 0.012) retained significance on binary logistic regression analysis. The prediction model devised performed well (area under the receiver operating characteristic 0.778, 95% CI 0.681–0.875). Conclusion The prediction of mortality can be done accurately at the bedside using TBSA and APACHE II score.

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