{'fraction_non_alphanumeric': 0.019839142091152815, 'fraction_numerical': 0.007506702412868633, 'mean_word_length': 5.640569395017794, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
A comprehensive, retrospective analysis of variables for potential mortality impact in patients with thermal or inhalation injury.

Age, percent total body surface area burned, and presence of inhalation injury have been used historically in the prediction of mortality in thermally injured patients despite other factors being also being associated with mortality. Recent literature has identified novel factors associated with increased length of stay and may provide a better prediction model for mortality in burn patients. The study objective was to perform a subset analysis of a multitude of known and novel variables for potential association with mortality. Demographics and injury characteristics along with during stay variables were collected and analyzed. This study is a re-analysis of a retrospective study examining variables associated with increased length of stay. Of the 629 patients screened, 396 were included in the analysis. After univariable analysis, 35 variables had significant associations with mortality including age, house fire, acute kidney injury, heart failure, inhalation injury, and history of diabetes. After multivariable analysis, the best performing model included: heart failure, acute kidney injury, admission Glasgow Coma Scale score, and revised Baux score. Quantile analysis of age revealed greater than 60 years was most predictive of mortality. The best multivariable model for patients greater than 60 years old included: heart failure, vasopressor use, acute respiratory distress syndrome, and total body surface area burned. Considering only variables present on admission, the best multivariable model for patients greater than 60 years old included: heart failure, percent total body surface area burned, and inhalation injury. Addition of variables into current prediction models and databases may be warranted.