Jared Gallaher1, Laura N Purcell2, Wone Banda3, Trista Reid2, Anthony Charles4. 1. Department of Surgery, University of North Carolina School of Medicine, Chapel Hill, North Carolina. Electronic address: jared_gallaher@med.unc.edu. 2. Department of Surgery, University of North Carolina School of Medicine, Chapel Hill, North Carolina. 3. Department of Surgery, Kamuzu Central Hospital, Lilongwe, Malawi. 4. Department of Surgery, University of North Carolina School of Medicine, Chapel Hill, North Carolina; Department of Surgery, Kamuzu Central Hospital, Lilongwe, Malawi.
Abstract
BACKGROUND: This global burden of burn injury is suffered disproportionately by people in low-income and middle-income countries, where 70% of all burns occur. Models based in high-income countries to prognosticate burn mortality treat age as a linearly increasing risk factor. It is unclear whether this relationship is similar in resource-limited settings. METHODS: We analyzed patients from the Kamuzu Central Hospital Burn Registry in Lilongwe, Malawi, from 2011 to 2019. We examined the relationship between burn-associated mortality and age using adjusted survival analysis over 60 d, categorized into four groups: (1) younger children <5 y; (2) older children 5-17 y; (3) adults 18-40 y; and (4) older adults >40 y. RESULTS: A total of 2499 patients were included. Most patients were <5 y old (n = 1444) with only 133 patients >40 y. Older adults had the highest crude mortality at 34.6% and older children with the lowest at 13%. Compared to younger children, the hazard ratio adjusted for sex, percent total body surface area, and operative intervention was 0.59 (95% confidence interval, 0.44, 0.79) for older children and 0.55 (95% confidence interval, 0.40, 0.76) for adults. Older adults were statistically similar to younger children. CONCLUSIONS: We show in this cohort study of burn-injured patients in a resource-limited environment that the relationship between mortality and age is not linear and that the use of age-categorized mortality prediction models is more accurate in delineating mortality characteristics. Categorizing age based on local burn epidemiology will help describe burn mortality characteristics more accurately, leading to better-informed management strategies aimed at attenuating burn mortality for different populations.
BACKGROUND: This global burden of burn injury is suffered disproportionately by people in low-income and middle-income countries, where 70% of all burns occur. Models based in high-income countries to prognosticate burn mortality treat age as a linearly increasing risk factor. It is unclear whether this relationship is similar in resource-limited settings. METHODS: We analyzed patients from the Kamuzu Central Hospital Burn Registry in Lilongwe, Malawi, from 2011 to 2019. We examined the relationship between burn-associated mortality and age using adjusted survival analysis over 60 d, categorized into four groups: (1) younger children <5 y; (2) older children 5-17 y; (3) adults 18-40 y; and (4) older adults >40 y. RESULTS: A total of 2499 patients were included. Most patients were <5 y old (n = 1444) with only 133 patients >40 y. Older adults had the highest crude mortality at 34.6% and older children with the lowest at 13%. Compared to younger children, the hazard ratio adjusted for sex, percent total body surface area, and operative intervention was 0.59 (95% confidence interval, 0.44, 0.79) for older children and 0.55 (95% confidence interval, 0.40, 0.76) for adults. Older adults were statistically similar to younger children. CONCLUSIONS: We show in this cohort study of burn-injured patients in a resource-limited environment that the relationship between mortality and age is not linear and that the use of age-categorized mortality prediction models is more accurate in delineating mortality characteristics. Categorizing age based on local burn epidemiology will help describe burn mortality characteristics more accurately, leading to better-informed management strategies aimed at attenuating burn mortality for different populations.
Authors: Joana Grudziak; Carolyn Snock; Tiyamike Zalinga; Wone Banda; Jared Gallaher; Laura Purcell; Bruce Cairns; Anthony Charles Journal: Burns Date: 2017-10-28 Impact factor: 2.744
Authors: Sandra L Taylor; MaryBeth Lawless; Terese Curri; Soman Sen; David G Greenhalgh; Tina L Palmieri Journal: Burns Date: 2014-05-17 Impact factor: 2.744
Authors: Megan M Rybarczyk; Jesse M Schafer; Courtney M Elm; Shashank Sarvepalli; Pavan A Vaswani; Kamna S Balhara; Lucas C Carlson; Gabrielle A Jacquet Journal: Afr J Emerg Med Date: 2017-01-28