Introduction of a standardised protocol, including systematic use of tranexamic acid, for management of severe adult trauma patients in a low-resource setting: the MSF experience from Port-au-Prince, Haiti.

BACKGROUND: Bleeding is an important cause of death in trauma victims. In 2010, the CRASH-2 study, a multicentre randomized control trial on the effect of tranexamic acid (TXA) administration to trauma patients with suspected significant bleeding, reported a decreased mortality in randomized patients compared to placebo. Currently, no evidence on the use of TXA in humanitarian, low-resource settings is available. We aimed to measure the hospital outcomes of adult patients with severe traumatic bleeding in the Médecins Sans Frontières Tabarre Trauma Centre in Port-au-Prince, Haiti, before and after the implementation of a Massive Haemorrhage protocol including systematic early administration of TXA. METHODS: Patients admitted over comparable periods of four months (December2015- March2016 and December2016 - March2017) before and after the implementation of the Massive Haemorrhage protocol were investigated. Included patients had blunt or penetrating trauma, a South Africa Triage Score ≥ 7, were aged 18-65 years and were admitted within 3 h from the traumatic event. Measured outcomes were hospital mortality and early mortality rates, in-hospital time to discharge and time to discharge from intensive care unit. RESULTS: One-hundred and sixteen patients met inclusion criteria. Patients treated after the introduction of the Massive Haemorrhage protocol had about 70% less chance of death during hospitalization compared to the group "before" (adjusted odds ratio 0.3, 95%confidence interval 0.1-0.8). They also had a significantly shorter hospital length of stay (p = 0.02). CONCLUSIONS: Implementing a Massive Haemorrhage protocol including early administration of TXA was associated with the reduced mortality and hospital stay of severe adult blunt and penetrating trauma patients in a context with poor resources and limited availability of blood products.

The modified south African triage scale system for mortality prediction in resource-constrained emergency surgical centers: a retrospective cohort study.

BACKGROUND: The South African Triage Scale (SATS) was developed to facilitate patient triage in emergency departments (EDs) and is used by Médecins Sans Frontières (MSF) in low-resource environments. The aim was to determine if SATS data, reason for admission, and patient age can be used to develop and validate a model predicting the in-hospital risk of death in emergency surgical centers and to compare the model's discriminative power with that of the four SATS categories alone. METHODS: We used data from a cohort hospitalized at the Nap Kenbe Surgical Hospital in Haiti from January 2013 to June 2015. We based our analysis on a multivariate logistic regression of the probability of death. Age cutoff, reason for admission categorized into nine groups according to MSF classifications, and SATS triage category (red, orange, yellow, and green) were used as candidate parameters for the analysis of factors associated with mortality. Stepwise backward elimination was performed for the selection of risk factors with retention of predictors with P < 0.05, and bootstrapping was used for internal validation. The likelihood ratio test was used to compare the combined and restricted models. These models were also applied to data from a cohort of patients from the Kunduz Trauma Center, Afghanistan, to validate mortality prediction in an external trauma patients population. RESULTS: A total of 7618 consecutive hospitalized patients from the Nap Kenbe Hospital were analyzed. Variables independently associated with in-hospital mortality were age > 45 and < = 65 years (odds ratio, 2.04), age > 65 years (odds ratio, 5.15) and the red (odds ratio, 65.08), orange (odds ratio, 3.5), and non-trauma (odds ratio, 3.15) categories. The combined model had an area under the receiver operating characteristic curve (AUROC) of 0.8723 and an AUROC corrected for optimism of 0.8601. The AUROC of the model run on the external data-set was 0.8340. The likelihood ratio test was highly significant in favor of the combined model for both the original and external data-sets. CONCLUSIONS: SATS category, patient age, and reason for admission can be used to predict in-hospital mortality. This predictive model had good discriminative ability to identify ED patients at a high risk of death and performed better than the SATS alone.