Background: Consistent data on head injury is lacking especially in the low- and middle-income countries. Our study tries to characterize patients with head injury at the emergency department of one of the few tertiary public hospitals giving neurosurgical care in the country.
Methods: A retrospective cross-sectional study was performed from May 2015 to October 2015 in one of the neurosurgical teaching hospitals, Black Lion Specialized Hospital. All adult patients with head injury who visited the emergency department during the study period were included. Data on patients' sociodemographic, mechanism of trauma, clinical presentation, imaging findings, and presence of polytrauma were collected by a pretested questionnaire. The source of data was emergency department logbooks and patient charts.
Results: A total of 390 patients with head injury who visited the emergency department were included during the study period. There were 335 males (85.9%) and 55 females (14.1%) with the mean age (standard deviation) of 35.4 (15.6) years. Majority of patients came by taxi constituting 149 (38.2%) of all patients, whereas 147 patients (37.7%) used ambulance. Of 147 patients brought by ambulances, 133 (90.4%) were referred from other hospitals. The majority, 26 (45.6%), of patients who came directly to the emergency department used taxis. It is shown that the mode of arrival and origin of arrival are significantly related, P = 0.000. Mortality of severe head injury at the emergency department was 50.8%.
Conclusions: Prehospital care coverage was low and ambulances were used mainly for interhospital transfers. Mortality of severe head injury at the emergency department is high and significantly associated with preventable causes like vital sign derangement.
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http://dx.doi.org/10.1016/j.wneu.2019.03.044 | DOI Listing |
Am J Emerg Med
January 2025
Department of Emergency Medicine, Yale University School of Medicine, New Haven, CT, USA; Center for Outcomes Research and Evaluation, Yale University, New Haven, CT, USA.
Background: This study aimed to examine how physician performance metrics are affected by the speed of other attendings (co-attendings) concurrently staffing the ED.
Methods: A retrospective study was conducted using patient data from two EDs between January-2018 and February-2020. Machine learning was used to predict patient length of stay (LOS) conditional on being assigned a physician of average speed, using patient- and departmental-level variables.
Am J Emerg Med
January 2025
Faculty of Medicine, Universidad de Valladolid, Valladolid, Spain; Emergency Department, Hospital Clínico Universitario, Gerencia Regional de Salud de Castilla y León, Valladolid, Spain.
Background: The study of the inclusion of new variables in already existing early warning scores is a growing field. The aim of this work was to determine how capnometry measurements, in the form of end-tidal CO2 (ETCO2) and the perfusion index (PI), could improve the National Early Warning Score (NEWS2).
Methods: A secondary, prospective, multicenter, cohort study was undertaken in adult patients with unselected acute diseases who needed continuous monitoring in the emergency department (ED), involving two tertiary hospitals in Spain from October 1, 2022, to June 30, 2023.
JMIR AI
January 2025
Department of Radiology, Children's National Hospital, Washington, DC, United States.
Clin Infect Dis
January 2025
Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Infectious Diseases, Respiratory Medicine and Critical Care, Berlin, Germany.
Background: Existing risk evaluation tools underperform in predicting intensive care unit (ICU) admission for patients with the Coronavirus Disease 2019 (COVID-19). This study aimed to develop and evaluate an accurate and calculator-free clinical tool for predicting ICU admission at emergency room (ER) presentation.
Methods: Data from patients with COVID-19 in a nationwide German cohort (March 2020-January 2023) were analyzed.
PLoS One
January 2025
Animal and Human Health Department, International Livestock Research Institute, Nairobi, Kenya.
Non-conformance with antibiotic withdrawal period guidelines represents a food safety concern, with potential for antibiotic toxicities and allergic reactions as well as selecting for antibiotic resistance. In the Kenyan domestic pig market, conformance with antibiotic withdrawal periods is not a requirement of government legislation and evidence suggests that antibiotic residues may frequently be above recommended limits. In this study, we sought to explore enablers of and barriers to conformance with antibiotic withdrawal periods for pig farms supplying a local independent abattoir in peri-urban Nairobi.
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