Articles: emergency-medical-services.
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Multicenter Study Observational Study
Annual patterns in the outcomes and post-arrest care for pediatric out-of-hospital cardiac arrest: a nationwide multicenter prospective registry in Japan.
Out-of-hospital cardiac arrest (OHCA) has a poor prognosis in children; however, the annual patterns of prognosis and treatment have not been fully investigated. ⋯ Despite an increase in the rate of bystander-initiated CPR and pre-hospital adrenaline administration, there was no significant change in one-month survival.
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Multicenter Study
A simple scoring rule to predict survival to discharge after out of hospital cardiac arrest at the time of ED arrival.
It is important to be able to predict the chance of survival to hospital discharge upon ED arrival in order to determine whether to continue or terminate resuscitation efforts after out of hospital cardiac arrest. This study was conducted to develop and validate a simple scoring rule that could predict survival to hospital discharge at the time of ED arrival. ⋯ A simple scoring rule consisting of five, binary variables could aid in the prediction of the survival to hospital discharge at the time of ED arrival, showing comparable results to conventional machine learning classifiers.
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Multicenter Study
Derivation and validation of a blood biomarker score for 2-day mortality prediction from prehospital care: a multicenter, cohort, EMS-based study.
Identifying potentially life-threatening diseases is a key challenge for emergency medical services. This study aims at examining the role of different prehospital biomarkers from point-of-care testing to derive and validate a score to detect 2-day in-hospital mortality. We conducted a prospective, observational, prehospital, ongoing, and derivation-validation study in three Spanish provinces, in adults evacuated by ambulance and admitted to the emergency department. ⋯ The following risk levels for 2-day mortality were identified from the score: low risk (score < 1), where only 8.2% of non-survivors were assigned to; medium risk (1 ≤ score < 4); and high risk (score ≥ 4), where the 2-day mortality rate was 57.6%. The novel blood biomarker score provides an excellent association with 2-day in-hospital mortality, as well as real-time feedback on the metabolic-respiratory patient status. Thus, this score can help in the decision-making process at critical moments in life-threatening situations.
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Pediatric emergency care · Jul 2023
Multicenter StudyDrowning in Children and Predictive Parameters: A 15-Year Multicenter Retrospective Analysis.
Drowning is a serious and underestimated public health problem, with the highest morbidity and mortality reported among children. Data regarding pediatric outcomes of drowning are often inadequate, and data collection is poorly standardized among centers. This study aims to provide an overview of a drowning pediatric population in pediatric emergency department, focusing on its main characteristics and management and evaluating prognostic factors. ⋯ This study offers several perspectives on ED victims who drowned. One of the major finding is that no difference in outcomes was seen in patients who received cardiopulmonary resuscitation performed by bystanders or medical services, highlighting the importance of a prompt intervention.
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Journal of neurotrauma · Jul 2023
Multicenter StudyPrediction of Mortality Among Patients with Isolated Traumatic Brain Injury Using Machine Learning Models in Asian Countries: An International Multicenter Cohort Study.
Abstract Traumatic brain injury (TBI) is a significant healthcare concern in several countries, accounting for a major burden of morbidity, mortality, disability, and socioeconomic losses. Although conventional prognostic models for patients with TBI have been validated, their performance has been limited. Therefore, we aimed to construct machine learning (ML) models to predict the clinical outcomes in adult patients with isolated TBI in Asian countries. ⋯ Among the tested models, the gradient-boosted decision tree showed the best performance (AUPRC, 0.746 [0.700-0.789]; AUROC, 0.940 [0.929-0.952]). The most powerful contributors to model prediction were the Glasgow Coma Scale, O2 saturation, transfusion, systolic and diastolic blood pressure, body temperature, and age. Our study suggests that ML techniques might perform better than conventional multi-variate models in predicting the outcomes among adult patients with isolated moderate and severe TBI.