A sudden cardiac arrest in school or at a school event is potentially devastating to families and communities. An appropriate response to such an event-as promoted by developing, implementing, and practicing a cardiac emergency response plan (CERP)-can increase survival rates. Understanding that a trained lay-responder team within the school can make a difference in the crucial minutes between the time when the victim collapses and when emergency medical services arrive empowers school staff and can save lives. In 2015, the American Heart Association convened a group of stakeholders to develop tools to assist schools in developing CERPs. This article reviews the critical components of a CERP and a CERP team, the factors that should be taken into account when implementing the CERP, and recommendations for policy makers to support CERPs in schools.
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http://dx.doi.org/10.1177/1942602X16655839 | DOI Listing |
Intern Emerg Med
December 2024
Department of Emergency Medicine, JPS Health Network, 1500 S. Main St., Fort Worth, TX, 76104, USA.
The accuracy of using HEART (history, electrocardiogram, age, risk factors, and troponin) scores with high-sensitivity cardiac troponin (hs-cTn) to risk stratify emergency department (ED) chest pain patients remains uncertain. We aim to compare the performance accuracy of determining major adverse cardiac event (MACE) among three modified HEART (mHEART) scores with the use of hs-cTn to risk stratify ED chest pain patients. This retrospective single-center observational study included ED patients with suspected acute coronary syndrome who had HEAR scores calculated and at least one hs-cTnI result.
View Article and Find Full Text PDFZ Gerontol Geriatr
December 2024
2. Med. Abteilung, Klinik Landstraße, Juchgasse 25, 1030, Wien, Österreich.
Background: Little is known about how younger and older hospitalized patients differ with respect to reasons for admission, comorbidities, diagnostics, treatment and intercurrent problems.
Objective: The aim of the study was to compare the previously named characteristics in the clinical profile of patients > 90 years old (nonagenarians) with a control group of patients 70-75 years old admitted to an emergency hospital department for internal medicine and cardiology.
Material And Method: The study included all consecutive nonagenarians and gender-matched control patients who were admitted during 2011.
Respir Res
December 2024
Department of Medicine and Surgery, Pediatric Clinic, University of Parma, Via Gramsci 14, 43126, Parma, Italy.
Background: Exercise-induced bronchoconstriction (EIB) is common in children with asthma but can be present also in children without asthma, especially athletes. Differential diagnosis includes several conditions such as exercise-induced laryngeal obstruction (EILO), cardiac disease, or physical deconditioning. Detailed medical history, clinical examination and specific tests are mandatory to exclude alternative diagnoses.
View Article and Find Full Text PDFBMC Cardiovasc Disord
December 2024
Department of Internal Medicine, AdventHealth Sebring, Sebring, FL, USA.
Background: Acute Heart Failure (AHF) presents as a serious pathophysiological disease with significant morbidity and mortality rates, requiring immediate medical intervention. Traditional treatment involves diuretics and vasodilators, but a subset of patients develop resistance due to acute cardiorenal syndrome. Dapagliflozin, categorized as a sodium-glucose cotransporter-2 inhibitor (SGLT2i), has emerged as a promising therapy for AHF, demonstrating substantial benefits in reducing both mortality and morbidity among patients.
View Article and Find Full Text PDFSci Rep
December 2024
The Key Laboratory for Computer Systems of State Ethnic Affairs Commission, School of Computer and Artificial Intelligence, Southwest Minzu University, Chengdu, 610041, China.
Coronary artery disease represents a formidable health threat to middle-aged and elderly populations worldwide. This research introduces an advanced BP neural network algorithm, EPSOSA-BP, which integrates particle swarm optimization, simulated annealing, and a particle elimination mechanism to elevate the precision of heart disease prediction models. To address prior limitations in feature selection, the study employs single-hot encoding and Principal Component Analysis, thereby enhancing the model's feature learning capability.
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