Objectives: We sought to establish the diagnostic accuracy of transesophageal echocardiography (TEE) during cardiopulmonary resuscitation.
Background: Because of its bedside diagnostic capabilities, excellent cardiac images and lack of interference with resuscitation efforts, TEE is ideally suited to determine the cause of a circulatory arrest that is not due to severe arrhythmia. However, the diagnostic accuracy of TEE during resuscitation is unknown.
Methods: TEE was performed in patients with prolonged circulatory arrest. The TEE diagnoses were compared with diagnoses from autopsy, surgery and clinical follow-up.
Results: Of the 48 study patients (29 male, 19 female, mean age +/- SD 61 +/- 20 years), 28 had an in-hospital cardiac arrest and 20 an out-of-hospital onset of arrest. Forty-four patients eventually died; four survived to discharge. The diagnoses made with TEE were cardiac tamponade (n = 6), myocardial infarction (n = 21), pulmonary embolism (n = 6), ruptured aorta (n = 1), aortic dissection (n = 4), papillary muscle rupture (n = 1), other diagnosis (n = 2) and absence of structural cardiac abnormalities (n = 7). A definite diagnosis from a reference standard was available in 31 patients. The TEE diagnosis was confirmed in 27 of the 31-by postmortem examination (n = 19), operation (n = 2), angiography (n = 2) or clinical course (n = 4). In the other four patients the TEE diagnosis proved incorrect by postmortem examination. The sensitivity, specificity and positive predictive value of TEE were 93%, 50% and 87%, respectively. In 15 patients (31%), major therapeutic decisions were based on TEE findings.
Conclusions: TEE can reliably establish the cause of a circulatory arrest during cardiopulmonary resuscitation.
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http://dx.doi.org/10.1016/s0735-1097(97)00218-0 | DOI Listing |
Appl Neuropsychol Adult
January 2025
Faculty Xavier Institute of Engineering, Mahim, India.
In the fields of engineering, science, technology, and medicine, artificial intelligence (AI) has made significant advancements. In particular, the application of AI techniques in medicine, such as machine learning (ML) and deep learning (DL), is rapidly growing and offers great potential for aiding physicians in the early diagnosis of illnesses. Depression, one of the most prevalent and debilitating mental illnesses, is projected to become the leading cause of disability worldwide by 2040.
View Article and Find Full Text PDFJ Med Internet Res
January 2025
Department of Computer Science and Software Engineering, United Arab Emirates University, Al Ain, United Arab Emirates.
Background: Neuroimaging segmentation is increasingly important for diagnosing and planning treatments for neurological diseases. Manual segmentation is time-consuming, apart from being prone to human error and variability. Transformers are a promising deep learning approach for automated medical image segmentation.
View Article and Find Full Text PDFCrit Care Sci
January 2025
Department of Neurointensive Care, Instituto Estadual do Cérebro Paulo Niemeyer - Rio de Janeiro (RJ), Brazil.
Objective: To define the incidence of ventriculostomy-associated infections and their impact on the mortality and functional outcomes of patients with aneurysmal subarachnoid hemorrhage.
Methods: We prospectively included all consecutive adult aneurysmal subarachnoid hemorrhage patients admitted to the neurological intensive care units of the Instituto Estadual do Cérebro Paulo Niemeyer (Rio de Janeiro, Brazil) and Hospital Cristo Redentor (Rio Grande do Sul, Brazil) who required external ventricular drains from July 2015 to December 2020. Daily clinical and laboratory variables were collected at admission and during the hospital stay.
Codas
January 2025
Programa de Pós-graduação em Distúrbios da Comunicação Humana, Departamento de Fonoaudiologia, Universidade Federal de Santa Maria - UFSM - Santa Maria (RS), Brasil.
Purpose: To present the criterion validity, sensitivity, specificity, and cut-off scores for the Profiles of Early Expressive Phonological Skills Test - Brazilian Portuguese (PEEPS-BP) - Expanded List.
Methods: This was a quantitative cross-sectional psychometric study. The sample consisted of 30 children with no identified neurodevelopmental disorders aged 24 to 36 months.
Arq Bras Oftalmol
January 2025
Department of Ophthalmology and Visual Sciences, Escola Paulista de Medicina, Universidade Federal de São Paulo, São Paulo, SP, Brazil.
Purpose: To assess the sensitivity and specificity of the retinopathy of prematurity score (ROPScore) and weight, insulin-like growth factor-1, retinopathy of prematurity algorithm in predicting the risk of developing severe retinopathy of prematurity (prethreshold type 1) in a sample of preterm infants in Brazil.
Methods: Retrospective analysis of medical records of preterm infants (n=288) with birth weight of ≤1500 g and/or gestational age of 23-32 weeks in a neonatal unit in Southern Brazil from May 2013 to December 2020 (92 months).
Results: The incidence of confirmed severe retinopathy of prematurity was 6.
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