Publications by authors named "E Colin Ramirez"

Background: Pregnancy and birth uniquely alter female physiology, biology, and behavior. Contrasting findings on pregnancy and AD risk association suggest that confounding variables (e.g.

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: This study evaluated the appropriateness of transmucosal immediate-release fentanyl (TIRF) prescriptions in a Madrid emergency room during 2019 and 2022, following a 2018 warning about off-label use. : TIRF prescription in the emergency room search yielded 993 patients in 2019 and 1499 in 2022, of which 140 were randomized for the study, 70 in 2019, and 70 in 2022. Dose appropriateness and indication for TIRF were analyzed according to established criteria.

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Article Synopsis
  • Mumps is primarily a childhood infection characterized by swollen parotid glands, but a recent outbreak in Chile affected adults aged 20-35 despite the earlier success of the triple virus vaccine.
  • During 2018-2019, researchers analyzed 592 suspected mumps cases, finding a significant percentage positive for mumps antibodies (19.8% IgM and 95.9% IgG), with a notable male majority among positive IgM cases.
  • Genetic analysis revealed G and N genotypes in some cases, highlighting the importance of laboratory findings in diagnosing mumps and understanding the outbreak through an epidemiological surveillance program.
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This paper offers a systematic review of advancements in electronic nose technologies for early cancer detection with a particular focus on the detection and analysis of volatile organic compounds present in biomarkers such as breath, urine, saliva, and blood. Our objective is to comprehensively explore how these biomarkers can serve as early indicators of various cancers, enhancing diagnostic precision and reducing invasiveness. A total of 120 studies published between 2018 and 2023 were examined through systematic mapping and literature review methodologies, employing the PICOS (Population, Intervention, Comparison, Outcome, and Study design) methodology to guide the analysis.

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Objective: Deep learning approaches such as DeepACSA enable automated segmentation of muscle ultrasound cross-sectional area (CSA). Although they provide fast and accurate results, most are developed using data from healthy populations. The changes in muscle size and quality following anterior cruciate ligament (ACL) injury challenges the validity of these automated approaches in the ACL population.

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