Browsing by Autor "Sergio Mauricio Moreno"

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External Validation and Comparison of Two Clinical Prediction Models (PTP2013 and PTP2019) for Chest Pain in a Colombian Cohort
(2025) Nathaly Puentes; Ciro Rodríguez; Federico Ramos-Marquez; Diego A. Vargas-Hernández; Sergio Mauricio Moreno; L Guevara; Laura Rincón; Luz Karen Quintanilla Morales; Sílvia Paredes; Santiago Callegari
Abstract Aims The European Society of Cardiology (ESC) has proposed four pre-test probability (PTP) models for obstructive coronary artery disease (CAD). However, no studies have evaluated the diagnostic performance of any predictive model in the Latin American population. The aim of this study is to compare the PTP2013 and PTP2019 predictive models in order to determine which demonstrates a superior diagnostic performance for CAD in a cohort of Colombian patients. Methods A total of 408 patients who presented with chest pain and underwent coronary angiography (CA) and/or coronary computed tomography angiography (CCTA) at Fundación Santa Fe de Bogotá, between January 2019 and December 2023 were enrolled. Medical records were retrieved from the Hemodynamics and Radiology units. Pre-test probabilities were calculated for each patient using both the PTP2013 and PTP2019 models. CAD was defined as >50% stenosis on CA or CCTA. Each predictive model was assessed against CA and/or CCTA findings. The comparative performance of both models was evaluated. Results Prevalence of obstructive CAD of 24.9%. The PR2019 model underestimated the probability of CAD by 59%, whereas the PTP2013 model overestimated it by 35.6%. PTP2019 model yielded a C-statistic of 0.610 [95% CI: 0.544 - 0.676], while the PTP2013 model reported a C-statistic of 0.633 [95% CI: 0.570 - 0.696] (comparative p-value: 0.060). The net reclassification improvement was 14.7%). At a 15% threshold, the PTP2013 model demonstrated a sensitivity of 90% (82.38 - 95.10%), compared to 48% (37.9 - 58.22%) for the PTP2019 model. Conclusion The PTP2013 model is favored, as it showed higher sensitivity and a tendency to overestimate risk, in contrast to the PTP2019 model, which exhibited a concerning underdiagnosis of CAD. Consequently, the methodological challenge of identifying the predictive model with the highest diagnostic performance remains, highlighting the need to develop a tailored prediction model for the local population.
Severity and Mortality of Acute Respiratory Failure in Pediatrics: A Prospective Cohort at 2,600 Meters Above Sea Level
(Research Square (United States), 2023) Catalina Vargas‐Acevedo; Mónica Botero Marín; Catalina Jaime Trujillo; Laura Jimena Hernández; Melisa Naranjo Vanegas; Sergio Mauricio Moreno; Paola Rueda‐Guevara; Juan Gabriel Piñeros; Olga Baquero; Carolina Bonilla
Abstract Background: Acute respiratory failure (ARF) is the most frequent cause of cardiorespiratory arrest and subsequent death in children worldwide, therefore several efforts have been made to better understand its etiology and risk factors for further progression (1–4). The aim of this study was to calculate mortality and describe associated factors for severity and mortality in children with acute respiratory failure. Methods: The study was conducted within a prospective multicentric cohort that evaluated the natural history of pediatric acute respiratory failure (ARF). For this analysis three primary outcomes were studied: mortality, invasive mechanical ventilation, and pediatric intensive care unit length of stay. Setting: Pediatric emergency, in-hospital, and critical care services in three hospitals in Bogotá, Colombia, from April 2020 to June 2021. Patients : Eligible patients were children older than 1 month and younger than 18 years of age with respiratory difficulty at time of admission. Patients who developed ARF were followed at time of ARF, 48 hours later, at time of admission and at 30 and 60 days after discharge. Measurements and main results : Out of a total of 685 eligible patients, 296 developed ARF for a calculated incidence of ARF of 43.2%. Of the ARF group, ninety patients (30.4%) needed orotracheal intubation, for a mean of 9.57 days of ventilation (interquartile range = 3.00–11.5). Incidence of mortality was 6.1% ( n = 18). The associated factors for mortality in ARF were a history of a neurologic comorbidity and a higher fraction of inspired oxygen at ARF diagnosis. For PICU length of stay associated factors were age between 2 and 5 years of age, exposure to smokers, and respiratory comorbidity. Finally, for mechanical ventilation, the risk factors were obesity and being unstable at admission. Conclusions : ARF is a common cause of morbidity and mortality in children. Understanding the factors associated with greater mortality and severity of ARF might allow earlier recognition and initiation of prompt treatment strategies.