Assessment of a Comparative Bayesian-Enhanced Population-Based Decision Model for COVID-19 Critical Care Prediction in the Dominican Republic Social Security Affiliates.

INTRODUCTION: The novel coronavirus disease 2019 (COVID-19) has been a major health concern worldwide. This study aims to develop a Bayesian model to predict critical outcomes in patients with COVID-19. METHODS: Sensitivity and specificity were obtained from previous meta-analysis studies. The complex vulnerability index (IVC-COV2 index for its abbreviation in Spanish) was used to set the pretest probability. Likelihood ratios were integrated into a Fagan nomogram for posttest probabilities, and IVC-COV2 + National Early Warning Score (NEWS) values and CURB-65 scores were generated. Absolute and relative diagnostic gains (RDGs) were calculated based on pretest and posttest differences. RESULTS: The IVC-COV2 index was derived from a population of 1,055,746 individuals and was based on mortality in high-risk (71.97%), intermediate-risk (26.11%), and low-risk (1.91%) groups. The integration of models in which IVC-COV2 intermediate + NEWS ≥ 5 and CURB-65 > 2 led to a "number needed to (NNT) diagnose" that was slightly improved in the CURB-65 model (2 vs. 3). A comparison of diagnostic gains revealed that neither the positive likelihood ratio (P = 0.62) nor the negative likelihood ratio (P = 0.95) differed significantly between the IVC-COV2 NEWS model and the CURB-65 model. CONCLUSION: According to the proposed mathematical model, the combination of the IVC-COV2 intermediate score and NEWS or CURB-65 score yields superior results and a greater predictive value for the severity of illness. To the best of our knowledge, this is the first population-based/mathematical model developed for use in COVID-19 critical care decision-making.

Psychological distress and unsatisfied information needs in heart failure patients and ventricular dysfunction without previously diagnosed psychiatric disorder. Cross-sectional study in a national reference center / Distrés psicológico y necesidades de información insatisfechas en pacientes con insuficiencia cardiaca y disfunción ventricular sin trastorno psiquiátrico previamente diagnosticado. Estudio transversal en un centro de referencia nacional.

Introduction: Heart failure (HF) is a chronic disease that acutely and progressively reduces physical functionality. The patient commonly suffers from intermittent relapses that increase the likelihood of comorbidities such as chronic insomnia, cognitive impairment, alterations in sexual response, psychological distress, symptoms of anxiety and depression disorder, and decreased self-care behaviors. The objective of this study was to identify the main needs for psychological support in patients with HF. Methodology: A descriptive, cross-sectional and analytical study was carried out. Participants were selected through consecutive non-probability samples. 150 patients with a diagnosis of HF who attended the Specialized Center for Heart Failure at the National Institute of Cardiology "Ignacio Chávez" were evaluated from November 2018 to April 2019, applying the inventories: Quality of life in patients with HF (Minnesota), Hospital Anxiety and Depression Scale (HADS), psychological distress thermometer (visual analog scale) and the HF Patient Information Needs Inventory. Results: 33% of the patients perceive a high level of psychological distress that requires immediate assistance and 26.6% report a medium level that requires monitoring. The main information needs reported by the patients were information on taking medications (53.7%) and managing psychological distress (43.9%). Conclusion: Active assessment of psychological distress and unmet information needs is relevant in patients with heart failure, thus highlighting the importance of their identification and the correct design and application of evidence-based interventions aimed at their resolution.

Introducción: La insuficiencia cardiaca crónica (ICC) es una enfermedad que reduce de manera aguda y progresiva la funcionalidad física. El paciente comúnmente sufre de recaídas intermitentes que aumentan la probabilidad de comorbilidades como insomnio crónico, deterioro cognitivo, alteraciones en la respuesta sexual, estrés psicológico, síntomas de trastorno de ansiedad y depresión y disminución de las conductas de autocuidado. Objetivo: Identificar las principales necesidades de apoyo psicológico en pacientes con IC. Metodología: Se realizó un estudio descriptivo, transversal y analítico. Se evaluaron 150 pacientes con ICC del Centro Especializado en Insuficiencia Cardiaca del Instituto Nacional de Cardiología Ignacio Chávez de noviembre de 2018 a abril de 2019. Se aplicaron los inventarios: Calidad de vida en pacientes con IC (Minnesota), Escala de Ansiedad y Depresión Hospitalaria (HADS), termómetro del distrés psicológico (escala analógica visual) y el Inventario de Necesidades de Información del Paciente con IC. Resultados: Treinta y tres por ciento de los pacientes perciben un nivel alto de distrés psicológico que requiere asistencia inmediata y el 26.6% reporta un nivel medio que requiere monitoreo. Las principales necesidades de información reportadas por los pacientes fueron información sobre la toma de medicamentos (53.7%) y manejo del estrés psicológico (43.9%). Conclusión: En pacientes con IC es relevante la valoración activa de distrés psicológico y necesidades de información no cubiertas, resaltando de este modo la importancia de su identificación y el correcto diseño y aplicación de intervenciones basadas en la evidencia enfocadas a su resolución.

"On the job" learning: A bioinformatics course incorporating undergraduates in actual research projects and manuscript submissions.

The sequencing of whole genomes and the analysis of genetic information continues to fundamentally change biological and medical research. Unfortunately, the people best suited to interpret this data (biologically trained researchers) are commonly discouraged by their own perceived computational limitations. To address this, we developed a course to help alleviate this constraint. Remarkably, in addition to equipping our undergraduates with an informatic toolset, we found our course design helped prepare our students for collaborative research careers in unexpected ways. Instead of simply offering a traditional lecture- or laboratory-based course, we chose a guided inquiry method, where an instructor-selected research question is examined by students in a collaborative analysis with students contributing to experimental design, data collection, and manuscript reporting. While students learn the skills needed to conduct bioinformatic research throughout all sections of the course, importantly, students also gain experience in working as a team and develop important communication skills through working with their partner and the class as a whole, and by contributing to an original research article. Remarkably, in its first three semesters, this novel computational genetics course has generated 45 undergraduate authorships across three peer-reviewed articles. More importantly, the students that took this course acquired a positive research experience, newfound informatics technical proficiency, unprecedented familiarity with manuscript preparation, and an earned sense of achievement. Although this course deals with analyses of genetic systems, we suggest the basic concept of integrating actual research projects into a 16-week undergraduate course could be applied to numerous other research-active academic fields.