Post-traumatic stress disorder, anxiety, and depression symptoms in healthcare workers during COVID-19 pandemic in Colombia

Background: Mental health outcomes in healthcare workers (HCWs) in low- and middle-income countries (LMICs) have been poorly explored during COVID-19 pandemic. Our aim was to carry out a cross-sectional study of the prevalence of mental health symptoms in HCWs in Colombia. Methods: A cross-sectional web-survey study was performed during the COVID-19 pandemic mid-2021 including HCWs in two hospitals in Colombia. The PCL-5, GAD-7, and PHQ-9 scales were used to assess the prevalence of symptoms and severity of PTSD, anxiety, and depression in Colombia. Results: From 257 surveyed respondents, 44.36% were nurses, 36.58% physicians and 19.07% other health professionals. The prevalence of PTSD, anxiety, and depressive symptoms were 18.68%, 43.19%, and 26.85%, amongst HCWs. The regression model evidence a strong risk of PTSD, anxiety, and depressive symptoms in HCWs in Colombia during the second wave of COVID-19 in the middle of 2021. Conclusions: The prevalence for several mental health symptoms in HCWs in Colombia were higher compared with the general population. HCWs are at-risk population to develop chronic symptoms and mental disorders during and after outbreaks. These results will be helpful to tailor strategies to support the physical and mental health of the HCWs in LMICs. (PsycInfo Database Record (c) 2023 APA, all rights reserved)

Diagnostic performance of artificial intelligence algorithms for detection of pulmonary involvement by COVID-19 based on portable radiography. / Rendimiento diagnóstico de algoritmos de inteligencia artificial para detección de compromiso pulmonar por COVID-19 basados en radiografía portátil.

INTRODUCTION AND OBJECTIVES: To evaluate the diagnostic performance of different artificial intelligence (AI) algorithms for the identification of pulmonary involvement by SARS-CoV-2 based on portable chest radiography (RX). MATERIAL AND METHODS: Prospective observational study that included patients admitted for suspected COVID-19 infection in a university hospital between July and November 2020. The reference standard of pulmonary involvement by SARS-CoV-2 comprised a positive PCR test and low-tract respiratory symptoms. RESULTS: 493 patients were included, 140 (28%) with positive PCR and 32 (7%) with SARS-CoV-2 pneumonia. The AI-B algorithm had the best diagnostic performance (areas under the ROC curve AI-B 0.73, vs. AI-A 0.51, vs. AI-C 0.57). Using a detection threshold greater than 55%, AI-B had greater diagnostic performance than the specialist [(area under the curve of 0.68 (95% CI 0.64-0.72), vs. 0.54 (95% CI 0.49-0.59)]. CONCLUSION: AI algorithms based on portable RX enabled a diagnostic performance comparable to human assessment for the detection of SARS-CoV-2 lung involvement.

Diagnostic performance of artificial intelligence algorithms for detection of pulmonary involvement by COVID-19 based on portable radiography.

Introduction and objectives: To evaluate the diagnostic performance of different artificial intelligence (AI) algorithms for the identification of pulmonary involvement by SARS-CoV-2 based on portable chest radiography (RX). Material and methods: Prospective observational study that included patients admitted for suspected COVID-19 infection in a university hospital between July and November 2020. The reference standard of pulmonary involvement by SARS-CoV-2 comprised a positive PCR test and low-tract respiratory symptoms. Results: 493 patients were included, 140 (28%) with positive PCR and 32 (7%) with SARS-CoV-2 pneumonia. The AI-B algorithm had the best diagnostic performance (areas under the ROC curve AI-B 0.73, vs. AI-A 0.51, vs. AI-C 0.57). Using a detection threshold greater than 55%, AI-B had greater diagnostic performance than the specialist [(area under the curve of 0.68 (95% CI 0.64-0.72), vs. 0.54 (95% CI 0.49-0.59)]. Conclusion: AI algorithms based on portable RX enabled a diagnostic performance comparable to human assessment for the detection of SARS-CoV-2 lung involvement.

Introducción y objetivo: Evaluar el rendimiento diagnóstico de diferentes algoritmos de inteligencia artificial (IA) para la identificación de compromiso pulmonar por SARS-CoV-2 basados en radiografía (Rx) de tórax portátil. Material y método: Estudio observacional prospectivo que incluyó pacientes ingresados por sospecha de infección por COVID-19 en un hospital universitario entre julio y noviembre de 2020. El patrón de referencia de compromiso pulmonar por SARS-CoV-2 comprendió una PCR positiva y síntomas respiratorios bajos. Resultados: Se incluyeron 493 pacientes, 140 (28%) con PCR positiva y 32 (7%) con neumonía por SARS-CoV-2. El algoritmo AI-B tuvo el mejor rendimiento diagnóstico (áreas bajo la curva ROC AI-B 0,73 vs. AI-A 0,51 vs. AI-C 0,57). Utilizando un umbral de detección superior al 55%. AI-B presentó mayor precisión que el especialista (área bajo la curva de 0,68 [IC 95%: 0,64­0,72] vs. 0,54 [IC 95%: 0,49­0,59]). Conclusión: Los algoritmos de IA basados en Rx portátiles permiten una precisión diagnóstica comparable a la humana para la detección de compromiso pulmonar por SARS-CoV-2.

Prevalence and associated factors of mental health outcomes among healthcare workers in Northern Colombia: A cross-sectional and multi-centre study.

Background: Mental health outcomes in Healthcare Workers (HCWs) has been few evaluated during COVID-19 pandemic in low-and middle-income countries. Our aim was carry-out a study to identify the prevalence of stress, anxiety, depressive symptoms in HCWs and associated factors to severe illness in a northern region in Colombia. Method: A cross-sectional, hospital-based survey was conducted to assess mental health outcomes in 1,149 HCWs in Colombia. The study used Perceived Stress Scale (PSS-10), 7-item Generalized Anxiety Disorder (GAD-7), and 9-item Patient Health Questionnaire (PHQ-9) to evaluate stress, anxiety, and depression symptoms, respectively. Results: 682 HCWs completed the questionnaire. The 58,21% (397/682) were nurses, 31,23% were physicians (213/682), and 10,56% (72/682) were other health professionals. The proportion of HCWs with stress, anxiety, and depressive symptoms were 59,97%, 44,87%, and 23,02%, respectively. HCWs in emergency room and Intensive Care Units (ICU) have 2-3-fold increase risk to have severe symptoms of stress. Staff in ICU have 64% more likely to have severe anxiety symptoms, and 97% more likely to have severe depression symptoms. Limitations: Including HCWs only in the northern region in Colombia; a non-probabilistic sample, and a cross-sectional design to identify causality. Conclusion: A higher proportion on mental health outcomes has been reported in HCWs in Colombia. There are work areas related with severe mental symptoms such as ICU and emergency room. Hospitals and patient-care institutions in Latin-America needs consider the mental and physical health of HCWs during outbreaks and identify health staff at-risk to implementing support strategies to mitigate adverse mental outcomes.

Post-Traumatic Stress Disorder, Anxiety, and Depression Symptoms in Healthcare Workers during COVID-19 Pandemic in Colombia

Background : Mental health outcomes in healthcare workers (HCWs) in low- and middle-income countries (LMICs) have been poorly explored during COVID-19 pandemic. Our aim was to carry out a cross-sectional study of the prevalence of mental health symptoms in HCWs in Colombia. Methods : A cross-sectional web-survey study was performed during the COVID-19 pandemic mid-2021 including HCWs in two hospitals in Colombia. The PCL-5, GAD-7, and PHQ-9 scales were used to assess the prevalence of symptoms and severity of PTSD, anxiety, and depression in Colombia. Results : From 257 surveyed respondents, 44.36% were nurses, 36.58% physicians and 19.07% other health professionals. The prevalence of PTSD, anxiety, and depression symptoms were 18.68%, 43.19%, and 26.85%, amongst HCWs. The regression model evidence a strong risk of PTSD, anxiety, and depression symptoms in HCWs in Colombia during the second wave of COVID-19 in the middle of 2021. Conclusions : The prevalence for several mental health symptoms in HCWs in Colombia were higher compared with the general population. HCWs are at-risk population to develop chronic symptoms and mental disorders during and after outbreaks. These results will be helpful to tailor strategies to support the physical and mental health of the HCWs in LMICs.

Rendimiento Diagnóstico de Algoritmos de Inteligencia Artificial para Detección de Compromiso Pulmonar por COVID-19 Basados en Radiografía Portátil Diagnostic Performance of Artificial Intelligence Algorithms for Detection of Pulmonary Involvement by COVID-19 Based on Portable Radiography

INTRODUCCIÓN Y OBJETIVO: Evaluar rendimiento diagnóstico de diferentes algoritmos de inteligencia artificial (IA) para la identificación de compromiso pulmonar por SARS-COV-2 basados en radiografía de tórax portátil (RX). MATERIAL Y MÉTODO: Estudio observacional prospectivo que incluyo pacientes ingresados por sospecha de infección por COVID-19 en un hospital universitario entre Julio y Noviembre de 2020. El patrón de referencia de compromiso pulmonar por SARS-COV-2 comprendió una PCR positiva y síntomas respiratorios bajos. RESULTADOS: Se incluyeron 493 pacientes, 140 (28%) con PCR positiva y 32 (7%) con neumonía por SARS-COV-2. El algoritmo AI-B tuvo el mejor rendimiento diagnóstico (áreas bajo la curva ROC AI-B 0.73, vs. AI-A 0.51, vs. AI-C 0.57). Utilizando un umbral de detección superior al 55%, AI-B presento mayor precisión que el especialista (área bajo la curva de 0.68 (IC 95% 0.64-0.72), vs. 0.54 (IC 95% 0.49-0.59)]. CONCLUSIÓN: Los algoritmos de IA basados ​​en RX portátiles permiten una precisión diagnóstica comparable a la humana para la detección de compromiso pulmonar por SARS-COV-2.

Economía social como alternativa ante una sociedad post coronavirus

El COVID 19 ha impactado en todos los estamentos de la sociedad, por lo que algunas voces se levantan para advertir el impacto económico que se espera de esta pandemia. Por tanto, se deben buscar soluciones integrales que prioricen la condición humana antes que la maximización de las utilidades. Asimismo, la economía social recobra fuerzas como alternativa para frenar el impacto generado por esta crisis. El presente artículo tiene como fundamento describir el papel que puede desempeñar la economía social en un mundo posterior al COVID 19. Para lograrlo se plantean algunas definiciones sustentadoras como soporte teórico. Metodológicamente se basó en un enfoque cuantitativo, de tipo descriptivo con un diseño no experimental y transaccional, la población estuvo conformada por 14 profesionales con experiencia universitaria en áreas económicas o sociales, la técnica manejada fue la encuesta y como instrumento un cuestionario tipo Likert. La validez fue ponderada por la evaluación de tres expertos y la confiabilidad por la aplicación del coeficiente Alfa Cronbach. Los resultados arrojaron que existe evidencia de una crisis económica creada por esta pandemia, sin embargo, se concluye que, la economía social plantea alternativas, posteriores al Covid 19, que pueden mejorar el crecimiento económico y productivo en Latinoamérica.Alternate abstract:COVID 19 has impacted all levels of society, which is why some voices are raised to warn of the economic impact expected from this pandemic. Therefore, comprehensive solutions must be sought that prioritize the human condition over profit maximization. Likewise, the social economy is regaining its strength as an alternative to curb the impact generated by this crisis. This article is based on describing the role that the social economy can play in a post-COVID 19 world. To achieve this, some supportive definitions are proposed as theoretical support. Methodologically, it was based on a quantitative, descriptive approach with a non-experimental and transactional design, the population was made up of 14 professionals with university experience in economic or social areas, the technique used was the survey and a Likert-type questionnaire as an instrument. The validity was weighted by the evaluation of three experts and the reliability by the application of the Alpha Cronbach coefficient. The results showed that there is evidence of an economic crisis created by this pandemic, however, it is concluded that the social economy raises alternatives, after Covid 19, that can improve economic and productive growth in Latin America.