Development and evaluation of a machine learning-based in-hospital COVID-19 disease outcome predictor (CODOP): A multicontinental retrospective study

New SARS-CoV-2 variants, breakthrough infections, waning immunity, and sub-optimal vaccination rates account for surges of hospitalizations and deaths. There is an urgent need for clinically valuable and generalizable triage tools assisting the allocation of hospital resources, particularly in resource-limited countries. We developed and validate CODOP, a machine learning-based tool for predicting the clinical outcome of hospitalized COVID-19 patients. CODOP was trained, tested and validated with six cohorts encompassing 29223 COVID-19 patients from more than 150 hospitals in Spain, the USA and Latin America during 2020-22. CODOP uses 12 clinical parameters commonly measured at hospital admission for reaching high discriminative ability up to 9 days before clinical resolution (AUROC: 0.90-0.96), it is well calibrated, and it enables an effective dynamic risk stratification during hospitalization. Furthermore, CODOP maintains its predictive ability independently of the virus variant and the vaccination status. To reckon with the fluctuating pressure levels in hospitals during the pandemic, we offer two online CODOP calculators, suited for undertriage or overtriage scenarios, validated with a cohort of patients from 42 hospitals in three Latin American countries (78-100% sensitivity and 89-97% specificity). The performance of CODOP in heterogeneous and geographically disperse patient cohorts and the easiness of use strongly suggest its clinical utility, particularly in resource-limited countries

Impact of Physical Activity on Frailty Status and How to Start a Semiological Approach to Muscular System

Introduction: The world population is aging, and this demographic fact is associated with an increased prevalence of sedentary lifestyles, sarcopenia and frailty; all of them with impact on health status. Biologic reserve determination in the elderly with comorbidity poses a challenge for medical activities. Frailty is an increasingly used concept in the geriatric medicine literature, which refers to an impairment in biologic reserve. There is a close and multidirectional relationship between physical activity, the muscular system function, and a fit status; decline in this dimensions is associated with poor outcomes. The aim of this article is to make a narrative review on the relationship between physical activity, sarcopenia and frailty syndrome. Results: The low level of physical activity, sarcopenia and frailty, are important predictors for development of disability, poor quality of life, falls, hospitalizations and all causes mortality. For clinical practice we propose a semiological approach based on measurement of muscle performance, mass and also level of physical activity, as a feasible way to determine the biologic reserve. This evidence shows us that the evaluation of muscle mass and performance, provides important prognostic information because the deterioration of these variables is associated with poor clinical outcomes in older adults followed up in multiple cohorts. Conclusions: Low activity is a mechanism and at the same time part of the frailty syndrome. The determination of biologic reserve is important because it allows the prognostic stratification of the patient and constitutes an opportunity for intervention. The clinician should be aware of the clinical tools that evaluate muscular system and level of physical activity, because they place us closer to the knowledge of health status

Artemisia: Validation of a deep learning model for automatic breast density categorization

Background: The aim of this study is to validate a deep learning model for the classification of breast density according to American College of Radiology’s breast density patterns. Methods: A convolutional neural network was developed with 10,229 digital screening mammogram images. Once the network was developed and tested, its performance was evaluated before a group of six professionals, the majority report and a commercial software application. We selected randomly 451 new mammographic images from different studies and patients. The categorization process by professionals was repeated in two stages. Results: The agreement between the convolutional neural network and the majority report was k=0.64 (95% CI: 0.58–0.69) in the first stage and k=0.57 (95% CI: 0.52–0.63) in the second stage. The agreement between the CNN and the commercial software application was k=0.54 (95% CI: 0.48–0.60). In both cases, we observed that the concordances of the CNN were within or above the range of professionals’ concordances values. Conclusions: Considering the internal reference standard (majority report) and the external reference standard (commercial software application), we can affirm the CNN achieved professional level performance.Fil: Tajerian, Matías N.. Hospital Italiano. Instituto Universitario. Escuela de Medicina; ArgentinaFil: Pesce, Karina. Hospital Italiano. Instituto Universitario. Escuela de Medicina; ArgentinaFil: Frangella, Julia. Hospital Italiano. Instituto Universitario. Escuela de Medicina; ArgentinaFil: Quiroga, Ezequiel. Hospital Italiano. Instituto Universitario. Escuela de Medicina; ArgentinaFil: Boietti, Bruno Rafael. Hospital Italiano. Instituto Universitario. Escuela de Medicina; ArgentinaFil: Chico, Maria José. Hospital Italiano. Instituto Universitario. Escuela de Medicina; ArgentinaFil: Swiecicki, María Paz. Hospital Italiano. Instituto Universitario. Escuela de Medicina; ArgentinaFil: Benitez, Sonia. Hospital Italiano. Instituto Universitario. Escuela de Medicina; ArgentinaFil: Rabellino, Martín. Hospital Italiano. Instituto Universitario. Escuela de Medicina; ArgentinaFil: Luna, Daniel Roberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Medicina Traslacional e Ingeniería Biomédica - Hospital Italiano. Instituto de Medicina Traslacional e Ingeniería Biomédica.- Instituto Universitario Hospital Italiano de Buenos Aires. Instituto de Medicina Traslacional e Ingeniería Biomédica; Argentin

Emergency department visits and hospital readmissions in an Argentine health system

Background and goal of study: The scope of health in the Sustainable Development Goals is much broader than the Millennium Development Goals, spanning functions such as health-system access and quality of care. Hospital readmission rate and ED-visits within 30 days from discharge are considered low-cost quality indicators. This work assesses an indicator of quality of care in a tertiary referral hospital in Argentina, using data available from clinical records. Purpose: To estimate the rate of ED-visits and the hospital readmission rate (HRR) after a first hospitalization (First-H), and to identify associated factors. Methods: This retrospective cohort included patients who had a First-H in Hospital Italiano de Buenos Aires between 2014–2015. Follow-up occurred from discharge until ED-visit, readmission, death, disaffiliation from health insurance, or 13 months. We present HRR at 30 days and ED-visits rate at 72 h, using the Cox proportional-hazards regression model to explore associated factors, and reporting adjusted hazard ratios (HR) with their respective 95 %CI. Results: The study comprised 10,598 hospitalizations (median age was 68 years). Of these, 5966 had at least one consultation to the ED during follow up, resulting in a 24 h rate of consultations to ED of 1.51 % (95 %CI 1.29−1.72); at 48 h 3.18 % (95 %CI 2.86−3.54); at 72 h 4.71 % (95 %CI 4.32−5.13). In multivariable models, factors associated for 72 h ED-visits were: age (aHR 1.06), male (aHR 1.14), Charlson Comorbidity Index (aHR 1.16), unscheduled hospitalization (aHR 1.39), prior consultation with the ED (aHR 1.08) and long hospital stay (aHR 1.39). Meanwhile, 2345 patients had at least one hospital readmission (98 % unscheduled), resulting a 24 h rate of 0.5 % (95 %CI 0.42−0.71), at 48 h 0.98 % (95 %CI 0.80−1.18), at 72 h 1.4 % (95 %CI 1.2−1.6); at 30 days 7.7 % (95 %CI 7.2−8.2); at 90 days 13 % (95 %CI 12.4–13.8); and one-year 22.5 % (95 %CI 21.7−23.4). Associated factors for HRR at 30 days were: age (HR 1.16), male (HR 1.09), Charlson comorbidities score (HR 1.27), social service requirement during First-H (HR 1.37), unscheduled First-H (HR 1.16), previous ED-visits (HR 1.03) and length of stay (HR 1.08). Conclusion: Priorities efforts to improve must include greater attention to patients’ readiness prior discharge, to explore causes of preventable readmissions, and better support for patient self-management.Fil: Giunta, Diego Hernan. Hospital Italiano. Instituto Universitario. Escuela de Medicina; ArgentinaFil: Marquez Fosser, Santiago. Université Mcgill; CanadáFil: Boietti, Bruno Rafael. Hospital Italiano. Instituto Universitario. Escuela de Medicina; ArgentinaFil: Acion, Laura. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Cálculo; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Calculo. - Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Calculo; ArgentinaFil: Pollan, Javier Alberto. Hospital Italiano. Instituto Universitario. Escuela de Medicina; ArgentinaFil: Martínez, Bernardo. Hospital Italiano. Instituto Universitario. Escuela de Medicina; ArgentinaFil: Luna, Daniel Roberto. Hospital Italiano. Instituto Universitario. Escuela de Medicina; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Bonella, Maria Belen. Hospital Italiano. Instituto Universitario. Escuela de Medicina; ArgentinaFil: Grande Ratti, Maria Florencia. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Hospital Italiano. Instituto Universitario. Escuela de Medicina; Argentin

Telemedicina: Validação de um questionário para avaliar a experiência dos profissionais de saúde

Objetivo. El siguiente trabajo tiene como objetivo desarrollar y validar un cuestionario para evaluar la experiencia de los profesionales de la salud con los sistemas de telemedicina. Métodos. A partir de la versión abreviada en español y validada localmente del cuestionario para pacientes desarrollado por Parmanto y col., un grupo de expertos consensuó una versión para evaluar la experiencia de profesionales de la salud que brindan servicios de telemedicina. El comportamiento psicométrico de los ítems se testeó en una primera muestra de 129 profesionales a través de un análisis factorial exploratorio. Luego, se evaluó su comprensibilidad a través de entrevistas cognitivas. Por último, en una nueva muestra de 329 profesionales, se evaluó la validez de constructo del cuestionario mediante un análisis factorial confirmatorio (AFC), y su validez de criterio externo, mediante la evaluación de su puntaje con el de una pregunta de resumen. Resultados. Se obtuvo un cuestionario de 12 ítems con una estructura de dos factores con indicadores de ajuste aceptables, documentada mediante AFC. La fiabilidad, la validez convergente y la validez discrimi- nante fueron apropiadas. La validez de criterio externo mostró resultados óptimos. Conclusiones. El instrumento obtenido cuenta con propiedades psicométricas adecuadas y contribuirá a la evaluación objetiva de la experiencia de los profesionales que realizan telemedicina.Objective. This objective of this work is to develop and validate a questionnaire to evaluate health professionals' experience with telemedicine systems. Methods. Based on an abbreviated, locally validated Spanish-language version of the patient questionnaire developed by Parmanto et al., a group of experts developed a version to evaluate the experience of health professionals who provide telemedicine services. The psychometric behavior of the items was tested in an initial sample of 129 professionals, using exploratory factor analysis. The comprehensibility of the items was then assessed through cognitive interviews. Finally, in a new sample of 329 professionals, the construct validity of the questionnaire was evaluated by means of confirmatory factor analysis (CFA); its criteria of external validity were assessed by comparing the score with that of a summary question. Results. A 12-item questionnaire was obtained, with a two-factor structure and acceptable adjustment indicators documented through CFA. Reliability, convergent validity, and discriminant validity were appropriate. The criteria of external validity showed optimal results. Conclusions. The instrument obtained has adequate psychometric properties and will contribute to the objective evaluation of the experience of health professionals who perform telemedicine.Objetivo. Desenvolver e validar um questionário para avaliar a experiência dos profissionais de saúde com os sistemas de telemedicina. Métodos. Com base na versão abreviada em espanhol e validada localmente do questionário para pacientes desenvolvido por Parmanto et al., um grupo de especialistas gerou uma versão de consenso para avaliar a experiência de profissionais de saúde que prestam serviços de telemedicina. O comportamento psicométrico dos itens foi testado em uma primeira amostra de 129 profissionais, por meio de análise fatorial exploratória. Em seguida, sua compreensibilidade foi avaliada por meio de entrevistas cognitivas. Por fim, em uma nova amostra de 329 profissionais, avaliouse a validade de construto do questionário por meio de uma análise fatorial confirmatória (AFC), e sua validade de critério externo, mediante a avaliação de sua pontuação com a de uma pergunta resumo. Resultados. Obteve-se um questionário de 12 itens com estrutura de dois fatores, com indicadores de ajuste aceitáveis, documentados pela AFC. A confiabilidade, a validade convergente e a validade discriminante foram adequadas. A validade de critério externo apresentou ótimos resultados. Conclusões. O instrumento obtido possui propriedades psicométricas adequadas e contribuirá para a ava- liação objetiva da experiência dos profissionais que realizam telemedicina.Fil: Sommer, Janine. Hospital Italiano. Departamento de Informática En Salud.; ArgentinaFil: Torres, Ana Clara. Hospital Italiano; ArgentinaFil: Bibiloni, Nuria. Hospital Italiano; ArgentinaFil: Plazzotta, Fernando. Hospital Italiano. Departamento de Informática En Salud.; ArgentinaFil: Vázquez Peña, Fernando. Hospital Italiano; ArgentinaFil: Terrasa, Sergio Adrián. Hospital Italiano; ArgentinaFil: Boietti, Bruno Rafael. Hospital Italiano; ArgentinaFil: Bruchanski, Lucila. Hospital Italiano. Departamento de Informática En Salud.; ArgentinaFil: Mazzuoccolo, Luis Daniel. Hospital Italiano; ArgentinaFil: Luna, Daniel Roberto. Hospital Italiano. Departamento de Informática En Salud.; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Medicina Traslacional e Ingeniería Biomédica - Hospital Italiano. Instituto de Medicina Traslacional e Ingeniería Biomédica.- Instituto Universitario Hospital Italiano de Buenos Aires. Instituto de Medicina Traslacional e Ingeniería Biomédica; Argentin

Institutional Registry of Elderly Patients With Hip Fracture in a Community-Based Tertiary Care Hospital in Argentina (RIAFC)

Background: A clinical registry encompasses a selective set of rigorously collected and stored clinical data focused on a specific condition. Hip fracture is a common complication of osteoporosis in elderly patients. Hip fracture substantially increases the risk of death and major morbidity in the elderly patients. Limited data regarding hip fracture are available from Latin America and Argentina. The purpose of this project is to create an institutional registry of elderly patients with hip fracture in order to obtain data that reveal the impact of this disease in our environment, allowing us to evaluate different strategies of patient’s care and clinical outcomes. Objective: To describe the implementation of an institutional registry of elderly patients with hip fracture in Argentina. Methods: In this article, we described the creation, implementation, and data management of a prospective registry of elderly patients with hip fracture. The registry contains information on baseline demographics, comorbidities, laboratory, and radiological data. Follow-up at 3 and 12 months postfracture is done by phone interview to assess physical function, readmissions, and morbi-mortality. Clinical Trials registry number NCT02279550. Conclusion: In this project, we have created a hip fracture registry. We hope that this registry will provide valuable data that can lead us to new lines of research, addressed to answer questions raised in clinical practice

Development and validation of COEWS (COVID-19 Early Warning Score) for hospitalized COVID-19 with laboratory features: A multicontinental retrospective study

Background: The emergence of new SARS-CoV-2 variants with significant immune-evasiveness, the relaxation of measures for reducing the number of infections, the waning of immune protection (particularly in high-risk population groups), and the low uptake of new vaccine boosters, forecast new waves of hospitalizations and admission to intensive care units. There is an urgent need for easily implementable and clinically effective Early Warning Scores (EWSs) that can predict the risk of complications within the next 24–48 hr. Although EWSs have been used in the evaluation of COVID-19 patients, there are several clinical limitations to their use. Moreover, no models have been tested on geographically distinct populations or population groups with varying levels of immune protection. Methods: We developed and validated COVID-19 Early Warning Score (COEWS), an EWS that is automatically calculated solely from laboratory parameters that are widely available and affordable. We benchmarked COEWS against the widely used NEWS2. We also evaluated the predictive performance of vaccinated and unvaccinated patients. Results: The variables of the COEWS predictive model were selected based on their predictive coefficients and on the wide availability of these laboratory variables. The final model included complete blood count, blood glucose, and oxygen saturation features. To make COEWS more actionable in real clinical situations, we transformed the predictive coefficients of the COEWS model into individual scores for each selected feature. The global score serves as an easy-to-calculate measure indicating the risk of a patient developing the combined outcome of mechanical ventilation or death within the next 48 hr. Conclusions: The COEWS score predicts death or MV within the next 48 hr based on routine and widely available laboratory measurements. The extensive external validation, its high performance, its ease of use, and its positive benchmark in comparison with the widely used NEWS2 position COEWS as a new reference tool for assisting clinical decisions and improving patient care in the upcoming pandemic waves. Funding: University of Vienna