Objective: To evaluate the effect of brief counseling on patient readiness for behavioral change and cessation/reduction of tobacco and alcohol use. Methods: This clinical trial randomized patients in blocks, stratified by risk factor. Adult smokers or at-risk drinkers undergoing surgical or diagnostic procedures were recruited. Outcome assessments and analyses were blinded. Brief counseling was compared with educational materials for the outcomes progress in stage of change and smoking/alcohol cessation/reduction. Results: Overall, 222 participants were randomly assigned to the intervention group and 218 to the control group. Among them, 28 and 18 patients were lost to follow-up, respectively. Progress in change stage was 94.1% at 1 month in both groups (RR = 1.00; 95%CI 0.95-1.05) and 94.8 vs. 90.5% at 3 months (RR = 1.05; 95%CI 0.99-1.11) in the intervention and control groups, respectively. Smoking cessation and alcohol reduction rates at 3 months were 57.2 vs. 41% (RR = 1.40; 95%CI 1.14-1.71) in the intervention and control groups, respectively. Only brief counseling led to significant differences in smoking cessation (51.4 vs. 35.1%; RR = 1.46; 95%CI 1.12-1.92). Conclusions: Brief counseling and educational materials improved patient motivation for behavioral change, but brief counseling had a greater effect on smoking cessation. Clinical trial registration: NCT03521622

Resumen Introducción. Las intervenciones dirigidas a la cesación del tabaquismo son una prioridad en los escenarios de atención médica, incluido el hospitalario. Objetivos. Describir las características sociodemográficas, familiares y clínicas de fumadores atendidos en un hospital de cuarto nivel y establecer las variables asociadas con la intención de cesación del tabaquismo con el fin de optimizar el manejo de este factor de riesgo en el entorno hospitalario. Materiales y métodos. Estudio transversal realizado en 321 fumadores activos atendidos entre abril de 2018 y noviembre de 2019 en Bogotá D.C., Colombia. Se calculó la prevalencia de tabaquismo y se obtuvo información sociodemográfica, familiar y clínica, la cual fue analizada mediante estadística descriptiva. Se establecieron asociaciones entre dichas variables y la intención de cesación mediante un análisis bivariado (prueba X2) y uno multivariado (modelo de regresión logística ordinal con sus correspondientes intervalos de confianza al 95%). Resultados. La prevalencia de tabaquismo activo fue de 8.89% (IC95%: 7.97-9.82), (N=3 609; n=321 fumadores activos). La mayoría fueron hombres (66.67%), de estrato socioeconómico bajo o medio (96.89%), con nivel educativo básico (52.34%) y el 42.06% estaban entre los 46 y 64 años. La mayoría de los fumadores activos tenían un grado leve de tabaquismo y un bajo nivel de dependencia a la nicotina (78.82% y 81.62%, respectivamente); además, el 78.82% reportó intentos previos de cesación. El tipo de familia predominante fue la nuclear (58.57%) y 40.19% de los fumadores experimentaban algún grado de disfuncionalidad familiar. Los fumadores con mayor percepción de beneficios derivados de dejar de fumar y con alta autoeficacia tienen una mayor probabilidad de realizar un intento de cesación de tabaquismo (OR=9.44; IC95%: 1.27-85.03 and OR=3.73; 95%CI: 1.55-8.78, respectivamente). Conclusiones. La identificación y caracterización de fumadores en el entorno hospitalario brinda claves para personalizar las intervenciones de cesación del tabaquismo.

Abstract Introduction: Smoking cessation interventions are a priority in medical care settings, including hospitals. Objectives: To describe the sociodemographic, family, and clinical characteristics of smokers treated in a quaternary care hospital and to establish the variables associated with smoking cessation intention in order to optimize the management of this risk factor in the hospital setting. Materials and methods. A cross-sectional study was conducted in 321 active smokers treated between April 2018 and November 2019 in Bogotá D.C., Colombia. Smoking prevalence was calculated, and participants' sociodemographic, family, and clinical information was obtained and subsequently analyzed using descriptive statistics. Associations between said variables and cessation intention were established by means of bivariate (chi-squared test) and multivariate analyses (ordinal logistic regression model with the corresponding 95% confidence intervals). Results: Smoking prevalence was 8.89% (95%CI: 7.97-9.82), (N=3609; n=321 active smokers). Most participants were men (66.67%), had a low or middle socioeconomic status (96.89%) and a basic educational level (52.34%), and 42.06% were between 46 and 64 years old. The majority of active smokers had a mild degree of smoking consumption and low level of nicotine dependence (78.82% and 81.62%, respectively). Furthermore, 78.82% reported previous attempts to quit smoking. Nuclear family was the predominant family type (58.57%), and 40.19% of smokers experienced some degree of family dysfunction. Smokers with more perceived benefits derived from smoking cessation and high self-efficacy are more likely to make a smoking cessation attempt (OR=9.44, 95%CI:1.27-85.03 and OR=3.73, 95%CI:1.55-8.78, respectively). Conclusions: The identification and characterization of smokers in the hospital setting provides useful insights to personalize smoking cessation interventions.

Resumen Introducción: La mortalidad por SARS-COV-2 ha disminuido en diferentes países, pero no se ha evaluado si es igual en Colombia, o si se relaciona con las carac terísticas de los pacientes y tratamientos utilizados. Objetivo: Comparar la mortalidad por SARS-COV-2, en dos periodos de tiempo controlando por factores de riesgo asociados con mortalidad. Metodología: Estudio observacional, basado en una cohorte retrospectiva de pacientes con SARS-COV-2 atendidos en el Hospital Universitario San Ignacio, Bogotá (Colombia), desde el 19 de marzo al 12 de noviembre, 2020. Se comparó la tasa de mortalidad intrahospitalaria de los pacientes egresados antes y después del 21 de agosto de 2020 (primer pico de mortalidad en Colombia) y se analizó el impacto del momento de atención controlando por comorbilidades, severidad al ingreso y tratamiento recibido, usando un modelo de regresión logística. Resultados: 1399 pacientes (944 antes y 455 después del primer pico de mortalidad) fueron analizados. La tasa de mortalidad intrahospitalaria global fue similar en ambos periodos (17.6% vs 16.3%, p=0.539). En el análisis multivariado se encontró que la atención en el segundo periodo de tiempo se asoció a menor mortalidad (OR 0.66 IC95% 0.47; 0.93, p=0.018), a diferencia del aumento de la misma asociado a la edad (OR 1.06 IC95% 1.05; 1.07, p<0.001), sexo masculino (OR 1.84 IC95% 1.33; 2.54 p<0.001), cirrosis (OR 1.89 IC95% 1.24; 2.88, p=0.003), enfermedad renal (OR 1.36 IC95% 1.00; 1.83, p=0.043) y el uso de dexametasona (OR 1.53 IC95% 1.03; 2.28, p=0.031). Conclusiones: La tasa de mortalidad intrahospitalaria se redujo después del 21 de agosto durante la primera ola de la pandemia en Bogotá, posiblemente asociado a la mejoría en la capacidad de respuesta del sistema de salud en ese momento, o a un menor inoculo viral de los pacientes infectados. Estos hallazgos pueden cambiar con la saturación del sistema de salud.

Abstract Introduction: Mortality secondary to SARS-COV 2 has decreases around the world, however this has not been evaluated in Colombia neither has the correlation between patient characteristics or treatments. Objective: To compare the mortality due to SARS-COV-2, in two periods of time, controlling risk factors associated with mortality. Methodology: Observational retrospective cohort study of patients with SARS- COV-2 treated at the San Ignacio University Hospital in Bogotá (Colombia), from March 19 to November 12, 2020. The in-hospital mortality rate of patients discharged before and after August 21, 2020 (surge mortality in Colombia) was com pared. The impact of the moment of attention was analyzed controlled by comorbidities, severity at admission and treatment received using a bivariate and multivariate logistic regression model. Results: 1399 patients (944 before and 455 after August 21) were analyzed. The overall in-hospital mortality rate was similar at both times (17.6%vs16.3percentage, p=0.539). In the multivariate analysis, it was found that the moment of attention was associated with lower mortality (OR 0.66 95% CI0.47;0.93,p=0.018), in contrast to its increase associated with age (OR 1.06 95% CI 1.05;1.07,p=<0.001), male sex (OR 1.84 95%CI 1.33;2.54,p=<0.001), cirrhosis (OR1.89 95%CI 1.24;2.88, p=0.003), kidney disease (OR 1.36 95% CI1.00;1.83,p=0.043) and the use of dexamethasone (OR1.53 95%CI 1.03;2.28,p=0.031). Conclusions: The in-hospital mortality rate fell after August 21 during the first wave of the pandemic in Bogotá-Colombia, possibly associated with an improvement in response capacity, or a lower viral inoculum of infected patients. These findings may change with the saturation of the health system

ABSTRACT Background: People living with HIV are at increased risk of cardiovascular disease. Cardiovascular risk (CVR) prediction scores are powerful tools for individualized assessment that inform decision-making about follow-up frequency, hypolipemiant treatment intensification, and choice antiretroviral therapy. Objectives: The objectives of the study were to evaluate the performance of multiple cardiovascular assessment scores in predicting major adverse cardiovascular events (MACE) at 5 and 10 years. Framingham (2004, 2008, and Colombia-adjusted), SCORE, PROCAM, ASCVD, and D:A:D scores were included in the analysis. Methods: Data were obtained from a medical registry of adults living with HIV attended by a teaching hospital in Colombia. All patients with complete information necessary for risk score calculations and determination of MACE at 5 and 10 years were included in the study. Receiver operating characteristic curves (ROC) were generated using calculations with all the aforementioned models for every individual. Differences between curves were compared with DeLong's test. Results: A total of 808 patients were included in the analysis. Mean age was 35 years, and 12% were female. The majority of subjects had low and very low CVR. Eight MACE occurred during follow-up. Area under ROC curves were: Framingham (0.90), Framingham ATP3 (0.92), Framingham calibrated for Colombia (0.90), SCORE (0.92), PROCAM (0.92), ASCVD (0.89), and D:A:D (0.92), with no statistically significant differences. Conclusions: The evaluated scores had an acceptable performance for HIV-infected patients in the studied cohort, especially for those in low and very low risk categories.

Resumen El triaje permite la priorización de pacientes según su urgencia médica, y de ahí que este artículo se proponga realizar un modelo estadístico correlacionado con la mortalidad para generar alertas desde el triaje con una cohorte prospectiva de 6438 adultos que ingresaron a urgencias del Hospital Universitario San Ignacio del 1/3/2018 al 28/2/2019. Se dividieron aleatoriamente los datos en entrenamiento y prueba. Sobre los datos de entrenamiento se ejecutó una regresión logística bivariada entre triaje y mortalidad y, luego, una regresión logística multivariada. Después, el modelo se redujo mediante pruebas de razón de verosimilitud. En los datos de prueba se realizaron áreas bajo la curva (ROC, por sus siglas en inglés) para el cálculo de punto de corte, que se evaluó con medidas de asociación. Hubo ROC para los modelos realizados y se halló el modelo triaje con una ROC de 0,82; “reducido”, con una ROC de 0,90, y “Edad + sistólica”, con una ROC de 0,87, sin diferencia significativa. Se seleccionó el “reducido” con una sensibilidad de 0,869; una especificidad de 0,842; una VPP de 0,066, y una VPN de 0,998. El punto de corte se seleccionó con un árbol de decisiones según las variables significativas, que encontró una mayor mortalidad en pacientes triaje 1-2, con TAS menor de 117 mmHg y mayores de 58 años. El modelo final podría funcionar como tamización para generar alarmas de mortalidad en triaje iguales.

Abstract Triage allows priorization of patients according to their medical urgency. Multiple triage systems have been developed in the world. We propose a statistical model using triage to create an alert system related to mortality rates that could be used as a screening tool during triage. A prospective cohort of 6438 adults who were admitted to the emergency room of Hospital Universitario San Ignacio between 03/01/2018 and /02/28/2019 was used. The data was divided into “training” and “testing”. A bivariate logistic regression between triage and mortality using “training” data was done. Afterwards, a multivariate logistic regression was downgraded using the previous information. In order to find the set point, an Area Under the Curve (ROC) was calculated using the “testing data”. The efficiency was evaluated using measures of association. Three different ROC models were created: “triage” which showed an ROC-0.82, “reduced” with an ROC-0.90 and “age+systolic” with an ROC-0.87, thereby not exhibiting significant difference. The reduced model was chosen, presenting sensitivity of 0.869, specificity of 0.842, PPV 0.062, and NPV 0.998. A set point was chosen according to significant variables, demonstrating a higher mortality rate in those classified as triage 1-2, those over 58 years old, and those presenting with SBP below 117mmHg. Our final model could be useful as an additional screening measure for patients within the same triage classification as an alert system for mortality.