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RESUMEN Introducción: Los pacientes con lupus eritematoso sistémico (LES) tienen un riesgo aumen tado de padecer infecciones tanto adquiridas en la comunidad como asociadas con el cuidado de la salud. Las infecciones bacterianas son las más frecuentes y graves durante la hospitalización de estos pacientes. Objetivo: Desarrollar y validar internamente un modelo de predicción clínica de pronóstico del riesgo de infección bacteriana adquirida en el hospital en pacientes con LES, usando datos clínicos y de laboratorio obtenidos durante las primeras horas de hospitalización. Métodos: Se analizó una cohorte retrospectiva de pacientes con LES mayores de 16 arios, hos pitalizados por motivos diferentes a infección bacteriana en 2 hospitales de alta complejidad de Medellín entre 2011 y 2016. Se compararon las características de los pacientes que des arrollaron el desenlace de infección bacteriana entre el día 3 y el día 15 de hospitalización con aquellos que no lo presentaron. Las variables significativas en el análisis bivariado fueron consideradas para la construcción del modelo por medio de regresión logística multivariada. Resultados: Se incluyeron 765 episodios, de los cuales 98 (12,8%) presentaron el desenlace de interés. Se consideraron 35 predictores candidatos. Las variables incorporadas en el modelo final fueron: edad, recuento de neutrófilos, puntaje de actividad lúpica SLEDAI, uso de sonda vesical, uso de catéter venoso central en las primeras 72 h, dosis de glucocorticoides en el mes previo y el uso de un antimalárico en los 3 meses previos. La capacidad de discrimi nación del modelo fue aceptable a buena (AUC-ROC 0,74; IC 95% 0,69-0,80). La prueba de bondad de ajuste de Hosmer-Lemeshow (p = 0,637) evidenció una adecuada calibración. Conclusión: Desarrollamos un modelo de predicción clínica de pronóstico del riesgo de infec ción bacteriana nosocomial en pacientes con LES. El modelo desarrollado está compuesto por variables clínicas y de laboratorio simples disponibles en el momento del ingreso al hospital. Se requieren estudios de validación externa y de impacto clínico antes de su implementación rutinaria.
ABSTRACT Introduction: Patients with systemic lupus erythematosus (SLE) have an increased risk of developing community-acquired infections, as well as those associated with health care. Bacterial infections are the most common and serious while these patients are in hospital. Objective: To develop, and internally validate, a clinical prediction model for the prognosis of the risk of hospital-acquired bacterial infection in SLE patients using clinical and laboratory data obtained during the first hours of hospital admission. Methods: An analysis was performed on retrospective cohort of patients with SLE older than 16 years and admitted for reasons other than bacterial infection in 2 highly complex hospitals in Medellín between 2011 and 2016. The characteristics of the patients who developed a bacterial infection were compared between day 3 and day 15 of hospital admission with those who did not develop one. The significant variables in the bivariate analysis were used for the construction of the model using multivariate logistic regression. Results: A total of 765 episodes were included, of which 98 (12.8%) presented the outcome of interest. Thirty-five candidate predictors were considered. The variables incorporated in the final model were: age, neutrophil count, SLEDAI lupus activity score, use of a bladder catheter, use of a central venous catheter in the first 72 h, glucocorticoid doses in the previous month, and use of an antimalarial drug in the 3 previous months. The discrimination capacity of the model was acceptable to good (AUC-ROC 0.74; 95% CI 0.69-0.80). The Hosmer-Lemeshow goodness of fit test (P = .637) suggested adequate calibration. Conclusion: A clinical prediction model of prognostic risk of nosocomial bacterial infection in patients with SLE has been developed. This model is made up of simple clinical and laboratory variables available at the time of hospital admission. External validation and clinical impact studies are required before routine implementation.
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Humanos , Adolescente , Adulto , Predicción , Pronóstico , Infecciones Bacterianas y Micosis , Estudios de Cohortes , Enfermedades de la Piel y Tejido Conjuntivo , Modelos Inmunológicos , Lupus Eritematoso Sistémico , AntimaláricosRESUMEN
BACKGROUND: All definitions for diagnosing sarcopenia include the estimation of muscle mass. This can be made using bioelectrical impedance analysis (BIA) or dual x-ray absorptiometry (DXA). BIA is a portable and inexpensive method suitable for clinical settings, while DXA is cumbersome, more expensive and less available. OBJECTIVES: To evaluate the interchangeability of both techniques for skeletal muscle mass index (SMI) estimation, and assess whether the two methods are comparable for the diagnosis of sarcopenia. APPROACH: Prospective, cross-sectional study. SETTING: Faculty for Health Sciences, Universidad de Caldas, Colombia. PARTICIPANTS: Seventy-two subjects aged 65-80 years were recruited. MEASUREMENTS: BIA and DXA for SMI estimation and sarcopenia diagnoses using the definition of the European Working Group on Sarcopenia in Older People (EWGSOP). Of the 72 patients, 28 were diagnosed with sarcopenia by BIA and corroborated by DXA were included in the study. To establish the agreement between techniques, the intraclass correlation coefficient and the concordance correlation coefficient were calculated. A Bland-Altman plot evaluated the agreement. To evaluate agreement on the diagnosis of sarcopenia, a Cohen's kappa test was performed. MAIN RESULTS: Agreement between SMI by BIA and DXA was good according to the intraclass correlation coefficient (ICC 0.7 95% CI 0.5 to 0.8) but poor when the concordance correlation coefficient was used (CCC 0.4 was calculated 95% CI 0.3 to 0.5). The Bland-Altman analysis showed a clinically unacceptable discrepancy between the methods; the confidence intervals were too wide; the difference between methods tends to get larger as the average increases and the scatter around the bias line get larger as the average gets higher. Cohen's kappa test was 0.2 (SEE: 0.1). SIGNIFICANCE: The agreement between BIA and DXA was weak. We concluded that, in this studied population, the methods were not interchangeable. Results may improve if a specific formula in a greater sample size is used.