Introduction: The safety of inpatients is a priority in the health care system. The Global Trigger Tool seems to be suitable to estimate the incidence of adverse events (AE) in pediatric inpatients. Objectives: To describe the incidence and categories of AE in pediatric inpatients using the Global Trigger Tool and to identify risk factors associated to their development. Population and methods: Retrospective study. Medical records of 200 patients hospitalized at Hospital Elizalde during 2013 were included. Outcome measures: number of AE/100 admissions and distribution of harm. A chi² test, Student's t test and Pearson's correlation test were carried out. Significance level = p < 0.05. Results: The study detected 289 triggers (1.4/patient); 52 AEs (26 AEs/100 patients, 95% CI: 20.4-32.5). There was at least one AE every 36 patients; 7 patients had more than one AE; 45 AEs were in the E and F categories (temporary harm). Medical care triggers were associated to AEs (OR 8.1; 95% CI: 3.7-17.3, p < 0.001). A positive correlation was found between the number of triggers and the number of AEs per patient (R= 0.46; p < 0.001). Being hospitalized in a closed unit (OR 2.8; 95% CI: 1.2-6.5; p= 0.03) and a longer hospital stay were associated to AEs (p < 0.001). Conclusion: An AE frequency of 26% was identified, and most AEs resulted in temporary harm. The presence of AEs was associated to hospitalization in a closed unit, longer hospital stay, higher number of triggers and general care triggers.

Introducción: La seguridad del paciente hospitalizado es prioritaria para el sistema de salud. La herramienta de disparadores globales parecería ser adecuada para estimar la incidencia de eventos adversos (EA) en niños hospitalizados. Objetivos: Describir la incidencia y la categorización de EA en niños hospitalizados utilizando la herramienta de disparadores globales e identificar los factores de riesgo asociados a su aparición. Población y métodos: Estudio retrospectivo. Se incluyeron 200 historias clínicas de pacientes internados en el Hospital Elizalde en el año 2013. Variables de resultado: número de EA/100 ingresos y distribución del dano. Se utilizó la prueba de chi cuadrado, la prueba de t y la correlación de Pearson. Nivel de significación de p < 0,05. Resultados: Se detectaron 289 disparadores (1,4/paciente); 52 EA (26 EA cada 100 pacientes, IC 95%: 20,4-32,5). Presentaron, al menos, un EA 36 pacientes; 7 pacientes sufrieron más de uno; 45 EA fueron categoría E y F (dano temporario). Los disparadores de cuidados médicos se asociaron con EA (OR 8,1; IC 95%: 3,7-17,3; p < 0,001). Se encontró una correlación positiva entre el número de disparadores y el número de EA por paciente (R= 0,46; p < 0,001). Los pacientes internados en unidad cerrada (OR 2,8; IC 95%: 1,2-6,5; p= 0,03) y el mayor promedio de días de internación se asociaron a EA (p < 0,001). Conclusión: Se identificó una frecuencia de 26% de EA; la mayoría fue dano temporario. La internación en una unidad cerrada, la mayor cantidad de días de internación, el mayor número de disparadores y los disparadores de cuidados generales se asociaron con la presencia de EA.

OBJETIVOS: Estimar a prevalência de burnout entre residentes pediátricos e avaliar o impacto de uma intervenção breve voltada para o controle da doença. MÉTODOS: Foi realizado um estudo controlado randomizado em 74 residentes de pediatria. Todos preencheram o Inventário de Burnout de Maslach, e foram coletadas informações demográficas (idade, sexo, filhos, coabitantes e ano de residência). O grupo experimental (n = 37) participou de oficinas de autocuidado durante 2 meses, e o grupo controle (n = 37) não recebeu nenhuma intervenção. Após a intervenção, os participantes preencheram novamente o Inventário de Burnout de Maslach. Todos os potenciais preditores de burnout foram incluídos em um modelo de regressão logística. A eficácia da intervenção foi avaliada pelo teste qui-quadrado. Os valores p < 0,05 foram considerados significativos. RESULTADOS: A prevalência de burnout entre residentes pediátricos foi de 66%. Após controle para idade, gênero, filhos e coabitantes, a prevalência de burnout foi maior entre residentes do terceiro ano (razão de chances = 11,8; intervalo de confiança de 95% 2,3-59,3; p = 0,003). Não foram encontradas diferenças significativas na prevalência de burnout no grupo experimental entre os períodos inicial e pós-intervenção (p = 0,8) ou entre os dois grupos após a intervenção (p = 0,8). A única diferença observada foi uma melhora quanto à "despersonalização", no grupo experimental (p = 0,031). CONCLUSÕES: A prevalência de burnout entre residentes pediátricos foi de 66%, sendo maior entre os residentes do terceiro ano. Uma intervenção breve não foi eficaz na redução da prevalência de burnout, apesar da melhora no quesito "despersonalização".

OBJECTIVES: To estimate burnout prevalence among pediatric residents and to evaluate the impact of a brief intervention aimed at controlling burnout. METHODS: A randomized controlled trial was conducted on 74 pediatric residents. The Maslach Burnout Inventory was administered to all subjects, and demographic information was gathered (age, gender, children, cohabitants, and residency year). The experimental group (n = 37) participated in self-care workshops over the course of 2 months, and the control group (n = 37) did not receive any intervention. After the intervention, the Maslach Burnout Inventory was administered again to all participants. All potential predictors of burnout were included in a logistic regression model. The efficacy of the intervention was evaluated by the chi-square test. P values < 0.05 were considered significant. RESULTS: The burnout prevalence among pediatric residents was 66%. After controlling for age, gender, children, and cohabitants, the prevalence of burnout was significantly higher among third-year residents (odds ratio = 11.8; 95% confidence interval 2.3-59.3; p = 0.003). There were no significant differences regarding burnout prevalence in the experimental group between the baseline and post-intervention periods (p = 0.8) or between the two groups after intervention (p = 0.8). The only difference observed was an improvement regarding "depersonalization" in the experimental group (p = 0.031). CONCLUSIONS: The burnout prevalence among pediatric residents was 66% and was higher among third-year residents. A brief intervention was not effective in reducing burnout prevalence, despite the achievement of an improvement in "depersonalization."

Introduction. Despite most meningitis are not bacterial, antibiotics are usually administered on admission because bacterial meningitis is difficult to be rule-out. Distinguishing bacterial from aseptic meningitis on admission could avoid inappropriate antibiotic use and hospitalization. We aimed to validate a clinical prediction rule to distinguish bacterial from aseptic meningitis in children, on arriving to the emergency room. Methods. This prospective study included patients aged < 19 years with meningitis. Cerebrospinal fluid (CSF) and peripheral blood neutrophil count were obtained from all patients. The BMS (Bacterial Meningitis Score) described by Nigrovic (Pediatrics 2002; 110: 712), was calculated: positive CSF Gram stain= 2 points, CSF absolute neutrophil count ≥ 1000 cells/mm³, CSF protein ≥ 80 mg/dl, peripheral blood absolute neutrophil count ≥ 10.000/mm³, seizure = 1 point each. Sensitivity (S), specificity (E), positive and negative predictive values (PPV and NPV), positive and negative likelihood ratios (PLR and NLR) of the BMS to predict bacterial meningitis were calculated. Results. Seventy patients with meningitis were included (14 bacterial meningitis). When BMS was calculated, 25 patients showed a BMS= 0 points, 11 BMS= 1 point, and 34 BMS ≥ 2 points. A BMS = 0 showed S: 100%, E: 44%, VPP: 31%, VPN: 100%, RVP: 1,81 RVN: 0. A BMS ≥ 2 predicted bacterial meningitis with S: 100%, E: 64%, VPP: 41%, VPN: 100%, PLR: 2.8, NLR:0. Conclusions. Using BMS was simple, and allowed identifying children with very low risk of bacterial meningitis. It could be a useful tool to assist clinical decision making.

Introducción. La mayoría de las meningitis en la infancia no son bacterianas, pero la dificultad en descartar tal etiología obliga con frecuencia a utilizar antibióticos inicialmente. El objetivo de este trabajo fue validar, en nuestro medio, una regla de predicción clínica para diferenciar la etiología de las meningitis en niños a su ingreso al hospital. Método. Estudio prospectivo que incluyó pacientes < 19 años de edad con diagnóstico de meningitis. En todos se obtuvo líquido cefalorraquídeo (LCR) para análisis directo, citoquímico y cultivo, y hemograma. Se calculó el BMS (Bacterial Meningitis Score: puntaje de meningitis bacteriana) descripto por Nigrovic (Pediatrics 2002; 110: 712): tinción de Gram en LCR positiva= 2 puntos; proteinorraquia ≥ 80 mg/dl, neutrófilos en sangre periférica ≥ 10 000/mm³, neutrófilos en LCR ≥ 1000/mm³, convulsiones, 1 punto cada uno. Se calculó sensibilidad (S), especificidad (E), valores predictivos positivo y negativo (VPP y VPN) y razones de verosimilitud positiva y negativa (RVP y RVN) del BMS para predecir meningitis bacteriana. Resultados. Se incluyeron 70 pacientes con meningitis (14 bacterianas). Veinticinco pacientes presentaron BMS= 0 puntos, 11 BMS= 1 punto y 34 BMS ≥ 2 puntos. Un BMS= 0 evidenció S: 100%, E: 44%, VPP: 31%, VPN: 100%, RVP: 1,81 RVN: 0 para predecir meningitis bacteriana. Un BMS ≥ 2 mostró S: 100%, E: 64%, VPP: 41%, VPN: 100%, RVP: 2,8 RVN: 0 para predecir meningitis bacteriana. Conclusión. La utilización del BMS fue simple y permitió identificar pacientes con bajo riesgo de meningitis bacteriana. Su empleo podría constituir una herramienta útil en la toma de decisiones clínicas.