Utilidad del Holter insertable con detección remota en el diagnóstico etiológico del ictus criptogénico: análisis de 73 pacientes / Use of the insertable Holter with remote detection in the etiological diagnosis of cryptogenic stroke: Analysis of 73 patients

Introducción El ictus criptogénico constituye el 25% del total de ictus isquémicos, de los cuales un 20-30% son debidos a fibrilación auricular (FA). Con el objetivo de aumentar la tasa de detección, surgen los dispositivos de monitorización prolongada implantables. El estudio del perfil del candidato ideal subsidiario de dicha monitorización otorgaría un mejor entendimiento de los mecanismos que subyacen en este subtipo de ictus. Objetivo Determinar qué variables están relacionadas y pueden predecir la detección de FA silente en pacientes con ictus criptogénico. Pacientes y métodos Se trata de una cohorte longitudinal con selección desde marzo de 2017 hasta mayo de 2022. Son pacientes portadores de dispositivo de monitorización implantable e ictus criptogénico con monitorización mínima de un año. Resultados El total de pacientes incluidos fue de 73, con edad media de 58,8 años, siendo el 56,2% varones. Se detectó FA en 21 pacientes (28,8%). Los factores de riesgo cardiovascular más frecuentes fueron hipertensión (47,9%) y dislipidemia (45,2%). La topografía más frecuente fue cortical (52%). En cuanto a los parámetros ecocardiográficos, un 22% tenían la aurícula izquierda dilatada, un 19% tenían foramen oval permeable y un 22% presentaron taquicardia supraventricular de alta densidad (>1%) en el Holter. En el análisis multivariante, la única variable predictora de FA es la presencia taquicardia supraventricular de alta densidad, con un área bajo la curva de 0,726 (IC 0,57-0,87, p=0,04), una sensibilidad del 47,6%, una especificidad del 97,5%, un valor predictivo positivo del 90,9%, un valor predictivo negativo del 78,8% y una exactitud del 80,9%. Conclusiones La presencia de taquicardia supraventricular de alta densidad puede ser orientativa para predecir FA silente. No se han observado otras variables que nos permitan predecir la detección de FA en estos pacientes (AU)

Introduction Cryptogenic stroke constitutes 25% of all ischemic strokes, of which 20–30% are due to atrial fibrillation (AF). With the aim of increasing the detection rate, implantable long-term monitoring devices have emerged. The study of the profile of the ideal candidate subsidiary to such monitoring would provide a better understanding of the mechanisms underlying this subtype of stroke. Objective To determine which variables are related and can predict the detection of silent AF in patients with cryptogenic stroke. Patients and methods This is a longitudinal cohort with recruitment from March 2017 to May 2022. They are patients with an implantable monitoring device and cryptogenic stroke with a minimum monitoring of one year. Result The total number of patients included was 73, with a mean age of 58.8 years, 56.2% were male. AF was detected in 21 patients (28.8%). The most frequent cardiovascular risk factors were hypertension (47.9%) and dyslipidemia (45.2%). The most frequent topography was cortical (52%). Regarding the echocardiographic parameters, 22% had a dilated left atrium, 19% had a patent foramen ovale, and 22% had high-density supraventricular tachycardia (>1%) on Holter monitoring. In the multivariate analysis, the only variable that predicts AF is the presence of high-density supraventricular tachycardia, with an area under the curve of 0.726 (CI 0.57–0.87, p=0.04), sensitivity of 47.6%, specificity of 97.5%, positive predictive value of 90.9%, negative predictive value of 78.8%, and accuracy of 80.9%. Conclusions The presence of high-density supraventricular tachycardia can be indicative for predicting silent AF. No other variables have been observed that allow us to predict detection of AF in these patients (AU)

[Use of the insertable Holter with remote detection in the etiological diagnosis of cryptogenic stroke: Analysis of 73 patients]. / Utilidad del Holter insertable con detección remota en el diagnóstico etiológico del ictus criptogénico: análisis de 73 pacientes.

INTRODUCTION: Cryptogenic stroke constitutes 25% of all ischemic strokes, of which 20-30% are due to atrial fibrillation (AF). With the aim of increasing the detection rate, implantable long-term monitoring devices have emerged. The study of the profile of the ideal candidate subsidiary to such monitoring would provide a better understanding of the mechanisms underlying this subtype of stroke. OBJECTIVE: To determine which variables are related and can predict the detection of silent AF in patients with cryptogenic stroke. PATIENTS AND METHODS: This is a longitudinal cohort with recruitment from March 2017 to May 2022. They are patients with an implantable monitoring device and cryptogenic stroke with a minimum monitoring of one year. RESULTS: The total number of patients included was 73, with a mean age of 58.8 years, 56.2% were male. AF was detected in 21 patients (28.8%). The most frequent cardiovascular risk factors were hypertension (47.9%) and dyslipidemia (45.2%). The most frequent topography was cortical (52%). Regarding the echocardiographic parameters, 22% had a dilated left atrium, 19% had a patent foramen ovale, and 22% had high-density supraventricular tachycardia (>1%) on Holter monitoring. In the multivariate analysis, the only variable that predicts AF is the presence of high-density supraventricular tachycardia, with an area under the curve of 0.726 (CI 0.57-0.87, p=0.04), sensitivity of 47.6%, specificity of 97.5%, positive predictive value of 90.9%, negative predictive value of 78.8%, and accuracy of 80.9%. CONCLUSIONS: The presence of high-density supraventricular tachycardia can be indicative for predicting silent AF. No other variables have been observed that allow us to predict detection of AF in these patients.

Factores predictores de meningitis bacteriana en los pacientes atendidos en urgencias / Predictive factors of bacterial meningitis in the patients seen in emergency departments

OBJETIVOS: Analizar y comparar los factores predictivos de meningitis bacteriana (MB) en los pacientes que acuden al servicio de urgencias (SU) por un episodio de meningitis aguda (MA). MÉTODOS: Estudio observacional y prospectivo de pacientes adultos (≥15años) diagnosticados de MA en un SU desde agosto de 2009 hasta noviembre de 2015. Se analizaron 32 variables (epidemiológicas, de comorbilidad, clínicas y analíticas) que pudieran predecir etiología bacteriana. Se realizó un estudio multivariable mediante regresión logística. RESULTADOS: Se incluyó a 154 pacientes, de los que 53 (34,4%) fueron MB. Cuatro variables se asociaron de forma significativa como predictores de etiología bacteriana: lactato en líquido cefalorraquídeo (LCR) ≥33mg/dl (odds ratio [OR]: 50,84; intervalo de confianza [IC] al 95%: 21,63-119,47; p < 0,001); procalcitonina (PCT) sérica ≥0,8ng/ml (OR: 46,34; IC95%: 19,71-108,89; p < 0,001), glucorraquia <60% de la glucemia (OR: 20,82; IC95%: 8,86-48,96; p = 0,001), proporción de polimorfonucleares (PMN) en LCR >50% (OR: 20,19; IC 95%: 8,31-49,09; p = 0,002). El área bajo la curva-ROC del modelo (PCT≥0,8ng/ml+lactato en LCR ≥33mg/dl) fue 0,992 (IC95%: 0,979-1; p < 0,001) y consigue una sensibilidad del 99% y una especificidad del 98% para predecir MB. CONCLUSIONES: La PCT sérica, junto con la valoración del lactato, glucorraquia y proporción de PMN del LCR en la evaluación inicial del paciente con sospecha de MA en el SU, tienen un excelente rendimiento diagnóstico para predecir la MB

OBJECTIVES: To analyse and compare predictive factors of bacterial meningitis in the patients seen in the Emergency Departments (ED) due to an episode of acute meningitis (AM). METHODS: A prospective, observational study was carried out in patients aged 15 years and older seen in ED due to AM between August 2009 and November 2015. Thirty-two variables for predicting bacterial meningitis were assessed. They covered epidemiological, comorbidity, clinical and analytical factors. Multivariate logistic regression analysis was performed. RESULTS: The study included 154 patients. The diagnosis was bacterial meningitis in 53 (34.4%) patients. Four variables were significantly associated with bacterial aetiology: cerebrospinal fluid (CSF) lactate concentration ≥33mg/dl (odds ratio [OR] 50.84; 95% confidence interval [CI]: 21.63-119.47, P<.001), serum procalcitonin (PCT) ≥0.8ng/ml (OR 46.34; 95%CI: 19.71-108.89; P<.001), CSF glucose <60% of blood value (OR 20.82; 95%CI: 8.86-48.96; P=.001), CSF polymorphonuclears greater than 50% (OR 20.19; 95%CI: 8.31-49.09; P=.002]. The area under the curve for the model serum PCT≥0.8ng/ml plus CSF lactate ≥33mg/dl was 0.992 (95%CI: 0.979-1; P<.001), and achieved 99% sensitivity and 98% specificity for predicting bacterial meningitis. CONCLUSIONS: Serum PCT with CSF lactate, CSF glucose and CSF polymorphonuclears evaluated in an initial assessment in the ED for patients with AM, achieved an excellent diagnostic usefulness for predicting bacterial meningitis

Predictive factors of bacterial meningitis in the patients seen in emergency departments. / Factores predictores de meningitis bacteriana en los pacientes atendidos en urgencias.

OBJETIVES: To analyse and compare predictive factors of bacterial meningitis in the patients seen in the Emergency Departments (ED) due to an episode of acute meningitis (AM). METHODS: A prospective, observational study was carried out in patients aged 15 years and older seen in ED due to AM between August 2009 and November 2015. Thirty-two variables for predicting bacterial meningitis were assessed. They covered epidemiological, comorbidity, clinical and analytical factors. Multivariate logistic regression analysis was performed. RESULTS: The study included 154 patients. The diagnosis was bacterial meningitis in 53 (34.4%) patients. Four variables were significantly associated with bacterial aetiology: cerebrospinal fluid (CSF) lactate concentration ≥33mg/dl (odds ratio [OR] 50.84; 95% confidence interval [CI]: 21.63-119.47, P<.001), serum procalcitonin (PCT) ≥0.8ng/ml (OR 46.34; 95%CI: 19.71-108.89; P<.001), CSF glucose <60% of blood value (OR 20.82; 95%CI: 8.86-48.96; P=.001), CSF polymorphonuclears greater than 50% (OR 20.19; 95%CI: 8.31-49.09; P=.002]. The area under the curve for the model serum PCT≥0.8ng/ml plus CSF lactate ≥33mg/dl was 0.992 (95%CI: 0.979-1; P<.001), and achieved 99% sensitivity and 98% specificity for predicting bacterial meningitis. CONCLUSIONS: Serum PCT with CSF lactate, CSF glucose and CSF polymorphonuclears evaluated in an initial assessment in the ED for patients with AM, achieved an excellent diagnostic usefulness for predicting bacterial meningitis.

Respuesta: Pannus reumatoide: una nomenclatura equívoca / Reply: Rheumatoid pannus: an ambiguous nomenclature

No disponible

No disponible

Mielopatía cervical por pannus reumatoide como forma de la artritis reumatoide / Cervical mielopathy by rheumatoid pannusas onset form of rheumatoid arthritis

No disponible

No disponible

Hidrocefalia triventricular secundaria a espacios de Virchow-Robin dilatados mesencefálicos / No disponible

No disponible

Hidrocefalia triventricular secundaria a espacios de Virchow-Robin dilatados mesencefálicos / No disponible

No disponible