Mejora en el manejo de la sospecha del síndrome aórtico agudo en urgencias mediante un algoritmo clínico y el estudio de factores predictivos / Improvement in the management of suspected acute aortic syndrome in the emergency room through a clinical algorithm and study of predictive factors

Antecedentes y objetivo: El síndrome aórtico agudo (SAA) es poco frecuente y difícil de diagnosticar, con una gran variabilidad en su cuadro clínico inicial. Los objetivos son: 1) desarrollar un algoritmo informático, o un sistema de apoyo a las decisiones clínicas (SADC), para el manejo y la solicitud de estudios de diagnóstico por imagen en el servicio de Urgencias, en concreto de una tomografía computarizada (TC) de la aorta, ante la sospecha de SAA, 2) determinar el efecto de la implantación de este sistema, y 3) determinar los factores asociados a un diagnóstico radiológico positivo que mejoren la capacidad predictiva de los hallazgos de la TC de aorta. Material y métodos: Tras desarrollar e implementar un algoritmo basado en la evidencia, se estudiaron casos de sospecha de SAA. Se utilizó el test de la χ2 para analizar la asociación entre las variables incluidas en el algoritmo y el diagnóstico radiológico, con 3 categorías: sin hallazgos relevantes, positivo para SAA y diagnósticos alternativos. Resultados: Se identificaron 130 solicitudes; 19 (14,6%) tenían SAA y 34 (26,2%) tenían otra patología aguda. De las 19 con SAA, 15 habían sido estratificadas como de alto riesgo y 4 como de riesgo intermedio. La probabilidad de SAA era 3,4 veces mayor en los pacientes con aneurisma aórtico conocido (p=0,021, IC del 95%: 1,2-9,6) y 5,1 veces mayor en los pacientes con un soplo de insuficiencia vascular aórtica de novo(p=0,019, IC del 95 %: 1,3-20,1). La probabilidad de tener una enfermedad aguda grave alternativa fue 3,2 veces mayor en los pacientes con hipotensión o choque (p=0,02, IC del 95 %: 1,2-8,5). Conclusión: El uso de un SADC en el servicio de Urgencias puede ayudar a optimizar el diagnóstico del SAA. Se demostró que la presencia de un aneurisma aórtico conocido y de insuficiencia valvular aórtica de nueva aparición aumentan significativamente la probabilidad de SAA. Se necesitan más estudios para establecer una regla de predicción clínica.(AU)

Background and objective: Acute aortic syndrome (AAS) is uncommon and difficult to diagnose, with great variability in clinical presentation. To develop a computerized algorithm, or clinical decision support system (CDSS), for managing and requesting imaging in the emergency department, specifically computerized tomography of the aorta (CTA), when there is suspicion of AAS, and to determine the effect of implementing this system. To determine the factors associated with a positive radiological diagnosis that improve the predictive capacity of CTA findings. Materials and methods: After developing and implementing an evidence-based algorithm, we studied suspected cases of AAS. Chi-squared test was used to analyze the association between the variables included in the algorithm and radiological diagnosis, with 3 categories: no relevant findings, positive for AAS, and alternative diagnoses. Results: 130 requests were identified; 19 (14.6%) had AAS and 34 (26.2%) had a different acute pathology. Of the 19 with AAS, 15 had been stratified as high risk and 4 as intermediate risk. The probability of AAS was 3.4 times higher in patients with known aortic aneurysm (P=.021, 95% CI 1.2–9.6) and 5.1 times higher in patients with a new aortic regurgitation murmur (P=.019, 95% CI 1.3–20.1). The probability of having an alternative severe acute pathology was 3.2 times higher in patients with hypotension or shock (P=.02, 95% CI 1.2–8.5). Conclusion: The use of a CDSS in the emergency department can help optimize AAS diagnosis. The presence of a known aortic aneurysm and new-onset aortic regurgitation were shown to significantly increase the probability of AAS. Further studies are needed to establish a clinical prediction rule.(AU)

Improvement in the management of suspected acute aortic syndrome in the emergency room through a clinical algorithm and study of predictive factors.

BACKGROUND AND OBJECTIVE: Acute aortic syndrome (AAS) is uncommon and difficult to diagnose, with great variability in clinical presentation. To develop a computerized algorithm, or clinical decision support system (CDSS), for managing and requesting imaging in the emergency department, specifically computerized tomography of the aorta (CTA), when there is suspicion of AAS, and to determine the effect of implementing this system. To determine the factors associated with a positive radiological diagnosis that improve the predictive capacity of CTA findings. MATERIALS AND METHODS: After developing and implementing an evidence-based algorithm, we studied suspected cases of AAS. Chi-squared test was used to analyze the association between the variables included in the algorithm and radiological diagnosis, with 3 categories: no relevant findings, positive for AAS, and alternative diagnoses. RESULTS: 130 requests were identified; 19 (14.6%) had AAS and 34 (26.2%) had a different acute pathology. Of the 19 with AAS, 15 had been stratified as high risk and 4 as intermediate risk. The probability of AAS was 3.4 times higher in patients with known aortic aneurysm (P = .021, 95% CI 1.2-9.6) and 5.1 times higher in patients with a new aortic regurgitation murmur (P = .019, 95% CI 1.3-20.1). The probability of having an alternative severe acute pathology was 3.2 times higher in patients with hypotension or shock (P = .02, 95% CI 1.2-8.5). CONCLUSION: The use of a CDSS in the emergency department can help optimize AAS diagnosis. The presence of a known aortic aneurysm and new-onset aortic regurgitation were shown to significantly increase the probability of AAS. Further studies are needed to establish a clinical prediction rule.

Effects of oral probiotic supplements on vaginal microbiota during pregnancy: a randomised, double-blind, placebo-controlled trial with microbiome analysis.

OBJECTIVE: To determine the effects on the vaginal microbiota of an oral probiotic preparation administered from early pregnancy. DESIGN: Randomised, double blind, placebo-controlled trial. SETTING: Four maternity units in the UK. POPULATION: Women aged 16 years or older recruited at 9-14 weeks' gestation. METHODS: Participants were randomly allocated to receive oral capsules of probiotic containing Lactobacillus rhamnosus GR-1 and Lactobacillus reuteri RC-14 each at 2.5 × 109 colony-forming units (CFUs) or placebo once daily from recruitment until the end of pregnancy. MAIN OUTCOME MEASURE: Rates of bacterial vaginosis (BV, defined as Nugent score ≥7) at 18-20 weeks' gestation compared by logistic regression adjusted for possible confounders. RESULTS: The primary analysis included 78% (238/304) of participants who initially consented (probiotic group 123, placebo group 115). Of these participants, 95% (227/238) reported an intake of 93% or more of the required number of capsules. The rates of BV did not differ between groups at 18-20 weeks' gestation (15% (19/123) in the probiotic group vs. 9% (10/115) in the placebo group, adjusted odds ratio 1.82, 95% confidence interval 0.64-5.19). There were also no differences between the groups in the proportion of women colonised with the probiotic strains, Escherichia coli, group B streptococci or other vaginal microbiota. There were no differences in the alpha diversity or composition of the bacterial communities between or within the probiotic and placebo groups at 9-14 and 18-20 weeks' gestation. CONCLUSIONS: Oral probiotics taken from early pregnancy did not modify the vaginal microbiota. TWEETABLE ABSTRACT: The oral probiotic preparation used in this study does not prevent BV in pregnant women.

Correction to: Prognostic factors of mortality after surgery in infective endocarditis: systematic review and meta-analysis.

The original version of this article unfortunately contained a mistake.

Prognostic factors of mortality after surgery in infective endocarditis: systematic review and meta-analysis.

PURPOSE: There is a lack of consensus about which endocarditis-specific preoperative characteristics have an actual impact over postoperative mortality. Our objective was the identification and quantification of these factors. METHODS: We performed a systematic review of all the studies which reported factors related to in-hospital mortality after surgery for acute infective endocarditis, conducted according to PRISMA recommendations. A search string was constructed and applied on three different databases. Two investigators independently reviewed the retrieved references. Quality assessment was performed for identification of potential biases. All the variables that were included in at least two validated risk scores were meta-analyzed independently, and the pooled estimates were expressed as odds ratios (OR) with their confidence intervals (CI). RESULTS: The final sample consisted on 16 studies, comprising a total of 7484 patients. The overall pooled OR were statistically significant (p < 0.05) for: age (OR 1.03, 95% CI 1.00-1.05), female sex (OR 1.56, 95% CI 1.35-1.81), urgent or emergency surgery (OR 2.39 95% CI 1.91-3.00), previous cardiac surgery (OR 2.19, 95% CI 1.84-2.61), NYHA ≥ III (OR 1.84, 95% CI 1.33-2.55), cardiogenic shock (OR 4.15, 95% CI 3.06-5.64), prosthetic valve (OR 1.98, 95% CI 1.68-2.33), multivalvular affection (OR 1.35, 95% CI 1.01-1.82), renal failure (OR 2.57, 95% CI 2.15-3.06), paravalvular abscess (OR 2.39, 95% CI 1.77-3.22) and S. aureus infection (OR 2.27, 95% CI 1.89-2.73). CONCLUSIONS: After a systematic review, we identified 11 preoperative factors related to an increased postoperative mortality. The meta-analysis of each of these factors showed a significant association with an increased in-hospital mortality after surgery for active infective endocarditis. Graph summary of the Pooled Odds Ratios of the 11 preoperative factors analyzed after the systematic review and meta-analysis.