Taquicardia de complexos QRS alargados com manifestações eletrocardiográficas atípicas elucidada através de cardio-exploração transesofágica - Relato de caso

Taquicardia de compLexos QRS aLargados (com morfoLogia de bLoqueio do ramo esquerdo) foi desencadeada durante Cardioexploração Eletrofisiológica Transesofágica. 0 E. C. G. de 12 derivações demonstrou duração dos complexos superior a 140 ms., desvio do eixo elétrico para esquerda no plano frontal e sugestivos batimentos de jusão, caracteristicas que na ausência previa de pré-excitação anter6grada ou bloqueio de ramo, sugeriram uma origem ventricular da taquiarritmia. Obteve-se reversão da mesma mediante aplicação de manobras vagais e reprodução por estimulação atrial programada. Numa etapa posterior, foi induzida taquicardia de complexos QRS estreitos, onde os impulsos iniciais apresentavam morfologia aberrante, identica ao padrao observado anteriormente. Tais achados conduziram ao diagnóstico de taquicardia supra-ventricular com condução aberrante. A observação de encurtamento do ciclo da mesma ap6s estreitamento dos complexos QRS, permitiu pressupor a presença de uma via acessória esquerda oculta envolvida na sua origem. A analise isolada de critérios eletrocardiográficos no caso em questão, poderia ter conduzido a erro diagnóstico. Uma avaliação detalhada, atraves de cardioexploração transesofagica (CETE) e manipulação autonômica possibilitou a diferenciação, assim como estabelecer 0 mecanismo preciso da taquicardia

Seminário de Dissertação (2024)

Página da disciplina de Seminário de Dissertação (MPPP, UFPE, 2022) Lista de participantes == https://docs.google.com/spreadsheets/d/1mrULe1y04yPxHUBaF50jhaM1OY8QYJ3zva4N4yvm198/edit#gid=

ABC₂-SPH risk score for in-hospital mortality in COVID-19 patients

Objectives: The majority of available scores to assess mortality risk of coronavirus disease 2019 (COVID-19) patients in the emergency department have high risk of bias. Therefore, this cohort aimed to develop and validate a score at hospital admission for predicting in-hospital mortality in COVID-19 patients and to compare this score with other existing ones. Methods: Consecutive patients (≥ 18 years) with confirmed COVID-19 admitted to the participating hospitals were included. Logistic regression analysis was performed to develop a prediction model for in-hospital mortality, based on the 3978 patients admitted between March–July, 2020. The model was validated in the 1054 patients admitted during August–September, as well as in an external cohort of 474 Spanish patients. Results: Median (25–75th percentile) age of the model-derivation cohort was 60 (48–72) years, and in-hospital mortality was 20.3%. The validation cohorts had similar age distribution and in-hospital mortality. Seven significant variables were included in the risk score: age, blood urea nitrogen, number of comorbidities, C-reactive protein, SpO2/FiO2 ratio, platelet count, and heart rate. The model had high discriminatory value (AUROC 0.844, 95% CI 0.829–0.859), which was confirmed in the Brazilian (0.859 [95% CI 0.833–0.885]) and Spanish (0.894 [95% CI 0.870–0.919]) validation cohorts, and displayed better discrimination ability than other existing scores. It is implemented in a freely available online risk calculator (https://abc2sph.com/). Conclusions: An easy-to-use rapid scoring system based on characteristics of COVID-19 patients commonly available at hospital presentation was designed and validated for early stratification of in-hospital mortality risk of patients with COVID-19.</p

ABC-SPH risk score for in-hospital mortality in COVID-19 patients : development, external validation and comparison with other available scores

The majority of available scores to assess mortality risk of coronavirus disease 2019 (COVID-19) patients in the emergency department have high risk of bias. Therefore, this cohort aimed to develop and validate a score at hospital admission for predicting in-hospital mortality in COVID-19 patients and to compare this score with other existing ones. Consecutive patients (≥ 18 years) with confirmed COVID-19 admitted to the participating hospitals were included. Logistic regression analysis was performed to develop a prediction model for in-hospital mortality, based on the 3978 patients admitted between March-July, 2020. The model was validated in the 1054 patients admitted during August-September, as well as in an external cohort of 474 Spanish patients. Median (25-75th percentile) age of the model-derivation cohort was 60 (48-72) years, and in-hospital mortality was 20.3%. The validation cohorts had similar age distribution and in-hospital mortality. Seven significant variables were included in the risk score: age, blood urea nitrogen, number of comorbidities, C-reactive protein, SpO/FiO ratio, platelet count, and heart rate. The model had high discriminatory value (AUROC 0.844, 95% CI 0.829-0.859), which was confirmed in the Brazilian (0.859 [95% CI 0.833-0.885]) and Spanish (0.894 [95% CI 0.870-0.919]) validation cohorts, and displayed better discrimination ability than other existing scores. It is implemented in a freely available online risk calculator (https://abc2sph.com/). An easy-to-use rapid scoring system based on characteristics of COVID-19 patients commonly available at hospital presentation was designed and validated for early stratification of in-hospital mortality risk of patients with COVID-19