Prevenção secundária de morte súbita cardíaca na cardiopatia chagásica crônica e função ventricular quase-normal

Introdução: A cardiopatia chagásica crônica (CCC) engloba complexo espectro de apresentações, não sendo incomuns episódios de morte arrítmica em portadores de função ventricular esquerda preservada (FVEP) ou quase normal (FVEQN). Métodos: Avaliação retrospectiva de 7 portadores de CCC por 4 anos, com FVEP, submetidos a implante de cardiodesfibrilador implantável (CDI) devido taquicardia ou fibrilação ventricular (TV/FV). Foram realizadas avaliações clínica, estrutural e eletrocardiográfica. Resultados: Idade média: 57,5±4,45 anos e 71,4% do sexo masculino. Função ventricular esquerda (FVE) inicial foi de 56,14%±4,45, com alterações contrácteis em 100% e hipocinesia inferior em 85,7%. Classe funcional I: 100% sem modificações ao  eguimento. Escore de Rassi avaliado previamente ao evento foi de 4,85±0,89. Síncope constituiu a apresentação inicial em 100%, média de 2 episódios por paciente e intervalo de 4 semanas entre os mesmos. Houve alterações em 85,71% dos eletrocardiogramas, sendo bloqueio de ramo direito a principal. TV sustentada foi encontrada em 100%; sítio epicárdico em 71,42% e saída anterolateral do ventrículo esquerdo em 57,14%. A FVE sequencial foi de 54%±3,31; sem alterações contráteis novas. Amiodarona e betabloqueadores foram os fármacos utilizados. Terapias apropriadas aconteceram em 100%; média de 2,1 choques por paciente, com 52,63% dos registros nos primeiros 14 meses. Não foram evidenciados óbitos, terapias inapropriadas ou tempestade elétrica. Conclusão: O elevado número de terapias corrobora o risco arrítmico desta população, ratifica a importância do dispositivo e alerta para a eficácia da terapia clínica. Síncope pode estar associada a maior risco de eventos arrítmicos na CCC

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

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