Real-Time Energy Management System for Microgrids

Abstract: Microgrids (MD) is a new technology to improve efficiency, resilience, and reliability in the electricity sector. MD are most likely to have a clean energy generation, but the increase of microgrids with this kind of generation brings new challenges for energy management (EMS), especially concerning load uncertainties and variation of energy generation. In this context, this study has the main objective to propose a method of how to attend this matter, verifying the difference between the day before and real-time. The EMS proposed analyses the MD in real-time, calculating the deviation between dispatched and what was predicted to happen in the operation point in a three-dimensional analysis approach, considering renewable energy generation, battery State of Charge (SOC) and load curve. The system categorized the deviation in three possible quantities (small, medium, or high) and it acts accordingly. For the Next Operation Point predictor are used an artificial neural network (ANN) methodology. For the Decision Support System, it's used a fuzzy logic system to adjust the next operation point, and it uses a mixed-integer linear programming (MILP) approach when the deviation is too high, and the dispatched operation is unfeasible. Simulations with real data and information of a pilot project of MD are carried out to test and validate the proposed method. Results show that the methodology used to attend the matters of uncertainties and variation of energy generation. A reduction of operational cost is observed in the simulations.

Validação de um Algoritmo de Inteligência Artificial para a Predição Diagnóstica de Doença Coronariana: Comparação com um Modelo Estatístico Tradicional / Validation of an Artificial Intelligence Algorithm for Diagnostic Prediction of Coronary Disease: Comparison with a Traditional Statistical Model

Resumo Fundamento: A análise prognóstica multivariada tem sido realizada tradicionalmente por modelos de regressão. No entanto, muitos algoritmos surgiram, capazes de traduzir uma infinidade de padrões em probabilidades. A acurácia dos modelos de inteligência artificial em comparação à de modelos estatísticos tradicionais não foi estabelecida na área médica. Objetivo: Testar a inteligência artificial como um algoritmo preciso na predição de doença coronariana no cenário de dor torácica aguda, e avaliar se seu desempenho é superior a do modelo estatístico tradicional. Métodos: Foi analisada uma amostra consecutiva de 962 pacientes admitidos com dor torácica. Dois modelos probabilísticos de doença coronariana foram construídos com os primeiros 2/3 dos pacientes: um algoritmo machine learning e um modelo logístico tradicional. O desempenho dessas duas estratégias preditivas foi avaliado no último terço de pacientes. O modelo final de regressão logística foi construído somente com variáveis significativas a um nível de significância de 5%. Resultados: A amostra de treinamento tinha idade média de 59 ± 15 anos, 58% do sexo masculino, e uma prevalência de doença coronariana de 52%. O modelo logístico foi composto de nove preditores independentes. O algoritmo machine learning foi composto por todos os candidatos a preditores. Na amostra teste, a área sob a curva ROC para predição de doença coronariana foi de 0,81 (IC95% = 0,77 - 0,86) para o algoritmo machine learning, similar à obtida no modelo logístico (0,82; IC95% = 0,77 - 0,87), p = 0,68. Conclusão: O presente estudo sugere que um modelo machine learning acurado não garante superioridade à um modelo estatístico tradicional

Abstract Background: Multivariate prognostic analysis has been traditionally performed by regression models. However, many algorithms capable of translating an infinity of patterns into probabilities have emerged. The comparative accuracy of artificial intelligence and traditional statistical models has not been established in the medical field. Objective: To test the artificial intelligence as an accurate algorithm for predicting coronary disease in the scenario of acute chest pain and evaluate whether its performance is superior to traditional statistical model. Methods: A consecutive sample of 962 patients admitted with chest pain was analyzed. Two probabilistic models of coronary disease were built using the first two-thirds of patients: a machine learning algorithm and a traditional logistic model. The performance of these two predictive strategies were evaluated in the remaining third of patients. The final logistic regression model had significant variables only, at the 5% significance level. Results: The training sample had an average age of 59 ± 15 years, 58% males, and a 52% prevalence of coronary disease. The logistic model was composed of nine independent predictors. The machine learning algorithm was composed of all candidates for predictors. In the test sample, the area under the ROC curve for prediction of coronary disease was 0.81 (95% CI = 0.77 - 0.86) for the machine learning algorithm, similar to that obtained in logistic model (0.82; 95% CI = 0.77 - 0.87), p = 0.68. Conclusion: The present study suggests that an accurate machine learning prediction tool did not prove to be superior to the statistical model of logistic regression.

Does Advanced Age Reduce the Typicality of Clinical Presentation in Patients with Acute Chest Pain Related to Coronary Artery Disease? / Idade Avançada Reduz a Tipicidade da Apresentação Clínica em Pacientes Com Dor Torácica Aguda Relacionada a Doença Coronária Obstrutiva?

BACKGROUND: According to traditional diagnosis thinking, very elderly individuals are more predisposed to develop atypical symptoms in acute coronary syndromes. OBJECTIVE: To test the hypothesis that very elderly individuals are more predisposed to atypical chest pain manifestations due to obstructive coronary artery disease (CAD). METHODS: The Registry of Thoracic Pain includes patients admitted with acute chest pain. Firstly, the typicality index of this clinical manifestation was constructed: the sum of 12 symptom characteristics (8 typical and 4 atypical symptoms). In the subgroup of patients with coronary etiology, the typicality index was compared between octogenarian and non-octogenarian individuals. Statistical significance was defined by p<0.05. RESULTS: 958 patients were included in the registry, and 486 (51%) had a supposedly coronary etiology. In this group, 59 (12%) octogenarians (age 84±3.5, 50% men) were compared to 427 patients aged <80 (60±12 years, 71% men). The typicality index in octogenarians was 3.42±1.92, which is similar to that of non-octogenarians (3.44±1.74; p=0.92 in univariate analysis and p=0.80 after adjustment for sex by analysis of variance - ANOVA). There was also no statistically significant difference when the sample was divided into median age (62 years; 3.41±1.77 vs. 3.49 ± 1.77; p=0.61). There was no statistically significant linear association between age and typicality index (r=- 0.05; p=0.24). Logistic regression analysis for prediction of CAD in the general sample of 958 patients showed no interaction of typicality index with numeric age (p=0.94), octogenarians (p=0.22) or age above median (p=0.74). CONCLUSION: In patients with acute chest pain of coronary etiology, advanced age does not influence the typical clinical presentation.

FUNDAMENTO: De acordo com o pensamento diagnóstico tradicional, indivíduos muito idosos estão mais predispostos a desenvolver sintomas atípicos em síndromes coronarianas agudas. OBJETIVO: Testar a hipótese de que indivíduos muito idosos estão mais predispostos a manifestações de dor torácica atípica devido à doença arterial coronariana obstrutiva (DAC). MÉTODOS: O Registro de dor torácica inclui pacientes internados com dor torácica aguda. Primeiramente, foi construído o índice de tipicidade dessa manifestação clínica: a soma de 12 características de sintomas (8 sintomas típicos e 4 sintomas atípicos). No subgrupo de pacientes com etiologia coronariana, o índice de tipicidade foi comparado entre octogenários e não octogenários. A significância estatística foi definida por p<0,05. RESULTADOS: 958 pacientes foram incluídos no registro, sendo que 486 (51%) tinham etiologia supostamente coronariana. Nesse grupo, 59 (12%) octogenários (idade 84±3,5; 50% homens) foram comparados a 427 pacientes com idade <80 (60±12 anos; 71% homens). O índice de tipicidade em octogenários foi 3,42±1,92, que é semelhante ao de não octogenários (3,44±1,74; p=0,092 na análise univariada e p=0,80 após ajuste para sexo pela análise de variância ­ ANOVA). Também não houve diferença estatisticamente significativa quando a amostra foi dividida em idade mediana (62 anos; 3,41±1,77 vs. 3,49 ± 1,77; p=0,61). Não houve associação linear estatisticamente significativa entre idade e índice de tipicidade (r=- 0,05; p=0,24). A análise de regressão logística para predição de DAC na amostra geral de 958 pacientes não mostrou interação do índice de tipicidade com a idade numérica (p=0,94), octogenários (p=0,22) ou idade acima da mediana (p=0,74). CONCLUSÃO: Em pacientes com dor torácica aguda de etiologia coronariana, a idade avançada não influencia o quadro clínico típico.

Idade Avançada Reduz a Tipicidade da Apresentação Clínica em Pacientes Com Dor Torácica Aguda Relacionada a Doença Coronária Obstrutiva? / Does Advanced Age Reduce the Typicality of Clinical Presentation in Patients with Acute Chest Pain Related to Coronary Artery Disease?

Resumo Fundamento De acordo com o pensamento diagnóstico tradicional, indivíduos muito idosos estão mais predispostos a desenvolver sintomas atípicos em síndromes coronarianas agudas. Objetivo Testar a hipótese de que indivíduos muito idosos estão mais predispostos a manifestações de dor torácica atípica devido à doença arterial coronariana obstrutiva (DAC). Métodos O Registro de dor torácica inclui pacientes internados com dor torácica aguda. Primeiramente, foi construído o índice de tipicidade dessa manifestação clínica: a soma de 12 características de sintomas (8 sintomas típicos e 4 sintomas atípicos). No subgrupo de pacientes com etiologia coronariana, o índice de tipicidade foi comparado entre octogenários e não octogenários. A significância estatística foi definida por p<0,05. Resultados 958 pacientes foram incluídos no registro, sendo que 486 (51%) tinham etiologia supostamente coronariana. Nesse grupo, 59 (12%) octogenários (idade 84±3,5; 50% homens) foram comparados a 427 pacientes com idade <80 (60±12 anos; 71% homens). O índice de tipicidade em octogenários foi 3,42±1,92, que é semelhante ao de não octogenários (3,44±1,74; p=0,092 na análise univariada e p=0,80 após ajuste para sexo pela análise de variância — ANOVA). Também não houve diferença estatisticamente significativa quando a amostra foi dividida em idade mediana (62 anos; 3,41±1,77 vs. 3,49 ± 1,77; p=0,61). Não houve associação linear estatisticamente significativa entre idade e índice de tipicidade (r=- 0,05; p=0,24). A análise de regressão logística para predição de DAC na amostra geral de 958 pacientes não mostrou interação do índice de tipicidade com a idade numérica (p=0,94), octogenários (p=0,22) ou idade acima da mediana (p=0,74). Conclusão Em pacientes com dor torácica aguda de etiologia coronariana, a idade avançada não influencia o quadro clínico típico.

Abstract Background According to traditional diagnosis thinking, very elderly individuals are more predisposed to develop atypical symptoms in acute coronary syndromes. Objective To test the hypothesis that very elderly individuals are more predisposed to atypical chest pain manifestations due to obstructive coronary artery disease (CAD). Methods The Registry of Thoracic Pain includes patients admitted with acute chest pain. Firstly, the typicality index of this clinical manifestation was constructed: the sum of 12 symptom characteristics (8 typical and 4 atypical symptoms). In the subgroup of patients with coronary etiology, the typicality index was compared between octogenarian and non-octogenarian individuals. Statistical significance was defined by p<0.05. Results 958 patients were included in the registry, and 486 (51%) had a supposedly coronary etiology. In this group, 59 (12%) octogenarians (age 84±3.5, 50% men) were compared to 427 patients aged <80 (60±12 years, 71% men). The typicality index in octogenarians was 3.42±1.92, which is similar to that of non-octogenarians (3.44±1.74; p=0.92 in univariate analysis and p=0.80 after adjustment for sex by analysis of variance — ANOVA). There was also no statistically significant difference when the sample was divided into median age (62 years; 3.41±1.77 vs. 3.49 ± 1.77; p=0.61). There was no statistically significant linear association between age and typicality index (r=- 0.05; p=0.24). Logistic regression analysis for prediction of CAD in the general sample of 958 patients showed no interaction of typicality index with numeric age (p=0.94), octogenarians (p=0.22) or age above median (p=0.74). Conclusion In patients with acute chest pain of coronary etiology, advanced age does not influence the typical clinical presentation.

Validation of an Artificial Intelligence Algorithm for Diagnostic Prediction of Coronary Disease: Comparison with a Traditional Statistical Model. / Validação de um Algoritmo de Inteligência Artificial para a Predição Diagnóstica de Doença Coronariana: Comparação com um Modelo Estatístico Tradicional.

BACKGROUND: Multivariate prognostic analysis has been traditionally performed by regression models. However, many algorithms capable of translating an infinity of patterns into probabilities have emerged. The comparative accuracy of artificial intelligence and traditional statistical models has not been established in the medical field. OBJECTIVE: To test the artificial intelligence as an accurate algorithm for predicting coronary disease in the scenario of acute chest pain and evaluate whether its performance is superior to traditional statistical model. METHODS: A consecutive sample of 962 patients admitted with chest pain was analyzed. Two probabilistic models of coronary disease were built using the first two-thirds of patients: a machine learning algorithm and a traditional logistic model. The performance of these two predictive strategies were evaluated in the remaining third of patients. The final logistic regression model had significant variables only, at the 5% significance level. RESULTS: The training sample had an average age of 59 ± 15 years, 58% males, and a 52% prevalence of coronary disease. The logistic model was composed of nine independent predictors. The machine learning algorithm was composed of all candidates for predictors. In the test sample, the area under the ROC curve for prediction of coronary disease was 0.81 (95% CI = 0.77 - 0.86) for the machine learning algorithm, similar to that obtained in logistic model (0.82; 95% CI = 0.77 - 0.87), p = 0.68. CONCLUSION: The present study suggests that an accurate machine learning prediction tool did not prove to be superior to the statistical model of logistic regression.

FUNDAMENTO: A análise prognóstica multivariada tem sido realizada tradicionalmente por modelos de regressão. No entanto, muitos algoritmos surgiram, capazes de traduzir uma infinidade de padrões em probabilidades. A acurácia dos modelos de inteligência artificial em comparação à de modelos estatísticos tradicionais não foi estabelecida na área médica. OBJETIVO: Testar a inteligência artificial como um algoritmo preciso na predição de doença coronariana no cenário de dor torácica aguda, e avaliar se seu desempenho é superior a do modelo estatístico tradicional. MÉTODOS: Foi analisada uma amostra consecutiva de 962 pacientes admitidos com dor torácica. Dois modelos probabilísticos de doença coronariana foram construídos com os primeiros 2/3 dos pacientes: um algoritmo machine learning e um modelo logístico tradicional. O desempenho dessas duas estratégias preditivas foi avaliado no último terço de pacientes. O modelo final de regressão logística foi construído somente com variáveis significativas a um nível de significância de 5%. RESULTADOS: A amostra de treinamento tinha idade média de 59 ± 15 anos, 58% do sexo masculino, e uma prevalência de doença coronariana de 52%. O modelo logístico foi composto de nove preditores independentes. O algoritmo machine learning foi composto por todos os candidatos a preditores. Na amostra teste, a área sob a curva ROC para predição de doença coronariana foi de 0,81 (IC95% = 0,77 ­ 0,86) para o algoritmo machine learning, similar à obtida no modelo logístico (0,82; IC95% = 0,77 ­ 0,87), p = 0,68. CONCLUSÃO: O presente estudo sugere que um modelo machine learning acurado não garante superioridade à um modelo estatístico tradicional.

Prognostic Contrast between Anatomical and Clinical Models Regarding Fatal and Non-Fatal Outcomes in Acute Coronary Syndromes. / Competência Prognóstica Distinta entre Modelo Clínico e Anatômico em Síndromes Coronarianas Agudas: Comparação por Tipo de Desfecho.

BACKGROUND: Recurrent ischemic events are mediated by atherosclerotic plaque instability, whereas death after an ischemic event results from gravity of insult and ability of the organism to adapt. The distinct nature of those types of events may respond for different prediction properties of clinical and anatomical information regarding type of outcome. OBJECTIVE: To identify prognostic properties of clinical and anatomical data in respect of fatal and non-fatal outcomes of patients hospitalized with acute coronary syndromes (ACS). METHODS: Patients consecutively admitted with ACS who underwent coronary angiography were recruited. The SYNTAX score was utilized as an anatomic model and the GRACE score as a clinical model. The predictive capacity of those scores was separately evaluated for prediction of non-fatal ischemic outcomes (infarction and refractory angina) and cardiovascular death during hospitalization. It was considered as significant a p-value <0,05. RESULTS: EAmong 365 people, cardiovascular death was observed in 4,4% and incidence of non-fatal ischemic outcomes in 11%. For cardiovascular death, SYNTAX and GRACE score presented similar C-statistic of 0,80 (95% IC: 0,70 - 0,92) and 0,89 (95% IC 0,81 - 0,96), respectively - p = 0,19. As for non-fatal ischemic outcomes, the SYNTAX score presented a moderate predictive value (C-statistic = 0,64; 95%IC 0,55 - 0,73), whereas the GRACE score did not presented association with this type of outcome (C-statistic = 0,50; 95%IC 0,40-0,61) - p = 0,027. CONCLUSION: Clinical and anatomic models similarly predict cardiovascular death in ACS. However, recurrence of coronary instability is better predicted by anatomic variables than clinical data. (Arq Bras Cardiol. 2020; [online].ahead print, PP.0-0).

FUNDAMENTO: Eventos isquêmicos recorrentes decorrem de instabilidade de placa aterosclerótica, enquanto morte após um evento isquêmico decorre da gravidade do insulto. A natureza diversa desses tipos de eventos pode fazer com que dados clínicos e anatômicos tenham diferentes capacidades prognósticas a depender do tipo de desfecho. OBJETIVO: Identificar as predileções prognósticas de dados clínicos e dados anatômicos em relação a desfechos coronários fatais e não fatais durante hospitalização de pacientes com síndromes coronarianas agudas (SCA). MÉTODOS: Pacientes consecutivamente admitidos por SCA que realizaram coronariografia foram recrutados. O escore SYNTAX foi utilizado como modelo anatômico e o escore GRACE como modelo clínico. A capacidade preditora desses escores foi comparada quando à predição de desfechos isquêmicos não fatais (infarto ou angina refratária) e de morte cardiovascular durante hospitalização. Significância estatística foi definida por p < 0,05. RESULTADOS: Entre 365 indivíduos, 4,4% foi a incidência de óbito hospitalar e 11% de desfechos isquêmicos não fatais. Para morte cardiovascular, ambos os escores ­ SYNTAX e GRACE ­ apresentaram capacidade discriminatória, com estatísticas-C similares: 0,80 (95%IC: 0,70­0,92) e 0,89 (95%IC 0,81­0,96), respectivamente ­ p=0,19. Quantos aos desfechos isquêmicos não fatais, o escore SYNTAX apresentou valor preditor (estatística-C = 0,64; 95%IC 0,55­0,73), porém o escore GRACE não mostrou associação com esse tipo de desfecho (estatística-C = 0,50; 95%IC: 0,40­0,61) ­ p=0,027. CONCLUSÃO: Os modelos clínico e anatômico predizem satisfatoriamente morte cardiovascular em SCA, enquanto a recorrência de instabilidade coronária é melhor prevista por características anatômicas do que por dados clínicos. (Arq Bras Cardiol. 2020; 115(2):219-225).

Competência Prognóstica Distinta entre Modelo Clínico e Anatômico em Síndromes Coronarianas Agudas: Comparação por Tipo de Desfecho / Prognostic Contrast between Anatomical and Clinical Models Regarding Fatal and Non-Fatal Outcomes in Acute Coronary Syndromes

Resumo Fundamento Eventos isquêmicos recorrentes decorrem de instabilidade de placa aterosclerótica, enquanto morte após um evento isquêmico decorre da gravidade do insulto. A natureza diversa desses tipos de eventos pode fazer com que dados clínicos e anatômicos tenham diferentes capacidades prognósticas a depender do tipo de desfecho. Objetivo Identificar as predileções prognósticas de dados clínicos e dados anatômicos em relação a desfechos coronários fatais e não fatais durante hospitalização de pacientes com síndromes coronarianas agudas (SCA). Métodos Pacientes consecutivamente admitidos por SCA que realizaram coronariografia foram recrutados. O escore SYNTAX foi utilizado como modelo anatômico e o escore GRACE como modelo clínico. A capacidade preditora desses escores foi comparada quando à predição de desfechos isquêmicos não fatais (infarto ou angina refratária) e de morte cardiovascular durante hospitalização. Significância estatística foi definida por p < 0,05. Resultados Entre 365 indivíduos, 4,4% foi a incidência de óbito hospitalar e 11% de desfechos isquêmicos não fatais. Para morte cardiovascular, ambos os escores — SYNTAX e GRACE — apresentaram capacidade discriminatória, com estatísticas-C similares: 0,80 (95%IC: 0,70-0,92) e 0,89 (95%IC 0,81-0,96), respectivamente — p=0,19. Quantos aos desfechos isquêmicos não fatais, o escore SYNTAX apresentou valor preditor (estatística-C = 0,64; 95%IC 0,55-0,73), porém o escore GRACE não mostrou associação com esse tipo de desfecho (estatística-C = 0,50; 95%IC: 0,40-0,61) — p=0,027. Conclusão Os modelos clínico e anatômico predizem satisfatoriamente morte cardiovascular em SCA, enquanto a recorrência de instabilidade coronária é melhor prevista por características anatômicas do que por dados clínicos. (Arq Bras Cardiol. 2020; 115(2):219-225)

Abstract Background Recurrent ischemic events are mediated by atherosclerotic plaque instability, whereas death after an ischemic event results from gravity of insult and ability of the organism to adapt. The distinct nature of those types of events may respond for different prediction properties of clinical and anatomical information regarding type of outcome. Objective To identify prognostic properties of clinical and anatomical data in respect of fatal and non-fatal outcomes of patients hospitalized with acute coronary syndromes (ACS). Methods Patients consecutively admitted with ACS who underwent coronary angiography were recruited. The SYNTAX score was utilized as an anatomic model and the GRACE score as a clinical model. The predictive capacity of those scores was separately evaluated for prediction of non-fatal ischemic outcomes (infarction and refractory angina) and cardiovascular death during hospitalization. It was considered as significant a p-value <0,05. Results EAmong 365 people, cardiovascular death was observed in 4,4% and incidence of non-fatal ischemic outcomes in 11%. For cardiovascular death, SYNTAX and GRACE score presented similar C-statistic of 0,80 (95% IC: 0,70 - 0,92) and 0,89 (95% IC 0,81 - 0,96), respectively - p = 0,19. As for non-fatal ischemic outcomes, the SYNTAX score presented a moderate predictive value (C-statistic = 0,64; 95%IC 0,55 - 0,73), whereas the GRACE score did not presented association with this type of outcome (C-statistic = 0,50; 95%IC 0,40-0,61) - p = 0,027. Conclusion Clinical and anatomic models similarly predict cardiovascular death in ACS. However, recurrence of coronary instability is better predicted by anatomic variables than clinical data. (Arq Bras Cardiol. 2020; [online].ahead print, PP.0-0)

Prognostic Value of NT-proBNP versus Killip Classification in Patients with Acute Coronary Syndromes / Valor Prognóstico do NT-proBNP versus Classificação de Killip em Pacientes com Síndromes Coronarianas Agudas

Abstract Background: Plasma levels of brain natriuretic peptides have better diagnostic accuracy compared to clinical-radiologic judgment for acute heart failure. In acute coronary syndromes (ACS), the prognostic value of acute heart failure is incorporated into predictive models through Killip classification. It is not established whether NT-proBNP could increment prognostic prediction. Objective: To evaluate whether NT-proBNP, as a measure of left ventricular dysfunction, improves the in-hospital prognostic value of the GRACE score in ACS. Methods: Patients admitted due to acute chest pain, with electrocardiogram and/or troponin criteria for ACS were included in the study. The plasma level of NT-proBNP was measured at hospital admission and the primary endpoint was defined as cardiovascular death during hospitalization. P-value < 0.05 was considered as significant. Results: Among 352 patients studied, cardiovascular mortality was 4.8%. The predictive value of NT-proBNP for cardiovascular death was shown by a C-statistic of 0.78 (95% CI = 0.65-0.90). After adjustment for the GRACE model subtracted by Killip variable, NT-proBNP remained independently associated with cardiovascular death (p = 0.015). However, discrimination by the GRACE-BNP logistic model (C-statistics = 0.83; 95%CI = 0.69-0.97) was not superior to the traditional GRACE Score with Killip (C-statistic = 0.82; 95%CI = 0.68-0.97). The GRACE-BNP model did not provide improvement in the classification of patients to high risk by the GRACE Score (net reclassification index = - 0.15; p = 0.14). Conclusion: Despite the statistical association with cardiovascular death, there was no evidence that NT-proBNP increments the prognostic value of GRACE score in ACS.

Resumo Fundamento: Os níveis plasmáticos de peptídeos natriuréticos cerebrais têm melhor precisão diagnóstica em comparação com a avaliação clínico-radiológica para insuficiência cardíaca aguda. Nas síndromes coronárias agudas (SCA), o valor prognóstico da insuficiência cardíaca aguda é incorporado nos modelos preditivos através da classificação de Killip. Não está estabelecido se o NT-proBNP poderia aumentar a previsão prognóstica. Objetivo: Avaliar se o NT-proBNP, como medida da disfunção ventricular esquerda, melhora o valor prognóstico intra-hospitalar do escore GRACE na SCA. Métodos: Foram incluídos no estudo pacientes admitidos por dor torácica aguda, com eletrocardiograma e/ou critérios de troponina para SCA. O nível plasmático de NT-proBNP foi medido no momento da admissão hospitalar e o desfecho primário foi definido como morte cardiovascular durante a hospitalização. Foi considerado significativo o valor de p < 0,05. Resultados: A mortalidade cardiovascular entre os 352 pacientes estudados foi de 4,8%. O valor preditivo do NT-proBNP para morte cardiovascular foi mostrado por uma estatística C de 0,78 (IC 95% = 0,65-0,90). Após o ajuste para o modelo GRACE subtraído pela variável Killip, o NT-proBNP permaneceu independentemente associado à morte cardiovascular (p = 0,015). No entanto, a discriminação pelo modelo logístico GRACE-BNP (estatística C = 0,83; IC 95% = 0,69-0,97) não foi superior ao escore GRACE tradicional com Killip (estatística C = 0,82; IC 95% = 0,68-0,97). O modelo GRACE-BNP não proporcionou melhora na classificação dos pacientes de alto risco pelo Escore GRACE (índice líquido de reclassificação = - 0,15; p = 0,14). Conclusão: Apesar da associação estatística com a morte cardiovascular, não houve evidências de que o NT-proBNP aumente o valor prognóstico do escore GRACE na SCA.

Prognostic Value of NT-proBNP versus Killip Classification in Patients with Acute Coronary Syndromes.

BACKGROUND: Plasma levels of brain natriuretic peptides have better diagnostic accuracy compared to clinical-radiologic judgment for acute heart failure. In acute coronary syndromes (ACS), the prognostic value of acute heart failure is incorporated into predictive models through Killip classification. It is not established whether NT-proBNP could increment prognostic prediction. OBJECTIVE: To evaluate whether NT-proBNP, as a measure of left ventricular dysfunction, improves the in-hospital prognostic value of the GRACE score in ACS. METHODS: Patients admitted due to acute chest pain, with electrocardiogram and/or troponin criteria for ACS were included in the study. The plasma level of NT-proBNP was measured at hospital admission and the primary endpoint was defined as cardiovascular death during hospitalization. P-value < 0.05 was considered as significant. RESULTS: Among 352 patients studied, cardiovascular mortality was 4.8%. The predictive value of NT-proBNP for cardiovascular death was shown by a C-statistic of 0.78 (95% CI = 0.65-0.90). After adjustment for the GRACE model subtracted by Killip variable, NT-proBNP remained independently associated with cardiovascular death (p = 0.015). However, discrimination by the GRACE-BNP logistic model (C-statistics = 0.83; 95%CI = 0.69-0.97) was not superior to the traditional GRACE Score with Killip (C-statistic = 0.82; 95%CI = 0.68-0.97). The GRACE-BNP model did not provide improvement in the classification of patients to high risk by the GRACE Score (net reclassification index = - 0.15; p = 0.14). CONCLUSION: Despite the statistical association with cardiovascular death, there was no evidence that NT-proBNP increments the prognostic value of GRACE score in ACS.

Behavioral Influence of Known Prognostic Markers on the Cardiologist's Decision following Acute Coronary Syndrome: the GRACE Score Paradox / Influência comportamental da predição de risco no processo de decisão do cardiologista: o paradoxo do Escore GRACE

Abstract Background: Behavioral scientists consistently point out that knowledge does not influence decisions as expected. GRACE Score is a well validated risk model for predicting death of patients with acute coronary syndromes (ACS). However, whether prognostic assessment by this Score modulates medical decision is not known. Objective: To test the hypothesis that the use of a validated risk score rationalizes the choice of invasive strategies for higher risk patients with non-ST-elevation ACS. Methods: ACS patients were consecutively included in this prospective registry. GRACE Score was routinely used by cardiologists as the prognostic risk model. An invasive strategy was defined as an immediate decision of the coronary angiography, which in the selective strategy was only indicated in case of positive non-invasive test or unstable course. Firstly, we evaluated the association between GRACE and invasiviness; secondly, in order to find out the actual determinants of the invasive strategy, we built a propensity model for invasive decision. For this analysis, a p-value < 0.05 was considered as significant. Results: In a sample of 570 patients, an invasive strategy was adopted for 394 (69%). GRACE Score was 118 ± 38 for the invasive group, similar to 116 ± 38 for the selective group (p = 0.64). A propensity score for the invasive strategy was derived from logistic regression: positive troponin and ST-deviation (positive associations) and hemoglobin (negative association). This score predicted an invasive strategy with c-statistics of 0.68 (95%CI: 0.63-0.73), opposed to GRACE Score (AUC 0.51; 95%CI: 0.47-0.57). Conclusion: The dissociation between GRACE Score and invasive decision in ACS suggests that the knowledge of prognostic probabilities might not determine medical decision.

Resumo Fundamento: Cientistas behavioristas ressaltam consistentemente que conhecimento não influencia decisão como esperado. O escore GRACE é um modelo de risco bem validado para prever morte de pacientes com síndromes coronarianas agudas (SCA). Todavia, não se sabe se a avaliação prognóstica pelo GRACE modula decisão médica. Objetivo: Testar a hipótese de que a utilização de escore de risco validado racionaliza a escolha de estratégias invasivas para pacientes de alto risco com SCA sem supradesnivelamento do segmento ST. Métodos: Pacientes com SCA foram consecutivamente incluídos neste registro prospectivo. O escore GRACE foi rotineiramente utilizado pelos cardiologistas como modelo de risco prognóstico. Estratégia invasiva foi definida como decisão imediata de cinecoronariografia, que na conservadora só era indicada se teste não invasivo positivo ou curso instável. Primeiro, avaliamos a associação entre GRACE e invasividade; segundo, a fim de descobrir atuais determinantes da estratégia invasiva, construímos um modelo de propensão para ela. Foi considerado significante um valor de p < 0,05 para esta análise. Resultados: Em amostra de 570 pacientes, estratégia invasiva foi adotada para 394 (69%). O escore GRACE foi de 118 ± 38 para o grupo invasivo, semelhante a 116 ± 38 do conservador (p = 0,64). O escore de propensão para estratégia invasiva foi derivado da regressão logística: troponina positiva e desvio de ST (associações positivas) e hemoglobina (associação negativa). Esse escore predisse estratégia invasiva com estatística-c de 0,68 (IC95%: 0,63-0,73), contrariando o Escore GRACE (AUC 0,51; IC95%: 0,47-0,57). Conclusão: A dissociação observada entre o valor do Escore GRACE e decisão invasiva em SCA sugere que o pensamento probabilístico pode não ser um importante determinante da decisão médica.

Behavioral Influence of Known Prognostic Markers on the Cardiologist's Decision following Acute Coronary Syndrome: the GRACE Score Paradox.

BACKGROUND: Behavioral scientists consistently point out that knowledge does not influence decisions as expected. GRACE Score is a well validated risk model for predicting death of patients with acute coronary syndromes (ACS). However, whether prognostic assessment by this Score modulates medical decision is not known. OBJECTIVE: To test the hypothesis that the use of a validated risk score rationalizes the choice of invasive strategies for higher risk patients with non-ST-elevation ACS. METHODS: ACS patients were consecutively included in this prospective registry. GRACE Score was routinely used by cardiologists as the prognostic risk model. An invasive strategy was defined as an immediate decision of the coronary angiography, which in the selective strategy was only indicated in case of positive non-invasive test or unstable course. Firstly, we evaluated the association between GRACE and invasiviness; secondly, in order to find out the actual determinants of the invasive strategy, we built a propensity model for invasive decision. For this analysis, a p-value < 0.05 was considered as significant. RESULTS: In a sample of 570 patients, an invasive strategy was adopted for 394 (69%). GRACE Score was 118 ± 38 for the invasive group, similar to 116 ± 38 for the selective group (p = 0.64). A propensity score for the invasive strategy was derived from logistic regression: positive troponin and ST-deviation (positive associations) and hemoglobin (negative association). This score predicted an invasive strategy with c-statistics of 0.68 (95%CI: 0.63-0.73), opposed to GRACE Score (AUC 0.51; 95%CI: 0.47-0.57). CONCLUSION: The dissociation between GRACE Score and invasive decision in ACS suggests that the knowledge of prognostic probabilities might not determine medical decision.

Inconsistency prevents the valuable synergism of explanatory and pragmatic trails.

OBJECTIVE: To assess review articles on pragmatic trials in order to describe how authors define the aim of this type of study, how comprehensive methodological topics are covered, and which topics are most valued by authors. METHODS: Review articles were selected from Medline Database, based on the expression "pragmatic trial" in the titles. Five trained medical students evaluated the articles, based on a list of 15 self-explanatory methodological topics. Each article was evaluated regarding topics covered. Baseline statements on the aim of pragmatic trials were derived. RESULTS: Among 22 articles identified, there was general agreement that the aim of a pragmatic trial is to evaluate if the intervention works under real-world conditions. The mean number of methodological topics addressed by each article was 7.6 ± 3.1. Only one article covered all 15 topics, three articles (14%) responded to at least 75% of topics and 13 articles (59%) mentioned at least 50% of the topics. The relative frequency each of the 15 topics was cited by articles had a mean of 50% ± 25%. No topic was addressed by all articles, only three (20%) were addressed by more than 75% of articles. CONCLUSIONS: There is agreement on the different aims of explanatory and pragmatic trials. But there is a large variation on methodological topics used to define a pragmatic trial, which led to inconsistency in defining the typical methodology of a pragmatic trial.

Prognostic Accuracy of the GRACE Score in Octogenarians and Nonagenarians with Acute Coronary Syndromes.

BACKGROUND: The GRACE Score was derived and validated from a cohort in which octogenarians and nonagenarians were poorly represented. OBJECTIVE: To test the accuracy of the GRACE score in predicting in-hospital mortality of very elderly individuals with acute coronary syndromes (ACS). METHODS: Prospective observational study conducted in the intensive coronary care unit of a tertiary center from September 2011 to August 2016. Patients consecutively admitted due to ACS were selected, and the very elderly group was defined by age ≥ 80 years. The GRACE Score was based on admission data and its accuracy was tested regarding prediction of in-hospital death. Statistical significance was defined by p value < 0,05. RESULTS: A total of 994 individuals was studied, 57% male, 77% with non-ST elevation myocardial infarction and 173 (17%) very elderly patients. The mean age of the sample was 65 ± 13 years, and the mean age of very elderly patients subgroup was 85 ± 3.7 years. The C-statistics of the GRACE Score in very elderly patients was 0.86 (95% CI = 0.78 - 0.93), with no difference when compared to the value for younger individuals 0.83 (95% CI = 0.75 - 0.91), with p = 0.69. The calibration of the score in very elderly patients was described by χ2 test of Hosmer-Lemeshow = 2.2 (p = 0.98), while the remaining patients presented χ2 = 9.0 (p = 0.35). Logistic regression analysis for death prediction did not show interaction between GRACE Score and variable of very elderly patients (p = 0.25). CONCLUSION: The GRACE Score in very elderly patients is accurate in predicting in-hospital ACS mortality, similarly to younger patients.

Prognostic Accuracy of the GRACE Score in Octogenarians and Nonagenarians with Acute Coronary Syndromes / Acurácia Prognóstica do Escore GRACE em Octogenários e Nonagenários com Síndromes Coronarianas Agudas

Abstract Background: The GRACE Score was derived and validated from a cohort in which octogenarians and nonagenarians were poorly represented. Objective: To test the accuracy of the GRACE score in predicting in-hospital mortality of very elderly individuals with acute coronary syndromes (ACS). Methods: Prospective observational study conducted in the intensive coronary care unit of a tertiary center from September 2011 to August 2016. Patients consecutively admitted due to ACS were selected, and the very elderly group was defined by age ≥ 80 years. The GRACE Score was based on admission data and its accuracy was tested regarding prediction of in-hospital death. Statistical significance was defined by p value < 0,05. Results: A total of 994 individuals was studied, 57% male, 77% with non-ST elevation myocardial infarction and 173 (17%) very elderly patients. The mean age of the sample was 65 ± 13 years, and the mean age of very elderly patients subgroup was 85 ± 3.7 years. The C-statistics of the GRACE Score in very elderly patients was 0.86 (95% CI = 0.78 - 0.93), with no difference when compared to the value for younger individuals 0.83 (95% CI = 0.75 - 0.91), with p = 0.69. The calibration of the score in very elderly patients was described by χ2 test of Hosmer-Lemeshow = 2.2 (p = 0.98), while the remaining patients presented χ2 = 9.0 (p = 0.35). Logistic regression analysis for death prediction did not show interaction between GRACE Score and variable of very elderly patients (p = 0.25). Conclusion: The GRACE Score in very elderly patients is accurate in predicting in-hospital ACS mortality, similarly to younger patients.

Resumo Fundamento: O Escore GRACE foi derivado e validado por coorte de questionável representatividade de indivíduos octogenários e nonagenários. Objetivo: Testar a acurácia do Escore GRACE na predição de óbito hospitalar em indivíduos muito idosos com síndromes coronarianas agudas (SCAs). Métodos: Coleta prospectiva realizada em unidade coronariana de hospital terciário, durante o período de setembro de 2011 a agosto de 2016. Indivíduos consecutivamente internados com SCA foram selecionados e o grupo muito idoso definido por idade ≥ 80 anos. A acurácia do Escore GRACE foi testada quanto à predição de óbito hospitalar. A significância estatística foi definida por valor p < 0,05. Resultados: Foram estudados 994 indivíduos, sendo 57% do sexo masculino, 77% com SCA sem supradesnível do segmento ST e 173 pacientes muito idosos. A média geral de idade foi 65 ± 13 anos, e a média de idade dos pacientes muito idosos, 85 ± 3,7 anos. A estatística-C do Escore GRACE em indivíduos muito idosos foi de 0,86 (95% IC = 0,78 - 0,93), sem diferença em relação aos indivíduos mais jovens (0,83; 95% IC = 0,75 - 0,91), com p = 0,69. A calibração do escore em muito idosos foi descrita por Teste χ2 de Hosmer-Lemeshow = 2,2 (p = 0,98), enquanto os demais pacientes apresentaram χ2 = 9,0 (p = 0,35). A análise de regressão logística para predição de óbito não revelou interação entre Escore GRACE e a variável muito idoso (p = 0,25). Conclusão: O Escore GRACE em indivíduos muito idosos é acurado para predição de mortalidade hospitalar em SCA, semelhante para indivíduos mais jovens.

Zero Calcium Score as a Filter for Further Testing in Patients Admitted to the Coronary Care Unit with Chest Pain / Inferência Bayesiana quanto ao Valor do Escore de Cálcio Zero como Filtro na Investigação da Dor Torácica Aguda em Unidade Coronariana

Abstract Background: The accuracy of zero coronary calcium score as a filter in patients with chest pain has been demonstrated at the emergency room and outpatient clinics, populations with low prevalence of coronary artery disease (CAD). Objective: To test the gatekeeping role of zero calcium score in patients with chest pain admitted to the coronary care unit (CCU), where the pretest probability of CAD is higher than that of other populations. Methods: Patients underwent computed tomography for calcium scoring, and obstructive CAD was defined by a minimum 70% stenosis on invasive angiography. Results: In 146 patients studied, the prevalence of CAD was 41%. A zero calcium score was present in 35% of the patients. The sensitivity and specificity of zero calcium score yielded a negative likelihood ratio of 0.16. After logistic regression adjustment for pretest probability, zero calcium score was independently associated with lower odds of CAD (OR = 0.12, 95%CI = 0.04-0.36), increasing the area under the ROC curve of the clinical model from 0.76 to 0.82 (p = 0.006). Zero calcium score provided a net reclassification improvement of 0.20 (p = 0.0018) over the clinical model when using a pretest probability threshold of 10% for discharging without further testing. In patients with pretest probability < 50%, zero calcium score had a negative predictive value of 95% (95%CI = 83%-99%), with a number needed to test of 2.1 for obtaining one additional discharge. Conclusion: Zero calcium score substantially reduces the pretest probability of obstructive CAD in patients admitted to the CCU with acute chest pain. (Arq Bras Cardiol. 2017; [online].ahead print, PP.0-0)

Resumo Fundamento: A acurácia do escore de cálcio coronário zero como um filtro nos pacientes com dor torácica aguda tem sido demonstrada na sala de emergência e nos ambulatórios, populações com baixa prevalência de doença arterial coronariana (DAC). Objetivos: Testar o papel do escore de cálcio zero como filtro nos pacientes com dor torácica admitidos numa unidade coronariana intensiva (UCI), na qual a probabilidade pré-teste de DAC é maior do que em outras populações. Métodos: Pacientes foram submetidos a tomografia computadorizada para quantificar o escore de cálcio, DAC obstrutiva foi definida por uma estenose mínima de 70% na cineangiocoronariografia invasiva. Um escore clínico para estimar a probabilidade pré-teste de DAC obstrutiva foi criado em amostra de 370 pacientes, usado para definir subgrupos na definição de valores preditivos negativos do escore zero. Resultados: Em 146 pacientes estudados, a prevalência de DAC foi 41% e o escore de cálcio zero foi demonstrado em 35% deles. A sensibilidade e a especificidade para escore de cálcio zero resultaram numa razão de verossimilhança negativa de 0,16. Após ajuste com um escore clínico com a regressão logística para a probabilidade pré-teste, o escore de cálcio zero foi preditor independente associado a baixa probabilidade de DAC (OR = 0,12, IC95% = 0,04-0,36), aumentando a área abaixo da curva ROC do modelo clínico de 0,76 para 0,82 (p = 0,006). Considerando a probabilidade de DAC < 10% como ponto de corte para alta precoce, o escore de cálcio aumentou a proporção de pacientes para alta precoce de 8,2% para 25% (NRI = 0,20; p = 0,0018). O escore de cálcio zero apresentou valor preditivo negativo de 90%. Em pacientes com probabilidade pré-teste < 50%, o valor preditivo negativo foi 95% (IC95% = 83%-99%). Conclusão: O escore de cálcio zero reduz substancialmente a probabilidade pré-teste de DAC obstrutiva em pacientes internados em UCI com dor torácica aguda. (Arq Bras Cardiol. 2017; [online].ahead print, PP.0-0)

Zero Calcium Score as a Filter for Further Testing in Patients Admitted to the Coronary Care Unit with Chest Pain.

BACKGROUND:: The accuracy of zero coronary calcium score as a filter in patients with chest pain has been demonstrated at the emergency room and outpatient clinics, populations with low prevalence of coronary artery disease (CAD). OBJECTIVE:: To test the gatekeeping role of zero calcium score in patients with chest pain admitted to the coronary care unit (CCU), where the pretest probability of CAD is higher than that of other populations. METHODS:: Patients underwent computed tomography for calcium scoring, and obstructive CAD was defined by a minimum 70% stenosis on invasive angiography. RESULTS:: In 146 patients studied, the prevalence of CAD was 41%. A zero calcium score was present in 35% of the patients. The sensitivity and specificity of zero calcium score yielded a negative likelihood ratio of 0.16. After logistic regression adjustment for pretest probability, zero calcium score was independently associated with lower odds of CAD (OR = 0.12, 95%CI = 0.04-0.36), increasing the area under the ROC curve of the clinical model from 0.76 to 0.82 (p = 0.006). Zero calcium score provided a net reclassification improvement of 0.20 (p = 0.0018) over the clinical model when using a pretest probability threshold of 10% for discharging without further testing. In patients with pretest probability < 50%, zero calcium score had a negative predictive value of 95% (95%CI = 83%-99%), with a number needed to test of 2.1 for obtaining one additional discharge. CONCLUSION:: Zero calcium score substantially reduces the pretest probability of obstructive CAD in patients admitted to the CCU with acute chest pain. (Arq Bras Cardiol. 2017; [online].ahead print, PP.0-0). FUNDAMENTO:: A acurácia do escore de cálcio coronário zero como um filtro nos pacientes com dor torácica aguda tem sido demonstrada na sala de emergência e nos ambulatórios, populações com baixa prevalência de doença arterial coronariana (DAC). OBJETIVOS:: Testar o papel do escore de cálcio zero como filtro nos pacientes com dor torácica admitidos numa unidade coronariana intensiva (UCI), na qual a probabilidade pré-teste de DAC é maior do que em outras populações. MÉTODOS:: Pacientes foram submetidos a tomografia computadorizada para quantificar o escore de cálcio, DAC obstrutiva foi definida por uma estenose mínima de 70% na cineangiocoronariografia invasiva. Um escore clínico para estimar a probabilidade pré-teste de DAC obstrutiva foi criado em amostra de 370 pacientes, usado para definir subgrupos na definição de valores preditivos negativos do escore zero. RESULTADOS:: Em 146 pacientes estudados, a prevalência de DAC foi 41% e o escore de cálcio zero foi demonstrado em 35% deles. A sensibilidade e a especificidade para escore de cálcio zero resultaram numa razão de verossimilhança negativa de 0,16. Após ajuste com um escore clínico com a regressão logística para a probabilidade pré-teste, o escore de cálcio zero foi preditor independente associado a baixa probabilidade de DAC (OR = 0,12, IC95% = 0,04-0,36), aumentando a área abaixo da curva ROC do modelo clínico de 0,76 para 0,82 (p = 0,006). Considerando a probabilidade de DAC < 10% como ponto de corte para alta precoce, o escore de cálcio aumentou a proporção de pacientes para alta precoce de 8,2% para 25% (NRI = 0,20; p = 0,0018). O escore de cálcio zero apresentou valor preditivo negativo de 90%. Em pacientes com probabilidade pré-teste < 50%, o valor preditivo negativo foi 95% (IC95% = 83%-99%). CONCLUSÃO:: O escore de cálcio zero reduz substancialmente a probabilidade pré-teste de DAC obstrutiva em pacientes internados em UCI com dor torácica aguda. (Arq Bras Cardiol. 2017; [online].ahead print, PP.0-0).

Accuracy of gestalt perception of acute chest pain in predicting coronary artery disease.

AIM: To test accuracy and reproducibility of gestalt to predict obstructive coronary artery disease (CAD) in patients with acute chest pain. METHODS: We studied individuals who were consecutively admitted to our Chest Pain Unit. At admission, investigators performed a standardized interview and recorded 14 chest pain features. Based on these features, a cardiologist who was blind to other clinical characteristics made unstructured judgment of CAD probability, both numerically and categorically. As the reference standard for testing the accuracy of gestalt, angiography was required to rule-in CAD, while either angiography or non-invasive test could be used to rule-out. In order to assess reproducibility, a second cardiologist did the same procedure. RESULTS: In a sample of 330 patients, the prevalence of obstructive CAD was 48%. Gestalt's numerical probability was associated with CAD, but the area under the curve of 0.61 (95%CI: 0.55-0.67) indicated low level of accuracy. Accordingly, categorical definition of typical chest pain had a sensitivity of 48% (95%CI: 40%-55%) and specificity of 66% (95%CI: 59%-73%), yielding a negligible positive likelihood ratio of 1.4 (95%CI: 0.65-2.0) and negative likelihood ratio of 0.79 (95%CI: 0.62-1.02). Agreement between the two cardiologists was poor in the numerical classification (95% limits of agreement = -71% to 51%) and categorical definition of typical pain (Kappa = 0.29; 95%CI: 0.21-0.37). CONCLUSION: Clinical judgment based on a combination of chest pain features is neither accurate nor reproducible in predicting obstructive CAD in the acute setting.