Usefulness of dual imaging stress echocardiography for the diagnosis of coronary allograft vasculopathy in heart transplant recipients.

BACKGROUND: Coronary allograft vasculopathy (CAV) is the main factor limiting long-term survival after cardiac transplantation. Dual imaging stress echocardiography with wall motion and Doppler-derived coronary flow reserve (CRF) of the left anterior descending artery (LAD) is a state-of-the-art methodology during dipyridamole stress echocardiography (DiSE). This study involving 74 heart transplanted patients has the purpose to assess the diagnostic value of dipyridamole stress echocardiography with evaluation of wall motion (WM) and Doppler-derived coronary flow reserve for the diagnosis of coronary allograft vasculopathy. METHODS AND RESULTS: All patients underwent DiSE and coronary angiography. Moderate-severe CAV was defined according to International Society of Heart and Lung Transplant (ISHLT) recommended nomenclature for CAV, and CFR < 2 was considered to be impaired. Moderate-severe CAV was present in 11 patients. WM analysis revealed four patients (5%) with rest WM abnormalities. CFR analysis revealed that 40 (54%) individuals had an abnormal result. The combined evaluation of WM analysis and CFR resulted in a sensitivity of 72.7% (95% CI: 39.3 to 92.6%), a specificity of 49.2% (95% CI: 36.5 to 61.9%), a positive predictive value of 20% (95% CI: 9.6 to 36.1%), and negative predictive value of 91.1% (95% CI: 75.1 to 97.6%) for the diagnosis of CAV. CONCLUSIONS: Our results support the inclusion of DiSE performance in Heart transplant follow up protocol. The addition of CFR evaluation offers valuable information to the angiography findings in the detection of CAV and could be helpful in selected patients to adjust the time and indications of coronary angiography.

Real incidence of diabetes mellitus in a coronary disease population.

The high prevalence of unknown diabetes mellitus (DM) in patients with coronary disease and that the oral glucose tolerance test (OGTT) is the best diagnostic method in this context are well known. However, data about the incidence of DM in this population have not been well described. In the present study, we sought to determine the actual incidence of new-onset DM in patients with coronary disease using the OGTT. Our secondary objective was to validate a predictive model. We studied a series of 338 patients with coronary disease without known DM using the OGTT. After the OGTT, the patients were reclassified as normoglycemic, prediabetic, and unknown DM, according to the American Diabetes Association 2010 criteria. After 3 years of follow-up, the patients without DM were again reassessed using the OGTT. We then built a predictive model using the multivariate logistic regression method and validated it using the leave-one-out method. The final sample was 191 patients. The mean follow-up was 3.13 years. The overall incidence of DM was 43.6 cases/1,000 person-years (95% confidence interval [CI] 26.8 to 60.4). The incidence was significantly different between the initially normoglycemic patients (11.5%, 95% CI 2.3% to 31.8%) and the prediabetic patients (70.5%, 95% CI 42.7% to 98.3%; p <0.001). A risk model that included the glucose level 2 hours after challenge, glycosylated hemoglobin and triglyceride levels, and presence of noncoronary vascular disease showed good predictive capacity for incident DM (area under the curve 0.882, 95% CI 0.819 to 0.946; p <0.0001). In conclusion, the real incidence of new DM is very high in the coronary population, especially in those with prediabetes. It is necessary to use the OGTT for diagnosis, but we can optimize its indication using a risk model.

Rendimiento de la glucohemoglobina y un modelo de riesgo para la detecci¨®n de diabetes desconocida en pacientes coronarios / Performance of glycated hemoglobin and a risk model for detection of unknown diabetes in coronary patients

Introducción y objetivos: Clásicamente, la sobrecarga oral de glucosa ha diagnosticado la diabetes desconocida. Recientemente, la American Diabetes Association ha aceptado un valor de glucohemoglobina ≥ 6,5% como criterio de diabetes desconocida. Pretendemos conocer la rentabilidad que tiene la glucohemoglobina para la detección de diabetes desconocida y validar un modelo que permita ajustar la realización de la sobrecarga oral de glucosa en enfermos coronarios. Métodos: Se estudia el perfil glucémico de 338 enfermos coronarios sin diabetes conocida. Se usan los criterios de la American Diabetes Association de 2010 y, mediante regresión logística, se construye un modelo predictor de diabetes desconocida. Se valida el modelo en otra cohorte. Resultados: Se diagnosticó diabetes desconocida a 26 enfermos mediante glucohemoglobina y/o glucemia basal. Los demás presentaban, tras realizar sobrecarga oral de glucosa: diabetes desconocida, 53 (17%); prediabetes, 144 (46,2%), y normoglucemia, 115 (36,8%). Método diagnóstico de diabetes desconocida: glucemia basal, 25,3%; glucohemoglobina, 7,6%, y sobrecarga oral de glucosa, 67,1%. Un modelo que incluye glucemia basal, glucohemoglobina, fracción de eyección de ventrículo izquierdo, edad y enfermedad vascular no coronaria resultó eficaz como predictor de diabetes desconocida tras sobrecarga oral de glucos: área bajo la curva ROC, 0,8 (intervalo de confianza del 95%, 0,74-0,87). Realizando sobrecarga oral de glucosa sólo a la población con puntuación del modelo > 6 (el 31% del total), podemos localizar al 83% de los casos de diabetes desconocida reales (sensibilidad, 75%; especificidad, 73%; valor predictivo positivo, 40%; valor predictivo negativo, 93%). El modelo se validó correctamente en otra cohorte de 115 pacientes (área bajo la curva ROC, 0,84 [intervalo de confianza del 95%, 0,74-0,95]). Conclusiones: La glucohemoglobina diagnostica aisladamente pocos casos de diabetes desconocida. Sin embargo, su incorporación a un modelo de riesgo permite optimizar la indicación de la sobrecarga oral de glucosa, con un aprovechamiento óptimo (AU)

Introduction and objectives: Traditionally, the oral glucose tolerance test has been useful to diagnose unknown diabetes. Recently, the American Diabetes Association committee has accepted glycated hemoglobin ≥6.5% as a criterion for unknown diabetes. The aim was to determine the benefit of glycated hemoglobin for diagnosing unknown diabetes and also create a predictive model that adjusts the indication for oral glucose tolerance test in coronary patients. Methods: We examined the glycemic profile of 338 coronary patients without previous diagnosis of diabetes, applying 2010 American Diabetes Association criteria. A unknown diabetes risk predictive model was developed using logistic regression analysis, and then validated in another cohort. Results: Using the glycated hemoglobin criteria and/or fasting plasma glucose, unknown diabetes was diagnosed in 26 patients. The remaining patients were classified according to oral glucose tolerance test as follows: unknown diabetes 53 (17%), prediabetes 144 (46.2%), and normoglycemic 115 (36.8%). The diagnostic method for unknown diabetes was fasting plasma glucose in 25.3%, glycated hemoglobin in 7.6%, and oral glucose tolerance test in 67.1%. A risk model including fasting plasma glucose, glycated hemoglobin, left ventricular ejection fraction, age, and noncoronary vascular disease was shown to effectively predict unknown diabetes after oral glucose tolerance test: area under the ROC curve 0.8 (95% interval confidence: 0.74-0.87). When the oral glucose tolerance test is restricted to patients with a risk score >6 (31% of our sample) we properly identify 83% of unknown diabetes cases (sensitivity: 75%, specificity: 73%, positive predictive value: 40%, negative predictive value: 93%). The model was adequately validated in another cohort of 115 patients (area under the ROC curve 0.84 [95% interval confidence: 0.74-0.95]). Conclusions: In coronary patients, glycated hemoglobin alone failed to detect many cases of unknown diabetes. However, its inclusion in a risk prediction model leads to optimizing the usefulness of oral glucose tolerance test (AU)

[Performance of glycated hemoglobin and a risk model for detection of unknown diabetes in coronary patients]. / Rendimiento de la glucohemoglobina y un modelo de riesgo para la detección de diabetes desconocida en pacientes coronarios.

INTRODUCTION AND OBJECTIVES: Traditionally, the oral glucose tolerance test has been useful to diagnose unknown diabetes. Recently, the American Diabetes Association committee has accepted glycated hemoglobin ≥ 6.5% as a criterion for unknown diabetes. The aim was to determine the benefit of glycated hemoglobin for diagnosing unknown diabetes and also create a predictive model that adjusts the indication for oral glucose tolerance test in coronary patients. METHODS: We examined the glycemic profile of 338 coronary patients without previous diagnosis of diabetes, applying 2010 American Diabetes Association criteria. A unknown diabetes risk predictive model was developed using logistic regression analysis, and then validated in another cohort. RESULTS: Using the glycated hemoglobin criteria and/or fasting plasma glucose, unknown diabetes was diagnosed in 26 patients. The remaining patients were classified according to oral glucose tolerance test as follows: unknown diabetes 53 (17%), prediabetes 144 (46.2%), and normoglycemic 115 (36.8%). The diagnostic method for unknown diabetes was fasting plasma glucose in 25.3%, glycated hemoglobin in 7.6%, and oral glucose tolerance test in 67.1%. A risk model including fasting plasma glucose, glycated hemoglobin, left ventricular ejection fraction, age, and noncoronary vascular disease was shown to effectively predict unknown diabetes after oral glucose tolerance test: area under the ROC curve 0.8 (95% confidence interval: 0.74-0.87). When the oral glucose tolerance test is restricted to patients with a risk score >6 (31% of our sample) we properly identify 83% of unknown diabetes cases (sensitivity: 75%, specificity: 73%, positive predictive value: 40%, negative predictive value: 93%). The model was adequately validated in another cohort of 115 patients (area under the ROC curve 0.84 [95% confidence interval: 0.74-0.95]). CONCLUSIONS: In coronary patients, glycated hemoglobin alone failed to detect many cases of unknown diabetes. However, its inclusion in a risk prediction model leads to optimizing the usefulness of oral glucose tolerance test.

[Contrast-induced nephropathy]. / Nefropatía inducida por contraste.

Contrast-induced nephropathy is a major complication resulting from percutaneous coronary interventional procedures characterized by acute or subacute deterioration of renal function due to exposure to iodinated contrast medium that is associated with increased morbidity and mortality. Promoting factors for the development of nephropathy have been widely described in literature as well as hydration and pharmacological measures to prevent its development; However, few of them have shown evidence level A so far, hence a major research front remains open, not only in the prevention but also in the treatment of this pathology. In this article we review epidemiological and pathophysiological aspects of this complication, and various preventive and therapeutic modalities currently available.