Risk stratifier for sudden cardiac death beyond the left ventricular ejection fraction in Chagas cardiomyopathy.

BACKGROUND: Sudden cardiac death (SCD) risk markers are needed in Chagas cardiomyopathy (CC). Action potential duration restitution (APDR) dynamics is capable of extracting information on cardiac regional heterogeneity. This study intends to develop a patient-specific variables-based algorithm to predict SCD in the low-intermediate subgroups of the Rassi risk score. METHODS: Cross-sectional study of patients who underwent 24-h Holter for research purposes between January 1992 and February 2017. From 4-h ECG segment, RR series were generated and APDR dynamics metrics were calculated. Classification tree and sensitivity analysis were applied. As outcomes, SCD, SCD-free and non-cardiovascular death and 34 variables were included. RESULTS: Two hundred twenty-one (129 in the group SCD-free, 80 in the SCD group and 12 non-cardiovascular death group) were analyzed. In the groups with and without SCD (209 patients), the median age was 66 years, 52% were female, the cardiac involvement was mild to moderate in 72% with a Rassi point median of 8 (IQ: 3 to 11). The SCD group had more ventricular remodeling and more ventricular electrical instability. The occurrence of a %beats QTend/TendQ ratio > 1 (AUC, 0.96 (95% CI 0.89-0.98) present in more than 56.7% of the 4-h ECG segments was sufficient to identify patients of the SCD subgroup. Variables representing different stages of CC were also relevant in the model. CONCLUSION: It is possible to use APDR dynamics as an adjuvant in the SCD risk assessment in a subgroup of patients with a high risk of SCD and a very low risk of non-CV death with high power of discrimination.

In-hospital Outcomes of Infective Endocarditis from 1978 to 2015: Analysis Through Machine-Learning Techniques.

BACKGROUND: Early identification of patients with infective endocarditis (IE) at higher risk for in-hospital mortality is essential to guide management and improve prognosis. METHODS: A retrospective analysis was conducted of a cohort of patients followed up from 1978 to 2015, classified according to the modified Duke criteria. Clinical parameters, echocardiographic data, and blood cultures were assessed. Techniques of machine learning, such as the classification tree, were used to explain the association between clinical characteristics and in-hospital mortality. Additionally, the log-linear model and graphical random forests (GRaFo) representation were used to assess the degree of dependence among in-hospital outcomes of IE. RESULTS: This study analyzed 653 patients: 449 (69.0%) with definite IE; 204 (31.0%) with possible IE; mean age, 41.3 ± 19.2 years; 420 (64%) men. Mode of IE acquisition: community-acquired (67.6%), nosocomial (17.0%), undetermined (15.4%). Complications occurred in 547 patients (83.7%), the most frequent being heart failure (47.0%), neurologic complications (30.7%), and dialysis-dependent renal failure (6.5%). In-hospital mortality was 36.0%. The classification tree analysis identified subgroups with higher in-hospital mortality: patients with community-acquired IE and peripheral stigmata on admission; and patients with nosocomial IE. The log-linear model showed that surgical treatment was related to higher in-hospital mortality in patients with neurologic complications. CONCLUSIONS: The use of a machine-learning model allowed identification of subgroups of patients at higher risk for in-hospital mortality. Peripheral stigmata, nosocomial IE, absence of vegetation, and surgery in the presence of neurologic complications are predictors of fatal outcomes in machine learning-based analysis.

CONTEXTE: Le dépistage précoce des patients atteints d'endocardite infectieuse (EI) présentant un risque élevé de mortalité à l'hôpital est essentiel pour orienter la prise en charge et améliorer le pronostic. MÉTHODOLOGIE: Une analyse rétrospective a été réalisée sur une cohorte de patients suivis de 1978 à 2015 et classés selon les critères de Duke modifiés. Les paramètres cliniques, les données des échocardiographies et les hémocultures ont été évalués. Des techniques d'apprentissage automatique, comme l'arbre de classification, ont été utilisées pour expliquer l'association entre les caractéristiques cliniques et la mortalité hospitalière. De plus, le modèle log-linéaire et la représentation graphique en forêts aléatoires ont été utilisés pour évaluer le degré de dépendance entre les résultats hospitaliers et l'EI. RÉSULTATS: Cette étude a permis d'analyser 653 patients : 449 (69,0 %) avec une EI avérée; 204 (31,0 %) avec une EI possible; âge moyen de 41,3 ± 19,2 ans; 420 (64 %) étaient des hommes. Mode d'acquisition de l'EI : communautaire (67,6 %), nosocomial (17,0 %), indéterminé (15,4 %). Des complications sont survenues chez 547 patients (83,7 %), les plus fréquentes étant l'insuffisance cardiaque (47,0 %), les complications neurologiques (30,7 %) et l'insuffisance rénale dépendante de la dialyse (6,5 %). La mortalité hospitalière était de 36,0 %. L'analyse de l'arbre de classification a permis d'identifier des sous-groupes présentant une mortalité hospitalière plus élevée : les patients présentant une EI communautaire et des stigmates périphériques à l'admission; et les patients présentant une EI nosocomiale. Le modèle log-linéaire a montré que le traitement chirurgical était lié à une mortalité hospitalière plus élevée chez les patients présentant des complications neurologiques. CONCLUSIONS: L'utilisation d'un modèle d'apprentissage automatique a permis d'identifier des sous-groupes de patients présentant un risque plus élevé de mortalité à l'hôpital. Les stigmates périphériques, l'EI nosocomiale, l'absence de végétation et la chirurgie en présence de complications neurologiques sont des prédicteurs d'issue fatale dans l'analyse basée sur l'apprentissage automatique.

Survival Probability in Patients with Sickle Cell Anemia Using the Competitive Risk Statistical Model.

The clinical picture of patients with sickle cell anemia (SCA) is associated with several complications some of which could be fatal. The objective of this study is to analyze the causes of death and the effect of sex and age on survival of Brazilian patients with SCA. Data of patients with SCA who were seen and followed at HEMORIO for 15 years were retrospectively collected and analyzed. Statistical modeling was performed using survival analysis in the presence of competing risks estimating the covariate effects on a sub-distribution hazard function. Eight models were implemented, one for each cause of death. The cause-specific cumulative incidence function was also estimated. Males were most vulnerable for death from chronic organ damage (p = 0.0005) while females were most vulnerable for infection (p=0.03). Age was significantly associated (p ≤ 0.05) with death due to acute chest syndrome (ACS), infection, and death during crisis. The lower survival was related to death from infection, followed by death due to ACS. The independent variables age and sex were significantly associated with ACS, infection, chronic organ damage and death during crisis. These data could help Brazilian authorities strengthen public policies to protect this vulnerable population.

A screening system for smear-negative pulmonary tuberculosis using artificial neural networks.

OBJECTIVES: Molecular tests show low sensitivity for smear-negative pulmonary tuberculosis (PTB). A screening and risk assessment system for smear-negative PTB using artificial neural networks (ANNs) based on patient signs and symptoms is proposed. METHODS: The prognostic and risk assessment models exploit a multilayer perceptron (MLP) and inspired adaptive resonance theory (iART) network. Model development considered data from 136 patients with suspected smear-negative PTB in a general hospital. RESULTS: MLP showed higher sensitivity (100%, 95% confidence interval (CI) 78-100%) than the other techniques, such as support vector machine (SVM) linear (86%; 95% CI 60-96%), multivariate logistic regression (MLR) (79%; 95% CI 53-93%), and classification and regression tree (CART) (71%; 95% CI 45-88%). MLR showed a slightly higher specificity (85%; 95% CI 59-96%) than MLP (80%; 95% CI 54-93%), SVM linear (75%, 95% CI 49-90%), and CART (65%; 95% CI 39-84%). In terms of the area under the receiver operating characteristic curve (AUC), the MLP model exhibited a higher value (0.918, 95% CI 0.824-1.000) than the SVM linear (0.796, 95% CI 0.651-0.970) and MLR (0.782, 95% CI 0.663-0.960) models. The significant signs and symptoms identified in risk groups are coherent with clinical practice. CONCLUSIONS: In settings with a high prevalence of smear-negative PTB, the system can be useful for screening and also to aid clinical practice in expediting complementary tests for higher risk patients.

Impact of the Use of Benznidazole Followed by Antioxidant Supplementation in the Prevalence of Ventricular Arrhythmias in Patients With Chronic Chagas Disease: Pilot Study.

Patients with chronic Chagas disease have a higher prevalence of premature ventricular contraction (PVC) because of immunoinflammatory response magnified by the increased oxidative stress. Thus, the sequential treatment with benznidazole (BZN) and antioxidants can reduce the prevalence of PVC. We wish to establish whether the etiological treatment of Chagas disease followed by supplementation with the antioxidant vitamins E and C decreases the prevalence of PVC in these patients. A sample of 41 patients with chronic Chagas disease at different stages of the heart disease was selected for the treatment against the causative agent using BZN (5 mg·kg·d, minimum dose 300 mg daily) for 2 months followed by supplementation with antioxidants such as vitamins E (800 UI/d) and C (500 mg/d) for 6 months. The prevalence of PVC was observed by conducting 24-hour Holter. To evaluate the oxidative status of the patients, serum markers of oxidative stress like glutathione peroxidase, superoxide dismutase, catalase, glutathione reductase, and glutathione S-transferase were measured, and also reduced glutathione, vitamin E, and markers of tissue damage like thiobarbituric acid reactive substances and protein carbonyl. A decrease in the prevalence of PVC in patients with advanced Chagas heart disease was observed (5391 vs. 1185, P = 0.0068). This reduction was followed by decrease of serum markers of oxidative stress. In patients with a lower degree of cardiac damage, the reduction on prevalence of PVC was not significant. The etiological treatment with BZN followed by supplementation with antioxidant vitamins E and C reduces episodes of PVC in patients with severe Chagas heart disease.

Is poststroke depression a major depression?

BACKGROUND: Poststroke depression (PSD) is the most common neuropsychiatric consequence of stroke. A large number of studies have focused on the pathogenesis of PSD, but only a few aimed to characterize its psychopathology; these studies yielded results that are difficult to compare because of the different methods utilized. The current study aimed to characterize the symptom profile of PSD in an attempt to better understand the disease and allow a more accurate diagnosis. METHODS: The study sample comprised 64 patients divided into three groups: stroke patients without diagnosis of depression (n = 33), stroke patients diagnosed with PSD (PSD group, n = 14) and patients diagnosed with major depression (MD) but with no clinical comorbidity (MD group, n = 17). All patients were diagnosed using the Structured Clinical Interview for DSM-IV Axis I Disorders (SCID-I). The initial diagnostic interview was complemented by the Mini Mental State Examination (MMSE), the Rankin Scale, and four scales for the assessment of the intensity of symptoms of anxiety and depression: the Beck Depression Inventory (BDI), the Hospital Anxiety and Depression General Scale (HADS), the Hamilton Depression Rating Scale (HAM-D) and the Hamilton Rating Scale for Anxiety (HAM-A). The Star Plot, a graphical method of data visualization, was used to analyze the results. The t test was used for independent samples (two-tailed analysis). RESULTS: As measured by the BDI, HAM-D and HAM-A scales and HADS depression subscale, the average total scores of symptoms for the sample of patients diagnosed with MD without clinical comorbidity was significantly higher than that of the PSD patients (p < 0.05). Similar results were obtained by plotting the BDI data on Star Plot. The PSD patients showed mild typical depressive symptoms such as less depressed mood, anhedonia, disinterest, guilt, negative thoughts, depreciation, suicidal ideation and anxiety, when evaluated by the HAM-A scale. Moreover, the somatic symptoms of depression did not lead to increased diagnosis of major depression in stroke patients. CONCLUSIONS: The results indicate that the PSD clinical picture comprised, in general, symptoms of mild/moderate intensity, especially those considered as pillars for the diagnosis of depression: depressed mood, loss of pleasure and lack of interest. Given the imprecision of boundaries that separate the clinical forms of depression from subclinical and nonpathological forms, or even from the concepts of demoralization and adjustment disorders, we situate PSD in a complex biopsychosocial context in which a better understanding of its psychopathological profile could provide diagnostic and therapeutic alternatives best suited to the difficult reality experienced by stroke patients.