Interest in quality of life in mental health care has been stimulated by the deinstitutionalization of psychiatric patients as well as a parallel interest in understanding the scope of their daily lives. This study aims to investigate the socio-demographic and clinical variables related to low quality of life, using a cross-sectional design to evaluate quality of life by means of the QLS-BR scale. We interviewed a sample of 123 outpatients from a reference mental health center in Divinópolis, Minas Gerais State, Brazil, clinically diagnosed with schizophrenia. Univariate and multivariate logistic regression analyses were carried out. The results showed that low quality of life is associated with one or more of the following: male gender, single marital status, low income plus low schooling, use of three or more prescribed psychoactive drugs, psychomotor agitation during the interview, and current follow-up care. The study identifies plausible indicators for the attention and care needed to improve psychiatric patient treatment.

Quality of life has been increasingly emphasized in public health research in recent years. Typically, the results of quality of life are measured by means of ordinal scales. In these situations, specific statistical methods are necessary because procedures such as either dichotomization or misinformation on the distribution of the outcome variable may complicate the inferential process. Ordinal logistic regression models are appropriate in many of these situations. This article presents a review of the proportional odds model, partial proportional odds model, continuation ratio model, and stereotype model. The fit, statistical inference, and comparisons between models are illustrated with data from a study on quality of life in 273 patients with schizophrenia. All tested models showed good fit, but the proportional odds or partial proportional odds models proved to be the best choice due to the nature of the data and ease of interpretation of the results. Ordinal logistic models perform differently depending on categorization of outcome, adequacy in relation to assumptions, goodness-of-fit, and parsimony.

BackgroundTrypanosoma cruzi parasite, the causative agent of Chagas disease, infects about six million individuals in more than 20 countries. Monitoring parasite persistence in infected individuals is of utmost importance to develop and evaluate treatments to control the disease. Routine screening for infected human individuals is achieved by serological assays; PCR testing to monitor spontaneous or therapy-induced parasitological cure has limitations due to the low and fluctuating parasitic load in circulating blood. The aim of the present study is to evaluate a newly developed antibody profiling assay as an indirect method to assess parasite persistence based on waning of antibodies following spontaneous or therapy-induced clearance of the infection.Methodology/Principal findingsWe designed a multiplex serology assay, an array of fifteen optimized T. cruzi antigens, to evaluate antibody diversity in 1654 serum samples from chronic Chagas patients. One specific antibody response (antibody 3, Ab3) showed a strong correlation with T. cruzi parasite persistence as determined by T. cruzi PCR positive results. High and sustained Ab3 signal was strongly associated with PCR positivity in untreated patients, whereas significant decline in Ab3 signals was observed in BZN-treated patients who cleared parasitemia based on blood PCR results.Conclusion/SignificanceAb3 is a new surrogate biomarker that strongly correlates with parasite persistence in chronic and benznidazole-treated Chagas patients. We hypothesize that Ab3 is induced and maintained by incessant stimulation of the immune system by tissue-based and shed parasites that are not consistently detectable by blood based PCR techniques. Hence, a simple immunoassay measurement of Ab3 could be beneficial for monitoring the infectious status of seropositive patients.

Introduction Mobile-technology-based interventions are promising strategies for promoting behavioural change in obese patients. The aims of this study were to evaluate the feasibility of implementing a text message intervention, and to assess the effects of the intervention on body mass index (BMI) and self-reported behavioural change. Methods TELEFIT was a three-phase feasibility study comprising the following stages: (a) the development of text messages; (b) testing; and (c) a quasi-experimental pilot study in which patients who were engaged in obesity/overweight educational groups in public primary care centres in Belo Horizonte, Brazil, were recruited. A bank of text messages was drafted and reviewed by an expert panel, text message delivery software was developed and tested, and a pilot study assessed patients before and after receiving the intervention using validated questionnaires and body measures. The data were analysed using the Wilcoxon test. Results A total of 46 patients completed the follow-up; 93.5% were women and the median age was 42 years (interquartile range (IQR) 34-52 years). At four months, participants had a significant reduction in BMI (median 31.3 (IQR 28.2-34.6) vs. 29.9 (IQR 27.2-34.6) kg/m, p < 0.001), systolic (median 125 (IQR 120-132) vs. 120 (IQR 110-130) mmHg, p = 0.013) and diastolic blood pressure (median 80 (IQR 70-100) vs. 80 (IQR 70-80) mmHg, p = 0.006), when compared to baseline. All patients reported to be satisfied and willing to continue receiving the intervention, and 93.3% felt that the intervention helped them change their behaviours. Discussion This study has shown that a text message intervention to promote behavioural change and weight loss was feasible and effective in a short-term period. Participants were satisfied and willing to continue receiving the SMS messages.

Background Risk stratification of Chagas disease patients in the limited‐resource setting would be helpful in crafting management strategies. We developed a score to predict 2‐year mortality in patients with Chagas cardiomyopathy from remote endemic areas. Methods and Results This study enrolled 1551 patients with Chagas cardiomyopathy from Minas Gerais State, Brazil, from the SaMi‐Trop cohort (The São Paulo‐Minas Gerais Tropical Medicine Research Center). Clinical evaluation, ECG, and NT ‐proBNP (N‐terminal pro‐B‐type natriuretic peptide) were performed. A Cox proportional hazards model was used to develop a prediction model based on the key predictors. The end point was all‐cause mortality. The patients were classified into 3 risk categories at baseline (low, <2%; intermediate, ≥2% to 10%; high, ≥10%). External validation was performed by applying the score to an independent population with Chagas disease. After 2 years of follow‐up, 110 patients died, with an overall mortality rate of 3.505 deaths per 100 person‐years. Based on the nomogram, the independent predictors of mortality were assigned points: age (10 points per decade), New York Heart Association functional class higher than I (15 points), heart rate ≥80 beats/min (20 points), QRS duration ≥150 ms (15 points), and abnormal NT ‐pro BNP adjusted by age (55 points). The observed mortality rates in the low‐, intermediate‐, and high‐risk groups were 0%, 3.6%, and 32.7%, respectively, in the derivation cohort and 3.2%, 8.7%, and 19.1%, respectively, in the validation cohort. The discrimination of the score was good in the development cohort (C statistic: 0.82), and validation cohort (C statistic: 0.71). Conclusions In a large population of patients with Chagas cardiomyopathy, a combination of risk factors accurately predicted early mortality. This helpful simple score could be used in remote areas with limited technological resources.