IntroductionSince 2020, the world has been going through a viral pandemic with a high morbidity and mortality rate along with the potential to evolve from an acute infection to post-acute and long-COVID, which is still in the process of elucidation. Diagnostic and prognostic research is essential to understand the complexity of factors and contexts involving the illness’s process. This protocol introduces a study strategy to analyse predictors, sequelae, and repercussions of COVID-19 in adults and older adults with different disease severities in the State of Paraná, Brazil.Methods and analysisA mixed-methods sequential explanatory design. The quantitative data will be conducted by an ambispective cohort study, which will explore the manifestations of COVID-19 for 18 months, with nearly 3000 participants with confirmed diagnoses of COVID-19 (reverse transcription-PCR test) between March and December of 2020, retrieved from national disease reporting databases, over 18 years old, living in a Brazilian State (Paraná) and who survived the viral infection after being discharged from a health service. Data collection will be conducted through telephone interviews, at two different occasions: the first will be a recall 12 months after the acute phase as a retrospective follow-up, and the second will be another prospective interview, with data of the following 6 months. For the qualitative step, Grounded Theory will be used; participants will be selected from the cohort population. The first sample group will be composed of people who were discharged from the intensive care unit, and other sample groups will be composed according to theoretical saturation. The qualitative data will follow the temporal design and classification of the disease provided for in the cohort.Ethics and disseminationEthics approval was granted by the State University of Maringá, under opinion number: 4 165 272 and CAAE: 34787020.0.0000.0104 on 21 July 2020, and Hospital do Trabalhador (Worker’s Hospital), which is accountable for the Health Department of the State of Paraná, under opinion number: 4 214 589 and CAAE: 34787020.0.3001.5225 on 15 August 2020. The participants will verbally consent to the research, their consent will be recorded, and the informed consent form will be sent by mail or email. Outcomes will be widely disseminated through peer-reviewed manuscripts, conference presentations, media and reports to related authorities.
BackgroundStudies show that educational interventions improve glycemic control in patients with diabetes mellitus (DM), reducing the occurrence of complications associated with the disease.ObjectivesTo evaluate the effects of a mobile DM consultancy on clinical and laboratory parameters, disease knowledge, and quality of life in patients with type 2 DM (T2DM) at a primary health care network in Brazil.MethodsRandomized clinical trial conducted in a city in southern Brazil with 52 patients with T2DM receiving care at a primary health care setting. The intervention lasted for 6 months and consisted of a follow-up with an endocrinologist (five meetings), treatment adjustment based on clinical evaluation and laboratory tests, and educational activities with conversation maps in DM. The statistical analysis included comparison and association tests, considering p values ≤0.05 as statistically significant.ResultsThe mean age of the patients was 63.8 years. Most participants were female (63.5 %), had low educational level (59.6 %) and family history of T2DM (71.2 %), used only oral hypoglycemic agents to manage their DM (73.2 %), presented unfavorable anthropometric and laboratory parameters, a high or medium risk of complications (84.6 %), and inadequate glycemic control (67.3 %; with 71 % of the high-risk patients presenting a HbA1c level >9 %). Adjustment in pharmacological treatment was required in 63.5 % of the patients. After the intervention, we observed a significant 0.46 % decrease in mean HbA1c level (p = 0.0218), particularly among individuals with inadequate glycemic control (0.71 %; p = 0.0136). Additionally, there was an increase in disease knowledge scores and a significant decrease in mean body mass index, waist circumference, and disease impact scores.ConclusionThe intervention improved glycemic control and disease knowledge, reduced the values of body mass index and waist circumference, and the impact of the disease on patients’ lives. This indicates that care and educational measures improve the experience of the patients with DM and control of the disease.
Objective: to analyze the trend of hospitalizations of adolescents due to mental and behavioral disorders in Paraná, from 1998 to 2015. Method: ecological study of time series. Data were analyzed by means of segmented linear regression modeling for time series, estimated for each of the four health macro-regions. Results: the East macro-region showed a greater trend to increase hospitalizations from January 1998 to November 2003 (β1=0.006, p<0.001). In other macro-regions, there were similar trends with a sudden increase in February 2010, but with a further gradual decrease until December 2015. In the quadrennium 2012-2015, 38.06% of the hospitalizations lasted 29 or more days, and in the Northwest macro-region, hospitalizations lasted for up to seven days. The main cause of hospitalization was the use of alcohol and other drugs. Conclusion: there is a need to strengthen health actions to prevent drug use and improvements in the care network.
Methods to generate a discrete analogue of a continuous distribution have been widely considered in recent decades. In general, the discretization procedure comprises in transform continuous attributes into discrete attributes generating new probability distributions that could be an alternative to the traditional discrete models, such as Poisson and Binomial models, commonly used in analysis of count data. It also avoids the use of continuous in the analysis of strictly discrete data. In this paper, using the discretization method based on the survival function, it is introduced a discrete analogue of power Lindley distribution. Some mathematical properties are studied. The maximum likelihood theory is considered for estimation and asymptotic inference concerns. A simulation study is also carried out in order to evaluate some properties of the maximum likelihood estimators of the proposed model. The usefulness and accurate of the proposed model are evaluated using real datasets provided by the literature.
Objective: Due to the high cost and short term of passive immunization against the respiratory syncytial virus, the main virus causing acute viral bronchiolitis, predicting epidemic regions and epidemic months is extremely important. The objective of this study is to identify both the month when the seasonal peak begins and Brazilian regions and states with the highest incidence of monthly hospitalizations due acute viral bronchiolitis. Methods: Based on data obtained from DATASUS, monthly hospitalization rates due acute viral bronchiolitis were calculated for every 10,000 live births to children under 12 months of age in all Brazilian states and the Federal District between 2000 and 2019. Seasonal autoregressive integrated moving average models were estimated to forecast monthly hospitalization rates in 2020. Results: A higher incidence of hospitalizations was found for male children, especially under six months of age. As for Brazilian regions, between 2000 and 2019, the South region registered the highest incidence of hospitalizations, followed by the Southeast, Midwest, North and Northeast regions, in this order. Considering the seasonal peak, the period between March and July 2020 comprised the highest expected hospitalization rates. Conclusions: Palivizumab is suggested to be started between February/March and June/July for most Brazilian states, with the exception of Rio Grande do Sul, which, in addition to presenting the highest rates of hospitalizations for acute viral bronchiolitis per 10,000 live births, has the longest seasonal peak between May and September.
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