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1.
BMC Health Serv Res ; 23(1): 855, 2023 Aug 12.
Article in English | MEDLINE | ID: mdl-37573312

ABSTRACT

CONTEXT: Arterial Hypertension (AH) and Diabetes Mellitus (DM) are diseases that are getting worse all over the world. Linked to this advance, is the growing digital health market with numerous mobile health applications, which aim to help patients and professionals in the proper management of chronic diseases. The aim of this study was to analyze, through a systematic review and meta-analysis, the effectiveness of using mobile health applications in monitoring AH and/or DM in the adult and elderly population. METHODS: The systematic review and meta-analysis was carried out in accordance with the Preferred Reporting Items for Systematic Reviews and Metanalyses guidelines and involved searching five databases - Medline/PubMed, Embase, CINAHL, Virtual Library in Health and Cochrane Library. The review included randomized and cohort clinical trials testing the effects of the intervention on changing biochemical parameters and clinical efficacy in people treated for AH and/or DM. The quality of the selected studies was assessed based on the evaluation criteria of the Joanna Briggs Institute tool. The random effects meta-analysis method was used to explain effect distribution between studies, by Stata® software (version 11.0) and publication bias was examined by visual inspection of graphs and Egger test. RESULTS: We included 26 studies in the systematic review and 17 in the meta-analysis. These studies were published between 2014 to 2022 in 14 countries. Were reported improvement in knowledge and self-management of AH and DM, social motivation with treatment and behavioral change, reduction in glycated hemoglobin values, fasting glucose and blood pressure, improvement in adherence to drug treatment, among others. The result of the meta-analysis showed that there is evidence that the use of mobile applications can help reduce glycated hemoglobin by 0.39% compared to the usual care group. CONCLUSIONS: Monitoring and self-monitoring of behaviors and health care related to AH and DM in adults and the elderly through mobile applications, has clinically significant effectiveness in reducing glycated hemoglobin levels. Future studies should provide more evidence and recommendations for best practices and development of digital health interventions. TRIAL REGISTRATION: PROSPERO. International Prospective Registry of Systematic Reviews. CRD42022361928.


Subject(s)
Diabetes Mellitus , Hypertension , Mobile Applications , Adult , Humans , Aged , Glycated Hemoglobin , Diabetes Mellitus/therapy , Chronic Disease , Hypertension/diagnosis , Hypertension/therapy
2.
Article in English | MEDLINE | ID: mdl-35010675

ABSTRACT

This work aimed to apply the ARIMA model to predict the under-reporting of new Hansen's disease cases during the COVID-19 pandemic in Palmas, Tocantins, Brazil. This is an ecological time series study of Hansen's disease indicators in the city of Palmas between 2001 and 2020 using the autoregressive integrated moving averages method. Data from the Notifiable Injuries Information System and population estimates from the Brazilian Institute of Geography and Statistics were collected. A total of 7035 new reported cases of Hansen's disease were analyzed. The ARIMA model (4,0,3) presented the lowest values for the two tested information criteria and was the one that best fit the data, as AIC = 431.30 and BIC = 462.28, using a statistical significance level of 0.05 and showing the differences between the predicted values and those recorded in the notifications, indicating a large number of under-reporting of Hansen's disease new cases during the period from April to December 2020. The ARIMA model reported that 177% of new cases of Hansen's disease were not reported in Palmas during the period of the COVID-19 pandemic in 2020. This study shows the need for the municipal control program to undertake immediate actions in terms of actively searching for cases and reducing their hidden prevalence.


Subject(s)
COVID-19 , Leprosy , Brazil/epidemiology , Humans , Leprosy/epidemiology , Models, Statistical , Pandemics , SARS-CoV-2
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