ORCID Profile
0000-0003-4278-3771
Current Organisation
Universidade Federal de Minas Gerais
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Publisher: BMJ
Date: 04-2022
DOI: 10.1136/BMJOPEN-2021-053122
Abstract: There is an urgent need to reduce the burden of non-communicable diseases (NCDs), particularly in low-and middle-income countries, where the greatest burden lies. Yet, there is little research concerning the specific issues involved in scaling up NCD interventions targeting low-resource settings. We propose to examine this gap in up to 27 collaborative projects, which were funded by the Global Alliance for Chronic Diseases (GACD) 2019 Scale Up Call, reflecting a total funding investment of approximately US$50 million. These projects represent erse countries, contexts and adopt varied approaches and study designs to scale-up complex, evidence-based interventions to improve hypertension and diabetes outcomes. A systematic inquiry of these projects will provide necessary scientific insights into the enablers and challenges in the scale up of complex NCD interventions. We will apply systems thinking (a holistic approach to analyse the inter-relationship between constituent parts of scaleup interventions and the context in which the interventions are implemented) and adopt a longitudinal mixed-methods study design to explore the planning and early implementation phases of scale up projects. Data will be gathered at three time periods, namely, at planning (T P ), initiation of implementation (T 0 ) and 1-year postinitiation (T 1 ). We will extract project-related data from secondary documents at T P and conduct multistakeholder qualitative interviews to gather data at T 0 and T 1. We will undertake descriptive statistical analysis of T P data and analyse T 0 and T 1 data using inductive thematic coding. The data extraction tool and interview guides were developed based on a literature review of scale-up frameworks. The current protocol was approved by the Monash University Human Research Ethics Committee (HREC number 23482). Informed consent will be obtained from all participants. The study findings will be disseminated through peer-reviewed publications and more broadly through the GACD network.
Publisher: Public Library of Science (PLoS)
Date: 17-09-2020
Publisher: JMIR Publications Inc.
Date: 22-01-2023
Abstract: ral anticoagulation is the cornerstone treatment of several diseases. Its management is often challenging, and different telemedicine strategies have been implemented to support it. he aim of the study is to systematically review the evidence on the impact of telemedicine-based oral anticoagulation management compared to usual care on thromboembolic and bleeding events. andomized controlled trials were searched in 5 databases from inception to September 2021. Two independent reviewers performed study selection and data extraction. Total thromboembolic events, major bleeding, mortality, and time in therapeutic range were assessed. Results were pooled using random effect models. n total, 25 randomized controlled trials were included (n=25,746 patients) and classified as moderate to high risk of bias by the Cochrane tool. Telemedicine resulted in lower rates of thromboembolic events, though not statistically significant (n=13 studies, relative risk [RR] 0.75, 95% CI 0.53-1.07 i I /i sup /sup =42%), comparable rates of major bleeding (n=11 studies, RR 0.94, 95% CI 0.82-1.07 i I /i sup /sup =0%) and mortality (n=12 studies, RR 0.96, 95% CI 0.78-1.20 i I /i sup /sup =11%), and an improved time in therapeutic range (n=16 studies, mean difference 3.38, 95% CI 1.12-5.65 i I /i sup /sup =90%). In the subgroup of the multitasking intervention, telemedicine resulted in an important reduction of thromboembolic events (RR 0.20, 95% CI 0.08-0.48). elemedicine-based oral anticoagulation management resulted in similar rates of major bleeding and mortality, a trend for fewer thromboembolic events, and better anticoagulation quality compared to standard care. Given the potential benefits of telemedicine-based care, such as greater access to remote populations or people with ambulatory restrictions, these findings may encourage further implementation of eHealth strategies for anticoagulation management, particularly as part of multifaceted interventions for integrated care of chronic diseases. Meanwhile, researchers should develop higher-quality evidence focusing on hard clinical outcomes, cost-effectiveness, and quality of life. ROSPERO International Prospective Register of Systematic Reviews CRD42020159208 www.crd.york.ac.uk rospero/display_record.php?RecordID=159208
Publisher: JMIR Publications Inc.
Date: 13-04-2021
DOI: 10.2196/27275
Abstract: Although the potential of big data analytics for health care is well recognized, evidence is lacking on its effects on public health. The aim of this study was to assess the impact of the use of big data analytics on people’s health based on the health indicators and core priorities in the World Health Organization (WHO) General Programme of Work 2019/2023 and the European Programme of Work (EPW), approved and adopted by its Member States, in addition to SARS-CoV-2–related studies. Furthermore, we sought to identify the most relevant challenges and opportunities of these tools with respect to people’s health. Six databases (MEDLINE, Embase, Cochrane Database of Systematic Reviews via Cochrane Library, Web of Science, Scopus, and Epistemonikos) were searched from the inception date to September 21, 2020. Systematic reviews assessing the effects of big data analytics on health indicators were included. Two authors independently performed screening, selection, data extraction, and quality assessment using the AMSTAR-2 (A Measurement Tool to Assess Systematic Reviews 2) checklist. The literature search initially yielded 185 records, 35 of which met the inclusion criteria, involving more than 5,000,000 patients. Most of the included studies used patient data collected from electronic health records, hospital information systems, private patient databases, and imaging datasets, and involved the use of big data analytics for noncommunicable diseases. “Probability of dying from any of cardiovascular, cancer, diabetes or chronic renal disease” and “suicide mortality rate” were the most commonly assessed health indicators and core priorities within the WHO General Programme of Work 2019/2023 and the EPW 2020/2025. Big data analytics have shown moderate to high accuracy for the diagnosis and prediction of complications of diabetes mellitus as well as for the diagnosis and classification of mental disorders prediction of suicide attempts and behaviors and the diagnosis, treatment, and prediction of important clinical outcomes of several chronic diseases. Confidence in the results was rated as “critically low” for 25 reviews, as “low” for 7 reviews, and as “moderate” for 3 reviews. The most frequently identified challenges were establishment of a well-designed and structured data source, and a secure, transparent, and standardized database for patient data. Although the overall quality of included studies was limited, big data analytics has shown moderate to high accuracy for the diagnosis of certain diseases, improvement in managing chronic diseases, and support for prompt and real-time analyses of large sets of varied input data to diagnose and predict disease outcomes. International Prospective Register of Systematic Reviews (PROSPERO) CRD42020214048 www.crd.york.ac.uk rospero/display_record.php?RecordID=214048
Publisher: JMIR Publications Inc.
Date: 19-01-2021
Abstract: lthough the potential of big data analytics for health care is well recognized, evidence is lacking on its effects on public health. he aim of this study was to assess the impact of the use of big data analytics on people’s health based on the health indicators and core priorities in the World Health Organization (WHO) General Programme of Work 2019/2023 and the European Programme of Work (EPW), approved and adopted by its Member States, in addition to SARS-CoV-2–related studies. Furthermore, we sought to identify the most relevant challenges and opportunities of these tools with respect to people’s health. ix databases (MEDLINE, Embase, Cochrane Database of Systematic Reviews via Cochrane Library, Web of Science, Scopus, and Epistemonikos) were searched from the inception date to September 21, 2020. Systematic reviews assessing the effects of big data analytics on health indicators were included. Two authors independently performed screening, selection, data extraction, and quality assessment using the AMSTAR-2 (A Measurement Tool to Assess Systematic Reviews 2) checklist. he literature search initially yielded 185 records, 35 of which met the inclusion criteria, involving more than 5,000,000 patients. Most of the included studies used patient data collected from electronic health records, hospital information systems, private patient databases, and imaging datasets, and involved the use of big data analytics for noncommunicable diseases. “Probability of dying from any of cardiovascular, cancer, diabetes or chronic renal disease” and “suicide mortality rate” were the most commonly assessed health indicators and core priorities within the WHO General Programme of Work 2019/2023 and the EPW 2020/2025. Big data analytics have shown moderate to high accuracy for the diagnosis and prediction of complications of diabetes mellitus as well as for the diagnosis and classification of mental disorders prediction of suicide attempts and behaviors and the diagnosis, treatment, and prediction of important clinical outcomes of several chronic diseases. Confidence in the results was rated as “critically low” for 25 reviews, as “low” for 7 reviews, and as “moderate” for 3 reviews. The most frequently identified challenges were establishment of a well-designed and structured data source, and a secure, transparent, and standardized database for patient data. lthough the overall quality of included studies was limited, big data analytics has shown moderate to high accuracy for the diagnosis of certain diseases, improvement in managing chronic diseases, and support for prompt and real-time analyses of large sets of varied input data to diagnose and predict disease outcomes. nternational Prospective Register of Systematic Reviews (PROSPERO) CRD42020214048 www.crd.york.ac.uk rospero/display_record.php?RecordID=214048
Publisher: EDP Sciences
Date: 04-2021
DOI: 10.1051/0004-6361/202038488
Abstract: Aims. The giant H II region 30 Doradus (30 Dor) located in the eastern part of the Large Magellanic Cloud is one of the most active star-forming regions in the Local Group. Studies of H I data have revealed two large gas structures which must have collided with each other in the region around 30 Dor. In X-rays there is extended emission (~1 kpc) south of 30 Dor called the X-ray spur, which appears to be anticorrelated with the H I gas. We study the properties of the hot interstellar medium (ISM) in the X-ray spur and investigate its origin including related interactions in the ISM. Methods. We analyzed new and archival XMM-Newton data of the X-ray spur and its surroundings to determine the properties of the hot diffuse plasma. We created detailed plasma property maps by utilizing the Voronoi tessellation algorithm. We also studied H I and CO data, as well as optical line emission data of H α and [S II ], and compared them to the results of the X-ray spectral analysis. Results. We find evidence of two hot plasma components with temperatures of kT 1 ~ 0.2 keV and kT 2 ~ 0.5−0.9 keV, with the hotter component being much more pronounced near 30 Dor and the X-ray spur. In 30 Dor, the plasma has most likely been heated by massive stellar winds and supernova remnants. In the X-ray spur, we find no evidence of heating by stars. Instead, the X-ray spur must have been compressed and heated by the collision of the H I gas.
Publisher: JMIR Publications Inc.
Date: 10-07-2023
DOI: 10.2196/45922
Abstract: Oral anticoagulation is the cornerstone treatment of several diseases. Its management is often challenging, and different telemedicine strategies have been implemented to support it. The aim of the study is to systematically review the evidence on the impact of telemedicine-based oral anticoagulation management compared to usual care on thromboembolic and bleeding events. Randomized controlled trials were searched in 5 databases from inception to September 2021. Two independent reviewers performed study selection and data extraction. Total thromboembolic events, major bleeding, mortality, and time in therapeutic range were assessed. Results were pooled using random effect models. In total, 25 randomized controlled trials were included (n=25,746 patients) and classified as moderate to high risk of bias by the Cochrane tool. Telemedicine resulted in lower rates of thromboembolic events, though not statistically significant (n=13 studies, relative risk [RR] 0.75, 95% CI 0.53-1.07 I2=42%), comparable rates of major bleeding (n=11 studies, RR 0.94, 95% CI 0.82-1.07 I2=0%) and mortality (n=12 studies, RR 0.96, 95% CI 0.78-1.20 I2=11%), and an improved time in therapeutic range (n=16 studies, mean difference 3.38, 95% CI 1.12-5.65 I2=90%). In the subgroup of the multitasking intervention, telemedicine resulted in an important reduction of thromboembolic events (RR 0.20, 95% CI 0.08-0.48). Telemedicine-based oral anticoagulation management resulted in similar rates of major bleeding and mortality, a trend for fewer thromboembolic events, and better anticoagulation quality compared to standard care. Given the potential benefits of telemedicine-based care, such as greater access to remote populations or people with ambulatory restrictions, these findings may encourage further implementation of eHealth strategies for anticoagulation management, particularly as part of multifaceted interventions for integrated care of chronic diseases. Meanwhile, researchers should develop higher-quality evidence focusing on hard clinical outcomes, cost-effectiveness, and quality of life. PROSPERO International Prospective Register of Systematic Reviews CRD42020159208 www.crd.york.ac.uk rospero/display_record.php?RecordID=159208
Publisher: MDPI AG
Date: 30-03-2020
DOI: 10.3390/JCM9040941
Abstract: A growing body of literature on the 2019 novel coronavirus (SARS-CoV-2) is becoming available, but a synthesis of available data has not been conducted. We performed a scoping review of currently available clinical, epidemiological, laboratory, and chest imaging data related to the SARS-CoV-2 infection. We searched MEDLINE, Cochrane CENTRAL, EMBASE, Scopus and LILACS from 01 January 2019 to 24 February 2020. Study selection, data extraction and risk of bias assessment were performed by two independent reviewers. Qualitative synthesis and meta-analysis were conducted using the clinical and laboratory data, and random-effects models were applied to estimate pooled results. A total of 61 studies were included (59,254 patients). The most common disease-related symptoms were fever (82%, 95% confidence interval (CI) 56%–99% n = 4410), cough (61%, 95% CI 39%–81% n = 3985), muscle aches and/or fatigue (36%, 95% CI 18%–55% n = 3778), dyspnea (26%, 95% CI 12%–41% n = 3700), headache in 12% (95% CI 4%–23%, n = 3598 patients), sore throat in 10% (95% CI 5%–17%, n = 1387) and gastrointestinal symptoms in 9% (95% CI 3%–17%, n = 1744). Laboratory findings were described in a lower number of patients and revealed lymphopenia (0.93 × 109/L, 95% CI 0.83–1.03 × 109/L, n = 464) and abnormal C-reactive protein (33.72 mg/dL, 95% CI 21.54–45.91 mg/dL n = 1637). Radiological findings varied, but mostly described ground-glass opacities and consolidation. Data on treatment options were limited. All-cause mortality was 0.3% (95% CI 0.0%–1.0% n = 53,631). Epidemiological studies showed that mortality was higher in males and elderly patients. The majority of reported clinical symptoms and laboratory findings related to SARS-CoV-2 infection are non-specific. Clinical suspicion, accompanied by a relevant epidemiological history, should be followed by early imaging and virological assay.
Publisher: Elsevier BV
Date: 04-2023
No related grants have been discovered for Milena Soriano Marcolino.