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Background: Cases with negative reverse transcription-polymerase chain reaction (RT-PCR) results at initial testing for suspicion of SARS-CoV-2 infection, and found to be positive in a subsequent test, are considered as RT-PCR false-negative cases. False-negative cases have important implications for COVID-19 management, isolation, and risk of transmission. We aimed to review and critically appraise evidence about the proportion of RT-PCR false-negatives at initial testing for COVID-19. Methods: We performed a systematic review and critical appraisal of literature with high involvement of stakeholders in the review process. We searched on MEDLINE, EMBASE, LILACS, the WHO database of COVID-19 publications, the EPPI-Centre living systematic map of evidence about COVID-19, and the living systematic review developed by the University of Bern (ISPM). Two authors screened and selected studies according to the eligibility criteria and collected data of included studies (no-independent verification). Risk of bias was assessed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. We calculated the false-negative proportion with the corresponding 95% CI using a multilevel mixed-effect logistic regression model using STATA 16. Certainty of the evidence about false-negative cases was rated using the GRADE approach for tests and strategies. The information is current up to 6 April 2020. Findings: Five studies enrolling 957 patients were included. All studies were affected by several biases and applicability concerns. Pooled estimation of false-negative proportion was 0.085 (95% CI= 0.034 to 0.196; tau-squared = 1.08; 95% CI= 0.27 to 8.28; p<0.001); however, this estimation is highly affected by unexplained heterogeneity, and its interpretation should be avoided. The certainty of the evidence was judged as very low, due to the risk of bias, indirectness, and inconsistency issues. Conclusions: The collected evidence has several limitations, including risk of bias issues, high heterogeneity, and concerns about its applicability. Nonetheless, our findings reinforce the need for repeated testing in patients with suspicion of SARS-Cov-2 infection given that up to 29% of patients could have an initial RT-PCR false-negative result. Systematic review registration: Protocol available on OSF website: https://osf.io/gp38w/

Background A false-negative case of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is defined as a person with suspected infection and an initial negative result by reverse transcription-polymerase chain reaction (RT-PCR) test, with a positive result on a subsequent test. False-negative cases have important implications for isolation and risk of transmission of infected people and for the management of coronavirus disease 2019 (COVID-19). We aimed to review and critically appraise evidence about the rate of RT-PCR false-negatives at initial testing for COVID-19. Methods We searched MEDLINE, EMBASE, LILACS, as well as COVID-19 repositories, including the EPPI-Centre living systematic map of evidence about COVID-19 and the Coronavirus Open Access Project living evidence database. Two authors independently screened and selected studies according to the eligibility criteria and collected data from the included studies. The risk of bias was assessed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. We calculated the proportion of false-negative test results using a multilevel mixed-effect logistic regression model. The certainty of the evidence about false-negative cases was rated using the GRADE approach for tests and strategies. All information in this article is current up to July 17, 2020. Results We included 34 studies enrolling 12,057 COVID-19 confirmed cases. All studies were affected by several risks of bias and applicability concerns. The pooled estimate of false-negative proportion was highly affected by unexplained heterogeneity (tau-squared = 1.39; 90% prediction interval from 0.02 to 0.54). The certainty of the evidence was judged as very low due to the risk of bias, indirectness, and inconsistency issues. Conclusions There is substantial and largely unexplained heterogeneity in the proportion of false-negative RT-PCR results. The collected evidence has several limitations, including risk of bias issues, high heterogeneity, and concerns about its applicability. Nonetheless, our findings reinforce the need for repeated testing in patients with suspicion of SARS-Cov-2 infection given that up to 54% of COVID-19 patients may have an initial false-negative RT-PCR (very low certainty of evidence). Systematic review registration Protocol available on the OSF website: https://tinyurl.com/vvbgqya.

Introduction: Rates of chronic diseases will continue to rise in developing countries unless effective and cost-effective interventions are implemented. This review aims to discuss the impact of mobile health (m-health) on chronic disease outcomes in low-and middleincome countries (LMIC). Materials and Methods: Systematic literature searches were performed using CENTRAL, MEDLINE, EMBASE, and LILACS databases and gray literature. Scientific literature was searched to identify controlled studies evaluating cell phone voice and text message interventions to address chronic diseases in adults in low-or middle-income countries. Outcomes measured included morbidity, mortality, hospitalization rates, behavioral or lifestyle changes, process of care improvements, clinical outcomes, costs, patient-provider satisfaction, compliance, and health-related quality of life (HRQoL). Results: From the 1,709 abstracts retrieved, 163 articles were selected for full text review, including 9 randomized controlled trials with 4,604 participants. Most of the studies addressed more than one outcome. Of the articles selected, six studied clinical outcomes, six studied processes of care, three examined healthcare costs, and two examined HRQoL. M-health positively impacted on chronic disease outcomes, improving attendance rates, clinical outcomes, and HRQoL, and was cost-effective. Conclusions: M-health is emerging as a promising tool to address access, coverage, and equity gaps in developing countries and low-resource settings. The results for mhealth interventions showed a positive impact on chronic diseases in LMIC. However, a limiting factor of this review was the relatively small number of studies and patients enrolled, highlighting the need for more rigorous research in this area in developing countries.

Our review did not find evidence supporting a substantial role of MMSE as a stand-alone single-administration test in the identification of MCI patients who could develop dementia. Clinicians could prefer to request additional and extensive tests to be sure about the management of these patients. An important aspect to assess in future updates is if conversion to dementia from MCI stages could be predicted better by MMSE changes over time instead of single measurements. It is also important to assess if a set of tests, rather than an isolated one, may be more successful in predicting conversion from MCI to dementia.

BackgroundDementia is a progressive global cognitive impairment syndrome. In 2010, more than 35 million people worldwide were estimated to be living with dementia. Some people with mild cognitive impairment (MCI) will progress to dementia but others remain stable or recover full function. There is great interest in finding good predictors of dementia in people with MCI. The Mini-Mental State Examination (MMSE) is the best known and the most often used short screening tool for providing an overall measure of cognitive impairment in clinical, research and community settings.

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