Harnessing Machine Learning in Early COVID-19 Detection and Prognosis: A Comprehensive Systematic Review.

During the early phase of the COVID-19 pandemic, reverse transcriptase-polymerase chain reaction (RT-PCR) testing faced limitations, prompting the exploration of machine learning (ML) alternatives for diagnosis and prognosis. Providing a comprehensive appraisal of such decision support systems and their use in COVID-19 management can aid the medical community in making informed decisions during the risk assessment of their patients, especially in low-resource settings. Therefore, the objective of this study was to systematically review the studies that predicted the diagnosis of COVID-19 or the severity of the disease using ML. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA), we conducted a literature search of MEDLINE (OVID), Scopus, EMBASE, and IEEE Xplore from January 1 to June 31, 2020. The outcomes were COVID-19 diagnosis or prognostic measures such as death, need for mechanical ventilation, admission, and acute respiratory distress syndrome. We included peer-reviewed observational studies, clinical trials, research letters, case series, and reports. We extracted data about the study's country, setting, sample size, data source, dataset, diagnostic or prognostic outcomes, prediction measures, type of ML model, and measures of diagnostic accuracy. Bias was assessed using the Prediction model Risk Of Bias ASsessment Tool (PROBAST). This study was registered in the International Prospective Register of Systematic Reviews (PROSPERO), with the number CRD42020197109. The final records included for data extraction were 66. Forty-three (64%) studies used secondary data. The majority of studies were from Chinese authors (30%). Most of the literature (79%) relied on chest imaging for prediction, while the remainder used various laboratory indicators, including hematological, biochemical, and immunological markers. Thirteen studies explored predicting COVID-19 severity, while the rest predicted diagnosis. Seventy percent of the articles used deep learning models, while 30% used traditional ML algorithms. Most studies reported high sensitivity, specificity, and accuracy for the ML models (exceeding 90%). The overall concern about the risk of bias was "unclear" in 56% of the studies. This was mainly due to concerns about selection bias. ML may help identify COVID-19 patients in the early phase of the pandemic, particularly in the context of chest imaging. Although these studies reflect that these ML models exhibit high accuracy, the novelty of these models and the biases in dataset selection make using them as a replacement for the clinicians' cognitive decision-making questionable. Continued research is needed to enhance the robustness and reliability of ML systems in COVID-19 diagnosis and prognosis.

Quality appraisal of antibiotic prophylaxis guidelines to prevent infective endocarditis following dental procedures: a systematic review.

OBJECTIVE: To assess the quality of clinical practice guidelines (CPGs) for the use of antimicrobial prophylaxis to prevent infective endocarditis in indicated dental procedures. STUDY DESIGN: We searched on Medline/OVID, CINAHL/EBSCO, and EMBASE from January 2011 to January 2022. We included de novo guidelines and excluded adapted or adopted guidelines, and guidelines published before 2011. The guidelines were independently appraised by 4 reviewers using the Appraisal of Guidelines for Research & Evaluation II (AGREE II) Instrument. RESULTS: Four eligible CPGs were appraised: the European Society of Cardiology, the American Heart Association, the National Institute of Health and Care Excellence (NICE), and the Japanese Circulation Society (JCS). Their AGREE II first overall assessments (OA1) were 63%, 58%, 92%, and 71%, respectively. Both NICE and JCS scored the highest in OA1 (>70%), Domain 3 Rigor of Development (85%, 65%), and Domain 5 Applicability (76%, 48%), respectively. The second overall assessment (OA2) of using the CPGs in daily practice was not significantly variable (recommended for use with modifications). CONCLUSION: Three out of 4 CPGs support that the benefits of prevention of infective endocarditis outweigh the risks of antibiotic resistance.

The life and death of living systematic reviews: a methodological survey.

OBJECTIVES: The objectives of this study are to describe the characteristics of living systematic reviews (LSRs) and to understand their life cycles. STUDY DESIGN AND SETTING: We conducted a comprehensive search up to April 2021 then selected articles and abstracted data in duplicate and independently. We undertook descriptive analyses and calculated delay in version update and delay since the last published version. RESULTS: We included 76 eligible LSRs with a total of 279 eligible versions. The majority of LSRs was from the clinical field (70%), was COVID-19 related (63%), and had a funding source specified (62%). The median number of versions per LSR was 2 (interquartile range (IQR) 1-4; range 1-19). The median and IQR for the ratio of the actual period of update to the planned period of update was 1.12 (0.81; 1.71). Out of all reviews with a 'planned period of update' and at least one update (N = 19), eight LSRs (42%) had a period since last published version greater than 3 times the planned period of update. No LSR included a 'retirement notice' in their latest published version. CONCLUSION: While most LSR complied with the planned period of producing updates, a substantive proportion lagged since their last update.

Ventilation Techniques and Risk for Transmission of Coronavirus Disease, Including COVID-19: A Living Systematic Review of Multiple Streams of Evidence.

BACKGROUND: Mechanical ventilation is used to treat respiratory failure in coronavirus disease 2019 (COVID-19). PURPOSE: To review multiple streams of evidence regarding the benefits and harms of ventilation techniques for coronavirus infections, including that causing COVID-19. DATA SOURCES: 21 standard, World Health Organization-specific and COVID-19-specific databases, without language restrictions, until 1 May 2020. STUDY SELECTION: Studies of any design and language comparing different oxygenation approaches in patients with coronavirus infections, including severe acute respiratory syndrome (SARS) or Middle East respiratory syndrome (MERS), or with hypoxemic respiratory failure. Animal, mechanistic, laboratory, and preclinical evidence was gathered regarding aerosol dispersion of coronavirus. Studies evaluating risk for virus transmission to health care workers from aerosol-generating procedures (AGPs) were included. DATA EXTRACTION: Independent and duplicate screening, data abstraction, and risk-of-bias assessment (GRADE for certainty of evidence and AMSTAR 2 for included systematic reviews). DATA SYNTHESIS: 123 studies were eligible (45 on COVID-19, 70 on SARS, 8 on MERS), but only 5 studies (1 on COVID-19, 3 on SARS, 1 on MERS) adjusted for important confounders. A study in hospitalized patients with COVID-19 reported slightly higher mortality with noninvasive ventilation (NIV) than with invasive mechanical ventilation (IMV), but 2 opposing studies, 1 in patients with MERS and 1 in patients with SARS, suggest a reduction in mortality with NIV (very-low-certainty evidence). Two studies in patients with SARS report a reduction in mortality with NIV compared with no mechanical ventilation (low-certainty evidence). Two systematic reviews suggest a large reduction in mortality with NIV compared with conventional oxygen therapy. Other included studies suggest increased odds of transmission from AGPs. LIMITATION: Direct studies in COVID-19 are limited and poorly reported. CONCLUSION: Indirect and low-certainty evidence suggests that use of NIV, similar to IMV, probably reduces mortality but may increase the risk for transmission of COVID-19 to health care workers. PRIMARY FUNDING SOURCE: World Health Organization. (PROSPERO: CRD42020178187).

International alliance and AGREE-ment of 71 clinical practice guidelines on the management of critical care patients with COVID-19: a living systematic review.

OBJECTIVE: We aimed to systematically identify and critically assess the clinical practice guidelines (CPGs) for the management of critically ill patients with COVID-19 with the AGREE II instrument. STUDY DESIGN AND SETTING: We searched Medline, CINAHL, EMBASE, CNKI, CBM, WanFang, and grey literature from November 2019 - November 2020. We did not apply language restrictions. One reviewer independently screened the retrieved titles and abstracts, and a second reviewer confirmed the decisions. Full texts were assessed independently and in duplicate. Disagreements were resolved by consensus. We included any guideline that provided recommendations on the management of critically ill patients with COVID-19. Data extraction was performed independently and in duplicate by two reviewers. We descriptively summarized CPGs characteristics. We assessed the quality with the AGREE II instrument and we summarized relevant therapeutic interventions. RESULTS: We retrieved 3,907 records and 71 CPGs were included. Means (Standard Deviations) of the scores for the 6 domains of the AGREE II instrument were 65%(SD19.56%), 39%(SD19.64%), 27%(SD19.48%), 70%(SD15.74%), 26%(SD18.49%), 42%(SD34.91) for the scope and purpose, stakeholder involvement, rigor of development, clarity of presentation, applicability, editorial independence domains, respectively. Most of the CPGs showed a low overall quality (less than 40%). CONCLUSION: Future CPGs for COVID-19 need to rely, for their development, on standard evidence-based methods and tools.

Epidemiology of type 2 diabetes in the Middle East and North Africa: Challenges and call for action.

Type 2 diabetes continues to be a serious and highly prevalent public health problem worldwide. In 2019, the highest prevalence of diabetes in the world at 12.2%, with its associated morbidity and mortality, was found in the Middle East and North Africa region. In addition to a genetic predisposition in its population, evidence suggests that obesity, physical inactivity, urbanization, and poor nutritional habits have contributed to the high prevalence of diabetes and prediabetes in the region. These risk factors have also led to an earlier onset of type 2 diabetes among children and adolescents, negatively affecting the productive years of the youth and their quality of life. Furthermore, efforts to control the rising prevalence of diabetes and its complications have been challenged and complicated by the political instability and armed conflict in some countries of the region and the recent coronavirus disease 2019. Broad strategies, coupled with targeted interventions at the regional, national, and community levels are needed to address and curb the spread of this public health crisis.

Public health effects of travel-related policies on the COVID-19 pandemic: A mixed-methods systematic review.

OBJECTIVES: To map travel policies implemented due to COVID-19 during 2020, and conduct a mixed-methods systematic review of health effects of such policies, and related contextual factors. DESIGN: Policy mapping and systematic review. DATA SOURCES AND ELIGIBILITY CRITERIA: for the policy mapping, we searched websites of relevant government bodies and used data from the Oxford COVID-19 Government Response Tracker for a convenient sample of 31 countries across different regions. For the systematic review, we searched Medline (Ovid), PubMed, EMBASE, the Cochrane Central Register of Controlled Trials and COVID-19 specific databases. We included randomized controlled trial, non-randomized studies, modeling studies, and qualitative studies. Two independent reviewers selected studies, abstracted data and assessed risk of bias. RESULTS: Most countries adopted a total border closure at the start of the pandemic. For the remainder of the year, partial border closure banning arrivals from some countries or regions was the most widely adopted measure, followed by mandatory quarantine and screening of travelers. The systematic search identified 69 eligible studies, including 50 modeling studies. Both observational and modeling evidence suggest that border closure may reduce the number of COVID-19 cases, disease spread across countries and between regions, and slow the progression of the outbreak. These effects are likely to be enhanced when implemented early, and when combined with measures reducing transmission rates in the community. Quarantine of travelers may decrease the number of COVID-19 cases but its effectiveness depends on compliance and enforcement and is more effective if followed by testing, especially when less than 14 day-quarantine is considered. Screening at departure and/or arrival is unlikely to detect a large proportion of cases or to delay an outbreak. Effectiveness of screening may be improved with increased sensitivity of screening tests, awareness of travelers, asymptomatic screening, and exit screening at country source. While four studies on contextual evidence found that the majority of the public is supportive of travel restrictions, they uncovered concerns about the unintended harms of those policies. CONCLUSION: Most countries adopted full or partial border closure in response to COVID-19 in 2020. Evidence suggests positive effects on controlling the COVID-19 pandemic for border closure (particularly when implemented early), as well as quarantine of travelers (particularly with higher levels of compliance). While these positive effects are enhanced when implemented in combination with other public health measures, they are associated with concerns by the public regarding some unintended effects.