ABSTRACT
A clinical decision support system (CDSS) informs or generates medical recommendations for healthcare practitioners. An alert is the most common way for a CDSS to interact with practitioners. Research about alerts in CDSS has proliferated over the past ten years. The research trend is ongoing with new emerging terms and focus. Bibliometric analysis is ideal for researchers to understand the research trend and future directions. Influential articles, institutes, countries, authors, and commonly used keywords were analyzed to grasp a comprehensive view on our topic, alerts in CDSS. Articles published between 2011 and 2021 were extracted from the Web of Science database. There were 728 articles included for bibliometric analysis, among which 24 papers were selected for content analysis. Our analysis shows that the research direction has shifted from patient safety to system utility, implying the importance of alert usability to be clinically impactful. Finally, we conclude with future research directions such as the optimization of alert mechanisms and comprehensiveness to enhance alert appropriateness and to reduce alert fatigue.
ABSTRACT
BACKGROUND: COVID-19 has become a global epidemic, causing huge loss of life and property. Diabetes will affect the prognosis of COVID-19 patients in many ways. Both hyperglycemia and hypoglycemia can affect oxidative stress and lead to the release of inflammatory mediators, leading to multiple organ damage and chronic inflammation. Here, we want to know whether hyperglycemia or hypoglycemia will adversely affect patients with diabetes and COVID-19 comorbidities. This has very important practical significance for the control of blood glucose in the treatment of diabetes combined with SARS-COV-2 infection. METHODS: We will search electronic databases including PubMed, EMBASE, the Cochrane Central Register of Controlled Trials (CENTRAL), Chinese Biomedical Literature Database (CBM), China National Knowledge Infrastructure (CNKI), Chinese Science and Technology Periodical Database (VIP), and Wanfang database using keywords related to COVID-19, diabetes mellitus, hyperglycemia and hypoglycemia. We will manually search gray literature, such as conference proceedings and academic degree dissertations, and trial registries. Two independent reviewers will screen studies, extract data, and evaluate risk of bias. Data analysis will be conducted using the Review Manager software version 5.3.5 and STATA4.0 software for Mac. The main outcome was the mortality of COVID-19 which was included in meta-analysis and subgroup analysis. The bias of the study was evaluated independently by NOS scale, and published by funnel chart. The sensitivity was analyzed row by row. RESULTS: This study will provide a high-quality synthesis of hyperglycemia and hypoglycemia in patients with COVID-19 combined with diabetes mellitus. To provide evidence for clinical treatment of diabetes mellitus combined with COVID-19. And the results will be published at a peer-reviewed journal.INPLASY registration number INPLASY 202080096.
Subject(s)
Coronavirus Infections/complications , Glucose Metabolism Disorders/complications , Pneumonia, Viral/complications , Betacoronavirus , Blood Glucose , COVID-19 , Coronavirus Infections/blood , Glucose Metabolism Disorders/blood , Glucose Metabolism Disorders/virology , Humans , Meta-Analysis as Topic , Pandemics , Pneumonia, Viral/blood , SARS-CoV-2 , Systematic Reviews as TopicABSTRACT
BACKGROUND: DM is a common chronic metabolic disease. COVID-19 is an infectious disease infected by enveloped single-stranded RNA coronavirus. Meanwhile, DM is a common comorbidity of SARS-CoV-2 infection. The virus can directly or indirectly damage the pancreatic islets and cause stress hyperglycemia by causing cytokine storms, acute inflammatory reactions, binding to the ACE2 receptor, etc. At the same time, hyperglycemia is a risk factor for severe infection and an independent risk factor for mild to severe disease. However, there is no evidence-based medicine to confirm the relationship between hyperglycemia and the infection of COVID-19 in diabetic patients. Therefore, we will conduct a systematic review and meta-analysis to synthesize the existing clinical evidence. METHODS AND ANALYSIS: We will retrieve each database from December 2019 to July 2020. Chinese literature comes from CNKI, Wanfang, VIP, CBM databases. English literature mainly searches Cochrane Library, PubMed, Web of Science, EMBASE. At the same time, we will look for clinical trial registration and gray literature. This study only included clinical randomized controlled trials. The reviewers independently conduct literature selection, data analysis, bias risk assessment, subgroup and sensitivity analysis. The primary outcomes include fasting blood glucose, 2-hour postprandial blood glucose, glycated hemoglobin, fasting insulin, adverse effects, etc. Finally, we will conduct a meta-analysis through Review Manager software version 5.3. RESULTS: The results will be published in peer-reviewed journals. CONCLUSION: This study will explore the relationship between hyperglycemia and COVID-19 infection in diabetic patients. It will provide evidence-based support for clinical regulation of blood glucose and combating the COVID-19 epidemic. REGISTRATION NUMBER: INPLASY202060114.
Subject(s)
Coronavirus Infections/epidemiology , Diabetes Mellitus/epidemiology , Hyperglycemia/epidemiology , Pneumonia, Viral/epidemiology , Betacoronavirus , Blood Gas Analysis , COVID-19 , Glycated Hemoglobin , Humans , Pandemics , Randomized Controlled Trials as Topic , Research Design , Risk Factors , SARS-CoV-2 , Severity of Illness IndexABSTRACT
BACKGROUND: Novel coronavirus pneumonia (COVID-19) has become a worldwide epidemic, causing huge loss of life and property. Because of its unique pathological mechanism, diabetes affects the prognosis of patients with COVID-19 in many aspects. At present, there are many controversies about whether angiotensin-converting enzyme inhibitors/angiotensin receptor blockers (ACEI/ARB) should be used in the treatment of patients with diabetes mellitus and COVID-19 comorbidities. There is an urgent need to provide evidence for the use of ACEI/ARB through high-quality systematic evaluation and meta-analysis. METHODS: We will search electronic databases including PubMed, Embase, the Cochrane Central Register of Controlled Trials (CENTRAL), Chinese Biomedical Literature Database, China National Knowledge Infrastructure, Chinese Science and Technology Periodical Database, and Wanfang database using keywords related to COVID-19, diabetes mellitus, ACEI/ARB drugs, and randomized controlled trials . We will manually search gray literature, such as conference proceedings and academic degree dissertations, and trial registries. Two independent reviewers will screen studies, extract data, and evaluate risk of bias. Data analysis will be conducted using the Review Manager software version 5.3.5 and stata 14.0 software for Mac. Statistical heterogeneity will be assessed using a standard chi-square test with a significance level of Pâ<â.10. Biases associated with study will be investigated using funnel plots. RESULTS: This study will provide a high-quality synthesis of efficacy and safety of ACEI/ARB drugs in patients with COVID-19 combined with diabetes mellitus, providing evidence for clinical treatment of diabetes mellitus combined with COVID-19. And the results will be published at a peer-reviewed journal. CONCLUSION: Our study will draw conclusions on the efficacy and safety of ACEI / ARB drugs in patients with diabetes mellitus complicated with covid-19, so as to provide theoretical guidance for clinical practice of diabetes mellitus with covid-19. INPLASY REGISTRATION NUMBER: INPLASY 202060111.