The efficacy and safety of lecanemab 10 mg/kg biweekly compared to a placebo in patients with Alzheimer's disease: a systematic review and meta-analysis of randomized controlled trials.

Alzheimer's disease, prevalent in individuals aged 60 and above, constitutes most dementia cases and significantly impairs memory and cognitive functions. With global Alzheimer's cases projected to triple by 2050, there is a pressing need for effective interventions. Lecanemab, a monoclonal antibody targeting amyloid-beta plaques, shows promise in slowing Alzheimer's progression. Positive clinical trial results have instilled hope in patients, prompting ongoing research to advance understanding and intervention possibilities. To contribute to this knowledge base, we conducted a systematic review and meta-analysis, focusing on lecanemab's efficacy and safety at a dosage of 10 mg/kg. This comprehensive approach aimed to address gaps in the current literature, scrutinize research disparities, and guide future investigations. Applying strict inclusion/exclusion criteria, we assessed study details, participant information, and intervention specifics, using the Cochrane risk of bias tool for quality evaluation. Statistical analyses, conducted with R software, included risk ratios and mean differences, assessing heterogeneity and publication bias. The meta-analysis reveals a significant positive effect of lecanemab (10 mg/kg biweekly) on cognitive outcomes in Alzheimer's disease. Consistent reductions in ADCOMS, CDR-SB, and ADAS-cog14 scores across studies indicate drug efficacy with narrow confidence intervals and no significant heterogeneity. While TEAE shows no significant difference, heightened risks of ARIA-E and ARIA-H associated with lecanemab underscore the need for vigilant safety monitoring in clinical practice. Despite the drug efficacy, the study emphasizes a balanced assessment of benefits and potential risks associated with lecanemab, providing critical insights for clinicians evaluating its use in addressing cognitive impairment in individuals with Alzheimer's disease.

A systematic review of clinical health conditions predicted by machine learning diagnostic and prognostic models trained or validated using real-world primary health care data.

With the advances in technology and data science, machine learning (ML) is being rapidly adopted by the health care sector. However, there is a lack of literature addressing the health conditions targeted by the ML prediction models within primary health care (PHC) to date. To fill this gap in knowledge, we conducted a systematic review following the PRISMA guidelines to identify health conditions targeted by ML in PHC. We searched the Cochrane Library, Web of Science, PubMed, Elsevier, BioRxiv, Association of Computing Machinery (ACM), and IEEE Xplore databases for studies published from January 1990 to January 2022. We included primary studies addressing ML diagnostic or prognostic predictive models that were supplied completely or partially by real-world PHC data. Studies selection, data extraction, and risk of bias assessment using the prediction model study risk of bias assessment tool were performed by two investigators. Health conditions were categorized according to international classification of diseases (ICD-10). Extracted data were analyzed quantitatively. We identified 106 studies investigating 42 health conditions. These studies included 207 ML prediction models supplied by the PHC data of 24.2 million participants from 19 countries. We found that 92.4% of the studies were retrospective and 77.3% of the studies reported diagnostic predictive ML models. A majority (76.4%) of all the studies were for models' development without conducting external validation. Risk of bias assessment revealed that 90.8% of the studies were of high or unclear risk of bias. The most frequently reported health conditions were diabetes mellitus (19.8%) and Alzheimer's disease (11.3%). Our study provides a summary on the presently available ML prediction models within PHC. We draw the attention of digital health policy makers, ML models developer, and health care professionals for more future interdisciplinary research collaboration in this regard.

Barriers and facilitators to utilizing digital health technologies by healthcare professionals.

Digital technologies change the healthcare environment, with several studies suggesting barriers and facilitators to using digital interventions by healthcare professionals (HPs). We consolidated the evidence from existing systematic reviews mentioning barriers and facilitators for the use of digital health technologies by HP. Electronic searches were performed in five databases (Cochrane Database of Systematic Reviews, Embase®, Epistemonikos, MEDLINE®, and Scopus) from inception to March 2023. We included reviews that reported barriers or facilitators factors to use technology solutions among HP. We performed data abstraction, methodological assessment, and certainty of the evidence appraisal by at least two authors. Overall, we included 108 reviews involving physicians, pharmacists, and nurses were included. High-quality evidence suggested that infrastructure and technical barriers (Relative Frequency Occurrence [RFO] 6.4% [95% CI 2.9-14.1]), psychological and personal issues (RFO 5.3% [95% CI 2.2-12.7]), and concerns of increasing working hours or workload (RFO 3.9% [95% CI 1.5-10.1]) were common concerns reported by HPs. Likewise, high-quality evidence supports that training/educational programs, multisector incentives, and the perception of technology effectiveness facilitate the adoption of digital technologies by HPs (RFO 3.8% [95% CI 1.8-7.9]). Our findings showed that infrastructure and technical issues, psychological barriers, and workload-related concerns are relevant barriers to comprehensively and holistically adopting digital health technologies by HPs. Conversely, deploying training, evaluating HP's perception of usefulness and willingness to use, and multi-stakeholders incentives are vital enablers to enhance the HP adoption of digital interventions.

Telemedicine-Based Management of Oral Anticoagulation Therapy: Systematic Review and Meta-analysis.

BACKGROUND: Oral anticoagulation is the cornerstone treatment of several diseases. Its management is often challenging, and different telemedicine strategies have been implemented to support it. OBJECTIVE: 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. METHODS: 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. RESULTS: 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). CONCLUSIONS: 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. TRIAL REGISTRATION: PROSPERO International Prospective Register of Systematic Reviews CRD42020159208; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=159208.

The global effect of digital health technologies on health workers' competencies and health workplace: an umbrella review of systematic reviews and lexical-based and sentence-based meta-analysis.

Systematic reviews have quantified the effectiveness, feasibility, acceptability, and cost-effectiveness of digital health technologies (DHTs) used by health-care workers. We aimed to collate available evidence on technologies' effect on health-care workers' competencies and performance. We searched the Cochrane Database of Systematic Reviews, Embase, MEDLINE, Epistemonikos, and Scopus for reviews published from database inception to March 1, 2023. Studies assessing the effects of DHTs on the organisational, socioeconomic, clinical, and epidemiological levels within the workplace, and on health-care workers' performance parameters, were included. Data were extracted and clustered into 25 domains using vote counting based on the direction of effect. The relative frequency of occurrence (RFO) of each domain was estimated using R software. AMSTAR-2 tool was used to appraise the quality of reporting, and the Confidence in the Evidence from Reviews of Qualitative research approach developed by Grading of Recommendations Assessment, Development and Evaluation was used to analyse the certainty of evidence among included studies. The 12 794 screened reviews generated 132 eligible records for assessment. Top-ranked RFO identifiers showed associations of DHT with the enhancement of health-care workers' performance (10·9% [95% CI 5·3-22·5]), improvement of clinical practice and management (9·8% [3·9-24·2]), and improvement of care delivery and access to care (9·2% [4·1-20·9]). Our overview found that DHTs positively influence the daily practice of health-care workers in various medical specialties. However, poor reporting in crucial domains is widely prevalent in reviews of DHT, hindering our findings' generalisability and interpretation. Likewise, most of the included reviews reported substantially more data from high-income countries. Improving the reporting of future studies and focusing on low-income and middle-income countries might elucidate and answer current knowledge gaps.

Biologic Therapies in Chronic Rhinosinusitis with Nasal Polyposis: Overview of Systematic Reviews and Updated Systematic Review.

Objectives: Chronic rhinosinusitis with nasal polyposis (CRSwNP) is a highly prevalent and challenging disease to manage. Several systematic reviews (SRs) have been carried out to evaluate the efficacy and safety of biologic therapies. We aimed to evaluate the current and available evidence of the biologics in treating CRSwNP. Data Source: Systematic Review of three electronic databases. Review Methods: Following the PRISMA Statement, the authors explored three main databases through February 2020 for pertinent SRs and meta-analyses (MAs) as well as experimental and observational studies. A Measurement Tool to Assess Systematic Reviews Version-2 (AMSTAR-2), was employed to evaluate the quality of methodology of SRs and MAs. Results: A Total of five SRs were included in this overview. The AMSTAR-2 final summary was moderate to critically low. Although conflicting findings were reported, anti-immunoglobulin E (Anti-IgE) and anti-interleukin-4 (Anti-IL-4) were superior to placebo for improving total nasal polyp (NP) score, particularly in patients with asthma. Findings of the included reviews revealed that both sinus opacification and the Lund-Mackay (LMK) total scores significantly improved after biologics use. Subjective quality-of-life (QoL) assessment provided by general and specific questionnaires illustrated favorable results of biologics for CRSwNP, whereas no significant adverse events were reported. Conclusion: The current findings support the use of biologics for CRSwNP patients. However, the evidence for their use in such patients should be cautiously adopted because of the questionable evidence. Supplementary Information: The online version contains supplementary material available at 10.1007/s12070-022-03144-8.

Coronavirus disease (COVID-19) pandemic: an overview of systematic reviews.

BACKGROUND: Navigating the rapidly growing body of scientific literature on the SARS-CoV-2 pandemic is challenging, and ongoing critical appraisal of this output is essential. We aimed to summarize and critically appraise systematic reviews of coronavirus disease (COVID-19) in humans that were available at the beginning of the pandemic. METHODS: Nine databases (Medline, EMBASE, Cochrane Library, CINAHL, Web of Sciences, PDQ-Evidence, WHO's Global Research, LILACS, and Epistemonikos) were searched from December 1, 2019, to March 24, 2020. Systematic reviews analyzing primary studies of COVID-19 were included. Two authors independently undertook screening, selection, extraction (data on clinical symptoms, prevalence, pharmacological and non-pharmacological interventions, diagnostic test assessment, laboratory, and radiological findings), and quality assessment (AMSTAR 2). A meta-analysis was performed of the prevalence of clinical outcomes. RESULTS: Eighteen systematic reviews were included; one was empty (did not identify any relevant study). Using AMSTAR 2, confidence in the results of all 18 reviews was rated as "critically low". Identified symptoms of COVID-19 were (range values of point estimates): fever (82-95%), cough with or without sputum (58-72%), dyspnea (26-59%), myalgia or muscle fatigue (29-51%), sore throat (10-13%), headache (8-12%) and gastrointestinal complaints (5-9%). Severe symptoms were more common in men. Elevated C-reactive protein and lactate dehydrogenase, and slightly elevated aspartate and alanine aminotransferase, were commonly described. Thrombocytopenia and elevated levels of procalcitonin and cardiac troponin I were associated with severe disease. A frequent finding on chest imaging was uni- or bilateral multilobar ground-glass opacity. A single review investigated the impact of medication (chloroquine) but found no verifiable clinical data. All-cause mortality ranged from 0.3 to 13.9%. CONCLUSIONS: In this overview of systematic reviews, we analyzed evidence from the first 18 systematic reviews that were published after the emergence of COVID-19. However, confidence in the results of all reviews was "critically low". Thus, systematic reviews that were published early on in the pandemic were of questionable usefulness. Even during public health emergencies, studies and systematic reviews should adhere to established methodological standards.

Diagnostic accuracy of narrow-band imaging endoscopy with targeted biopsies compared with standard endoscopy with random biopsies in patients with Barrett's esophagus: A systematic review and meta-analysis.

BACKGROUND AND AIM: Endoscopic surveillance for dysplasia in Barrett's esophagus (BE) with random biopsies is the primary diagnostic tool for monitoring clinical progression into esophageal adenocarcinoma. As an alternative, narrow-band imaging (NBI) endoscopy offers targeted biopsies that can improve dysplasia detection. This study aimed to evaluate NBI-guided targeted biopsies' diagnostic accuracy for detecting dysplasia in patients undergoing endoscopic BE surveillance compared with the widely used Seattle protocol. METHODS: Cochrane DTA Register, MEDLINE/PubMed, EMBASE, OpenGrey, and bibliographies of identified papers were searched until 2018. Two independent investigators resolved discrepancies by consensus, study selection, data extraction, and quality assessment. Data on sensitivity, specificity, and predictive values were pooled and analyzed using a random-effects model. RESULTS: Of 9528 identified articles, six studies comprising 493 participants were eligible for quantitative synthesis. NBI-targeted biopsy showed high diagnostic accuracy in detection of dysplasia in BE with a sensitivity of 76% (95% confidence interval [CI]: 0.61-0.91), specificity of 99% (95% CI: 0.99-1.00), positive predictive value of 97% (95% CI: 0.96-0.99), and negative predictive value of 84% (95% CI: 0.69-0.99) for detection of all grades of dysplasia. The receiver-operating characteristic curve for NBI model performance was 0.8550 for detecting all dysplasia. CONCLUSION: Narrow-band imaging-guided biopsy demonstrated high diagnostic accuracy and might constitute a valid substitute for random biopsies during endoscopic surveillance for dysplasia in BE.

Impact of Big Data Analytics on People's Health: Overview of Systematic Reviews and Recommendations for Future Studies.

BACKGROUND: Although the potential of big data analytics for health care is well recognized, evidence is lacking on its effects on public health. OBJECTIVE: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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. TRIAL REGISTRATION: International Prospective Register of Systematic Reviews (PROSPERO) CRD42020214048; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=214048.

Clinical, laboratory and radiological characteristics and outcomes of novel coronavirus (SARS-CoV-2) infection in humans: A systematic review and series of meta-analyses.

New evidence on the COVID-19 pandemic is being published daily. Ongoing high-quality assessment of this literature is therefore needed to enable clinical practice to be evidence-based. This review builds on a previous scoping review and aimed to identify associations between disease severity and various clinical, laboratory and radiological characteristics. We searched MEDLINE, CENTRAL, EMBASE, Scopus and LILACS for studies published between January 1, 2019 and March 22, 2020. Clinical studies including ≥10 patients with confirmed COVID-19 of any study design were eligible. Two investigators independently extracted data and assessed risk of bias. A quality effects model was used for the meta-analyses. Subgroup analysis and meta-regression identified sources of heterogeneity. For hospitalized patients, studies were ordered by overall disease severity of each population and this order was used as the modifier variable in meta-regression. Overall, 86 studies (n = 91,621) contributed data to the meta-analyses. Severe disease was strongly associated with fever, cough, dyspnea, pneumonia, any computed tomography findings, any ground glass opacity, lymphocytopenia, elevated C-reactive protein, elevated alanine aminotransferase, elevated aspartate aminotransferase, older age and male sex. These variables typically increased in prevalence by 30-73% from mild/early disease through to moderate/severe disease. Among hospitalized patients, 30-78% of heterogeneity was explained by severity of disease. Elevated white blood cell count was strongly associated with more severe disease among moderate/severe hospitalized patients. Elevated lymphocytes, low platelets, interleukin-6, erythrocyte sedimentation rate and D-dimers showed potential associations, while fatigue, gastrointestinal symptoms, consolidation and septal thickening showed non-linear association patterns. Headache and sore throat were associated with the presence of disease, but not with more severe disease. In COVID-19, more severe disease is strongly associated with several clinical, laboratory and radiological characteristics. Symptoms and other variables in early/mild disease appear non-specific and highly heterogeneous. Clinical Trial Registration: PROSPERO CRD42020170623.

Relationship between body mass index, risk of venous thromboembolism and pulmonary embolism: A systematic review and dose-response meta-analysis of cohort studies among four million participants.

BACKGROUND: The relationship between body mass index (BMI) and risk of venous thromboembolism (VTE) and pulmonary embolism (PE) is a controversial issue. This dose-response meta-analysis was performed to investigate the association between BMI and risk of VTE and PE incidence based on cohort studies. METHOD: A comprehensive systematic search was conducted up to August 2019 in MEDLINE/PubMed, SCOPUS, and Cochrane. DerSimonian and Laird random-effects models were run to estimate combined hazard ratios (HRs) with 95% confidence intervals (CIs). Dose-response analysis was also carried out based on BMI values. RESULTS: Eleven articles with 16 arms and 3,910,747 participants were eligible for inclusion in this systematic review and meta-analysis. Pooled results showed a positive association between BMI and risk of VTE in the obese participants compared to participants classified in the normal BMI category (HR: 1.62, 95% CI: 1.29-2.04, I2 = 95%). Furthermore, results showed a significant association between lower BMI (underweight versus normal BMI category) and reduced risk of PE (HR: 0.80, 95% CI: 0.70-0.92, I2 = 9%) and higher risk of PE in obese versus normal BMI participants (HR: 2.24, 95% CI: 1.93-2.60, I2 = 0%). There was a significant linear relationship between BMI and risk of VTE (p < 0.001) and PE (p < 0.001). CONCLUSIONS: This systematic review and dose-response meta-analysis with 3,910,747 participants highlights obesity as a significant risk factor related to the incidence of VTE and PE.

Novel Coronavirus Infection (COVID-19) in Humans: A Scoping Review and Meta-Analysis.

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.

Effect of tomato consumption on fasting blood glucose and lipid profiles: A systematic review and meta-analysis of randomized controlled trials.

Tomato (Solanum lycopersicum) phytochemicals, which include phytoene, phytofluene, beta-carotene, flavonoids, lycopene, and polyphenols, have been shown to improve the effects of fasting on plasma triglyceride (TG), low-density lipoprotein cholesterol (LDL), high-density lipoprotein cholesterol (HDL), total cholesterol (TC), and fasting blood sugar (FBS). The aim of this study was to systematically evaluate the effects of Tomato TC, TG, HDL, LDL, and FBS in humans. A systematic literature search was conducted in PubMed/MEDLINE, Web of sciences, and SCOPUS databases by two researchers for studies published until August of 2019 without language and time limitations. Results were combined with random effect models. Six studies were included in this meta-analysis. Combined results reveal a significant reduction in cholesterol (weighted mean difference [WMD]: -4.39 mg/dl, 95% CI: -7.09, -1.68, I2 = % 48, p heterogeneity: .05), TG (WMD: -3.94 mg/dl, 95% CI: -7.67, -0.21, I2 = % 90, p heterogeneity: .001), LDL levels (WMD: -2.09 mg/dl, 95% CI: -3.73, -0.81, I2 = % 78, p heterogeneity: .001), and increasing in HDL levels (WMD: 2.25 mg/dl, 95% CI: 0.41, 4.10, I2 = % 97, p heterogeneity: .001). Tomato was found to have a higher reduction effect on TG and LDL in younger participants. While pooled results indicate no significant effect on FBS levels (WMD: 0.59 mg/dl, 95% CI: -0.28, 1.46, I2 = % 95, p heterogeneity: .001). In conclusion, the results indicate a significant reduction in total cholesterol, TG, and LDL and increase in HDL levels that is caused by tomato consumption.

The association of plasma levels of liver enzymes and risk of gestational diabetes mellitus: a systematic review and dose-response meta-analysis of observational studies.

AIMS: Relationship between liver enzymes such as gamma-glutamyl transferase (GGT), alanine aminotransferase (ALT), aspartate transaminase (AST) and alkaline phosphatase and risk of gestational diabetes mellitus (GDM) is a controversial issue. The aim of this systematic review and dose-response meta-analysis was to investigate the association between liver enzymes and risk of GDM in observational studies. METHODS: A comprehensive systematic literature search was conducted in MEDLINE/PubMed, SCOPUS and Web of Science databases up to September 2019. Combined odds ratios (ORs) with 95% confidence intervals (CIs) were evaluated by DerSimonian and Laird random-effects models. Dose-response analyses of these relationships were also carried out. RESULTS: Eight studies with 25,451 participants containing 2549 cases were included in this study. Pooled results showed a significant association between GGT levels and risk of GDM (OR 2.10, 95% CI 1.14-3.86, I2 84%). In addition, random-effects model indicated a dramatic and direct significant association between GGT and risk of GDM in nonlinear (p < 0.001) and linear (p < 0.001) dose-response analysis. Associations between ALT and AST with risk of GDM were found to be non-significant (OR 1.32, 95% CI 0.91-1.90, I2 65% and OR 0.76, 95% CI 0.52-1.10, I2 16%, respectively). CONCLUSION: This systematic review and dose-response meta-analysis highlights GGT as a significant and robust predictor of the incidence of GDM in pregnant women.

The health effects of medical nutrition therapy by dietitians in patients with diabetes: A systematic review and meta-analysis: Nutrition therapy and diabetes.

AIMS: Intensive lifestyle, dietary interventions and patient education have been recommended as key milestones in to facilitate the management of Diabetes and contain the growing incidence. We performed a systematic review and meta-analysis to assess the health benefits of medical nutrition therapy among patients with diabetes. DESIGN: A systematic search was performed in MEDLINE/PubMed, SCOPUS, and Cochrane library from onset up to February 2019 to identify trials investigating the health effect of Medical nutrition (MNT) in patients with diabetes. Random-effects models were used to calculate the effect sizes as weighted mean difference (WMD) and 95% confidence intervals (CI). RESULTS: Eleven studies containing 1227 participants were included in the meta-analysis. Pooled results showed a significant reduction in Fasting blood sugar (FBS) (WMD= -8.85mg/dl, 95% CI: -14.41, -3.28), HbA1c (WMD: -0.43%, 95% CI: -0.69, -0.17), weight (WMD: -1.54kg, 95% CI: -2.44, -0.64), Body mass index (BMI) (WMD: -0.34 Kg/m2, 95% CI: -0.52, -0.17), waist circumference (WMD: -2.16cm, 95% CI: -4.09, -0.23), cholesterol (WMD: -4.06mg/dl, 95% CI: -7.31, -0.81), Systolic blood pressure (SBP) (WMD: -7.90mmHg, 95% CI: -13.03, -2.77). Results of meta-regression analysis based on age of participants and duration of intervention were not significant. CONCLUSIONS: Patients with diabetes who received medical nutrition therapy showed significant improvements in outcome measures of FBS, HbA1c, weight, BMI, waist circumference, cholesterol, and SBP.