METHODS: A systematic review and meta-analysis of randomized controlled trials were performed to evaluate the efficacy, safety, and quality of life of automated BI titration versus conventional care. The literature in Medline, Embase, Web of Science, and the Cochrane databases from January 2000 to February 2022 were searched to identify relevant studies. Risk ratios (RRs), mean differences (MDs), and their 95% confidence intervals (CIs) were calculated using random-effect meta-analyses. Certainty of evidence was assessed using the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) approach.
FINDINGS: Six of the 7 eligible studies (889 patients) were included in meta-analyses. Low- to moderate-quality evidence suggests that patients who use automated BI titration versus conventional care may have a higher probability of reaching a target of HbA1c <7.0% (RR, 1.82 [95% CI, 1.16-2.86]); and a lower level of HbA1c (MD, -0.25% [95% CI, -0.43 to -0.06%]). No statistically significant differences were detected between the two groups in fasting glucose results, incidences of hypoglycemia, severe or nocturnal hypoglycemia, and quality of life, with low to very low certainty for all the evidence.
INTERPRETATION: Automated BI titration is associated with small benefits in reducing HbA1c without increasing the risk of hypoglycemia. Future studies should explore patient attitudes and the cost-effectiveness of this approach.
FUNDING: Sponsored by the Chinese Geriatric Endocrine Society.
DESIGN: In this pragmatic randomised controlled trial at five general medical or diabetes clinics in Hong Kong and Malaysia, we randomly assigned patients in a 1:1 ratio to the intervention group with Fibrosis-4 index and aspartate aminotransferase-to-platelet ratio index automatically calculated based on routine blood tests, followed by electronic reminder messages to alert clinicians of abnormal results, or the control group with usual care. The primary outcome was the proportion of patients with increased fibrosis scores who received appropriate care (referred for hepatology care or specific fibrosis assessment) within 1 year.
RESULTS: Between May 2020 and Oct 2021, 1379 patients were screened, of whom 533 and 528 were assigned to the intervention and control groups, respectively. A total of 55 out of 165 (33.3%) patients with increased fibrosis scores in the intervention group received appropriate care, compared with 4 of 131 (3.1%) patients in the control group (difference 30.2% (95% CI 22.4% to 38%); p<0.001). Overall, 11 out of 533 (2.1%) patients in the intervention group and 1 out of 528 (0.2%) patients in the control group were confirmed to have advanced liver disease (difference 1.9% (95% CI 0.61% to 3.5%); p=0.006).
CONCLUSION: Automated fibrosis score calculation and electronic reminders can increase referral of patients with type 2 diabetes and abnormal fibrosis scores at non-hepatology settings.
TRIAL REGISTRATION NUMBER: NCT04241575.
METHODS: We performed a meta-analysis of three GWAS comprising 684 patients with type 2 diabetes and 955 controls of Southern Han Chinese descent. We followed up the top signals in two independent Southern Han Chinese cohorts (totalling 10,383 cases and 6,974 controls), and performed in silico replication in multiple populations.
RESULTS: We identified CDKN2A/B and four novel type 2 diabetes association signals with p