Interventions to Decrease Carotid-Intima Media Thickness in Children and Adolescents With Type 1 Diabetes: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Introduction Hyperglycemia is associated with a higher cardiovascular risk, as evidenced by increased carotid-intima media thickness (CIMT) in youth with diabetes. We conducted a systematic review and meta-analysis to assess the effect of pharmacological or non-pharmacological interventions on CIMT in children and adolescents with prediabetes or diabetes. Methods We conducted systematic searches of MEDLINE, EMBASE, and CENTRAL, together with supplementary searches in trial registers and other sources for studies completed up to September 2019. Interventional studies assessing ultrasound CIMT in children and adolescents with prediabetes or diabetes were considered for inclusion. Where appropriate, data were pooled across studies using random-effect meta-analysis. Quality was assessed using The Cochrane Collaboration’s risk-of-bias tool and a CIMT reliability tool. Results Six studies involving 644 children with type 1 diabetes mellitus were included. No study involved children with prediabetes or type 2 diabetes. Three randomized controlled trials (RCTs) evaluated the effects of metformin, quinapril, and atorvastatin. Three non-randomized studies, with a before-and-after design, evaluated the effects of physical exercise and continuous subcutaneous insulin infusion (CSII). The mean CIMT at baseline ranged from 0.40 to 0.51 mm. The pooled difference in CIMT was -0.01 mm (95% CI: -0.04 to 0.01) for metformin compared to placebo (2 studies; 135 participants; I2: 0%). The difference in CIMT was -0.01 mm (95% CI: -0.03 to 0.01) for quinapril compared to placebo (1 study; 406 participants). The mean change from baseline in CIMT was -0.03 mm (95% CI: -0.14 to 0.08) after physical exercise (1 study; 7 participants). Inconsistent results were reported for CSII or for atorvastatin. CIMT measurement was rated at a higher quality on all reliability domains in 3 (50%) studies. The confidence in results is limited by the low number of RCTs and their small sample sizes, as well as the high risk of bias in before-and-after studies. Conclusions Some pharmacological interventions may decrease CIMT in children with type 1 diabetes. However, there is great uncertainty with respect to their effects and no strong conclusions can be drawn. Further evidence from larger RCTs is required. Systematic Review Registration PROSPERO, CRD42017075169
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.022 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.030 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".