Effects of chromium supplementation on blood pressure, body mass index, liver function enzymes and malondialdehyde in patients with type 2 diabetes: A systematic review and dose-response meta-analysis of randomized controlled trials
Bibliographic record
Abstract
Several studies reported beneficial effects of chromium supplementation for management of type 2 diabetes mellitus (T2DM). The present study aimed to provide a systematic review and meta-analysis of randomized controlled trials (RCTs) examining the effects of chromium supplementation on blood pressure, body mass index (BMI), liver function enzymes and malondialdehyde (MDA) in patients with T2DM. PubMed, Scopus, and Embase were searched up to 15 November 2020 with no language and time restriction. RCTs that reported the effects of chromium supplementation on blood pressure, BMI, liver function enzymes and MDA in patients with T2DM were included. A random-effects model was used to compute weighted mean differences (WMDs) with 95 % confidence intervals (CIs). Between-study heterogeneity was assessed by Cochran's Q test and quantified by I2 statistic. Of 3586 publications, 15 RCTs were included for the meta-analysis. Pooled effect sizes indicated that chromium significantly reduced diastolic blood pressure (DBP) (WMD): -2.36 mmHg, 95 % CI: −4.14, −0.60; P = 0.008), and MDA (WMD: −0.55 umol/l, 95 % CI: −0.96, −0.14; P = 0.008). However, chromium supplementation did not significantly affect BMI, systolic blood pressure (SBP), alanine aminotransferase (ALT), aspartate aminotransferase (AST). Meta-regression analysis did not show significant linear relationship between dose of chromium and change in BMI (p = 0.412), SBP (p = 0. 319), DBP (p = 0.102), ALT (p = 0.923), AST (p = 0.986) and MDA (p = 0.055). The present systematic review and meta-analysis shows that supplementation with chromium at dose of 200–1000 μg/day may reduce DBP and MDA in T2DM patients.
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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 | 0.012 | 0.024 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.038 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 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".