The effects of inositol supplementation on lipid profiles among patients with metabolic diseases: a systematic review and meta-analysis of randomized controlled trials
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Several studies have evaluated the effect of inositol supplementation on lipid profiles among population with metabolic diseases; however, the findings are controversial. This review of randomized controlled trials (RCTs) was performed to summarize the evidence of the effects of inositol supplementation on lipid profiles among population with metabolic diseases. METHODS: statistics were used. Data were pooled by using the random-effect model and standardized mean difference (SMD) was considered as summary of the effect size. RESULTS: Overall, 14 RCTs were included into meta-analysis. Pooled results showed that inositol supplementation among patients with metabolic diseases significantly decreased triglycerides (SMD - 1.24; 95% CI, - 1.84, - 0.64; P < 0.001), total- (SMD - 1.09; 95% CI, - 1.83, - 0.55; P < 0.001), and LDL-cholesterol levels (SMD - 1.31; 95% CI, - 2.23, - 0.39; P = 0.005). There was no effect of inositol supplementation on HDL-cholesterol levels (SMD 0.20; 95% CI, - 0.27, 0.67; P = 0.40). CONCLUSIONS: Inositol supplementation may result in reduction in triglycerides, total- and LDL-cholesterol levels, but did not affect HDL-cholesterol levels among patients with metabolic diseases. Additional prospective studies regarding the effect of inositol supplementation on lipid profiles in patients with metabolic diseases are necessary.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.015 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it