The Effect of Prebiotics, Alone or as Part of Synbiotics, on Cardiometabolic Parameters in Women with Polycystic Ovary Syndrome: A Systematic Review and Meta-Analysis of Randomized Controlled Trials
Bibliographic record
Abstract
Background/Objectives: This systematic review and meta-analysis aimed to investigate the effect of prebiotics, alone or as part of synbiotics, on cardiometabolic parameters in polycystic ovary syndrome (PCOS) women. Methods: Databases, including PubMed, Scopus, ISI Web of Science, Embase, and the Cochrane Central Register of Controlled Trials, were searched for relevant randomized-controlled trials (RCTs) until 12 December 2024. Changes in mean ± standard deviations were extracted and combined using a random-effects model. Bias was assessed using Cochrane risk of bias and evidence quality with GRADE. Results: Twenty RCTs with 1271 participants were included. Results showed high-quality evidence supporting prebiotics’ effects, alone or as part of synbiotics, in reducing body-mass index [n = 853; weighted-mean difference (WMD): −0.510, 95%CI: −0.669, −0.351 kg/m2] and diastolic blood pressure (WMD: −2.218, 95%CI: −4.425, −0.010 mmHg), moderate-quality evidence for weight, waist-to-hip ratio, and triglycerides improvements, and low or very-low-quality evidence for waist circumference (WC), fat mass, fasting plasma glucose, fasting insulin, low-density lipoprotein (LDL), total cholesterol (TC), high sensitive-C reactive protein, total testosterone, follicle-stimulating hormone and free androgen index improvements. Subgroup analyses revealed possible reduction in LDL with prebiotics, as well as possible decreases in WC, TC, and total testosterone with synbiotics. Dietary approaches to stop hypertension diet improved insulin sensitivity. Conclusions: This study suggests that prebiotics may beneficially affect several cardiometabolic parameters in PCOS women. Approximately one-third of the results were based on moderate-to-high-quality evidence. This study highlights the need for future well-designed, larger RCTs with longer treatment duration to strengthen the evidence base and guide clinical decision-making.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Meta-analysis | low |
| gpt | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Meta-analysis | high |
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 | 0.019 | 0.039 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.024 | 0.039 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".