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Record W4412852633 · doi:10.1002/ptr.70054

Investigating the Effects of <scp><i>Vaccinium myrtillus</i></scp> Supplementation on Cardiometabolic Indices: A Systematic Review and Meta‐Analysis

2025· review· en· W4412852633 on OpenAlexaff
Shokoofeh Talebi, Mahsa Shirani, Atena Mahdavi, Mohammad Bagherniya, Amirhossein Sahebkar

Bibliographic record

VenuePhytotherapy Research · 2025
Typereview
Languageen
FieldMedicine
TopicPhytochemicals and Antioxidant Activities
Canadian institutionsUniversité LavalCentre hospitalier de l'Université Laval
Fundersnot available
KeywordsBilberryVaccinium myrtillusMeta-analysisMedicineGlycemicInternal medicineWeb of scienceRandomized controlled trialLipid profileDiabetes mellitusTraditional medicineEndocrinologyFood scienceBiologyBotany

Abstract

fetched live from OpenAlex

Chronic diseases cause early death and financial strain worldwide. Cardio-metabolic health, crucial for preventing cardiovascular disease and type 2 diabetes, may benefit from bilberry's antioxidant and anti-inflammatory properties. This meta-analysis reviews studies of bilberry's impact on lipid profiles, glycemic indices, body composition, and inflammatory and oxidative factors. Inclusion criteria were randomized clinical trials assessing bilberry supplementation in adults for at least 1 week. A comprehensive review of literature was performed in PubMed, Web of Science, Scopus, and Google Scholar until July 21, 2024, without any time limitations. Mean changes and their SDs were used to calculate overall effect sizes, with the Hozo et al. method converting SEs, 95% CIs, and IQRs to SDs. A random-effects model accounted for between-study variations. Eleven RCTs, including 409 individuals, were incorporated into the present systematic review, and 8 were included in the meta-analysis. Combining five effect sizes from the five trials on long-term effects of bilberry administration compared with controls resulted in a non-significant decrease in FBG (WMD: -0.08 mmol/L, 95% CI: -0.22 to 0.07, p = 0.30). For HbA1c, the meta-analysis of three RCTs showed a marginally significant reduction (WMD: -1.63%, 95% CI: -3.36% to 0.11%, p = 0.06). The results of the meta-analysis on lipid profile showed a decreasing trend, although this reduction was not statistically significant for TC (WMD: -0.11 mmol/L, 95% CI: -0.30% to 0.08%, p = 0.27) or TG (WMD: -0.07 mmol/L, 95% CI: -0.32% to 0.19%, p = 0.62). However, a significant change in TG was reported in trials with a crossover design and RCTs with 4 weeks of intervention or less. Although HDL level did not show any significant change (WMD: -0.02 mmol/L, 95% CI: -0.10% to 0.07%, p = 0.70), the meta-analysis of five RCTs evaluating the long-term effects of bilberry supplementation revealed a significant change in LDL following bilberry supplementation (WMD: 0.07 mmol/L, 95% CI: 0.01%-0.14%, p = 0.01). Furthermore, no significant reduction was observed in SBP (WMD: -2.75 mmHg, 95% CI: -6.38% to 0.89%, p = 0.13) or DBP (WMD: -1.00 mmHg, 95% CI: -4.66% to 2.65%, p = 0.59) after bilberry supplementation. Finally, anthropometric indices including body weight (WMD: 0.04 Kg, 95% CI: -0.44% to 0.53%, p = 0.86) and inflammatory and oxidative stress markers including hs-CRP (WMD: -8.22 mg/L, 95% CI: -20.24% to 3.81%, p = 0.18), IL-6 (WMD: -7.19 pg/mL, 95% CI: -19.01% to 4.63%, p = 0.23), uric acid (WMD: -0.01 mmol/L, 95% CI: -0.03% to 0.01%, p = 0.36), and FRAP (WMD: -42.03 μmol/L, 95% CI: -100.54% to 16.48%, p = 0.16) showed no significant change after bilberry supplementation. Bilberry supplementation may have beneficial effects on HbA1c and TG, but not other cardio-metabolic indices. Therefore, long-term and high-quality trials are needed to confirm the promising effects of bilberries.

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

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.017
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.015
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0170.039
Bibliometrics0.0050.005
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.096
GPT teacher head0.435
Teacher spread0.338 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

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".

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Citations2
Published2025
Admission routes1
Has abstractyes

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