Assessment of reporting quality of randomized controlled trials investigating the effects of inulin-type fructans supplementation on cardiovascular disease risk factors: A systematic survey
Bibliographic record
Abstract
BACKGROUND: Transparent and detailed reporting of randomized controlled trials (RCTs) is essential to judge its validity and generalizability. We assessed the reporting quality of RCTs examining the effects of inulin-type fructans supplementation on cardiovascular risk factors, before and after the publication of the Consolidated Standards of Reporting Trials (CONSORT) in 2010. METHODS: We searched MEDLINE, EMBASE, Emcare, AMED, the Cochrane Library, and CINAHL from inception to May 15, 2022, including the reference lists of selected RCTs. We screened titles and abstracts and extracted the data independently and in duplicate. We included RCTs that investigated the effects of inulin-type fructans on cardiovascular disease risk factors (e.g., low-density lipoprotein cholesterol, triglycerides, fasting blood glucose) in adults (18 years or older). The primary outcomes of this study were: the overall reporting quality of RCTs (defined as the total number of items [0 to 36] present from the CONSORT checklist) published before and after CONSORT; and the study characteristics (e.g., sample size, significance of primary outcome) predictive of the CONSORT score. The secondary outcome was the reporting of each specific item of the CONSORT checklist during pre- and post-CONSORT periods. The mean difference in the total number of reported items in studies published before and after CONSORT were compared using a t-test and Poisson regression to explore the factors associated with overall reporting quality of RCTs. We used Fisher's exact test to compare the adherence to each of the 36 items during pre- and post-CONSORT periods. RESULTS: We identified 1,767 citations from our systematic search, of which 55 were eligible. There was a significant increase in the reporting of CONSORT items (mean difference 8.5, 95% confidence interval [CI] 5.24 to 11.71) between studies published before and after publication of CONSORT. The sole variable that was predictive of better reporting quality of RCTs was whether the study was published before or after CONSORT (incidence rate ratio 1.67, 95% CI 1.40 to 2.02). Completeness of reporting of RCTs only improved in 15 out of 36 items (41.6%) after the publication of CONSORT. CONCLUSION: The completeness of reporting in RCTs investigating inulin-type fructans supplementation on cardiovascular disease risk factors remains inadequate after the publication of CONSORT. Greater adherence to CONSORT by authors and enforcement of CONSORT by journals may improve the quality of reporting among RCTs.
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How this classification was reachedexpand
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 | 0.061 | 0.401 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.008 | 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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".