Artichoke leaf extract for treating hypercholesterolaemia
Post-publication record
Source: Retraction Watch, joined by DOI. OpenAlex records retraction as is_retracted, a boolean over a state space with at least four values, so it cannot express an expression of concern, a correction or a reinstatement; it reports them as false, which reads as “fine”.
Bibliographic record
Abstract
BACKGROUND: Hypercholesterolaemia is directly associated with an increased risk for coronary heart disease and other sequelae of atherosclerosis. Artichoke leaf extract (ALE) has been implicated in lowering cholesterol levels. Whether ALE is truly effective for this indication is still a matter of debate. This is an update of a review first published in 2002 and last updated in 2009. OBJECTIVES: To assess the efficacy and safety of ALE in the treatment of hypercholesterolaemia., SEARCH METHODS: We updated searches of the Cochrane Central Register of Controlled Trials (CENTRAL, The Cochrane Library) (2012, Issue 5); MEDLINE Ovid (1966 to May Week 2, 2012); EMBASE Ovid (1980 to 2012 Week 19); and CINAHL Ebsco (1982 to May 2012) on 17 May 2012. CISCOM was last searched until June 2001, and AMED until June 2008. We checked reference lists of articles, and contacted manufacturers of preparations containing artichoke extract, and experts on the subject. No language restrictions were applied. SELECTION CRITERIA: We included randomised controlled trials (RCTs) of ALE mono-preparations compared with placebo or reference medication for patients with hypercholesterolaemia. We excluded trials assessing ALE as one of several active components in a combination preparation or as a part of a combination treatment. DATA COLLECTION AND ANALYSIS: Data were extracted systematically and risk of bias was evaluated using the Cochrane 'Risk of bias' tool. Two authors independently performed the screening of studies, selection, data extraction and assessment of risk of bias. Disagreements in the evaluation of individual trials were resolved through discussion. MAIN RESULTS: We included three RCTs involving 262 participants. The trials were of adequate methodological quality but had some shortcomings. One trial was at low quality of risk, one at medium and one of unclear risk of bias. One trial is available as abstract only and includes a small sample. In the first trial the total cholesterol level in participants receiving ALE decreased by 4.2% from 7.16 (0.62) mmol/L to 6.86 (0.68) mmol/L after 12 weeks, and increased from 6.90 (0.49) mmol/L to 7.04 (0.61) mmol/L in patients receiving placebo, the total difference being statistically significant (P = 0.025). In the second trial ALE reduced total cholesterol levels by 18.5% from 7.74 mmol/L to 6.31 mmol/L after 42 ± 3 days of treatment, whereas placebo reduced cholesterol by 8.6% from 7.69 mmol/L to 7.03 mmol/L (P = 0.00001). The third trial, which is available as abstract only and provides limited data, stated that ALE significantly reduced blood cholesterol compared with placebo in a subgroup of patients with baseline total cholesterol levels of more than 230 mg/dL (P < 0.05). Trial reports indicate mild, transient and infrequent adverse events. AUTHORS' CONCLUSIONS: Data from three clinical trials assessing ALE for treating hypercholesterolaemia are available. Athough the trials are of adequate methodological quality they have some shortcomings and one is available as abstract only. There is an indication that ALE has potential in lowering cholesterol levels, but the evidence is, as yet, not convincing. The limited data on safety suggest only mild, transient and infrequent adverse events with the short term use of ALE.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".