Quality of systematic reviews supporting the 2017 ACC/AHA and 2018 ESC/ESH guidelines for the management of hypertension
Bibliographic record
Abstract
OBJECTIVE: To assess the methodological and reporting quality of systematic reviews (SRs) that informed recommendations in the recent American and European hypertension guidelines. DESIGN AND SETTINGS: Meta-epidemiological study. We identified SRs that were cited for class I recommendations based on Level of Evidence-A in the 2017 American College of Cardiology/American Heart Association (ACC/AHA) and the 2018 European Society of Cardiology/European Society of Hypertension (ESC/ESH) hypertension guidelines. MAIN OUTCOME MEASURES: Methodological and reporting quality of the SRs was assessed using A Measurement Tool to Assess Systematic Reviews (AMSTAR-2) checklist and Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist, respectively. RESULTS: A total of 40 SRs was included in the analysis (28 from 2017 ACC/AHA; 22 from 2018 ESC/ESH and 10 were included in both). Based on the AMSTAR-2 assessment, only 7.5% SRs were found to be of high methodological quality, 47.5% were of moderate, each 22.5% were of low and critically low quality. Based on the PRISMA checklist assessment, a mean of 24 items (SD (2.76) were reported appropriately, and only five SRs reported all 27 items appropriately. CONCLUSION: Methodological and reporting quality of SRs were found to vary considerably. Lack of information on the funding source of included studies, use of a protocol, integration of risk of bias assessments while interpreting findings and reporting of excluded studies were major methodological deficiencies.
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 | Metaresearch Domain: Evaluation · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | Metaresearch Domain: Evaluation · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Systematic review | 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 | 0.479 | 0.801 |
| Meta-epidemiology (narrow) | 0.003 | 0.004 |
| Meta-epidemiology (broad) | 0.014 | 0.026 |
| Bibliometrics | 0.026 | 0.022 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.013 | 0.009 |
| Open science | 0.006 | 0.007 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".