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Record W3165462729 · doi:10.1136/bmjebm-2021-111675

Quality of systematic reviews supporting the 2017 ACC/AHA and 2018 ESC/ESH guidelines for the management of hypertension

2021· article· en· W3165462729 on OpenAlexaboutno aff
Raju Kanukula, Rupasvi Dhurjati, Kota Vidyasagar, Nusrath Rehana, Arun Talari, Abdul Salam, Anthony Rodgers, Matthew J. Page

Bibliographic record

VenueBMJ evidence-based medicine · 2021
Typearticle
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsnot available
Fundersnot available
KeywordsChecklistSystematic reviewMedicineProtocol (science)MEDLINEFamily medicineCanadian Cardiovascular SocietyAlternative medicineInternal medicinePsychologyPathologyMyocardial infarction

Abstract

fetched live from OpenAlex

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 armCategoriesStudy designConfidence
gemmaMetaresearch
Domain: Evaluation · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
gptMetaresearch
Domain: Evaluation · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewhigh
models splitAgreement compares identical category sets and study designs across arms.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.361
metaresearch head score (Gemma)0.362
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.810
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.3610.362
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0060.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.962
GPT teacher head0.656
Teacher spread0.306 · 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

Labeled directly by 2 models reading the full record.

Metaresearch

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designObservational · Systematic review
DomainEvaluation
GenreEmpirical

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".

Quick stats

Citations3
Published2021
Admission routes1
Has abstractyes

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