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Record W2791163610 · doi:10.1136/bmj.k504

Outcomes of non-invasive diagnostic modalities for the detection of coronary artery disease: network meta-analysis of diagnostic randomised controlled trials

2018· review· en· W2791163610 on OpenAlexaff
George C.M. Siontis, Dimitris Mavridis, John P. Greenwood, Bernadette Coles, Adriani Nikolakopoulou, Peter Jüni, Georgia Salanti, Stephan Windecker

Bibliographic record

VenueBMJ · 2018
Typereview
Languageen
FieldMedicine
TopicCardiac Imaging and Diagnostics
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
FundersImperial College LondonSchool of Medicine, Duke UniversityUniversity College LondonBritish Heart Foundation
KeywordsMedicineCoronary artery diseaseAcute coronary syndromeInternal medicineMyocardial infarctionCardiologyMeta-analysisCochrane LibraryClinical trialOdds ratioRadiology

Abstract

fetched live from OpenAlex

OBJECTIVE: To evaluate differences in downstream testing, coronary revascularisation, and clinical outcomes following non-invasive diagnostic modalities used to detect coronary artery disease. DESIGN: Systematic review and network meta-analysis. DATA SOURCES: Medline, Medline in process, Embase, Cochrane Library for clinical trials, PubMed, Web of Science, SCOPUS, WHO International Clinical Trials Registry Platform, and Clinicaltrials.gov. ELIGIBILITY CRITERIA FOR SELECTING STUDIES: Diagnostic randomised controlled trials comparing non-invasive diagnostic modalities in patients presenting with symptoms suggestive of low risk acute coronary syndrome or stable coronary artery disease. DATA SYNTHESIS: A random effects network meta-analysis synthesised available evidence from trials evaluating the effect of non-invasive diagnostic modalities on downstream testing and patient oriented outcomes in patients with suspected coronary artery disease. Modalities included exercise electrocardiograms, stress echocardiography, single photon emission computed tomography-myocardial perfusion imaging, real time myocardial contrast echocardiography, coronary computed tomographic angiography, and cardiovascular magnetic resonance. Unpublished outcome data were obtained from 11 trials. RESULTS: 18 trials of patients with low risk acute coronary syndrome (n=11 329) and 12 trials of those with suspected stable coronary artery disease (n=22 062) were included. Among patients with low risk acute coronary syndrome, stress echocardiography, cardiovascular magnetic resonance, and exercise electrocardiograms resulted in fewer invasive referrals for coronary angiography than coronary computed tomographic angiography (odds ratio 0.28 (95% confidence interval 0.14 to 0.57), 0.32 (0.15 to 0.71), and 0.53 (0.28 to 1.00), respectively). There was no effect on the subsequent risk of myocardial infarction, but estimates were imprecise. Heterogeneity and inconsistency were low. In patients with suspected stable coronary artery disease, an initial diagnostic strategy of stress echocardiography or single photon emission computed tomography-myocardial perfusion imaging resulted in fewer downstream tests than coronary computed tomographic angiography (0.24 (0.08 to 0.74) and 0.57 (0.37 to 0.87), respectively). However, exercise electrocardiograms yielded the highest downstream testing rate. Estimates for death and myocardial infarction were imprecise without clear discrimination between strategies. CONCLUSIONS: For patients with low risk acute coronary syndrome, an initial diagnostic strategy of stress echocardiography or cardiovascular magnetic resonance is associated with fewer referrals for invasive coronary angiography and revascularisation procedures than non-invasive anatomical testing, without apparent impact on the future risk of myocardial infarction. For suspected stable coronary artery disease, there was no clear discrimination between diagnostic strategies regarding the subsequent need for invasive coronary angiography, and differences in the risk of myocardial infarction cannot be ruled out. SYSTEMATIC REVIEW REGISTRATION: PROSPERO registry no CRD42016049442.

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)0.043
metaresearch head score (Gemma)0.122
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 score0.043
Threshold uncertainty score0.229

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0430.122
Meta-epidemiology (narrow)0.0040.002
Meta-epidemiology (broad)0.0230.047
Bibliometrics0.0070.006
Science and technology studies0.0010.001
Scholarly communication0.0040.003
Open science0.0030.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.127
GPT teacher head0.396
Teacher spread0.269 · 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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Citations139
Published2018
Admission routes1
Has abstractyes

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