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Record W4401185318 · doi:10.69944/pjc.4b226fdfc1

Prognostic Impact of Coronary Collaterals in Acute Coronary Syndrome: A Meta-Analysis (PICC-ACS)

2016· article· en· W4401185318 on OpenAlexaboutno aff
Jaime Alfonso M. Aherrera, John Daniel A Ramos, Lowe Chiong, Mark A Vicente, Felix Eduardo R. Punzalan

Bibliographic record

VenuePhilippine journal of cardiology. · 2016
Typearticle
Languageen
FieldMedicine
TopicCardiac Health and Mental Health
Canadian institutionsnot available
Fundersnot available
KeywordsAcute coronary syndromeMedicineCardiologyInternal medicineMeta-analysisMyocardial infarction

Abstract

fetched live from OpenAlex

Background: The coronary collateral circulation (CCC) is an alternative source of blood supply in coronary artery disease (CAD). A recent meta-analysis found that among patients with stable CAD, the presence of CCC has a relevant protective effect in terms of mortality. Among patients with acute coronary syndrome (ACS), surrogate end-points such as infarct size, systolic function, ventricular dilatation and post-infarct aneurysm formation have positive results in relation to the presence of CCC. The prognostic value of the presence of CCC at the time of ACS is still undefined with regard to hard outcomes, specifically, reduction of mortality. Objective: To determine whether the presence of CCC demonstrated by coronary angiography during an ACS is associated with a reduction in mortality Methodology: We conducted a systematic search of studies using MEDLINE, EMBASE, ScienceDirect, Scopus, and the Cochrane Central Register of Controlled Trials databases in all languages and examined the reference lists of the studies. The inclusion criteria for studies were (1) observational or randomized controlled trials; (2) population included adults ≥19 years old with ACS; (3) reported data on mortality in association with the presence or absence of CCC on angiography; and (4) if observational study, should have controlled for confounders by using logistic regression analysis. Studies identified were assessed for quality using either the Newcastle-Ottawa Quality Assessment Scale for observational studies or the Cochrane Tool for Assessing Risk of Bias for randomized trials. The outcome of interest was reduction in all-cause mortality, assessed using Mantel-Haenszel analysis of random effects to compute for relative risk, carried out using Review Manager (RevMan) 5.3. Results: Pooled analysis from 12 identified trials showed that among patients with ACS who underwent coronary angiography, the presence of CCC showed a trend towards benefit in terms of mortality but no statistical difference from no CCC (RR 0.69, 95% CI 0.44–1.08, p<0.0001, I2=73%). In the secondary analysis, patients with ACS and CCC treated with PCI had a significant reduction in mortality compared to those without CCC (RR 0.48, 95% CI 0.35–0.65, p<0.00001, I2=0%). Conclusion: The presence of CCC during ACS showed a trend towards mortality reduction. Further, among patients treated with PCI, those with CCC had an incremental significant reduction in mortality compared to those without CCC. Keyword: coronary collaterals, acute coronary syndrome.

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)0.013
metaresearch head score (Gemma)0.029
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: Empirical · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.070

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.029
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0140.044
Bibliometrics0.0050.006
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.056
GPT teacher head0.374
Teacher spread0.319 · 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
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

Citations0
Published2016
Admission routes1
Has abstractyes

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