MétaCan
Menu
Back to cohort
Record W2130101433 · doi:10.1161/strokeaha.108.533018

Applying the Evidence

2009· article· en· W2130101433 on OpenAlexaffabout
Gustavo Saposnik, Shaun G. Goodman, Lawrence A. Leiter, Raymond T. Yan, David Fitchett, Neville Bayer, Amparo Casanova, Anatoly Langer, Andrew T. Yan

Bibliographic record

VenueStroke · 2009
Typearticle
Languageen
FieldMedicine
TopicLipoproteins and Cardiovascular Health
Canadian institutionsInstitute for Clinical Evaluative SciencesCanadian Heart Research CentreUniversity of TorontoSt. Michael's Hospital
FundersSanofi
KeywordsMedicineIntensive care medicine

Abstract

fetched live from OpenAlex

BACKGROUND AND PURPOSE: The importance of early and aggressive initiation of secondary prevention strategies for patients with both coronary artery disease (CAD) and cerebrovascular disease (CVD) is emphasized by multiple guidelines. However, limited information is available on cardiovascular protection and stroke prevention in an outpatient setting from community-based populations. We sought to evaluate and compare differences in treatment patterns and the attainment of current guideline-recommended targets in unselected high-risk ambulatory patients with CAD, CVD, or both. METHODS: This multicenter, prospective, cohort study was conducted from December 2001 to December 2004 among ambulatory patients in a primary care setting. The prospective Vascular Protection and Guidelines-Oriented Approach to Lipid-Lowering Registries recruited 4933 outpatients with established CAD, CVD, or both. All patients had a complete fasting lipid profile measured within 6 months before enrollment. The primary outcome measure was the achievement of blood pressure (BP) <140/90 mm Hg (or <130/80 mm Hg for patients with diabetes) and LDL cholesterol <2.5 mmol/L (<97 mg/dL) according to the Canadian guidelines in place at that time (similar to the National Cholesterol Education Program's value of 100 mg/dL). Secondary outcomes include use of antithrombotic, antihypertensive, and lipid-modifying therapies. RESULTS: Of the 4933 patients, 3817 (77%) had CAD only; 647 (13%) had CVD only; and 469 (10%) had both CAD and CVD. Mean+/-SD age was 67+/-10 years, and 3466 (71%) were male. Mean systolic and diastolic BPs were 130+/-16 and 75+/-9 mm Hg, respectively. Minor but significant differences were observed on baseline BP, total cholesterol, and LDL cholesterol measurements among the 3 groups. Overall, 83% of patients were taking a statin and 93% were receiving antithrombotic therapy (antiplatelet and/or anticoagulant agents). Compared with patients with CAD, those with CVD only were less likely to achieve the recommended BP (45.3% vs 57.3%, respectively; P<0.001) and lipid (19.4% vs 30.5%, respectively; P<0.001) targets. Among patients with CVD only, women were less likely to achieve the recommended BP and lipid targets compared with their male counterparts (for LDL cholesterol <2.5 mmol/L, 18.7% vs 23.8%, respectively; P=0.048). In multivariable analysis, patients with CVD alone were less likely to achieve treatment success (BP or lipid targets) after adjusting for age, sex, diabetes, and use of pharmacologic therapy. CONCLUSIONS: Despite the proven benefits of available antihypertensive and lipid-lowering therapies, current management of hypertension and dyslipidemia continues to be suboptimal. A considerable proportion of patients failed to achieve guideline-recommended targets, and this apparent treatment gap was more pronounced among patients with CVD and women. Quality improvement strategies should target these patient subgroups.

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)0.239
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.096
Threshold uncertainty score0.321

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0430.239
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0090.007
Science and technology studies0.0020.005
Scholarly communication0.0180.011
Open science0.0060.007
Research integrity0.0130.009
Insufficient payload (model declined to judge)0.0960.028

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 head0.032
GPT teacher head0.300
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 designNot applicable
Domainnot available
GenreCommentary

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

Citations64
Published2009
Admission routes2
Has abstractyes

Explore more

Same venueStrokeSame topicLipoproteins and Cardiovascular HealthFrench-language works237,207