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Baseline Predictors of Low-Density Lipoprotein Cholesterol and Systolic Blood Pressure Goal Attainment After 1 Year in the ISCHEMIA Trial

2019· article· en· W2985301387 on OpenAlexaff
Jonathan Newman, Karen P. Alexander, Xiangqiong Gu, Sean M. O’Brien, William E. Boden, Sajeev Chakanalil Govindan, Roxy Senior, Nagaraja Moorthy, Paulo Cury Rezende, Marcin Demkow, José López‐Sendón, O.L. Bockeria, Neeraj Pandit, Gilbert Gosselin, Peter H. Stone, John A. Spertus, Gregg W. Stone, Jerome L. Fleg, Judith S. Hochman, David J. Maron

Bibliographic record

VenueCirculation Cardiovascular Quality and Outcomes · 2019
Typearticle
Languageen
FieldMedicine
TopicLipoproteins and Cardiovascular Health
Canadian institutionsMontreal Heart Institute
FundersNational Center for Advancing Translational SciencesNational Heart, Lung, and Blood Institute
KeywordsMedicineBlood pressureBaseline (sea)CardiologyInternal medicineIschemiaCholesterol

Abstract

fetched live from OpenAlex

BACKGROUND: Risk factor control is the cornerstone of managing stable ischemic heart disease but is often not achieved. Predictors of risk factor control in a randomized clinical trial have not been described. METHODS AND RESULTS: The ISCHEMIA trial (International Study of Comparative Health Effectiveness with Medical and Invasive Approaches) randomized individuals with at least moderate inducible ischemia and obstructive coronary artery disease to an initial invasive or conservative strategy in addition to optimal medical therapy. The primary aim of this analysis was to determine predictors of meeting trial goals for LDL-C (low-density lipoprotein cholesterol, goal <70 mg/dL) or systolic blood pressure (SBP, goal <140 mm Hg) at 1 year post-randomization. We included all randomized participants in the ISCHEMIA trial with baseline and 1-year LDL-C and SBP values by January 28, 2019. Among the 3984 ISCHEMIA participants (78% of 5179 randomized) with available data, 35% were at goal for LDL-C, and 65% were at goal for SBP at baseline. At 1 year, the percent at goal increased to 52% for LDL-C and 75% for SBP. Adjusted odds of 1-year LDL-C goal attainment were greater with older age (odds ratio [OR], 1.11 [95% CI, 1.03-1.20] per 10 years), lower baseline LDL-C (OR, 1.19 [95% CI, 1.17-1.22] per 10 mg/dL), high-intensity statin use (OR, 1.30 [95% CI, 1.12-1.51]), nonwhite race (OR, 1.32 [95% CI, 1.07-1.63]), and North American enrollment compared with other regions (OR, 1.32 [95% CI, 1.06-1.66]). Women were less likely than men to achieve 1-year LDL-C goal (OR, 0.68 [95% CI, 0.58-0.80]). Adjusted odds of 1-year SBP goal attainment were greater with lower baseline SBP (OR, 1.27 [95% CI, 1.22-1.33] per 10 mm Hg) and with North American enrollment (OR, 1.35 [95% CI, 1.04-1.76]). CONCLUSIONS: In ISCHEMIA, older age, male sex, high-intensity statin use, lower baseline LDL-C, and North American location predicted 1-year LDL-C goal attainment, whereas lower baseline SBP and North American location predicted 1-year SBP goal attainment. Future studies should examine the effects of sex disparities, international practice patterns, and provider behavior on risk factor control.

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)0.006
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.015
GPT teacher head0.266
Teacher spread0.251 · 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 designObservational
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

Citations30
Published2019
Admission routes1
Has abstractyes

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