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Record W4307235023 · doi:10.1002/ejhf.2723

Optimal cardiometabolic health and risk of heart failure in type 2 diabetes: an analysis from the Look AHEAD trial

2022· article· en· W4307235023 on OpenAlex
Kershaw V. Patel, Muhammad Shahzeb Khan, Matthew W. Segar, Judy Bahnson, Katelyn R Garcia, Jeanne M. Clark, Ashok Balasubramanyam, Alain G. Bertoni, Muthiah Vaduganathan, Michael E. Farkouh, James L. Januzzi, Subodh Verma, Mark A. Espeland, Ambarish Pandey

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEuropean Journal of Heart Failure · 2022
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Health and Risk Factors
Canadian institutionsSt. Michael's HospitalHeart and Stroke FoundationCanadian Heart Research CentreUniversity of Toronto
FundersNational Center on Minority Health and Health DisparitiesNational Heart, Lung, and Blood InstituteTranslational Science Center, Wake Forest UniversityIndian Health ServiceNational Center for Research ResourcesCenters for Disease Control and PreventionNational Institutes of HealthU.S. Department of Veterans AffairsMassachusetts Institute of TechnologyUniversity of Tennessee, KnoxvilleUniversity of PittsburghHarvard CatalystNational Institute of Diabetes and Digestive and Kidney DiseasesJohns Hopkins UniversityUniversity of ColoradoNational Institute of General Medical SciencesNational Institute of Nursing ResearchMassachusetts General Hospital
KeywordsMedicineHazard ratioInternal medicineHeart failureGlycated hemoglobinType 2 diabetesConfidence intervalCardiologyProportional hazards modelEjection fractionBlood pressureCreatinineRenal functionFramingham Risk ScoreWaistDiabetes mellitusBody mass indexEndocrinologyDisease

Abstract

fetched live from OpenAlex

AIMS: To evaluate the contribution of baseline and longitudinal changes in cardiometabolic health (CMH) towards heart failure (HF) risk among adults with type 2 diabetes (T2D). METHODS AND RESULTS: Participants of the Look AHEAD trial with T2D and without prevalent HF were included. Adjusted Cox models were used to create a CMH score incorporating target levels of parameters weighted based on relative risk for HF. The associations of baseline and changes in the CMH score with risk of overall HF, HF with preserved (HFpEF) and reduced ejection fraction (HFrEF) were assessed using Cox models. Among the 5080 participants, 257 incident HF events occurred over 12.4 years of follow-up. The CMH score included 2 points each for target levels of waist circumference, glomerular filtration rate, urine albumin-to-creatinine ratio, and 1 point each for blood pressure and glycated haemoglobin at target. High baseline CMH score (6-8) was significantly associated with lower overall HF risk (adjusted hazard ratio [HR], ref = low score (0-3): 0.31, 95% confidence interval [CI] 0.21-0.47) with similar associations observed for HFpEF and HFrEF. Improvement in CMH was significantly associated with lower risk of overall HF (adjusted HR per 1-unit increase in score at 4 years: 0.80, 95% CI 0.70-0.91). In the ACCORD validation cohort, the baseline CMH score performed well for predicting HF risk with adequate discrimination (C-index 0.70), calibration (chi-square 5.53, p = 0.70), and risk stratification (adjusted HR [high (6-8) vs. low score (0-3)]: 0.35, 95% CI 0.26-0.46). In the Look AHEAD subgroup with available biomarker data, incorporating N-terminal pro-B-type natriuretic peptide to the baseline CMH score improved model discrimination (C-index 0.79) and risk stratification (adjusted HR [high (8-10) vs. low score (0-4)]: 0.18, 95% CI 0.09-0.35). CONCLUSIONS: Achieving target levels of more CMH parameters at baseline and sustained improvements were associated with lower HF risk in T2D.

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.

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)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.442
Threshold uncertainty score0.584

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.014
GPT teacher head0.265
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