The obesity paradigm on outcome in heart failure with reduced ejection fraction
Bibliographic record
Abstract
This commentary refers to ‘Anthropometric Measures and Adverse Outcomes in Heart Failure With Reduced Ejection Fraction: Revisiting the Obesity Paradox’, by J.H. Butt et al., https://doi.org/10.1093/eurheartj/ehad083 and the discussion piece ‘The obesity paradigm on outcome in heart failure with reduced ejection fraction’, by W. Doehner et al., https://doi.org/10.1093/eurheartj/ehad761. Dr Doehner and colleagues feel that our data are consistent with the existence of an obesity-survival paradox or ‘paradigm’. While analyses of body mass index (BMI), unadjusted for N-terminal pro-B-type natriuretic peptide (NT-proBNP), might appear to support their view, analyses using preferred alternative anthropometric measures do not.1 The value of BMI as a measure of adiposity has been questioned, particularly in global studies with racially and ethnically diverse participants.2–4 As stated in our manuscript, BMI does not consider the location or amount of body fat relative to muscle or the weight of the skeleton, which may differ according to age, sex, and race, and alternative anthropometric indices that may better reflect intra-abdominal fat or ‘central obesity’, such as waist-to-height ratio, are now recommended by organizations such as the National Institute for Health and Care Excellence in the United Kingdom (NICE).5 Unlike BMI, higher waist-to-height ratio was not associated with a significantly lower risk of mortality (whether due to cardiovascular or all causes), compared to normal weight, in unadjusted or adjusted analyses, with or without NT-proBNP.1 Moreover, we disagree with Dr. Doehner and colleagues about adjustment for NT-proBNP level. Applying their logic, we should not adjust for diabetes and hypertension either as these are more common in people with obesity, compared to those without. Patients with obesity (as with any other comorbidity) will inevitably differ from those without obesity (or the other comorbidity). Without adjustment, we cannot attempt to compare like-with-like. Dr Butt reports advisory board honoraria from Bayer; consultant honoraria from Novartis and AstraZeneca; travel grants from AstraZeneca. Dr McMurray reports payments through Glasgow University from work on clinical trials, consulting and other activities from: Amgen, AstraZeneca, Bayer, Cardurion, Cytokinetics, GSK, KBP Biosciences, and Novartis. Personal consultancy fees from: Alnylam Pharma., Bayer, BMS, George Clinical PTY Ltd., Ionis Pharma., Novartis, Regeneron Pharma., River 2 Renal Corporation. Personal lecture fees: Abbott, Alkem Metabolics, Astra Zeneca, Blue Ocean Scientific Solutions Ltd., Boehringer Ingelheim, Canadian Medical and Surgical Knowledge, Emcure Pharma. Ltd., Eris Lifesciences, European Academy of CME, Hikma Pharmaceuticals, Imagica health, Intas Pharma, J.B. Chemicals & Pharma. Ltd., Lupin Pharma, Medscape/Heart.Org, ProAdWise Communications, Radcliffe Cardiology, Sun Pharma, The Corpus, Translation Research Group, and Translational Medicine Academy. He is a director of Global Clinical Trial Partners Ltd.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.027 | 0.093 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.006 | 0.003 |
| Research integrity | 0.019 | 0.039 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".