The obesity paradigm in cardiovascular disease: the need for differentiated weight management
Bibliographic record
Abstract
This commentary refers to ‘Life-course explains the “obesity paradox” by T.E. Strandberg and A.Y. Strandberg, 2020;41(40):3963–3964. In the letter by Strandberg and Strandberg, the authors suggest that the findings from the ORIGIN study on the obesity paradox1 were a trompe d' oeil or ‘an illusion’.2 They argue that life-course weight trajectories may be an underlying factor for the outcome that could not be controlled for in short-term studies. They support this statement with a previous study showing that subjects with long-term weight loss [from overweight in mid-life to normal body mass index (BMI) at old age] had a higher mortality than subjects with other weight trajectories (stable overweight or stable normal weight or increasing body weight). In fact, this study is in support of our report as weight loss is confirmed to carry a higher mortality risk than stable weight or weight gain. Life-course trajectories of body weight may indeed carry further relevant information to explain life expectancy but are rarely obtained in patients and hence not widely applicable to support weight management recommendations. In turn, patients with cardiovascular diseases are predominantly elderly (mean age in the ORIGIN study 63.5 years). The finding that weight loss in cardiovascular patients over as little as 1 and 2 years was associated with a higher mortality than stable weight or weight gain over a mean follow-up of 6.2 years is an important observation. It highlights the clinical need to scrutinize weight loss that occurs in middle-aged and older patients and not to automatically assume cardiovascular or mortality benefit. This may contribute to the ongoing discussion towards more differentiated weight management recommendations taking into account individual factors such as age and pre-existing diseases.
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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 | 0.010 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.010 |
| Scholarly communication | 0.005 | 0.011 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.052 | 0.062 |
| Insufficient payload (model declined to judge) | 0.007 | 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".