Decline in Circulating Insulin-Like Growth Factors and Mortality in Older Adults: Cardiovascular Health Study All-Stars Study
Bibliographic record
Abstract
BACKGROUND: The association between changes in IGF-I and IGF binding protein (IGFBP) levels and mortality in older adults is unknown. STUDY DESIGN: Participants were 997 persons 77 to 100 yr old enrolled in the Cardiovascular Health Study All Stars Study. Plasma levels of IGF-I, IGFBP-1, and IGFBP-3 were assessed at two study examinations (1996-1997 and 2005-2006). Mortality was assessed between 2006 and 2010. RESULTS: Cumulative mortality (CM) was similar among individuals who had at least 10% decreases over time in IGF-I levels (CM = 29.6%), individuals who had at least 10% increases over time in IGF-I levels (CM = 24.7%), and individuals who had IGF-I levels remaining within ±10% over time (CM = 23.5%). Adjusted for age, sex, race, diabetes, body mass index, creatinine, albumin, and C-reactive protein, decreasing IGF-I level had no significant association with overall cancer mortality or noncancer mortality. Levels of IGFBP-1 increased markedly over time by 38% (median). Individuals with the largest increases in IGFBP-1 level over time had significantly increased risk of mortality. The adjusted hazard ratio per sd of IGFBP-1 change was 1.40 for overall cancer mortality (95% confidence interval = 1.10, 1.77; P = 0.01) and 1.14 for noncancer mortality (95% confidence interval = 1.02, 1.27; P = 0.02). Changes in IGFBP-3 levels were not significantly associated with mortality. CONCLUSION: Among older adults, decreasing IGF-I level over time does not predict subsequent all-cause mortality, whereas increasing IGFBP-1 predicts increased risk of mortality.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".