Attenuated IGF-1 predicts all-cause and cardiovascular mortality in a Black population: A five-year prospective study
Bibliographic record
Abstract
BACKGROUND: Inconsistent findings are reported on whether insulin-like growth factor-1 (IGF-1) is protective or harmful in predicting hypertension, carotid wall thickness and mortality. We determined the five-year prognostic value of IGF-1 for these outcomes in a large Black population prone to hypertension and cardiovascular disease. DESIGN: A longitudinal study as part of the PURE (Prospective Urban and Rural Epidemiology) study, North West Province, South Africa. METHODS: We measured IGF-1 and IGF binding protein-3 (IGFBP-3) in 1038 HIV-uninfected participants (age range 32-94 years) and assessed blood pressure, carotid intima-media thickness and mortality. RESULTS: Over five years 116 deaths occurred. Baseline IGF-1 was similar in survivors and non-survivors (p = 0.50), but tended to be higher in survivors upon adjustment for IGFBP-3 and covariates (p = 0.061). Normotensives and hypertensives (p = 0.072), and those with carotid intima-media thickness < 0.9 mm and ≥ 0.9 mm also displayed similar baseline IGF-1 (p = 0.55). Multivariable-adjusted Cox-regression indicated high IGF-1 predicting lower risk for all-cause mortality (hazard ratio 0.45; 0.23-0.88) and cardiovascular mortality (hazard ratio 0.26; 0.08-0.83) when also adjusting for IGFBP-3. When including normo- and hypertensives at baseline, high IGF-1 was related to normotension at follow-up (hazard ratio 0.68; 0.49-0.95). We found no association with carotid intima-media thickness (hazard ratio 0.59; 0.31-1.14). CONCLUSION: In a Black South African population with low socio-economic status and harmful health behaviours, we found a protective independent association between IGF-1 and hypertension, cardiovascular and all-cause mortality, with no association with carotid wall thickness.
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 distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".