Pro-Adrenomedullin predicts 10-year all-cause mortality in community-dwelling patients: a prospective cohort study
Bibliographic record
Abstract
BACKGROUND: Several studies found mid-regional pro-adrenomedullin (ProADM), the prohormone of the cardiovascular protein adrenomedullin, to be strongly associated with short-term mortality, mostly in the inpatient setting. We evaluated associations of ProADM levels with 10-year mortality in community-dwelling primary care patients with respiratory tract infections. METHODS: This is a post-hoc analysis using clinical and biomarker data of 134 primary care patients with respiratory tract infections. ProADM was measured on admission and after 7 days in batch-analysis. 10-year follow-up data was collected by GP, patient and relative tracing through phone interviews. We calculated Cox regression models and area under the receiver operating characteristics curves to assess associations of ProADM with 10-year all-cause mortality. RESULTS: During the 10-year follow-up 6% of included patients died. Median baseline ProADM blood levels (nmol/l) were significantly higher in non-survivors compared to survivors (0.5, IQR 0.4-1.3; vs. 0.2, IQR 0.1-0.5; p = 0.02) and showed a significant association with 10-year all-cause mortality in an age-adjusted cox regression model (HR: 2.5, 95%-CI: 1.0-6.1, p = 0.04). ProADM levels on day 7 showed similar results. CONCLUSIONS: This posthoc analysis found an association of elevated ProADM blood levels and 10-year all-cause mortality in a primary care cohort with respiratory tract infections. Due to the methodological limitations including incomplete data regarding follow-up information and biomarker measurement, this study warrants validation in future larger studies. TRIAL REGISTRATION: Current Controlled Trials, SRCTN73182671.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".