Measurement of Midregional Proadrenomedullin in Plasma with an Immunoluminometric Assay
Bibliographic record
Abstract
BACKGROUND: Adrenomedullin (ADM) is a potent vasodilatory peptide, and circulating concentrations have been described for several disease states, including dysfunction of the cardiovascular system and sepsis. Reliable quantification has been hampered by the short half-life, the existence of a binding protein, and physical properties. Here we report the technical evaluation of an assay for midregional pro-ADM (MR-proADM) that does not have these problems. METHODS: MR-proADM was measured in a sandwich immunoluminometric assay using 2 polyclonal antibodies to amino acids 45-92 of proADM. The reference interval was defined in EDTA plasma of 264 healthy individuals (117 male, 147 female), and increased MR-proADM concentrations were found in 95 patients with sepsis and 54 patients with cardiovascular disease. RESULTS: The assay has an analytical detection limit of 0.08 nmol/L, and the interassay CV was <20% for values >0.12 nmol/L. The assay was linear on dilution with undisturbed recovery of the analyte. EDTA-, heparin-, and citrate-plasma samples were stable (<20% loss of analyte) for at least 3 days at room temperature, 14 days at 4 degrees C, and 1 year at -20 degrees C. MR-proADM values followed a gaussian distribution in healthy individuals with a mean (SD) of 0.33 (0.07) nmol/L (range, 0.10-0.64 nmol/L), without significant difference between males or females. The correlation coefficient for MR-proADM vs age was 0.50 (P < 0.001). MR-proADM was significantly (P < 0.001) increased in patients with cardiovascular disease [median (range), 0.56 (0.08-3.9) nmol/L] and patients with sepsis [3.7 (0.72-25.4) nmol/L]. CONCLUSIONS: MR-proADM is stable in plasma of healthy individuals and patients. MR-proADM measurements may be useful for evaluating patients with sepsis, systemic inflammation, or heart failure.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".