Biomarkers of endothelial dysfunction predict sepsis mortality in young infants: a matched case-control study
Bibliographic record
Abstract
BACKGROUND: Reducing death due to neonatal sepsis is a global health priority, however there are limited tools to facilitate early recognition and treatment. We hypothesized that measuring circulating biomarkers of endothelial function and integrity (i.e. Angiopoietin-Tie2 axis) would identify young infants with sepsis and predict their clinical outcome. METHODS: We conducted a matched case-control (1:3) study of 98 young infants aged 0-59 days of life presenting to a referral hospital in Bangladesh with suspected sepsis. Plasma levels of Ang-1, Ang-2, sICAM-1, and sVCAM-1 concentrations were measured at admission. The primary outcome was mortality (n = 18); the secondary outcome was bacteremia (n = 10). RESULTS: Ang-2 concentrations at presentation were higher among infants who subsequently died of sepsis compared to survivors (aOR 2.50, p = 0.024). Compared to surviving control infants, the Ang-2:Ang-1 ratio was higher among infants who died (aOR 2.29, p = 0.016) and in infants with bacteremia (aOR 5.72, p = 0.041), and there was an increased odds of death across Ang-2:Ang-1 ratio tertiles (aOR 4.82, p = 0.013). CONCLUSIONS: This study provides new evidence linking the Angiopoietin-Tie2 pathway with mortality and bacteremia in young infants with suspected sepsis. If validated in additional studies, markers of the angiopoietin-Tie2 axis may have clinical utility in risk stratification of infants with suspected sepsis.
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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) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".