Host Biomarkers Are Associated With Response to Therapy and Long-Term Mortality in Pediatric Severe Malaria
Bibliographic record
Abstract
Abstract Background. Host responses to infection are critical determinants of disease severity and clinical outcome. The development of tools to risk stratify children with malaria is needed to identify children most likely to benefit from targeted interventions. Methods. This study investigated the kinetics of candidate biomarkers of mortality associated with endothelial activation and dysfunction (angiopoietin-2 [Ang-2], soluble FMS-like tyrosine kinase-1 [sFlt-1], and soluble intercellular adhesion molecule-1 [sICAM-1]) and inflammation (10 kDa interferon γ-induced protein [CXCL10/IP-10] and soluble triggering receptor expressed on myeloid cells-1 [sTREM-1]) in the context of a randomized, double-blind, placebo-controlled, parallel-arm trial evaluating inhaled nitric oxide versus placebo as adjunctive therapy to parenteral artesunate for severe malaria. One hundred eighty children aged 1–10 years were enrolled at Jinja Regional Referral Hospital in Uganda and followed for up to 6 months. Results. There were no differences between the 2 study arms in the rate of biomarker recovery. Median levels of Ang-2, CXCL10, and sFlt-1 were higher at admission in children who died in-hospital (n = 15 of 180; P < .001, P = .027, and P = .004, respectively). Elevated levels of Ang-2, sTREM-1, CXCL10, and sICAM-1 were associated with prolonged clinical recovery times in survivors. The Ang-2 levels were also associated with postdischarge mortality (P < .0001). No biomarkers were associated with neurodisability. Conclusions. Persistent endothelial activation and dysfunction predict survival in children admitted with severe malaria.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".