Oxidative Stress Biomarkers as Prognostic Indicators of Severity in Patients With Dengue
Bibliographic record
Abstract
There is evidence for the role of oxidative stress in severe dengue pathogenesis. However, previous observational studies presents certain methodological limitations, which may affect its internal and external validity. This study was a case-control analysis of patients with severe dengue and dengue with warning signs, to evaluate the serum protein carbonyls-PCOs and lipid hydroperoxides-LOOHs levels and activities of superoxide dismutases-SODs (MnSOD, Cu/ZnSOD and total SOD), as potential prognosis indicators of severity in dengue patients, using binary logistic regression analysis and strategy of double cross-validation. Therefore, the study population was subdivided into a derivation group (pediatric patients, Barranquilla-Colombia) and an external validation group (children and adults patients, National Institute of Health of Peru). PCOs was the only oxidative stress markers that showed a strongest association with the severity of dengue, both in children and adults. In the derivation group, the optimal cut-off point was estimated at 5.29 nmol/mg of protein, and in the external validation group, it was 5.77 nmol/mg of protein. The prognostic models based on these two diagnostic thresholds showed a high discriminatory capacity of dengue severity, external reproducibility, geographic transportability, and typical characteristics of diagnostic validity and safety of screening tests.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".