No Association Between Protein C Levels and Bacteremia in Children With Febrile Neutropenia
Bibliographic record
Abstract
BACKGROUND: Little is known about protein C levels and outcomes of pediatric febrile neutropenia. The primary aim was to evaluate the relationship between markers of activated coagulation including protein C levels and bacteremia in pediatric oncology patients with febrile neutropenia. METHODS: In this prospective cohort study, we collected a blood specimen from pediatric oncology patients who were admitted to a tertiary care hospital between October 2, 2002 and February 3, 2006 with febrile neutropenia. Levels of protein C, soluble thrombomodulin, soluble endothelial protein C receptor, thrombin-antithrombin complex, fibrinogen degradation products and activated protein C were measured. Associations between markers of activated coagulation and bacteremia were examined using univariate logistic regression. RESULTS: Of the 73 evaluable patients, 10 had bacteremia. None of the above measured markers of activated coagulation were associated with bacteremia. More specifically, the median level of protein C in those with bacteremia was 0.64 U/mL (interquartile range: 0.58 to 0.72) in comparison with the median level in those without bacteremia of 0.73 U/mL (interquartile range: 0.61 to 0.92), odds ratio 0.18 (95% confidence interval 0.00 to 8.33); P=0.38. CONCLUSIONS: Protein C levels do not differ between pediatric febrile neutropenic patients with and without bacteremia.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".