Results From a Prospective, International, Epidemiologic Study of Invasive Candidiasis in Children and Neonates
Bibliographic record
Abstract
BACKGROUND: Candida species are the third most common cause of pediatric health care-associated bloodstream infection in the United States and Europe. To our knowledge, this report from the International Pediatric Fungal Network is the largest prospective, multicenter observational study dedicated to pediatric and neonatal invasive candidiasis. METHODS: From 2007 to 2011, we enrolled 196 pediatric and 25 neonatal patients with invasive candidiasis. RESULTS: Non-albicans Candida species predominated in pediatric (56%) and neonatal (52%) age groups, yet Candida albicans was the most common species in both groups. Successful treatment responses were observed in pediatric (76%) and neonatal patients (92%). Infection with Candida parapsilosis led to successful responses in pediatric (92%) and neonatal (100%) patients, whereas infection with Candida glabrata was associated with a lower successful outcome in pediatric patients (55%). The most commonly used primary antifungal therapies for pediatric invasive candidiasis were fluconazole (21%), liposomal amphotericin B (20%) and micafungin (18%). Outcome of pediatric invasive candidiasis was similar in response to polyenes (73%), triazoles (67%) and echinocandins (73%). The most commonly used primary antifungal therapies for neonatal invasive candidiasis were fluconazole (32%), caspofungin (24%) and liposomal amphotericin B (16%) and micafungin (8%). Outcomes of neonatal candidiasis by antifungal class again revealed similar response rates among the classes. CONCLUSIONS: We found a predominance of non-albicans Candida infection in children and similar outcomes based on antifungal class used. This international collaborative study sets the foundation for large epidemiologic studies focusing on the unique features of neonatal and pediatric candidiasis and comparative studies of therapeutic interventions in these populations.
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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".