Adjunctive Diagnostic Studies Completed Following Detection of Candidemia in Children: Secondary Analysis of Observed Practice From a Multicenter Cohort Study Conducted by the Pediatric Fungal Network
Bibliographic record
Abstract
BACKGROUND: Adjunctive diagnostic studies (aDS) are recommended to identify occult dissemination in patients with candidemia. Patterns of evaluation with aDS across pediatric settings are unknown. METHODS: Candidemia episodes were included in a secondary analysis of a multicenter comparative effectiveness study that prospectively enrolled participants age 120 days to 17 years with invasive candidiasis (predominantly candidemia) from 2014 to 2017. Ophthalmologic examination (OE), abdominal imaging (AbdImg), echocardiogram, neuroimaging, and lumbar puncture (LP) were performed per clinician discretion. Adjunctive diagnostic studies performance and positive results were determined per episode, within 30 days from candidemia onset. Associations of aDS performance with episode characteristics were evaluated via mixed-effects logistic regression. RESULTS: In 662 pediatric candidemia episodes, 490 (74%) underwent AbdImg, 450 (68%) OE, 426 (64%) echocardiogram, 160 (24%) neuroimaging, and 76 (11%) LP; performance of each aDS per episode varied across sites up to 16-fold. Longer durations of candidemia were associated with undergoing OE, AbdImg, and echocardiogram. Immunocompromised status (58% of episodes) was associated with undergoing AbdImg (adjusted odds ratio [aOR] 2.38; 95% confidence intervals [95% CI] 1.51-3.74). Intensive care at candidemia onset (30% of episodes) was associated with undergoing echocardiogram (aOR 2.42; 95% CI 1.51-3.88). Among evaluated episodes, positive OE was reported in 15 (3%), AbdImg in 30 (6%), echocardiogram in 14 (3%), neuroimaging in 9 (6%), and LP in 3 (4%). CONCLUSIONS: Our findings show heterogeneity in practice, with some clinicians performing aDS selectively, potentially influenced by clinical factors. The low frequency of positive results suggests that targeted application of aDS is warranted.
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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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".