Predictors of <i>Cryptococcus gattii</i> Clinical Presentation and Outcome: An International Study
Bibliographic record
Abstract
BACKGROUND: Infection by Cryptococcus gattii can lead to pulmonary or central nervous system (CNS) disease, or both. Whether the sites of infection and disease severity are associated with C. gattii species and lineages or with certain underlying medical conditions, or both is unclear. We conducted a retrospective cohort study to identify factors associated with site of infection and mortality among C. gattii cases. METHODS: We extracted data on 258 C. gattii cases from Australia, Canada, and the United States reported from 1999 to 2011. We conducted unadjusted and multivariable logistic regression analyses to evaluate factors associated with site of infection and C. gattii mortality among hospitalized cases (N = 218). RESULTS: Hospitalized C. gattii cases with CNS and other extrapulmonary disease were younger, more likely to reside in Australia, and be infected with variety gattii I (VGI) lineage but less likely to have comorbidities and die as compared to cases with pulmonary disease. The odds of having CNS and/or other extrapulmonary disease were 9 times higher in cases with VGI infection (adjusted odds ratio [aOR] = 9.21, 95% confidence interval [CI] = 3.28-25.89). Age ≥70 years (aOR = 6.69, 95% CI = 2.44-18.30), chronic lung disease (aOR = 2.62, 95% CI = 1.05-6.51) and an immunocompromised status (aOR = 2.08, 95% CI = 1.05-6.51) were associated with higher odds of C. gattii mortality. CONCLUSIONS: Among hospitalized cases, C. gattii species and lineage are associated with site of infection but not with the risk of death, whereas older age and comorbidities increase the risk of death.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".