Salvage combination antifungal therapy for acute invasive aspergillosis may improve outcomes: a systematic review and meta-analysis
Bibliographic record
Abstract
OBJECTIVE: A meta-analysis was performed to compare mold-active triazoles or lipid amphotericin B plus an echinocandin to non-echinocandin monotherapy for acute invasive aspergillosis (IA). METHODS: We searched PubMed, EMBASE, and other databases through May 2013 unrestricted by language. We included observational and experimental studies wherein patients with proven or probable IA by EORTC/MSG criteria underwent our comparative intervention. PRISMA and MOOSE guidelines were followed and quality was assessed using the Jadad and Newcastle-Ottawa criteria. Meta-regression with fixed and random effects and sensitivity analyses were performed. The primary study outcome measure was 12-week overall mortality. The secondary outcome assessed was complete and partial response. RESULTS: Only observational studies of primary 12-week survival showed heterogeneity (I(2)=48.96%, p=0.05). For salvage IA therapy, fixed effects models demonstrated improved 12-week survival (Peto odds ratio (OR) 1.80, 95% confidence interval (CI) 1.08-3.01) and success (Peto OR 2.17, 95% CI 1.21-3.91) of combination therapy. Significance remained after applying random effects as a sensitivity analysis (12-week survival: Peto OR 1.90, 95% CI 1.04-3.46, and unchanged value for success). Restriction to high quality studies and including echinocandins as the comparator for refractory IA revealed an adjusted OR of 1.72 (95% CI 0.96-3.09; p=0.07) for global success, while the survival endpoint remained unaltered. CONCLUSIONS: Combination antifungals for IA demonstrate improved outcomes over monotherapy in the salvage setting. Clinicians should consider this approach in certain situations.
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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 | 0.014 | 0.028 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.055 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".