Defining COVID-19–associated pulmonary aspergillosis: systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Pulmonary aspergillosis may complicate coronavirus disease 2019 (COVID-19) and contribute to excess mortality in intensive care unit (ICU) patients. The disease is poorly understood, in part due to discordant definitions across studies. OBJECTIVES: We sought to review the prevalence, diagnosis, treatment, and outcomes of COVID-19-associated pulmonary aspergillosis (CAPA) and compare research definitions. DATA SOURCES: PubMed, Embase, Web of Science, and MedRxiv were searched from inception to October 12, 2021. STUDY ELIGIBILITY CRITERIA: ICU cohort studies and CAPA case series including ≥3 patients were included. PARTICIPANTS: Adult patients in ICUs with COVID-19. INTERVENTIONS: Patients were reclassified according to four research definitions. We assessed risk of bias with an adaptation of the Joanna Briggs Institute cohort checklist tool for systematic reviews. METHODS: We calculated CAPA prevalence using the Freeman-Tukey random effects method. Correlations between definitions were assessed with Spearman's rank test. Associations between antifungals and outcome were assessed with random effects meta-analysis. RESULTS: Fifty-one studies were included. Among 3297 COVID-19 patients in ICU cohort studies, 313 were diagnosed with CAPA (prevalence 10%; 95% CI 8%-13%). Two hundred seventy-seven patients had patient-level data allowing reclassification. Definitions had limited correlation with one another (ρ = 0.268-0.447; p < 0.001), with the exception of Koehler and Verweij (ρ = 0.893; p < 0.001); 33.9% of patients reported to have CAPA did not fulfill any research definitions. Patients were diagnosed after a median of 8 days (interquartile range 5-14) in ICUs. Tracheobronchitis occurred in 3% of patients examined with bronchoscopy. The mortality rate was high (59.2%). Applying CAPA research definitions did not strengthen the association between mould-active antifungals and survival. CONCLUSIONS: The reported prevalence of CAPA is significant but may be exaggerated by nonstandard definitions.
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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 | 0.020 | 0.044 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.036 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".