Combined medical-interventional approaches for the management of complex fungal balls: a case series as a viable alternative in non-surgical patients
Bibliographic record
Abstract
Intracavitary pulmonary aspergilloma is a persistent and life-threatening infection that carries a mortality rate of up to 15%. It occurs when Aspergillus species gain entry to an existing lung cavity. In the absence of definitive treatment, patients may succumb to severe complications such as massive hemoptysis, cachexia, or secondary infections. Aspergillomas often show limited response to antifungal medications, mainly due to insufficient drug concentrations within the cavities. Surgery is frequently the preferred treatment option, but it poses significant risks, and many individuals are ineligible due to underlying health issues. We present the most extensive non-surgical fungal ball cohort to date, managed using an innovative multimodal strategy that combines antifungal therapy before and after bronchoscopic debulking. This was a cross-sectional observational study. For those who cannot undergo surgery, our medical center has pioneered a multimodal approach to aspergilloma resection. This approach combines bronchoscopic endoscopy with antifungal therapy and has been applied successfully to more than 18 patients that are presented in this series. The median age of the cohort was 58 years (range: 32–73), with an equal sex distribution. The mean percent predicted FEV 1 was 65.3%. The mean follow-up duration was 3.6 years (range: 0.5–10 years). The cohort receiving antifungals systematically prior to debridement showed a reduction of the pre-existing cavity (40.38 mm versus 34.02 mm, p = 0.021). Across the 18 patients during the follow-up period, 94% remained recurrence-free (defined by symptoms and radiology). Our study fills a critical knowledge gap regarding the significance of initiating antifungal treatment before bronchoscopic debulking and presents a viable approach in these cases for which there is a current unmet therapeutic need.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".