Strongyloidiasis-related lung involvement: too much of a bad thing
Bibliographic record
Abstract
PURPOSE OF REVIEW: Strongyloidiasis is a soil-transmitted helminthiasis, a neglected tropical disease that affects 300-900 million individuals globally. Strongyloides stercoralis is associated with cutaneous, respiratory, and gastrointestinal clinical manifestations. Chronicity is due to an autoinfective cycle, and host immunosuppression can lead to severe and fatal disease. Lung involvement is significant in severe strongyloidiasis, and Strongyloides has a complex association with a number of lung diseases, which will be discussed in this review. RECENT FINDINGS: The treatment of chronic lung diseases such as asthma and chronic obstructive pulmonary disease with corticosteroids is an important risk factor for Strongyloides hyperinfection syndrome (SHS)/disseminated strongyloidiasis. The use of corticosteroids in the treatment of coronavirus disease 2019 (COVID-19) and potentially COVID-19-induced eosinopenia are risk factors for severe strongyloidiasis. Recent findings have demonstrated a significant immunomodulatory role of Strongyloides in both latent and active pulmonary tuberculosis associated to an impaired immune response and poor outcomes in active pulmonary tuberculosis. SUMMARY: Strongyloides lung involvement is a common finding in severe infection. Prompt recognition of Strongyloides infection as well as prevention of severe disease by screening or presumptive treatment are important goals in order to improve Strongyloides outcomes in at-risk population.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".