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Record W3154423206 · doi:10.2147/jaa.s314846

Reducing Fungal Exposure Critical for Treating Rhinosinusitis with or without Polyps [Response to Letter]

2021· letter· en· W3154423206 on OpenAlexaff
Claus Bachert, Neil Bhattacharyya, Martin Desrosiers, Asif Khan

Bibliographic record

VenueJournal of Asthma and Allergy · 2021
Typeletter
Languageen
FieldMedicine
TopicSinusitis and nasal conditions
Canadian institutionsCentre Hospitalier de l’Université de Montréal
Fundersnot available
KeywordsMedicineNasal polypsChronic rhinosinusitisIntensive care medicineDermatologyInternal medicine

Abstract

fetched live from OpenAlex

We thank Dr Curtis for his interest in our article, 1 and welcome the opportunity to address the putative role of molds and fungi in chronic rhinosinusitis (CRS).The potential contribution of fungi to the pathophysiology of CRS has been a focus of investigation many years back, and showed strong variation depending on the environment and climate.2,3 The emerging understanding that the nose and sinuses naturally host a microbiome including viruses, bacteria, and fungi, suggests that the presence of microorganisms is itself not a key etiological factor in CRS. 4 Moreover, there is a lack of convincing immunological data to link fungi to the disease process in the great majority of CRS cases.5 Consistent with this understanding, a 2018 Cochrane Review found no good evidence that oral or topical antifungals have a positive effect of quality of life, symptoms, or signs of disease in patients with CRS. 6 Indeed, consensus guidelines advise against the use of antifungals in CRS. 4 Among the phenotypes of CRS, allergic fungal rhinosinusitis (AFRS) is recognized as distinct from CRS with nasal polyps (CRSwNP), which was the subject of our review, in its diagnosis, presentation, clinical course, pathophysiology, and management.4,7,8 AFRS is a chronic disease that occurs predominantly in warm, humid climates and is characterized by a robust type 2 inflammatory response directed against colonizing fungi with accumulation of eosinophilic mucin containing fungal hyphae leading to persistent sinus opacification and nasal polyp formation.However, there is good evidence that AFRS accounts for only approximately 5-10% of CRS cases.4,[9][10][11][12] The study referenced in Dr Curtis' letter, which reported presence of AFRS in 94 of 101 CRS surgical patients, investigated a heterogenous population of patients with CRSwNP as well as CRS without nasal polyps diagnosed by recurrent upper tract infections lasting longer than 3 months and inflammatory mucosal thickening, 13 which is not consistent with the current diagnostic criteria for CRSwNP, 4 and reported a large heterogeneity in polyp size from "minimal" to "massive".The contribution of fungi to CRS in this study is particularly unclear since 100% of the control population were reported as culture-positive for fungi, with a microbiome profile similar to that of CRS patients.While the potential association between CRS, including AFRS, and exposure to mold is an area of investigation, a causal relationship has never been demonstrated.A reduction in rhinosinusitis symptoms following reduction in allergen exposure is not surprising in patients with CRS and allergic rhinitis.However, a recent analysis of home mold

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.025
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0020.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0250.024
Insufficient payload (model declined to judge)0.0060.004

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.

Opus teacher head0.021
GPT teacher head0.294
Teacher spread0.273 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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".

Quick stats

Citations2
Published2021
Admission routes1
Has abstractyes

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