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Record W2120044408 · doi:10.1183/09031936.00226911

Global burden of chronic pulmonary aspergillosis complicating sarcoidosis

2012· article· en· W2120044408 on OpenAlexaff
David W. Denning, Alex Pleuvry, Donald C. Cole

Bibliographic record

VenueEuropean Respiratory Journal · 2012
Typearticle
Languageen
FieldMedicine
TopicAntifungal resistance and susceptibility
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineSarcoidosisPulmonary aspergillosisAspergillosisIntensive care medicineDermatologyImmunology

Abstract

fetched live from OpenAlex

Chronic pulmonary aspergillosis (CPA) may complicate pulmonary sarcoidosis. We re-estimated the global burden of sarcoidosis and the burden of CPA complicating sarcoidosis. We searched the literature and reference lists of retrieved papers to identify all published sarcoidosis incidence and prevalence data. We estimated the frequency of CPA from 11 papers relating to >3,000 patients with sarcoidosis to derive CPA patient numbers. We applied an annual attrition rate of 15% (range 10-25%) to estimate the global burden of CPA. We estimate that the annual incidence of sarcoidosis is 344,000 patients worldwide and the prevalence is ∼1,238,000 cases, distributed as follows: 165,979 in Europe, 224,000 in the Americas, 492,892 in Africa, 80,023 in the Eastern Mediterranean, 41,660 in the West Pacific and 234,010 in Southeast Asia. CPA complicates sarcoidosis in 3-12% of cases. Using a 6% frequency, we estimate a global burden of 71,907 (range 35,954-143,815 (3-12%)) CPA cases complicating sarcoidosis, with 24% and 37% of cases estimated to be present in the Americas and Africa, because of the higher incidence of sarcoidosis in black people. As CPA responds to long-term antifungal therapy, which may prevent life-threatening haemoptysis, screening periodically for CPA in those with pulmonary sarcoidosis may be important, especially in patients requiring corticosteroid therapy.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.089
Threshold uncertainty score0.575

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.039
GPT teacher head0.305
Teacher spread0.267 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations181
Published2012
Admission routes1
Has abstractyes

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