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Record W4309483659 · doi:10.1016/j.ijregi.2022.11.005

New estimation of the prevalence of chronic pulmonary aspergillosis (CPA) related to pulmonary TB – a revised burden for India

2022· article· en· W4309483659 on OpenAlexaff
David W. Denning, Donald C. Cole, Animesh Ray

Bibliographic record

VenueIJID Regions · 2022
Typearticle
Languageen
FieldMedicine
TopicAntifungal resistance and susceptibility
Canadian institutionsPublic Health OntarioUniversity of Toronto
Fundersnot available
KeywordsMedicineIncidence (geometry)Pulmonary tuberculosisCoinfectionPediatricsTuberculosisAspergillosisMortality rateInternal medicineHuman immunodeficiency virus (HIV)PathologyImmunology

Abstract

fetched live from OpenAlex

Background: Chronic pulmonary aspergillosis (CPA) may be confused with, or a coinfection of, pulmonary tuberculosis (PTB), or may manifest itself after completion of antituberculous therapy (ATT). Methods: Literature searches were conducted on PubMed. The selected studies stated the timing of CPA diagnosis with respect to PTB. The key assumptions for estimating the annual incidence, annual deaths, and 5-year-period prevalence related to CPA were: of the clinically diagnosed PTB patients , 19% of those HIV-negative had CPA and 7% of HIV-positive patients had CPA; the percentage of patients presenting in the first year after PTB diagnosis or developing CPA as ATT finished was 10%; the annual rate of development of CPA from 2-5 years after PTB diagnosis was 1.5%; and the mortality of CPA was 20% in year 1 and 7.5% thereafter to year 5. Findings: In India, the annual incidence of CPA arising in PTB patients in 2019 was estimated to be 363 601 cases (range 254 521 - 472 682) and 42 766 deaths (range 29 936-55 595) - 10.5% of total PTB deaths. The 5-year-period prevalence of CPA was estimated at 1 575 716 , with an additional 100 715 deaths' total range of deaths 100 436- 186 525) annually. Interpretation: The revised estimation indicates a substantial unmet need for better diagnosis of CPA as part of a complex PTB-related respiratory morbidity burden.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.720
Threshold uncertainty score0.361

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.016
GPT teacher head0.281
Teacher spread0.265 · 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

Citations44
Published2022
Admission routes1
Has abstractyes

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