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Record W4412556007 · doi:10.1016/j.chest.2025.06.028

Diagnosing Respiratory Long COVID

2025· review· en· W4412556007 on OpenAlexafffund
Andrea S. Gershon, Daisy Fung, Grace Y. Lam

Bibliographic record

VenueCHEST Journal · 2025
Typereview
Languageen
FieldMedicine
TopicLong-Term Effects of COVID-19
Canadian institutionsUniversity of TorontoWomen and Children’s Health Research InstituteUniversity of Alberta HospitalUniversity of AlbertaSunnybrook Health Science Centre
FundersCanadian Institutes of Health ResearchCanadian Thoracic Society
KeywordsCoronavirus disease 2019 (COVID-19)MedicineIntensive care medicineSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Respiratory system2019-20 coronavirus outbreakPersistence (discontinuity)DiseasePediatricsInternal medicinePathologyInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

Long COVID or a post-COVID condition, defined as the persistence of symptoms at least 3 months after acute COVID-19 infection, is a novel condition in which a definitive diagnostic marker and treatment have yet to be found. This condition, which has been estimated to impact > 65 million individuals worldwide, manifests with multisystem involvement, most commonly presenting with fatigue, brain fog, dyspnea, cough, or a combination thereof. The burden of these symptoms can range from mild to severe, with many patients reporting an inability to return to usual activities. Herein, we present several hypothetical but clinically representative case reports to allow discussion around how we approach the diagnosis of respiratory symptoms of long COVID in those with and without chronic lung disease.

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)0.002
metaresearch head score (Gemma)0.007
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.061
GPT teacher head0.405
Teacher spread0.344 · 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
GenreReview

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
Published2025
Admission routes2
Has abstractno

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