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Record W4365135975 · doi:10.1002/alr.23168

Determinants of physician assessment of chronic rhinosinusitis disease control using EPOS 2020 criteria and the importance of incorporating patient perspectives of disease control

2023· article· en· W4365135975 on OpenAlexaff
Ahmad R. Sedaghat, David S. Caradonna, Rakesh K. Chandra, Christine B. Franzese, Stacey T. Gray, Ashleigh A. Halderman, Claire Hopkins, Edward C. Kuan, Jivianne T. Lee, Edward D. McCoul, Erin K. O’Brien, Steven D. Pletcher, Melissa A. Pynnonen, Eric W. Wang, Sarah K. Wise, Bradford A. Woodworth, William C. Yao, Katie M. Phillips

Bibliographic record

VenueInternational Forum of Allergy & Rhinology · 2023
Typearticle
Languageen
FieldMedicine
TopicSinusitis and nasal conditions
Canadian institutionsSt. Thomas Hospital
Fundersnot available
KeywordsMedicineChronic rhinosinusitisNasal polypsNoseSurgeryPathology

Abstract

fetched live from OpenAlex

Abstract Background We identify chronic rhinosinusitis (CRS) manifestations associated with how rhinologists assess CRS control, with a focus on patient perspectives (patient‐reported CRS control). Methods Fifteen rhinologists were provided with real‐world data from 200 CRS patients. Participating rhinologists first classified patients’ CRS control as “controlled,” “partly controlled,” and “uncontrolled” using seven CRS manifestations reflecting European Position Paper on Rhinosinusitis and Nasal Polyps (EPOS) CRS control criteria (nasal obstruction, drainage, impaired smell, facial pain/pressure, sleep disturbance, use of systemic antibiotics/corticosteroids in past 6 months, and nasal endoscopy findings) and patient‐reported CRS control. They then classified patients’ CRS control without knowledge of patient‐reported CRS control. Interrater reliability and agreement of rhinologist‐assessed CRS control with patient‐reported CRS control and EPOS guidelines were determined. Results CRS control classification with and without knowledge of patient‐reported CRS control was highly consistent across rhinologists (κw = 0.758). Rhinologist‐assessed CRS control agreed with patient‐reported CRS control significantly better when rhinologists had knowledge of patient‐reported CRS control (κw = 0.736 vs. κw = 0.554, p < 0.001). Patient‐reported CRS control, nasal obstruction, drainage, and endoscopy findings were most strongly associated with rhinologists’ assessment of CRS control. Rhinologists’ CRS control assessments weakly agreed with EPOS CRS control guidelines with (κw = 0.529) and without (κw = 0.538) patient‐reported CRS control. Rhinologists classified CRS as more controlled than EPOS guidelines in almost 50% of cases. Conclusions This study directly demonstrates the importance of patient‐reported CRS control as a dominant influence on rhinologists’ CRS control assessment. Knowledge of patient‐reported CRS control may better align rhinologists’ CRS control assessments and treatment decisions with patients’ perspectives.

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)0.008
metaresearch head score (Gemma)0.028
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.008
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.028
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.011
GPT teacher head0.312
Teacher spread0.301 · 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 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

Citations13
Published2023
Admission routes1
Has abstractyes

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