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P94 Development and validation of the Hypersensitivity pneumonitis South Asian questionnaire for exposure (HP-SAQE)

2025· article· W4416134409 on OpenAlexaff
Surjit Singh, Ambika Sharma, Khushboo Pilania, Paramjit Singh, AK Sharma, Sahajal Dhooria, Vijay Hadda, Neeraj Gupta, Mansi Gupta, Amila Rathnapala, Amit Agarwal, Navneet Singh, Manjunath V. Joshi, Amit Kumar Mondal, J Bairwa, Virendra Singh, Kerri A. Johannson

Bibliographic record

Venuenot available
Typearticle
Language
FieldMedicine
TopicInterstitial Lung Diseases and Idiopathic Pulmonary Fibrosis
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsHypersensitivity pneumonitisCohortCohort studyDelphi methodPulmonologistsInterstitial lung diseaseReceiver operating characteristic

Abstract

fetched live from OpenAlex

Introduction There is an unmet need for a validated qualitative and quantitative tool to assess environmental exposures in patients with interstitial lung disease (ILD), particularly hypersensitivity pneumonitis (HP). This study aimed to develop and validate a comprehensive tool to systematically identify exposures in ILD patients across South Asia. Methods A systematic literature review identified exposures associated with ≥5 documented HP cases, which were evaluated through a two-round Delphi survey involving 39 pulmonologists from India, Sri Lanka, Pakistan, and Nepal. The preliminary questionnaire was pilot-tested (N=30) to ensure clarity and usability. Following refinement, the final questionnaire was prospectively validated in 202 ILD patients across six centres in India and Sri Lanka. Each patient underwent centralized, protocolized online multidisciplinary discussion. The questionnaire had a qualitative part and a quantitative score ranging from 0 to 14. Results The systematic review screened 5,170 records and included 407 studies, identifying 24 exposure categories. A 50-item Delphi survey achieved expert consensus (>70%) on 17 qualitative and 4 quantitative items. The questionnaire was translated into Hindi, Tamil, and Sinhala. In the derivation cohort (n=40), the HP-SAQE score was significantly higher in HP vs. non-HP patients (median: 11.0 vs. 8.5; p=0.0015). This finding was validated in a separate cohort (n=162; median: 10.0 vs. 2.5; p<0.001). ROC analysis showed good diagnostic performance (AUC: 0.79 derivation; 0.86 validation). In the derivation cohort, the exposure score demonstrated an AUC of 0.79, with a cutoff of ≥9 yielding 80% sensitivity, 50% specificity (Youden’s Index 0.30). A higher cutoff of ≥11 improved specificity to 90% with a moderate sensitivity of 55% (Youden’s Index 0.45). In the validation cohort, the AUC was 0.88, indicating excellent discriminative performance. A cutoff of ≥9 provided the optimal balance with 73% sensitivity, 81% specificity (Youden’s Index 0.54). Conclusion The HP-SAQE is the first regionally adapted, qualitative and quantitative exposure assessment tool for ILD patients, developed through systematic review, Delphi consensus, and multicentre prospective validation. Its high specificity and consistent centre-wise performance support its role in structured exposure assessment, particularly in resource-limited or high-burden settings. Lower score cutoffs may enhance its utility as a clinical screening tool.

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)0.053
metaresearch head score (Gemma)0.074
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.053
Threshold uncertainty score0.279

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0530.074
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0030.003
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.009
GPT teacher head0.243
Teacher spread0.234 · 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 designBench or experimental
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".

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Citations1
Published2025
Admission routes1
Has abstractyes

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