A practical guide for interpretation of ERS guidelines for methacholine challenge test (MCT)
Bibliographic record
Abstract
Rationale: A new ERS standard was published in 2017 providing guidance on how to perform the MCT, incorporating a change from evaluating the provocation concentration to the provocation dose (PD20). The standard includes significant useful detail and considerations regarding how one might undertake the MCT, with numerous appendices providing additional detail. The purpose of this abstract was to identify a small number of steps within the MCT process and provide a practical example of how the test could then be performed. Methods: The ERS standard / appendices was reviewed and the MCT process was broken down into the following discrete steps: a) preparation of methacholine solutions, b) calculation of doses at each concentration c) performance of actual challenge test, d) determination of PD20 and e) assessment of airway hyper-responsiveness (AHR). Each step was then expanded with supporting information Results: Using independently referenced (within the ERS standard) validation data from a breath actuated nebulizer (AeroEclipse* BAN) and 1 minute tidal breathing, it was possible to expand upon the five identified steps in order to provide example methacholine concentrations, dilutions and associated delivered doses. This then enabled an example test protocol to be formulated with the subsequent determination of PD20 and interpretation in terms of AHR. Conclusions: A five step guide to the 2017 ERS standard has been developed. This could either be used directly with the example nebulizer, or modified with alternative delivery systems once such systems have validated methacholine delivery data available.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.022 | 0.083 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.084 | 0.107 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".