Use of spirometry in family practice in Canada; results of a nationwide survey
Bibliographic record
Abstract
Aim: To determine the use of spirometry by family physicians in Canada, including barriers to testing and interpretation Method: A Spirometry questionaire was developed by the special interesest respiratory group of the College of Family Physicians of Canada to determine the use of spirometry in office Practice.Online Surveys were distributed by email through the college website to a group of family physicians identified as having an interest in respiratory medicine. Paper copies were distributed to all attendees at the College National Conference in Toronto in November 2015 and collected on site. Results: The majority of Physicians polled did use spirometry to aid in diagnosis of Copd and Asthma,and less often for other causes of dyspnea. 62 % had experienced barriers to accessing spirometry and obtain results,including long wait times and poor reports.Two thirds of respondents had moderate to severe discomfort with performing spirometry and more than half were uncomfortable or very uncomfortable with interpretation. Barriers to office spirometry included time constraints and lack of personnel to perform tests. When presented with a case,the majority of respondants would perform spirometry to make a diagnosis, although only 50% used spirometry to aid in diagnosis of undifferentiated dyspnea. Conclusion: Family physicians are interested in using spirometry to diagnose their patients with respiratory symptoms. There is a gap in knowledge in the performance and interpretation of spirometry, and variability in the availability of testing and consistency of test results. These needs can be addressed through ongoing education, including CME at the local and national level, and spirometry workshops.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".