Introduction of spirometry into clinical practice in Georgetown, Guyana: quality and diagnostic outcomes
Bibliographic record
Abstract
SETTING: Georgetown Public Hospital Corporation (GPHC), a 600-bed publicly funded referral hospital in Georgetown, Guyana. OBJECTIVE: To assess spirometry quality and diagnostic outcomes 2 years after the introduction of spirometry into routine clinical practice at GPHC. DESIGN: We performed a retrospective review of 476 consecutive spirometry assessments performed from November 2013 to November 2015. We assessed the proportion and trend of spirometry tests meeting acceptability criteria, along with diagnostic interpretations and spirometry laboratory referral patterns. RESULTS: Overall, 80.4% of the 454 initial spirometry measurements on unique patients met the acceptability criteria, with no significant change in the proportion of acceptable spirometry over the study period (P = 0.450). Of the 369 (81.3%) first tests considered interpretable, 139 (30.6%) were normal, 151 (33.3%) were obstructive, 54 (11.9%) were suggestive of a restrictive pattern, 25 (5.5%) were suggestive of a mixed disorder and 119 (26.2%) tests met the definition of reversibility. CONCLUSION: Over a 2-year period, high-quality spirometry was performed in GPHC, a publicly funded hospital in a middle-income country with no pre-existing specialised respiratory service.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".