Do the 2012 spirometric Global Lung Function Initiative equations accurately diagnose restriction in the extreme obese?
Bibliographic record
Abstract
Background: Extreme obesity (“super” (S) and “super-super” (SS) obesity (O): body mass index 50-59.9 and ≥ 60 kg/m2 for SO and SSO, respectively) has been progressively recognised as a major public health concern worldwide. It remains unknown, however, whether the 2012 Global Lung Function Initiative (GLI) equations for spirometry can reliably identify obesity-related restriction in this population. Methods: We reviewed basic and advanced pulmonary function tests of 182 extreme-obese subjects (91 SO, 130 females, aged 18 to 79) who were free of major chronic cardiorespiratory disease known to induce restriction or chronic obstructive pulmonary disease. Results: Fifty-six subjects (~30%) presented with restriction (total lung capacity (TLC) < lower limit of normal (LLN) according to Quanjer et al. equations). As expected, these subjects had lower forced vital capacity (FVC) and functional residual capacity but higher transfer coefficient and transfer factor for carbon monoxide compared to their non-restricted counterparts (p<0.05). Although ~90% of subjects (86/97) showing FVC ≥ LLN had preserved TLC (true-negative), ~50% of subjects (40/85) with FVC < LLN did not show evidence of restriction (false-positive). A ROC curve analysis failed to identify a specific z-score threshold for FVC which proved superior to the LLN in predicting restriction by the GLI equations (p>0.05). Conclusion: The GLI-2012 prediction equations for spirometry can reliably rule out restriction in the extreme obese. However, a reduced FVC should not be considered indicative of restriction unless confirmed by body plethysmography. Spirometric reference values for the extreme obese are warranted.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
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".