Poor Lung Function of Industrial Workers of Bhutan: a retrospective study
Bibliographic record
Abstract
Introduction: Occupational lung diseases are some of the common causes of lung function impairment. Spirometry is a gold standard to determine lung function and, to diagnose obstructive and restrictive lung diseases. Therefore, this study aimed to determine the prevalence of abnormal lung function among employees of different industries of Bhutan. Methods: This retrospective study was carried out by retrieving all the spirometry findings and demographic variables of employees of different industries of Bhutan from the Spirometry Software of Respiratory Laboratory at the Center for Research in Respiratory and Neuroscience (CRRN), Khesar Gyalpo University of Medical Sciences of Bhutan (KGUSMB) . All these retrieved data were saved in Microsoft Excel and simple descriptive statistics were used to analyze the data and were expressed in numbers, percentages, mean and standard deviation. Results: Spirometry and demographic results of 3508 industrial employees were obtained. The mean age was 33.8years and mean BMI was 24.95 Kg/m2. Non-smokers comprised 79.9% (2804) of the total industrial employees. Abnormal forced expiratory volume between 25% and 75% of vital capacity (FEF25%-75%), a marker of small airway disease, constituted 24.1% (846) of the total industrial employees. Furthermore, 1.1% (39) had abnormal forced vital capacity (FVC), 1.3% (46) presented abnormal forced expiratory volume in 1 second (FEV1 ) and 1.5% (53) showed reduced FEV1 /FVC. Conclusions: Small airway impairment is common among industrial workers of Bhutan indicating presence of high prevalence of occupational lung diseases in its early stage which may potentially become clinically apparent after long latency.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 teacher head, 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".