Systematic review: the impact of gastro‐oesophageal reflux disease on work productivity
Bibliographic record
Abstract
BACKGROUND: Gastro-oesophageal reflux disease has wide-ranging effects on patients' lives. AIM: To review systematically the effects of gastro-oesophageal reflux disease on work productivity. METHODS: Studies of gastro-oesophageal reflux disease and work productivity were identified in a systematic literature search and their results were valued in US dollars using the human capital method. Work productivity loss was defined as absence from work (absenteeism) plus reduced effectiveness while working (presenteeism). RESULTS: Eight eligible studies were included. Reported work productivity loss among individuals with gastro-oesophageal reflux disease ranged from 6% to 42% and was primarily because of presenteeism (6-40%) rather than absenteeism (<1% to 7%). Reported losses were greatest in patients experiencing sleep disturbance because of gastro-oesophageal reflux disease, and lowest in individuals from the general population taking appropriate prescription medication. Work productivity impairment correlated with symptom severity and responded to acid-suppressive therapy. Assuming a 40-h working week and average wages in the US, the weekly mean productivity loss per employee with gastro-oesophageal reflux disease can be estimated between 2.4 (62 dollars) and 16.6 h (430 dollars), depending on the population studied. CONCLUSIONS: Gastro-oesophageal reflux disease has a substantial impact on employee productivity, primarily by impairing productivity while working. Further studies are needed to confirm that this impact can be decreased by acid-suppressive therapy.
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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 | 0.010 | 0.057 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.008 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".