Economic burden made celiac disease an expensive and challenging condition for Iranian patients.
Bibliographic record
Abstract
AIM: The aim of this study was to estimate the economic burden of celiac disease (CD) in Iran. BACKGROUND: The assessment of burden of CD has become an important primary or secondary outcome measure in clinical and epidemiologic studies. METHODS: Information regarding medical costs and gluten free diet (GFD) costs were gathered using questionnaire and checklists offered to the selected patients with CD. The data included the direct medical cost (including Doctor Visit, hospitalization, clinical test examinations, endoscopies, etc.), GFD cost and loss productivity cost (as the indirect cost) for CD patient were estimated. The factors used for cost estimation included frequency of health resource utilization and gluten free diet basket. Purchasing Power Parity Dollar (PPP$) was used in order to make inter-country comparisons. RESULTS: Total of 213 celiac patients entered to this study. The mean (standard deviation) of total cost per patient per year was 3377 (1853) PPP$. This total cost including direct medical cost, GFD costs and loss productivity cost per patients per year. Also the mean and standard deviation of medical cost and GFD cost were 195 (128) PPP$ and 932 (734) PPP$ respectively. The total costs of CD were significantly higher for male. Also GFD cost and total cost were higher for unmarried patients. CONCLUSION: In conclusion, our estimation of CD economic burden is indicating that CD patients face substantial expense that might not be affordable for a good number of these patients. The estimated economic burden may put these patients at high risk for dietary neglect resulting in increasing the risk of long term complications.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".