P415 Trends in narcotic and corticosteroid prescriptions in patients with inflammatory bowel disease in the United States ambulatory care setting from 2003 to 2011
Bibliographic record
Abstract
Background: Prior to the availability of biologic therapies, corticosteroids and narcotics were frequently used in inflammatory bowel disease (IBD) patients due to a paucity of disease modifying therapies. The increased accessibility to effective biologics for IBD over the last decade should be leading to less use of corticosteroids and narcotic medications. Methods: Data from the National Ambulatory Medical Care Survey (NAMCS) and National Hospital Ambulatory Medical Care Survey (NHAMCS) were used to examine visits of patients with IBD. Trends in corticosteroid and narcotic prescriptions were explored, and predictors of use were assessed using survey-weighted chi-square tests. Results: From 2003 to 2011, a total of 1119 patients with IBD had visits recorded in the NAMCS and NHAMCS databases. Although biologic prescriptions significantly increased from 3.3% in 2003–05 to 15.9% in 2009–11 (p=0.004), there was no significant decrease in corticosteroid or narcotic prescriptions during this same time frame (Figure 1). Figure 1. Frequency of medication prescriptions during ambulatory visits for IBD patients. Patients with IBD were less likely to receive narcotics (odds ratio (OR) = 0.38) when seeing a medical specialist compared to primary care physicians or surgeons. Conclusions: Despite the availability of more effective biologic therapies, prescriptions for corticosteroids and narcotics did not decline in IBD patients visiting U.S. ambulatory clinics and emergency departments from 2003 to 2011.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".