Economic and Clinical Burden of Herpes Zoster Among Patients With Inflammatory Bowel Disease in the United States
Bibliographic record
Abstract
Abstract Background Patients with ulcerative colitis (UC) or Crohn’s disease (CD) are at increased risk of herpes zoster (HZ); however, relevant cost and healthcare resource utilization (HCRU) data are limited. Methods We estimated HCRU (hospitalization, emergency department [ED], and outpatient visits) and costs in patients with UC or CD, with and without HZ, using administrative claims data (October 2015–February 2020). HCRU and costs (2020 US dollars) were compared at 1 month, 1 quarter, and 1 year after the index date, using propensity score adjustment and generalized linear models. Results In total, 20 948 patients were included: UC+/HZ+ (n = 431), UC+/HZ– (n = 10 285), CD+/HZ+ (n = 435), and CD+/HZ– (n = 9797). Patients with HZ had higher all-cause HCRU rates and all-cause total healthcare costs relative to those without HZ. In the first month, adjusted incidence rate ratios (aIRRs) for hospitalizations and ED visits for patients with UC and HZ compared with UC alone were 2.87 (95% confidence interval [CI], 1.93–4.27) and 2.66 (95% CI,1.74–4.05), respectively; for those with CD and HZ, aIRRs were 3.34 (95% CI, 2.38–4.70) and 3.31 (95% CI, 2.32–4.71), respectively, compared with CD alone (all P < .001). Adjusted cost differences in UC and CD cohorts with HZ over the first month were $2189 and $3774, respectively, chiefly driven by higher inpatient costs. The incremental impact on HCRU and costs in cohorts with HZ predominantly occurred during the first quarter following diagnosis. Conclusions HZ is associated with increased HCRU and costs in patients with UC and CD, especially shortly after diagnosis.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".