Health care resource utilization before and after perampanel initiation among patients with epilepsy in the United States
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study was to evaluate changes in health care resource utilization following the initiation of perampanel for the treatment of epilepsy in the United States. METHODS: Health care claims from Symphony Health's Integrated Dataverse database between December 2012 and November 2015 were analyzed. Patients newly initiated on perampanel, having ≥1 epilepsy (International Classification of Diseases, Ninth Revision, Clinical Modification [ICD-9-CM] code 345.xx, ICD-10-CM code G40.xxx) or nonfebrile convulsion (ICD-9-CM code 780.39, ICD-10-CM code R56.9) diagnosis, and having ≥6 months of baseline and observation periods were included. Patients <12 years old at perampanel initiation were excluded. RESULTS: Of the 2,508 perampanel patients included in the study, the mean [median] (±standard deviation [SD]) age was 35.8 [34] (±16.0) years and 56.2% were female. The mean [median] (±SD) observation duration was 459.8 [462] (±146.3) days in the postperampanel period. The postperampanel period was associated with significantly lower rates of all health care resource utilization outcomes than the pre-period. For the post- versus pre-period, perampanel users had 42.3 versus 53.8 overall hospitalizations per 100 person-years (rate ratio [RR] = 0.80, p < 0.001) and 1,240.2 versus 1,343.8 outpatient visits per 100 person-years (RR = 0.91, p < 0.001). Epilepsy-related hospitalizations and outpatient visits were 25.2 versus 33.6 per 100 person-years (RR = 0.76, p < 0.001) and 327.0 versus 389.0 per 100 person-years (RR = 0.84, p < 0.001), respectively. Additionally, a significantly lower rate of status epilepticus in the post-period (1.8 events per 100 person-years) was observed compared to the pre-period (4.4 events per 100 person-years; RR = 0.43, p < 0.001). The monthly time trend of hospitalizations showed an increasing trend leading up to the initiation of perampanel, after which the hospitalizations decreased steadily. SIGNIFICANCE: Use of perampanel for the treatment of epilepsy was associated with significant reduction in all-cause and epilepsy-related health care resource utilization, including hospitalizations, especially for status epilepticus, and outpatient visits.
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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 | 0.002 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".