ArticleRisk management and healthcare policy2025
Epidemiology and Burden of Illness of Lennox-Gastaut Syndrome in Taiwan: A Retrospective Cohort Study.
Article in Risk management and healthcare policy, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Global trends in epilepsy and the Chinese experience: Epidemiological transitions, underlying mechanisms, and integrated strategies (1990-2021).Neuroprotection (Chichester, England) · 2026Review
- Taiwan's National Health Insurance Research Database (NHIRD): in the Era of Artificial Intelligence, Causal Inference, and Data Security.Clinical epidemiology · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: Examine the epidemiology and burden of illness of patients with Lennox-Gastaut syndrome (LGS) in Taiwan. Methods: The National Health Insurance Database (NHID) was used, complemented by the Chang Gung Research Database (CGRD). Confirmed LGS was defined by International Classification of Diseases-10 (ICD-10) LGS codes or ≥1 rufinamide prescription; probable LGS was defined as patients aged ≤10 years when receiving ≥3 antiseizure medications (ASMs), with ICD-9/10 codes for developmental delay. Independent clinical review/validation of all LGS cases in the CGRD was conducted. Prevalence, incidence, time to treatment/LGS diagnosis, hospitalizations, costs (US dollars), ASM usage, and mortality were assessed. For the NHID, a positive predicted value (PPV) was calculated from the CGRD validation step to adjust prevalence/incidence estimates. Results: In the NHID, 190 patients with confirmed LGS were identified. In 2018, PPV-adjusted prevalence was 2.4, 0.6, and 10.2 per 100,000 people and PPV-adjusted incidence was 0.6, 0.2, and 2.4 per 100,000 person-years in the total, adult, and pediatric populations, respectively. Of 92 (48%) hospitalized patients, 22 (24%) had ≥3 hospitalizations/year. Mean (standard deviation [SD]) time to treatment and LGS diagnosis were 12.3 (26.5) and 110.1 (54.7) months. Mean length of stay was around 12 days. Most hospitalizations (96%) were epilepsy related. Mean (SD) hospitalization cost was $237 ($216) per day. Mean (SD) total inpatient and outpatient costs were $5800 ($817) and $2667 ($132), respectively, per patient per year (PPPY); medication in hospital and ASM costs were $1910 ($108) and $1614 ($93) PPPY. Most prescribed ASMs were valproate (89%), levetiracetam (83%), clonazepam (69%), clobazam (68%), and topiramate (65%). Mortality was 0.01 deaths per 100,000 people in 2018. Conclusion: Although prevalence and incidence of LGS in Taiwan were lower than in other countries, the multifaceted burden of illness in LGS is highlighted herein. Reduced hospitalizations through better epilepsy control may reduce LGS expenditure.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.