Evidence map›Paper›PMID 36401798›Full record

ArticleEpilepsia2023

Flexible realistic simulation of seizure occurrence recapitulating statistical properties of seizure diaries.

Daniel M Goldenholz, M Brandon Westover

Open access · greenAbstract read
In one paragraph

Article in Epilepsia, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 1 pooled it
3.0field-weighted citation impact, top 8% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

21 citing papers in PubMed, 1 synthesis or guideline pooled it, 22 citations in OpenAlex.

  1. Pooled it
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  7. Review
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  9. The Road Not Taken: Misclassifying an Anti-Seizure Medication as a Failure.Annals of clinical and translational neurology · 2025
    Article
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  19. Prospective validation of a seizure diary forecasting falls short.medRxiv : the preprint server for health sciences · 2024
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Daniel M GoldenholzDepartment of Neurology, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA.ORCID 0000-0002-8370-2758
M Brandon WestoverDepartment of Neurology, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA.ORCID 0000-0003-4803-312X
Beth Israel Deaconess Medical Center · US

Funding

Institutional Career Development CoreKL2TR002542 · NCATS · HARVARD MEDICAL SCHOOL · PI BREDELLA, MIRIAM ANTOINETTE, RUTKOVE, SEWARD B. · 2018 to 2022
$8.7M
Data-Driven Sleep Biomarkers of Brain Health, Heart Health, and MortalityR01HL161253 · NHLBI · BETH ISRAEL DEACONESS MEDICAL CENTER · PI CLIFFORD, GARI DAVID, MIGNOT, EMMANUEL J · 2022 to 2025
$8.3M
Comparative Safety of Seizure Prophylaxis within the Medicare ProgramR01AG073410 · NIA · MASSACHUSETTS GENERAL HOSPITAL · PI Lidia Maria Veras Rocha de Moura · 2021 to 2026
$4.1M
Integrative Motor Activity Biomarker for the Risk of Alzheimer's RiskRF1AG064312 · NIA · BRIGHAM AND WOMEN'S HOSPITAL · PI HU, KUN · 2019 to 2019
$3.6M
Multimodal Network Connectivity Architecture (MOCA) of the Brain and its Role in the Recovery of Consciousness in Comatose Cardiac Arrest PatientsR01NS102574 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI GREER, DAVID MATTHEW, WU, ONA · 2018 to 2022
$3.4M
Investigation of Sleep in the Intensive Care Unit (ICU-SLEEP)R01NS102190 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI WESTOVER, MICHAEL BRANDON · 2018 to 2022
$3.2M
Prospective Validation of Neurophysiologic Outcome Prediction in Acute Brain InjuryR01NS126282 · NINDS · BETH ISRAEL DEACONESS MEDICAL CENTER · PI Aaron F Struck, Michael Brandon Westover · 2023 to 2026
$2.9M
Big Data and Deep Learning for the Interictal-Ictal-Injury ContiuumR01NS107291 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI WESTOVER, MICHAEL BRANDON · 2018 to 2022
$2.8M
Establishing a Brain Health Index from the Sleep ElectroencephalogramRF1NS120947 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI CASH, SYDNEY S, THOMAS, ROBERT JOSEPH · 2021 to 2021
$2.4M
Non-Invasive Seizure Forecasting System Using E-Diaries, Internal and External FactorsK23NS124656 · NINDS · BETH ISRAEL DEACONESS MEDICAL CENTER · PI Daniel M Goldenholz · 2022 to 2026
$954k
NCATS NIH HHS KL2 TR002542NHLBI NIH HHS R01 HL161253NIA NIH HHS R01 AG073410NIA NIH HHS RF1 AG064312NINDS NIH HHS K23 NS124656NINDS NIH HHS KL2TR002542NINDS NIH HHS L30 NS113085NINDS NIH HHS R01 NS102190NINDS NIH HHS R01 NS102574NINDS NIH HHS R01 NS107291NINDS NIH HHS R01 NS126282NINDS NIH HHS RF1 NS120947
6 · The paper itself

Abstract

objectiveA realistic seizure diary simulator is currently unavailable for many research needs, including clinical trial analysis and evaluation of seizure detection and seizure-forecasting tools. In recent years, important statistical features of seizure diaries have been characterized. These include (1) heterogeneity of individual seizure frequencies, (2) the relation between average seizure rate and standard deviation, (3) multiple risk cycles, (4) seizure clusters, and (5) limitations on inter-seizure intervals. The present study unifies these features into a single model.

methodsOur approach, Cyclic Heterogeneous Overdispersed Clustered Open-source L-relationship Adjustable Temporally limited E-diary Simulator (CHOCOLATES) is based on a hierarchical model centered on a gamma Poisson generator with several modifiers. This model accounts for the aforementioned statistical properties. The model was validated by simulating 10 000 randomized clinical trials (RCTs) of medication to compare with 23 historical RCTs. Metrics of 50% responder rate (RR50) and median percent change (MPC) were evaluated. We also used CHOCOLATES as input to a seizure-forecasting tool to test the flexibility of the model. We examined the area under the receiver-operating characteristic (ROC) curve (AUC) for test data with and without cycles and clusters.

resultsThe model recapitulated typical findings in 23 historical RCTs without the necessity of introducing an additional "placebo effect." The model produced the following RR50 values: placebo: 17 ± 4%; drug 38 ± 5%; and the following MPC values: placebo: 13 ± 6%; drug 40 ± 4%. These values are similar to historical data: for RR50: placebo, 21 ± 10%, drug: 43 ± 13%; and for MPC: placebo: 17 ± 10%, drug: 41 ± 11%. The seizure forecasts achieved an AUC of 0.68 with cycles and clusters, whereas without them the AUC was 0.51. SIGNIFICANCE: CHOCOLATES represents the most realistic seizure occurrence simulator to date, based on observations from thousands of patients in different contexts. This tool is open source and flexible, and can be used for many applications, including clinical trial simulation and testing of seizure-forecasting tools.

Indexed as

Epilepsy, GeneralizedSeizuresComputer SimulationForecastingHumansepilepsyseizure diarysimulationstatistics

Identifiers

PMID36401798
PMCPMC9905290
OpenAlexW4309409155

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.