Evidence map›Paper›PMID 28768851›Full record

ArticleNeurology2017

Underestimation of sudden deaths among patients with seizures and epilepsy.

Orrin Devinsky, Daniel Friedman, Jocelyn Y Cheng, Ellen Moffatt, Anthony Kim, Zian H Tseng

Open access · bronzeAbstract read
In one paragraph

Article in Neurology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed, 1 pooled it
7.1field-weighted citation impact, top 2% 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

32 citing papers in PubMed, 1 synthesis or guideline pooled it, 79 citations in OpenAlex.

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  17. Mortality among People with Epilepsy: A Retrospective Nationwide Analysis from 2016 to 2019.International journal of environmental research and public health · 2021
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors at 1 institution.

Orrin DevinskyFrom the Department of Neurology (O.D., D.F., J.Y.C.), Epilepsy Center, NYU School of Medicine; and Department of Pathology (E.M.), Department of Neurology (A.K.), and Electrophysiology and Arrhythmia Service (Z.H.T.), Department of Medicine, UCSF School of Medicine. od4@nyu.edu.
Daniel FriedmanFrom the Department of Neurology (O.D., D.F., J.Y.C.), Epilepsy Center, NYU School of Medicine; and Department of Pathology (E.M.), Department of Neurology (A.K.), and Electrophysiology and Arrhythmia Service (Z.H.T.), Department of Medicine, UCSF School of Medicine.
Jocelyn Y ChengFrom the Department of Neurology (O.D., D.F., J.Y.C.), Epilepsy Center, NYU School of Medicine; and Department of Pathology (E.M.), Department of Neurology (A.K.), and Electrophysiology and Arrhythmia Service (Z.H.T.), Department of Medicine, UCSF School of Medicine.
Ellen MoffattFrom the Department of Neurology (O.D., D.F., J.Y.C.), Epilepsy Center, NYU School of Medicine; and Department of Pathology (E.M.), Department of Neurology (A.K.), and Electrophysiology and Arrhythmia Service (Z.H.T.), Department of Medicine, UCSF School of Medicine.
Anthony KimFrom the Department of Neurology (O.D., D.F., J.Y.C.), Epilepsy Center, NYU School of Medicine; and Department of Pathology (E.M.), Department of Neurology (A.K.), and Electrophysiology and Arrhythmia Service (Z.H.T.), Department of Medicine, UCSF School of Medicine.
Zian H TsengFrom the Department of Neurology (O.D., D.F., J.Y.C.), Epilepsy Center, NYU School of Medicine; and Department of Pathology (E.M.), Department of Neurology (A.K.), and Electrophysiology and Arrhythmia Service (Z.H.T.), Department of Medicine, UCSF School of Medicine.
Indiana University School of Medicine

Funding

Comprehensive autopsy characterization of sudden cardiac deathR01HL102090 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI TSENG, ZIAN H · 2010 to 2014
$2.8M
NHLBI NIH HHS R01 HL102090
6 · The paper itself

Abstract

objectiveTo determine the definite and potential frequency of seizures and epilepsy as a cause of death (COD) and how often this goes unrecognized.

methodsProspective determination of seizures or epilepsy and final COD for individuals aged 18-90 years with out-of-hospital sudden cardiac deaths (SCDs) from the population-based San Francisco POST SCD Study. We compared prospective seizure or epilepsy diagnosis and final COD as adjudicated by a multidisciplinary committee (pathologists, electrophysiologists, and a vascular neurologist) vs retrospective adjudication by 2 epileptologists with expertise in seizure-related mortality.

resultsOf 541 SCDs identified during the 37-month study period (mean age 62.8 years, 69% men), 525 (97%) were autopsied; 39/525 (7.4%) had seizures or epilepsy (mean age: 58 years, range: 27-92; 67% men), comprising 17% of 231 nonarrhythmic sudden deaths. The multidisciplinary team identified 15 cases of epilepsy, 6 sudden unexpected deaths in epilepsy (SUDEPs), and no deaths related to acute symptomatic seizures. The epileptologists identified 25 cases of epilepsy and 8 definite SUDEPs, 10 possible SUDEPs, and 5 potential cases of acute symptomatic seizures as a COD.

conclusionsAmong the 25 patients identified with epilepsy by the epileptologists, they found definite or possible SUDEP in 72% (18/25) vs 24% (6/25) by the multidisciplinary group (6/15 cases they identified with epilepsy). The epileptologists identified acute symptomatic seizures as a potential COD in 5/14 patients with alcohol-related seizures. Epilepsy is underdiagnosed among decedents. Among patients with seizures and epilepsy who die suddenly, seizures and SUDEP often go unrecognized as a potential or definite COD.

Indexed as

AdolescentAdultAgedAged, 80 and overAutopsyCause of DeathData Interpretation, StatisticalDeath, Sudden, CardiacEpilepsyFemaleHumansMaleMiddle AgedProspective StudiesRetrospective StudiesSan Francisco

Identifiers

PMID28768851
PMCPMC5577966
OpenAlexW2740631934

What OpenQuestion holds

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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.