Evidence map›Paper›PMID 31229939›Full record

ArticleSeizure2019

Smartphone EEG and remote online interpretation for children with epilepsy in the Republic of Guinea: Quality, characteristics, and practice implications.

Jennifer A Williams, Fodé Abass Cisse, Mike Schaekermann, Foksouna Sakadi, Nana Rahamatou Tassiou, Gladia C Hotan, Aissatou Kenda Bah, Abdoul Bachir Djibo Hamani, Andrew Lim, Edward C W Leung and 11 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Seizure, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

12 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. A comprehensive guide to digital neurology. An update on current development on digital neurology derived from the Digital Neuro Hub project.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2025
    Review
  3. Review
  4. Article
  5. E = mcEpilepsia open · 2024
    Article
  6. Article
  7. Article
  8. EEG Data Quality in Real-World Settings: Examining Neural Correlates of Attention in School-Aged Children.Mind, brain and education : the official journal of the International Mind, Brain, and Education Society · 2022
    Article
  9. Article
  10. Article
  11. COVID-19 response in low- and middle-income countries: Don't overlook the role of mobile phone communication.International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases · 2020
    Review
  12. Article
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

21 authors.

Jennifer A WilliamsDepartment of Neurology, Massachusetts General Hospital, Boston, MA, USA; Division of Clinical Neurophysiology, Massachusetts General Hospital, Boston, MA, USA.
Fodé Abass CisseDepartment of Neurology, Ignace Deen Hospital, Conakry, Guinea.
Mike SchaekermannSchool of Computer Science, University of Waterloo, ON, Canada.
Foksouna SakadiDepartment of Neurology, Ignace Deen Hospital, Conakry, Guinea.
Nana Rahamatou TassiouDepartment of Neurology, Ignace Deen Hospital, Conakry, Guinea.
Gladia C HotanDepartment of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA.
Aissatou Kenda BahDepartment of Neurology, Ignace Deen Hospital, Conakry, Guinea.
Abdoul Bachir Djibo HamaniDepartment of Neurology, Ignace Deen Hospital, Conakry, Guinea.
Andrew LimDepartment of Neurology, University of Toronto, ON, Canada; Department of Neurology, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.
Edward C W LeungDivision of Pediatric Neurology, Department of Pediatrics and Child Health, University of Manitoba, Winnipeg, MB, Canada.
Tadeu A FantaneanuDivision of Neurology, Department of Medicine, University of Ottawa, ON, Canada.
Tracey A MilliganDepartment of Neurology, Brigham and Women's Hospital, Boston, MA, USA.
Vidita KhatriDepartment of Neurology, Brigham and Women's Hospital, Boston, MA, USA.
Daniel B HochDepartment of Neurology, Massachusetts General Hospital, Boston, MA, USA; Division of Clinical Neurophysiology, Massachusetts General Hospital, Boston, MA, USA.
Manav V VyasDepartment of Neurology, University of Toronto, ON, Canada; Department of Neurology, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.
Alice D LamDepartment of Neurology, Massachusetts General Hospital, Boston, MA, USA; Division of Clinical Neurophysiology, Massachusetts General Hospital, Boston, MA, USA.
Joseph M CohenDivision of Clinical Neurophysiology, Massachusetts General Hospital, Boston, MA, USA.
Andre C VogelNeurological Clinical Research Institute, Massachusetts General Hospital, Boston, MA, USA.
Edith LawSchool of Computer Science, University of Waterloo, ON, Canada.
Farrah J MateenDepartment of Neurology, Massachusetts General Hospital, Boston, MA, USA; Neurological Clinical Research Institute, Massachusetts General Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA. Electronic address: fmateen@mgh.harvard.edu.
Guinea Epilepsy Project

Funding

CLINICAL UTILITY OF A SMARTPHONE-BASED EEG SYSTEM FOR PEOPLE WITH EPILEPSY IN BHUTANR21NS098886 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI MATEEN, FARRAH JASMINE · 2017 to 2018
$396k
NINDS NIH HHS R21 NS098886
6 · The paper itself

Abstract

purposeChildren with epilepsy in low-income countries often go undiagnosed and untreated. We examine a portable, low-cost smartphone-based EEG technology in a heterogeneous pediatric epilepsy cohort in the West African Republic of Guinea.

methodsChildren with epilepsy were recruited at the Ignace Deen Hospital in Conakry, 2017. Participants underwent sequential EEG recordings with an app-based EEG, the Smartphone Brain Scanner-2 (SBS2) and a standard Xltek EEG. Raw EEG data were transmitted via Bluetooth

results97 children meeting the International League Against Epilepsy's definition of epilepsy (49 male; mean age 10.3 years, 29 untreated with an antiepileptic drug; 0 with a prior EEG) were enrolled. Epileptiform discharges were detected on 21 (25.3%) SBS2 and 31 (37.3%) standard EEG recordings. The SBS2 had a sensitivity of 51.6% (95%CI 32.4%, 70.8%) and a specificity of 90.4% (95%CI 81.4%, 94.4%) for all types of epileptiform discharges, with positive and negative predictive values of 76.2% and 75.8% respectively. For generalized discharges, the SBS2 had a sensitivity of 43.5% with a specificity of 96.2%.

conclusionsThe SBS2 has a moderate sensitivity and high specificity for the detection of epileptiform abnormalities in children with epilepsy in this low-income setting. Use of the SBS2+crowdEEG platform permits specialist input for patients with previously poor access to clinical neurophysiology expertise.

Indexed as

AdolescentChildChild, PreschoolElectroencephalographyEpilepsyFemaleGuineaHumansInfantMaleMobile ApplicationsNeurophysiological MonitoringSensitivity and SpecificitySmartphoneTelemedicineAfricaEEGmHealthPediatric epilepsy

Identifiers

PMID31229939
PMCPMC6783351

What OpenQuestion holds

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Registered trials

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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.