Purpose: To characterize the reasons, extent, and impact of traditional medicine use among people with epilepsy (PWE) in the Republic of Guinea.Methods: Guinea is a low-income country in sub-Saharan Africa (SSA) with limited healthcare resources. PWE and their caregivers were seen at a public referral hospital in Conakry, the capital city, where they completed semi-structured interviews with physicians regarding their beliefs about epilepsy, medical care, and engagement with traditional healers.Results: Of 132 participants (49% children, 44% female, 55% with a university-educated head of household), 79% had seen a traditional healer, and 71% saw a traditional healer before seeing a medical provider for their epilepsy. Participants were treated by a traditional healer for a mean of 39 months before seeing a medical provider. By contrast, 58% of participants reported taking AEDs regularly, 46% reported having undergone a head CT, 58% reported having had an electroencephalogram, and 4% reported having had a brain MRI. Conclusions:Traditional healers in Guinea provide frontline care for PWE in Guinea with considerable delays in AED initiation, even among a cohort of PWE actively seeking medical care. Engaging with these healers is critical for both influencing community perceptions and appropriately managing epilepsy throughout the country.

Children 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. Methods: : Children 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 ™ connection to an Android ™ tablet and uploaded for remote EEG specialist review and reporting via a new, secure web-based reading platform, crowdEEG. The results were compared to same-visit Xltek 10-20 EEG recordings for identification of epileptiform and nonepileptiform abnormalities. Results: : 97 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%. Conclusions: : The 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.

There is an urgent need to improve the standard of care for PWE in Guinea. Several missed opportunities were identified, including low use of AEDs and high use of traditional medicines, particularly in children. Targeted programs should be developed to prevent unintentional injury and improve seizure control.

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Background and purpose Epilepsy is most common in lower‐income settings where access to electroencephalography (EEG) is generally poor. A low‐cost tablet‐based EEG device may be valuable, but the quality and reproducibility of the EEG output are not established. Methods Tablet‐based EEG was deployed in a heterogeneous epilepsy cohort in the Republic of Guinea (2018–2019), consisting of a tablet wirelessly connected to a 14‐electrode cap. Participants underwent EEG twice (EEG1 and EEG2), separated by a variable time interval. Recordings were scored remotely by experts in clinical neurophysiology as to data quality and clinical utility. Results There were 149 participants (41% female; median age 17.9 years; 66.6% ≤21 years of age; mean seizures per month 5.7 ± SD 15.5). The mean duration of EEG1 was 53 ± 12.3 min and that of EEG2 was 29.6 ± 12.8 min. The mean quality scores of EEG1 and EEG2 were 6.4 [range, 1 (low) to 10 (high); both medians 7.0]. A total of 44 (29.5%) participants had epileptiform discharges (EDs) at EEG1 and 25 (16.8%) had EDs at EEG2. EDs were focal/multifocal (rather than generalized) in 70.1% of EEG1 and 72.5% of EEG2 interpretations. A total of 39 (26.2%) were recommended for neuroimaging after EEG1 and 22 (14.8%) after EEG2. Of participants without EDs at EEG1 (n = 53, 55.8%), seven (13.2%) had EDs at EEG2. Of participants with detectable EDs on EEG1 (n = 23, 24.2%), 12 (52.1%) did not have EDs at EEG2. Conclusions Tablet‐based EEG had a reproducible quality level on repeat testing and was useful for the detection of EDs. The incremental yield of a second EEG in this setting was ~13%. The need for neuroimaging access was evident.