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Record W4403892521 · doi:10.1186/s12889-024-20441-9

Treatment outcome and its predictors among children with epilepsy on chronic follow-up in Ethiopia: a systematic review and meta-analysis

2024· review· en· W4403892521 on OpenAlexaboutno aff
Gebremariam Wulie Geremew, Yilkal Abebaw Wassie, Gebresilassie Tadesse, Setegn Fentahun, Abebaw Setegn Yazie, Sisay Sitotaw Anberbr, Gebremariam Genet, Abaynesh Fentahun Bekalu, Gashaw Sisay Chanie, Tekletsadik Tekleslassie Alemayehu

Bibliographic record

VenueBMC Public Health · 2024
Typereview
Languageen
FieldMedicine
TopicEpilepsy research and treatment
Canadian institutionsnot available
FundersUniversity of Gondar
KeywordsMedicineBiostatisticsMeta-analysisPublic healthEpidemiologyEpilepsyOutcome (game theory)Systematic reviewPediatricsMEDLINEEnvironmental healthPsychiatryInternal medicinePathology

Abstract

fetched live from OpenAlex

BACKGROUND: Seventy percent of epileptic patients may not experience seizures if they receive proper treatment with antiepileptic drugs (AEDs). However, many children and adolescents face poor seizure control (PSC). Therefore, the purpose of this review is to systematically and quantitatively summarize the pooled prevalence of PSC and its predictors among children with epilepsy in Ethiopia. METHODS: The following databases were used to conduct a thorough literature search: Africa Journal of the Online Library, Hinari, Google Scholar, PubMed, Science Direct, EMBASE, Cochrane Database, Sci-Hub, and Scopus. To evaluate the quality of the studies, Newcastle‒Ottawa Scale (NOS) checklists were utilized. The data on study characteristics and prevalence estimates were then combined via random effects meta-analysis, followed by subgroup and sensitivity analyses. Both visual and statistical analyses were employed to assess for any potential publication bias. RESULTS: This review analyzed a total of 12 main studies and reported that the overall prevalence of PSC was 42.42% (95% CI: 33.42-51.42). However, there was significant heterogeneity in the results based on the study region, design, and seizure-free period. The subgroup analysis revealed that the highest prevalence of PSC was found in Southern Nations, Nationalities, and Peoples' (SNNPs) studies (61.88%; 95% CI: 35.91-87.85), studies with a cross-sectional design (46.73%; 95% CI: 36.83-56.62), and studies with a seizure-free period < 6 months (44.69%; 95% CI: 34.51-54.86). However, the lowest prevalence was observed in the Amhara region (35.54%; 95% CI: 27.40-43.67), cohort studies (29.53%; 95% CI: 21.26-38.21), and studies with a seizure-free duration of six months or more (41.64%; 95% CI: 29.94-53.35). The results also revealed a significant correlation between PSC and medication nonadherence (4.64, 95% CI: 2.84-7.58), comorbidities (2.08, 95% CI: 1.01-4.26), and seizure type (3.59, 95% CI: 1.18-10.8). CONCLUSION: Based on this review, the findings suggest a notable prevalence of poorly controlled seizures (PSC) among children with epilepsy who are receiving antiepileptic drugs (AEDs) in Ethiopian outpatient epilepsy clinics. Seizures of tonic‒clonic status, comorbidities, and medication nonadherence were associated with poor seizure control.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.011
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.017
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0110.025
Bibliometrics0.0050.006
Science and technology studies0.0010.000
Scholarly communication0.0030.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.168
GPT teacher head0.424
Teacher spread0.255 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2024
Admission routes1
Has abstractyes

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