Clinical characteristics of children with epilepsy managed at an urban hospital in Africa: a retrospective study
Bibliographic record
Abstract
Background Most children with epilepsy reside in resource-limited regions such as sub-Saharan Africa, where the majority of studies have been conducted in rural areas with limited investigations. Medical records from children with epilepsy seen at an urban hospital in Kenya were examined to provide a comprehensive description of epilepsy in children from this hospital. Methods A retrospective observational study was conducted which involved reviewing medical records of 426 epilepsy patients (260 males and 166 females) aged 0 - 18 years, seen at Aga Khan University Hospital, Nairobi, Kenya between February 2011 and December 2014. Results The most frequent age at presentation; documented in 29% was in infancy. Generalized seizures due to structural brain abnormalities were the most common form of epilepsy (28%). Lennox-Gastaut Syndrome was the most common electroclinical syndrome (7%). Focal seizures and focal seizures with loss of awareness were identified in 12% of the population. There were no cases of childhood absence epilepsy in this group. Brain atrophy was the most common MRI finding, occurring in a fifth of the population (20%), while cystic encephalomalacia occurred in 13%. Half (50%) of all EEG recordings performed for this cohort were abnormal. Generalized seizures due to structural brain abnormalities and Lennox-Gastaut Syndrome (LGS) were significant predictors of a treatment history of three or more AEDs. At the conclusion of the review period, 16% of the patients had not visited the clinic for more than 12 months and were considered to be lost to follow-up. Conclusion The highest frequency of epilepsy cases was documented in children less than one year of age. Generalized seizures due to structural abnormalities and Lennox-Gastaut syndrome were the most common seizure type and syndrome. Improvement of public awareness of different types of seizures in children may increase identification of children with childhood absence epilepsy.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".