Assessment and treatment of childhood epilepsy in Haiti
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Bibliographic record
Abstract
OBJECTIVE: The global burden of pediatric epilepsy is disproportionately concentrated in low- and middle-income countries (LMICs). However, little is known about the effectiveness of current treatment programs in this setting. We present the outcomes of children who were assessed and treated at the Clinique D'Épilepsie de Port-au-Prince (CLIDEP), the only pediatric epilepsy referral center in Haiti. METHODS: A 10-year retrospective review of children consecutively assessed and treated at CLIDEP was performed. The primary outcome was seizure control following treatment for epilepsy. The secondary outcome was an accurate determination of the diagnosis of epilepsy. A data-driven principle component regression (PCR) analysis was used to identify variables associated with outcomes of interest. RESULTS: Of the 812 children referred for evaluation, most children (82%) underwent electroencephalography to investigate a possible epilepsy diagnosis. Very few children (7%) underwent cranial imaging. Although many patients were lost to follow-up (24%), most children who returned to clinic had less frequent seizures (51%) and compliance with medication was relatively high (79%). Using PCR, we identified a patient phenotype that was strongly associated with poor seizure control which had strong contributions from abnormal neurological examination, higher number of antiepileptic drugs, comorbid diagnoses, epileptic encephalopathy or epilepsy syndrome, and developmental delay. Head circumference also contributed to epilepsy outcomes in Haiti with smaller head sizes being associated with a poor seizure outcome. A dissociable phenotype of febrile seizures, suspected structural abnormality, epileptic encephalopathy or epilepsy syndrome, and higher seizure frequency was associated with a diagnosis of epilepsy. SIGNIFICANCE: We describe the current landscape of childhood epilepsy in Haiti with an emphasis on diagnosis, treatment and outcomes. The findings provide evidence for the effectiveness of programs aimed at the diagnosis and management of epilepsy in LMICs and may inform the allocation of resources and create more effective referral structures.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it