Current neurologic treatment and emerging therapies in CDKL5 deficiency disorder
Bibliographic record
Abstract
BACKGROUND: CDKL5 deficiency disorder (CDD) is associated with refractory infantile onset epilepsy, global developmental delay, and variable features that include sleep, behavioral disturbances, and movement disorders. Current treatment is primarily symptom-based and informed by experience in caring for this population. METHODS: We describe medication and non-medication approaches to treatment of epilepsy and additional key neurologic symptoms (sleep disturbances, behavioral issues, movement disorders, and swallowing dysfunction) in a cohort of 177 individuals meeting criteria for CDD, 154 evaluated at 4 CDKL5 Centers of Excellence in the USA and 40 identified through the NIH Natural History Study of Rett and Related Disorders. RESULTS: The four most frequently prescribed anti-seizure medications were broad spectrum, prescribed in over 50% of individuals. While the goal was not to ascertain efficacy, we obtained data from 86 individuals regarding response to treatment, with 2-week response achieved in 14-48% and sustained 3-month response in 5-36%, of those with known response. Additional treatments for seizures included cannabis derivatives, tried in over one-third of individuals, and clinical trial medications. In combination with pharmacological treatment, 50% of individuals were treated with ketogenic diet for attempted seizure control. Surgical approaches included vagus nerve stimulators, functional hemispherectomy, and corpus callosotomy, but numbers were too limited to assess response. Nearly one-third of individuals received pharmacologic treatment for sleep disturbances, 13% for behavioral dysregulation and movement disorders, and 43% had gastrostomy tubes. CONCLUSIONS: Treatment for neurologic features of CDD is currently symptom-based and empiric rather than CDD-specific, though clinical trials for CDD are emerging. Epilepsy in this population is highly refractory, and no specific anti-seizure medication was associated with improved seizure control. Ketogenic diet is commonly used in patients with CDD. While behavioral interventions are commonly instituted, information on the use of medications for sleep, behavioral management, and movement disorders is sparse and would benefit from further characterization and optimization of treatment approaches. The heterogeneity in treatment approaches highlights the need for systematic review and guidelines for CDD. Additional disease-specific and disease-modifying treatments are in development.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".