Propranolol and central nervous system function: potential implications for paediatric patients with infantile haemangiomas
Bibliographic record
Abstract
Given its improved safety profile compared with systemic corticosteroids, propranolol has become the mainstay treatment of infantile haemangioma (IH) worldwide. There is evidence, mainly from adult volunteer studies, that propranolol use is associated with central nervous system (CNS) effects. Impairment to short- and long-term memory, psychomotor function, sleep quality and mood with relatively low doses and durations of treatment have been reported. The exact magnitude of CNS effects resulting from propranolol use, especially in the early developmental stages and for prolonged periods of use, is not currently known. These effects may not be readily recognizable and require specialized assessment of cognitive function not routinely performed. Furthermore, there may be a delay between exposure and cognitive defects. The evidence to date provides a strong rationale to proceed with caution when prescribing propranolol for IH: treatment should be used only when indicated (in the presence of ulceration, impairment of a vital function or risk of permanent disfigurement) and for a limited duration, and the benefits of treatment should be weighed carefully against potential adverse events before treatment is initiated. This narrative review describes the evidence for an effect of propranolol use on CNS function from volunteer and patient studies, including IH.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".