Corticosteroid and Steroid Therapies in PANDAS: A Systematic Review of Efficacy and Safety
Bibliographic record
Abstract
Pediatric Autoimmune Neuropsychiatric Disorders Associated with Streptococcal Infections (PANDAS) is characterized by sudden neuropsychiatric symptoms, such as obsessive-compulsive disorder (OCD) and tics, following streptococcal infections. Among the treatments explored, corticosteroids like prednisone have been used for their immunosuppressive effects to reduce inflammation and autoimmune responses. However, the comparison between corticosteroids and other steroid treatments in PANDAS management is still a subject of clinical debate. Corticosteroids tend to provide short-term relief in managing acute flares but are often associated with symptom recurrence post-treatment, making them a less favorable long-term solution. This review evaluates the effectiveness of corticosteroids versus regular steroids, analyzing their role in reducing symptom severity, flare duration, and relapse rates in PANDAS patients. While corticosteroids are widely used for their ability to control inflammation during acute episodes, other steroids may offer varied efficacy and side-effect profiles. The need for further research remains crucial to establishing clearer, long-term treatment guidelines.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".