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Record W4388902364 · doi:10.1080/13696998.2023.2286778

Real-world clinical management of individuals with Rett syndrome: a physician survey

2023· article· en· W4388902364 on OpenAlexaff
Damian M. May, Jeffrey L. Neul, Ambika Satija, Wendy Y. Cheng, Neema Lema, Andra Boca, Patrick Lefèbvre, J. Eric Piña-Garza

Bibliographic record

VenueJournal of Medical Economics · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics and Neurodevelopmental Disorders
Canadian institutionsGroup for Research in Decision Analysis
FundersACADIA Pharmaceuticals
KeywordsMedicineRett syndromeFamily medicinePediatricsPhysical therapy

Abstract

fetched live from OpenAlex

Background: Rett syndrome (RTT) is a severe neurodevelopmental disorder.Management strategies are heterogeneous with no clear definition of success.This study describes physician decision-making regarding diagnosis, therapeutic goals, and management strategies to better understand RTT clinical management in the US.Methods: This study was conducted among practicing physicians, specifically neurologists and pediatricians in the US with experience treating 2 individuals with RTT, including 1 individuals within the past two years.In-depth interviews with five physicians informed survey development.A cross-sectional survey was then conducted among 100 physicians.Results: Neurologists had treated more individuals with RTT (median: 12 vs. 5, p < 0.001) than pediatricians throughout their career and were more likely to report being "very comfortable" managing RTT (31 vs. 4%, p < 0.001).Among physicians with experience diagnosing RTT (93%), most evaluated symptoms (91%) or used genetic testing (86%) for RTT diagnoses; neurologists used the 2010 consensus diagnostic criteria more than pediatricians (54 vs. 29%; p 0.012).Improving the quality of life (QOL) of individuals with RTT was the most important therapeutic goal among physicians, followed by improving caregivers' QOL.Most physicians used clinical practice guidelines to monitor the progress of individuals with RTT, although neurologists relied more on clinical scales than pediatricians.Among all physicians, the most commonly treated symptoms included behavioral issues, epilepsy/seizures, and feeding issues.Management strategies varied by symptom, with referral to appropriate specialists being common across symptoms.A large proportion of physicians (37%) identified the lack of novel therapies and reliance on symptom-specific management as an unmet need.Conclusion: Although most physicians had experience and were comfortable diagnosing and treating individuals with RTT, better education and support among pediatricians is warranted.Additionally, novel treatments that target multiple symptoms associated with RTT could reduce the burden and improve the QOL of individuals with RTT and their caregivers.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.221
Threshold uncertainty score0.331

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.029
GPT teacher head0.310
Teacher spread0.281 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations5
Published2023
Admission routes1
Has abstractyes

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