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Record W4383098839 · doi:10.2196/45986

A Bespoke Electronic Health Journal for Monitoring Response to Botulinum Toxin in Treatment of Cervical Dystonia: Open-Label Observational Study of User Experience

2023· article· en· W4383098839 on OpenAlexvenueno aff
C. Edwards, Rebecca Borton, Anita Ross, Fiona Molloy

Bibliographic record

VenueJMIR Formative Research · 2023
Typearticle
Languageen
FieldMedicine
TopicBotulinum Toxin and Related Neurological Disorders
Canadian institutionsnot available
FundersIpsen
KeywordsCervical dystoniaMedicineBotulinum toxinObservational studyDysgeusiaBespokePhysical therapyInternal medicineSurgeryAdverse effect

Abstract

fetched live from OpenAlex

BACKGROUND: The mainstay of treatment for cervical dystonia (CD) is regular botulinum toxin injections every 3-4 months. Clinical evaluation of response is dependent on the patient's recall of how well symptoms responded to the previous injection. A mobile health app could assist both patients and health care professionals to monitor treatment benefits and side effects to assist with the selection of muscle and toxin dose to be injected at the next visit. The DystoniaDiary is a bespoke electronic health journal for monitoring symptoms of CD and response to treatment. OBJECTIVE: The objective of this study was to assess the acceptability and utility of the DystoniaDiary in patients with CD treated with botulinum toxins as part of their usual care. METHODS: In this open-label, single-center, single-arm observational study, patients attending a botulinum toxin injection clinic were invited to download the DystoniaDiary app. Patients selected up to 3 of their most troublesome CD symptoms (from a predefined list) and were prompted every 3 days to rate the control of these symptoms on a scale from 0 (very badly) to 100 (very well). Dates of onset and wearing off of response to injected botulinum toxin and responses to the Cervical Dystonia Impact Profile (CDIP-58) questionnaire at baseline and week 6 were also recorded in the app. RESULTS: A total of 34 patients installed DystoniaDiary. Twenty-five patients (25/34, 74%) recorded data for ≥12 weeks and 21 patients (21/34, 62%) for ≥16 weeks. Median time between the first and last data input was 140 days with a median of 13 recordings per patient. User experience questionnaires at weeks 4 and 12 (20 respondents) indicated that the majority of respondents found the DystoniaDiary app easy to install and use, liked using it, would recommend it to others (19/20), and wished to continue using it (16/20). A smaller proportion indicated that the DystoniaDiary gave a greater sense of control in managing their CD (13/20). There was interindividual variation in patients' perceptions of control of their symptoms after botulinum toxin injection. Response to treatment was apparent in the symptom control scores for some patients, whereas the severity of other patients' symptoms did not appear to change after treatment. CONCLUSIONS: This observational study demonstrated that the DystoniaDiary app was perceived as useful and acceptable for a large proportion of this sample of patients with CD attending a botulinum toxin clinic. Patients with CD appear to be willing to regularly record symptom severity for at least the duration of a botulinum injection treatment cycle (12-16 weeks). This app may be useful in monitoring and optimizing individual patient responses to botulinum toxin injection.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.005
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.015
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.330
GPT teacher head0.541
Teacher spread0.211 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2023
Admission routes1
Has abstractyes

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