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Record W2920390048 · doi:10.3390/jcm8030317

Effectiveness of the Botulinum Toxin for Treating Sialorrhea in Patients with Parkinson’s Disease: A Systematic Review

2019· review· en· W2920390048 on OpenAlexaboutno aff
Juan Antonio Ruiz‐Roca, Eduardo Pons-Fuster, Pía López‐Jornet

Bibliographic record

VenueJournal of Clinical Medicine · 2019
Typereview
Languageen
FieldMedicine
TopicBotulinum Toxin and Related Neurological Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsSialorrheaMedicineCochrane LibraryBotulinum toxinMEDLINESystematic reviewMeta-analysisInternal medicineSurgery

Abstract

fetched live from OpenAlex

The main objective was to assess the efficacy of botulinum toxin-based treatment for sialorrhea in adult patients with Parkinson's disease. The search was performed by using the Medline-PubMed, EMBASE and Cochrane Library databases from January 2000⁻December 2017, in English/Spanish in patients with Parkinson's disease and sialorrhea. The methodological quality of trials was carried out by following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) criteria and the Newcastle⁻Ottawa Scale (NOS). Finally, a total of 21 articles were identified as fulfilling the inclusion criteria. There is no consensus regarding the site of injection of the toxin (single or multiple points), toxin dose or follow-up period. In all cases there was a reduction of sialorrhea. Treatment safety increases with the use of ultrasonography. Effects approximately occur at one week post-injection and for 3⁻5 months. Botulinum toxin is an effective therapeutic strategy or option in treating sialorrhea in adult patients with Parkinson's disease. More studies with a better design, larger samples and a longer follow-up period are required to confirm these data.

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)0.006
metaresearch head score (Gemma)0.021
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.036
Threshold uncertainty score0.987

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0100.002
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.065
GPT teacher head0.413
Teacher spread0.348 · 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.

Study designSystematic review
Domainnot available
GenreReview

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

Citations38
Published2019
Admission routes1
Has abstractyes

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