MétaCan
Menu
Back to cohort
Record W4400582534 · doi:10.3233/jpd-240088

Unmet Need in Early-Onset Parkinson’s Disease: Deep Brain Stimulation and Pregnancy

2024· review· en· W4400582534 on OpenAlexafffund
Katarzyna Śmiłowska, Raja Mehanna, Jori Fleisher, Roy N. Alcalay, Kishore R. Kumar, Connie Marras, Annelien M. Oosterbaan, Bart Post, Owen A. Ross, Maria Elisa Pimentel Piemonte, Valérie Fraix, Elena Moro, Eng‐King Tan, Rodolfo Savica

Bibliographic record

VenueJournal of Parkinson s Disease · 2024
Typereview
Languageen
FieldMedicine
TopicNeurological disorders and treatments
Canadian institutionsUniversity of TorontoUniversity Health Network
FundersNational Center for Advancing Translational SciencesNational Institutes of HealthACADIA PharmaceuticalsNational Medical Research CouncilDavis Phinney FoundationCanadian Institutes of Health ResearchAmerican Brain FoundationIpsenCurePSPMedical Research CouncilInternational Parkinson and Movement Disorder SocietyBiogenSeqirusSanofi
KeywordsDeep brain stimulationPregnancyParkinson's diseaseMedicineDiseasePediatricsInternal medicine

Abstract

fetched live from OpenAlex

Pregnancy in women with early-onset Parkinson's disease (PD) is likely to have a higher frequency given the trend toward increasing maternal age, thus resulting in a greater overlap time between childbearing age and PD risk. Deep brain stimulation (DBS) therapy is nowadays offered to PD patients at earlier stage of the disease, when women can still be pre-menopausal. However, few data are available about DBS safety during pregnancy. From a review of the available literature, only one article was published on this topic so far. Therefore, we have developed a clinical consensus on the safety of DBS during pregnancy in PD patients.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.040
GPT teacher head0.345
Teacher spread0.305 · 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 designNot applicable
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

Citations5
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Parkinson s DiseaseSame topicNeurological disorders and treatmentsFrench-language works237,207