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Record W4206223460 · doi:10.1177/1753495x211041899

Myasthenia gravis in pregnancy: Systematic review and case series

2022· article· en· W4206223460 on OpenAlex
Harrison Banner, Kirsten M. Niles, Michelle Ryu, Mathew Sermer, Vera Bril, Kellie E. Murphy

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueObstetric Medicine · 2022
Typearticle
Languageen
FieldMedicine
TopicMyasthenia Gravis and Thymoma
Canadian institutionsUniversity Health NetworkUniversity of TorontoMount Sinai Hospital
Fundersnot available
KeywordsMyasthenia gravisMedicinePregnancyExacerbationPediatricsIncidence (geometry)ObstetricsDiseaseInternal medicine

Abstract

fetched live from OpenAlex

Background: Myasthenia gravis is an autoimmune disease which can impact pregnancy. Methods: Six databases were systematically searched for studies with at least five subjects reporting pregnancy outcomes for women with myasthenia gravis in pregnancy. Assessment of bias was performed for all included studies. Forty-eight cases from our own centre were also included in the analysis. Results: In total, 32 publications met inclusion criteria for systematic review, for a total of 33 unique data sets including 48 cases from our institution. Outcome data was available for 824 pregnancies. Spontaneous vaginal delivery occurred in 56.3% of pregnancies. Overall risk of myasthenia gravis exacerbation was 33.8% with a 6.4% risk of myasthenic crisis in pregnancy and 8.2% postpartum. The incidence risk of transient neonatal myasthenia gravis was 13.0%. Conclusions: The current systematic review provides the best estimates of risk currently available to aid in counselling women with myasthenia gravis in pregnancy.

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.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.900
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.018
GPT teacher head0.265
Teacher spread0.247 · 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