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Record W2614608804 · doi:10.2215/cjn.00130117

Pregnancy and Glomerular Disease

2017· review· en· W2614608804 on OpenAlexaff
Kimberly Blom, Ayodele Odutayo, Kate Bramham, Michelle Hladunewich

Bibliographic record

VenueClinical Journal of the American Society of Nephrology · 2017
Typereview
Languageen
FieldMedicine
TopicPregnancy and preeclampsia studies
Canadian institutionsHealth Sciences CentreUniversity of TorontoSunnybrook Health Science Centre
FundersNational Institute for Health and Care Research
KeywordsMedicineLupus nephritisPregnancyDiseaseIntrauterine growth restrictionIntensive care medicineObstetricsAdvanced maternal ageLow birth weightPediatricsFetusInternal medicine

Abstract

fetched live from OpenAlex

During pregnancy, CKD increases both maternal and fetal risk. Adverse maternal outcomes include progression of underlying renal dysfunction, worsening of urine protein, and hypertension, whereas adverse fetal outcomes include fetal loss, intrauterine growth restriction, and preterm delivery. As such, pregnancy in young women with CKD is anxiety provoking for both the patient and the clinician providing care, and because the heterogeneous group of glomerular diseases often affects young women, this is an area of heightened concern. In this invited review, we discuss pregnancy outcomes in young women with glomerular diseases. We have performed a systematic review in attempt to better understand these outcomes among young women with primary GN, we review the studies of pregnancy outcomes in lupus nephritis, and finally, we provide a potential construct for management. Although it is safe to say that the vast majority of young women with glomerular disease will have a live birth, the counseling that we can provide with respect to individualized risk remains imprecise in primary GN because the existing literature is extremely dated, and all management principles are extrapolated primarily from studies in lupus nephritis and diabetes. As such, the study of pregnancy outcomes and management strategies in these rare diseases requires a renewed interest and a dedicated collaborative effort.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.969
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.004
Bibliometrics0.0000.000
Science and technology studies0.0000.005
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.180
GPT teacher head0.463
Teacher spread0.283 · 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 designOther design
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

Citations107
Published2017
Admission routes1
Has abstractyes

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