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Record W2906971690 · doi:10.1007/s40620-018-00569-9

Fertility and reproductive care in chronic kidney disease

2019· review· en· W2906971690 on OpenAlexaff
Sandra M. Dumanski, Sofia B. Ahmed

Bibliographic record

VenueJournal of Nephrology · 2019
Typereview
Languageen
FieldMedicine
TopicPregnancy and Medication Impact
Canadian institutionsLibin Cardiovascular Institute of AlbertaAlberta Kidney Disease NetworkUniversity of Calgary
Fundersnot available
KeywordsMedicineFertilityInfertilityNephrologyReproductive medicineKidney diseasePopulationAssisted reproductive technologyReproductive endocrinology and infertilityKidney transplantationIntensive care medicineReproductive technologyReproductive EndocrinologyFertility preservationGynecologyTransplantationInternal medicinePregnancyBiologyEnvironmental healthHormone

Abstract

fetched live from OpenAlex

In both women and men, chronic kidney disease (CKD) is associated with decreased fertility. Though a multitude of factors contribute to the reduction in fertility in this population, progressively impaired function of the hypothalamic-pituitary-gonadal axis appears to play a key role in the pathophysiology. There is limited research on strategies to manage infertility in the CKD population, but intensive hemodialysis, kidney transplantation, medication management and assisted reproductive technologies (ART) have all been proposed. Though fertility and reproductive care are reported as important elements of care by CKD patients themselves, few nephrology clinicians routinely address fertility and reproductive care in clinical interactions. Globally, the average age of parenthood is increasing, with concurrent growth and expansion in the use of ART. Coupled with an increasing prevalence of CKD in women and men of reproductive age, the importance of understanding fertility and reproductive technologies in this population is highlighted. This review endeavors to explore the female and male factors that affect fertility in the CKD population, as well as the evidence supporting strategies for reproductive care.

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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.047
GPT teacher head0.377
Teacher spread0.331 · 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

Citations61
Published2019
Admission routes1
Has abstractyes

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