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Record W2980749285 · doi:10.1093/ndt/gfz196

Phosphate and bone fracture risk in chronic kidney disease patients

2019· review· en· W2980749285 on OpenAlexaff
Maria Fusaro, Rachel M. Holden, Charmaine E. Lok, Giorgio Iervasi, Mario Plebani, Andrea Aghi, Maurizio Gallieni, Mario Cozzolino

Bibliographic record

VenueNephrology Dialysis Transplantation · 2019
Typereview
Languageen
FieldMedicine
TopicParathyroid Disorders and Treatments
Canadian institutionsToronto General HospitalUniversity of TorontoUniversity Health NetworkQueen's University
Fundersnot available
KeywordsMedicineKidney diseaseFibroblast growth factor 23Parathyroid hormoneInternal medicineSclerostinEndocrinologyPhosphateChronic kidney disease-mineral and bone disorderSevelamerPopulationRisk factorHyperphosphatemiaRenal osteodystrophyCalciumBiochemistryBiology

Abstract

fetched live from OpenAlex

In chronic kidney disease (CKD), phosphate homoeostasis plays a central role in the development of mineral and bone disorder (MBD) together with decreased serum calcium and elevated serum parathyroid hormone, fibroblast growth factor 23 and sclerostin levels. Today there are only a few data exploring the direct role of abnormal phosphate homoeostasis and hyperphosphataemia in the development of CKD-MBD. On the other hand, several studies have looked at the link between hyperphosphataemia and cardiovascular morbidity and mortality in CKD, but there is a lack of evidence to indicate that lowering phosphate levels improves cardiovascular outcomes in this population. Furthermore, the impact of liberalizing phosphate targets on CKD-MBD progression and bone fracture is currently not known. In this review we discuss the central role of phosphate in the pathogenesis of CKD-MBD and how it may be associated with fracture risk, both in hyper- and hypophosphataemia.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.853
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.013
GPT teacher head0.289
Teacher spread0.276 · 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 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

Citations29
Published2019
Admission routes1
Has abstractyes

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