MétaCan
Menu
Back to cohort
Record W2321955636 · doi:10.2215/cjn.06040614

Comparison of Fracture Risk Prediction among Individuals with Reduced and Normal Kidney Function

2015· article· en· W2321955636 on OpenAlexafffundabout
Kyla L. Naylor, Amit X. Garg, Guangyong Zou, Lisa Langsetmo, William D. Leslie, Lisa-Ann Fraser, Jonathan D. Adachi, Suzanne N. Morin, David Goltzman, Brian C. Lentle, Stuart A. Jackson, Robert G. Josse, Sophie A. Jamal

Bibliographic record

VenueClinical Journal of the American Society of Nephrology · 2015
Typearticle
Languageen
FieldMedicine
TopicParathyroid Disorders and Treatments
Canadian institutionsUniversity of AlbertaUniversity of British ColumbiaUniversity of TorontoRoyal Victoria HospitalWestern UniversityUniversity of ManitobaMcGill UniversityInstitute for Clinical Evaluative SciencesWomen's College HospitalMcMaster UniversityLondon Health Sciences Centre
FundersCanadian Institutes of Health ResearchEli Lilly CanadaAstellas PharmaProcter and GambleAmgen CanadaServierPfizerOsteoporosis CanadaAmgen
KeywordsMedicineFRAXOsteoporosisInternal medicineRenal functionConfidence intervalBone mineralBone densityCohortUrologyOsteoporotic fracture

Abstract

fetched live from OpenAlex

BACKGROUND AND OBJECTIVES: The Fracture Risk Assessment Tool (FRAX) is widely used to predict the 10-year probability of fracture; however, the clinical utility of FRAX in CKD is unknown. This study assessed the predictive ability of FRAX in individuals with reduced kidney function compared with individuals with normal kidney function. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: The discrimination and calibration (defined as the agreement between observed and predicted values) of FRAX were examined using data from the Canadian Multicentre Osteoporosis Study (CaMos). This study included individuals aged ≥40 years with an eGFR value at year 10 of CaMos (defined as baseline). The cohort was stratified by kidney function at baseline (eGFR<60 ml/min per 1.73 m(2) [72.2% stage 3a, 23.8% stage 3b, and 4.0% stage 4/5] versus ≥60 ml/min per 1.73 m(2)) and followed individuals for a mean of 4.8 years for an incident major osteoporotic fracture (clinical spine, hip, forearm/wrist, or humerus). RESULTS: There were 320 individuals with an eGFR<60 ml/min per 1.73 m(2) and 1787 with an eGFR≥60 ml/min per 1.73 m(2). The mean age was 67±10 years and 71% were women. The 5-year observed major osteoporotic fracture risk was 5.3% (95% confidence interval [95% CI], 3.3% to 8.6%) in individuals with an eGFR<60 ml/min per 1.73 m(2), which was comparable to the FRAX-predicted fracture risk (6.4% with bone mineral density; 8.2% without bone mineral density). A statistically significant difference was not observed in the area under the curve values for FRAX in individuals with an eGFR<60 ml/min per 1.73 m(2) versus ≥60 ml/min per 1.73 m(2) (0.69 [95% CI, 0.54 to 0.83] versus 0.76 [95% CI, 0.70 to 0.82]; P=0.38). CONCLUSIONS: This study showed that FRAX was able to predict major osteoporotic fractures in individuals with reduced kidney function; further study is needed before FRAX should be routinely used in individuals with reduced kidney function.

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)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.061
Threshold uncertainty score0.121

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.043
GPT teacher head0.370
Teacher spread0.328 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations169
Published2015
Admission routes3
Has abstractyes

Explore more

Same venueClinical Journal of the American Society of NephrologySame topicParathyroid Disorders and TreatmentsFrench-language works237,207