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Record W2905869563 · doi:10.1186/s12877-018-1010-1

Validation of a one year fracture prediction tool for absolute hip fracture risk in long term care residents

2018· article· en· W2905869563 on OpenAlexafffundabout
Ahmed Negm, George Ioannidis, Micaela Jantzi, Jenn Bucek, Lora Giangregorio, Laura Pickard, John P. Hirdes, Jonathan D. Adachi, Julie Richardson, Lehana Thabane, Αλεξάνδρα Παπαϊωάννου

Bibliographic record

VenueBMC Geriatrics · 2018
Typearticle
Languageen
FieldMedicine
TopicBone health and osteoporosis research
Canadian institutionsImpactUniversity of WaterlooMcMaster Children's HospitalMcMaster UniversityResearch Institute for AgingSt. Peter's Hospital
FundersPublic Health Agency of Canada
KeywordsMedicineHip fractureRisk assessmentPhysical therapyLogistic regressionDemographyRehabilitationGerontologyInternal medicineOsteoporosis

Abstract

fetched live from OpenAlex

BACKGROUND: Frail older adults living in long term care (LTC) homes have a high fracture risk, which can result in reduced quality of life, pain and death. The Fracture Risk Scale (FRS) was designed for fracture risk assessment in LTC, to optimize targeting of services in those at highest risk. This study aims to examine the construct validity and discriminative properties of the FRS in three Canadian provinces at 1-year follow up. METHODS: LTC residents were included if they were: 1) Adults admitted to LTC homes in Ontario (ON), British Columbia (BC) and Manitoba (MB) Canada; and 2) Received a Resident Assessment Instrument Minimum Data Set Version 2.0. After admission to LTC, one-year hip fracture risk was evaluated for all the included residents using the FRS (an eight-level risk scale, level 8 represents the highest fracture risk). Multiple logistic regressions were used to determine the differences in incident hip or all clinical fractures across the provinces and FRS risk levels. We examined the differences in incident hip or all clinical fracture for each FRS level across the three provinces (adjusted for age, BMI, gender, fallers and previous fractures). We used the C-statistic to assess the discriminative properties of the FRS for each province. RESULTS: Descriptive statistics on the LTC populations in ON (n = 29,848), BC (n = 3129), and MB (n = 2293) are: mean (SD) age 82 (10), 83 (10), and 84 (9), gender (female %) 66, 64, and 70% respectively. The incident hip fractures and all clinical fractures for FRS risk level were similar among the three provinces and ranged from 0.5 to 19.2% and 1 to 19.2% respectively. The overall discriminative properties of the FRS were similar between ON (C-statistic = 0.673), BC (C-statistic = 0.644) and MB (C-statistic = 0.649) samples. CONCLUSION: FRS is a valid tool for identifying LTC residents at different risk levels for hip or all clinical fractures in three provinces. Having a fracture risk assessment tool that is tailored to the LTC context and embedded within the routine clinical assessment may have significant implications for policy, service delivery and care planning, and may improve care for LTC residents across Canada.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.006
Threshold uncertainty score0.448

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.025
GPT teacher head0.331
Teacher spread0.306 · 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.

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

Citations17
Published2018
Admission routes3
Has abstractyes

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