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Record W6982239551

Hip Fractures, Musculoskeletal Health, and Dementia: Population-Based Cohort Studies and Scoping Reviews Among Older Adults

2024· dissertation· en· W6982239551 on OpenAlexfundaboutno aff

Bibliographic record

VenueMacSphere (McMaster University) · 2024
Typedissertation
Languageen
FieldEnvironmental Science
TopicAmerican Environmental and Regional History
Canadian institutionsnot available
FundersCanadian Institutes of Health ResearchGovernment of Canada
KeywordsHip fractureCohort studyOsteoporosisCohortDementiaMEDLINEScale (ratio)Health carePsychological intervention
DOInot available

Abstract

fetched live from OpenAlex

Objectives: This study aimed to investigate the risks and impacts associated with fractures, osteoporosis, frailty, physical function, and dementia in older adults in community and LTC setting. The study aims to identify important factors influencing these health issues and identify strategies for improving management and outcomes. Methods: The research integrates data from three primary sources: Project 1 (ICES Data Repository): Healthcare utilization and administrative databases were linked using unique, encoded identifiers from the ICES Data Repository to estimate hip fractures and osteoporosis management among adults aged 66 and older from April 1, 2014, to March 31, 2018. Osteoporosis management was assessed through pharmacotherapy records. Sex-specific and age-standardized rates were compared based on pre-fracture residency and discharge location (e.g., LTC to LTC, community to LTC, or community to community). Fracture risk was determined using the Fracture Risk Scale (FRS). Project 2 (Canadian Longitudinal Study on Aging - CLSA): Participants aged 45 to 85 years who completed both the baseline and three-year follow-up assessments were included. Outcomes examined include frailty (Fried Frailty Phenotype), and physical function limitations. MSK conditions were self-reported diagnosis by a health care professional and included rheumatoid arthritis (RA), osteoarthritis (OA), low-back pain, osteoporosis, and related fractures. Project 3: The review employed Arksey and O'Malley's framework, guided by Joanna Briggs Institute methodology and PRISMA-ScR guidelines. A comprehensive search strategy was implemented across MEDLINE, EMBASE, CINAHL, and grey literature. Independent reviewers used Covidence software for study selection and data extraction. A narrative synthesis was conducted to summarize findings, identify patterns, and highlight gaps in the literature. Findings: We found increasing hip fracture rates and low osteoporosis treatment in LTC settings, highlighting to the need for improved screening and management of osteoporosis treatment in LTC. In community, hip fracture rates decreased. We found that older adults with musculoskeletal (MSK) conditions at baseline were more likely to experience frailty at the three-year follow-up compared to those without MSK conditions. However, this association was not significant in the unadjusted analysis. Individuals with cognitive decline experience worse outcomes following hip fractures, underscoring the need for integrated care addressing both physical and cognitive health. Conclusion: Hip fractures, frailty, physical function decline, and cognitive decline are prevalent and interrelated issues among older adults aged 65 and older. These findings underscore the need for improved screening and integrated care strategies to enhance management and prevention of these complex health challenges.

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)0.026
metaresearch head score (Gemma)0.107
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.026
Threshold uncertainty score0.135

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0260.107
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.006
Bibliometrics0.0240.021
Science and technology studies0.0010.001
Scholarly communication0.0040.003
Open science0.0010.003
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.008
GPT teacher head0.232
Teacher spread0.224 · 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 designSystematic review
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

Citations0
Published2024
Admission routes2
Has abstractyes

Explore more

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