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Record W2187764547

Acetylcholinesterase inhibitors and healing of hip fracture in Alzheimer's disease patients: a retrospective cohort study.

2013· article· en· W2187764547 on OpenAlexaff
Hazem Eimar, Almudena Pérez Lara, Iskandar Tamimi, Pilar Márquez Sánchez, Ivy Talavera, F. Tomba, Torcuato García de la Oliva, Faleh Tamimi

Bibliographic record

VenuePubMed · 2013
Typearticle
Languageen
FieldMedicine
TopicHip and Femur Fractures
Canadian institutionsMcGill University
Fundersnot available
KeywordsMedicineHip fractureRetrospective cohort studyInternal medicineBody mass indexCohortCohort studySurgeryOsteoporosis
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVES: This study was designed to assess effects of cholinergic stimulation using acetylcholinesterase inhibitors (AChEIs), a group of drugs that stimulate cholinergic receptors and are used to treat Alzheimer's disease (AD), on healing of hip fractures. METHODS: A retrospective cohort study was performed using 46-female AD patients, aged above 75 years, who sustained hip fractures. Study analyses included the first 6-months after hip fracture fixation procedure. Presence of AChEIs was used as predictor variable. Other variables that could affect study outcomes: age, body mass index (BMI), mental state or type of hip fracture, were also included. Radiographic union at fracture site (Hammer index), bone quality (Singh index) and fracture healing complications were recorded as study outcomes. The collected data was analyzed by student's-t, Mann-Whitney-U and chi-square tests. RESULTS: No significant differences in age, BMI, mental state or type of hip fracture were observed between AChEIs-users and nonusers. However, AChEIs-users had better radiographic union at the fracture site (relative risk (RR),2.7; 95%confidence interval (CI),0.9-7.8), better bone quality (RR,2.0; 95%CI,1.2-3.3) and fewer healing complications (RR,0.8; 95%CI,0.7-1.0) than nonusers. CONCLUSION: In elderly female patients with AD, the use of AChEIs might be associated with an enhanced fracture healing and minimized complications.

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 score0.007
Threshold uncertainty score0.484

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 head0.011
GPT teacher head0.243
Teacher spread0.232 · 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

Citations34
Published2013
Admission routes1
Has abstractyes

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