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Record W2896906684 · doi:10.1111/jgs.15603

Central Nervous System Medication Burden and Risk of Recurrent Serious Falls and Hip Fractures in Veterans Affairs Nursing Home Residents

2018· article· en· W2896906684 on OpenAlexfundno aff
Sherrie L. Aspinall, Sydney Springer, Xinhua Zhao, Francesca Cunningham, Carolyn T. Thorpe, Todd P. Semla, Ronald I. Shorr, Joseph T. Hanlon

Bibliographic record

VenueJournal of the American Geriatrics Society · 2018
Typearticle
Languageen
FieldMedicine
TopicPharmaceutical Practices and Patient Outcomes
Canadian institutionsnot available
FundersInstitute of AgingNational Institute on AgingAgency for Healthcare Research and QualityHealth Services Research and Development
KeywordsMedicineDiagnosis codeVeterans AffairsCurrent Procedural TerminologyEmergency medicineLogistic regressionEmergency departmentInjury preventionPoison controlPhysical therapyPediatricsInternal medicineSurgeryPopulationEnvironmental healthPsychiatry

Abstract

fetched live from OpenAlex

OBJECTIVES: To examine the association between central nervous system (CNS) medication dosage burden and risk of serious falls, including hip fractures, in individuals with a history of a recent fall. DESIGN: Nested case-control study. SETTING: Veterans Health Administration (VHA) Community Living Centers (CLCs). PARTICIPANTS: CLC residents aged 65 and older with a history of a fall or hip fracture in the year before a CLC admission between July 1, 2005, and June 30, 2009. Each case (n = 316) was matched to four controls (n = 1264) on age, sex, and length of stay. MEASUREMENTS: Outcomes were serious falls identified using International Classification of Diseases, Ninth Revision (ACD-9) or Current Procedural Terminology (CPT) E codes, diagnosis codes, or procedure codes associated with a VHA emergency department visit or hospitalization during the CLC stay. Bar code medication administration data were used to calculate CNS standardized daily doses (SDDs) for opioid and benzodiazepine receptor agonists, some antidepressants, antiepileptics, and antipsychotics received in the 6 days before the outcome date by dividing residents' actual CNS daily doses by the minimum effective geriatric daily doses and adding the results. Multivariable conditional logistic regression models were used to evaluate the association between total CNS medication dosage burden, categorized as 0, 1 to 2, and 3 or more SDDs, and the outcome of recurrent serious falls. RESULTS: More cases (44.3%) than controls (35.8%) received 3.0 or more CNS SDDs (p = .02). Risk of serious falls was greater in residents with 3.0 or more SDDs than in those with 0 (adjusted odds ratio (aOR)=1.49, 95% confidence interval (CI)=1.03-2.14). Those with 1.0 to 2.9 SDDs had a risk similar to that of those with 0 SDDs (aOR=1.03, 95%CI=0.72-1.48). CONCLUSION: Nursing home residents with a history of a fall or hip fracture receiving 3.0 or more CNS SDDs were more likely to have a recurrent serious fall than those taking no CNS medications. Interventions targeting this vulnerable population may help reduce serious falls. J Am Geriatr Soc 67:74-80, 2019.

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)0.001
metaresearch head score (Gemma)0.000
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 score0.146
Threshold uncertainty score0.289

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.023
GPT teacher head0.347
Teacher spread0.324 · 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

Citations31
Published2018
Admission routes1
Has abstractyes

Explore more

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