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Record W2567425049 · doi:10.14283/jnhrs.2016.9

VARIABILITY IN ONTARIO LONG-TERM CARE PRACTICES FOR SCREENING AND TREATMENT OF VITAMIN B12 DEFICIENCY

2016· article· en· W2567425049 on OpenAlexafffundabout
Kaylen J. Pfisterer, M. Sharratt, G.G. Heckman, Heather Keller

Bibliographic record

VenueThe Journal of Nursing Home Research Sciences · 2016
Typearticle
Languageen
FieldHealth Professions
TopicObesity and Health Practices
Canadian institutionsUniversity of Waterloo
FundersResearch Institute for Aging, University of WaterlooUniversity of Waterloo
KeywordsVitamin B12Term (time)MedicinePediatricsIntensive care medicineInternal medicine

Abstract

fetched live from OpenAlex

Background: Vitamin B12 deficiency is avoidable through screening and treatment. Deficiency in long-term care impacts ~35% of residents, yet it remains unclear as to what long-term care homes are doing to address this issue. Objective: For the first time, to describe the state of B12 screening and treatment protocols in Ontario long-term care homes, influence of geography and corporate structure on protocols, and the proportion of residents who are currently under treatment. Design: This cross-sectional study used stratified random sampling. Setting: Ontario long-term care homes. Participants: Forty-five standardized phone interviews were completed with the directors of nursing care. Measurements: The following measurements were collected: home demographics (geography, for-profit status etc.), protocols pertaining to vitamin B12 testing, treatment, the cutpoint each home uses to define B12 deficiency, proportion of residents receiving B12 and the treatment method (intramuscular injection vs. oral). Results: Cut-off values for determination of B12 deficiency varied (31% <156 pmol/L). Admission and follow-up B12 testing were routinely conducted in 66% (30/45) and 88% (35/40) of long-term care homes respectively. On average 25 16% of current residents received treatment (41/45 homes reporting). Conclusions: Variability in detection and treatment of B12 deficiency in LTC, potentially places residents at risk for undetected deficiency. Regular testing and monitoring beginning at admission may provide a solution, however, there is a need both for further studies targeted at addressing the effect of treatment on improved clinical outcomes as well as a formal cost-benefit analysis for screening and subsequent treatment.

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)0.027
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.145
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0270.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.001
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 head0.438
GPT teacher head0.598
Teacher spread0.160 · 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.

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

Citations1
Published2016
Admission routes3
Has abstractyes

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