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Record W2416806468 · doi:10.1111/jgs.13903

Response to Canbaz and Colleagues

2016· letter· en· W2416806468 on OpenAlexaffabout
Marie‐Josée Sirois, Véronique Provencher, Xavier Neveu, Marcel Émond

Bibliographic record

VenueJournal of the American Geriatrics Society · 2016
Typeletter
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsUniversité LavalUniversité de SherbrookeCentre hospitalier universitaire de Québec
Fundersnot available
KeywordsMedicineDeliriumActivities of daily livingGerontologyCognitive impairmentFalling (accident)CognitionPsychiatry

Abstract

fetched live from OpenAlex

To the Editor: In Canbaz and colleagues’ thoughtful comments1 on our recent article,2 they noted that, even without a precipitating trauma, older adults may experience functional decline over time. They thus questioned the absence of a control group to support that the observed decline was the result of injuries that would not have happened otherwise. We would like to clarify that our hypothesis was not to prove that trauma was the reason for the observed new activity of daily living (ADL) disabilities but was rather that older adults who developed these disabilities after injuries are frailer and more cognitively impaired than those who did not. Nonetheless, a substudy was conducted (manuscript in preparation) comparing ADL disabilities over time in older adults with injuries and those with medical conditions (matched on age, sex, baseline ADL function, comorbidities, frailty) discharged from emergency departments (EDs). Preliminary results indicate that new disabilities in both groups were similar but that individuals with medical conditions were more fearful of falling, more likely to use a walking aid, and more likely to use the ED and had much less social support than injured older adults. Canbaz and colleagues also state that delirium is common in EDs, which we completely agree with. Delirium was an exclusion criterion in the study. This was more clearly stated in other studies from our team.3, 4 In addition, because all subjects were fit for discharge home from the ED, the risk of missclassifying individuals with delirium as having persistent cognitive impairment was minimal. To answer the question about possible misclassification due to the Montreal Cognitive Assessment (MoCA) cutoff (23/30) used for in-person evaluations, Table 1 compares the initial published risk ratios (RRs) with those found when a MoCA cutoff of 21 is used and shows that the results were very similar to the initial findings.2 Twenty-three percent of older adults were below this, which is comparable to the 25.4% of older adults evaluated in telephone interviews (Modified Telephone Interview for Cognitive Status (TICS-m) cutoff 31/50). We believe that our findings of greater risk of new ADL disabilities with increasing frailty and cognitive impairment are valid. Unfortunately, separate comparative analyses on MoCA and TICS-m subsets could not be performed adequately. With fewer subjects (MoCA subset especially) and given the number of parameters to be estimated, we encountered convergence failures of the multivariate models. We thank Canbaz and colleagues for their interest in our work and hope exchanges like this will continue to help improve research in EDs that are engaged in improving care of older adults. Conflict of Interest: The editor in chief has reviewed the conflict of interest checklist provided by the authors and has determined that the authors have no financial or any other kind of personal conflicts with this paper. Author Contributions: Sirois, Provencher, Émond: preparation of letter. Neveu: statistical analyses. Sponsor's Role: Not applicable.

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)0.007
metaresearch head score (Gemma)0.051
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.044
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.051
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0010.001
Science and technology studies0.0040.004
Scholarly communication0.0060.006
Open science0.0050.003
Research integrity0.0440.045
Insufficient payload (model declined to judge)0.0180.017

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 head0.360
Teacher spread0.335 · 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 designNot applicable
Domainnot available
GenreEditorial

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
Published2016
Admission routes2
Has abstractyes

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