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Record W2035522605 · doi:10.3109/17482968.2011.626053

Formal ventilation patient education for ALS predicts real-life choices

2012· article· nl· W2035522605 on OpenAlexaff
Douglas McKim, Judy King, Kathy Walker, Carole LeBlanc, Debbie Timpson, Keith G. Wilson, Meridith B. Marks, Dorothyann Curran, Andrew Woolnough

Bibliographic record

VenueAmyotrophic Lateral Sclerosis · 2012
Typearticle
Languagenl
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsUniversity of OttawaOttawa Hospital
Fundersnot available
KeywordsAffect (linguistics)Ventilation (architecture)Session (web analytics)MedicinePsychological interventionLife supportPalliative carePsychologyPhysical therapyIntensive care medicineNursing

Abstract

fetched live from OpenAlex

Our objective was to evaluate a single-session, hands-on education programme on mechanical ventilation for ALS patients and caregivers in terms of knowledge, change in affect and to determine whether ventilator decisions made after the education sessions predict those made later in life. Questionnaires were administered to 26 patients and 26 caregivers on four separate occasions. The questionnaires assessed knowledge of ventilatory support, feedback on the nature of the education programme, as well as self-reported emotional well-being. All patients were followed until their death or until initiation of invasive ventilation. Both groups demonstrated significant improvements in knowledge as a result of the education session which was retained after one month. There was no change in patient or caregiver reports' self-reported emotional well-being. The choices of ventilatory support expressed at one month (T4) accurately predicted the real-life clinical choices made by 76% of patients. Any difference resulted from choosing palliative care. Hands-on patient and caregiver education results in improved knowledge, assists in decision-making with respect to ventilatory support, and is not associated with a worsening of affect. It also provides for an accurate prediction of real-life choices and avoids undesired life support interventions and critical care admissions.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.066
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.107
GPT teacher head0.362
Teacher spread0.255 · 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

Citations26
Published2012
Admission routes1
Has abstractyes

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