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Record W2806860937 · doi:10.4037/ccn2018336

Frailty in Critical Care: Examining Implications for Clinical Practices

2018· review· en· W2806860937 on OpenAlexaff
Jennifer A. Gibson, Sarah Crowe

Bibliographic record

VenueCritical Care Nurse · 2018
Typereview
Languageen
FieldMedicine
TopicFrailty in Older Adults
Canadian institutionsFraser HealthSt. Paul's Hospital
Fundersnot available
KeywordsMedicineDeliriumStressorHarmIntensive care medicineMEDLINEAdverse effectNursing assessmentGerontologyNursingPsychiatryPsychology

Abstract

fetched live from OpenAlex

Frailty is an aging-related, multisystem clinical state characterized by loss of physiological reserves and diminished capacity to withstand exposure to stressors. Frailty increases the risk of serious adverse outcomes, compared with that of nonfrail people of the same age. Adverse outcomes can be severe and may include procedural complications, delirium, significant functional decline and disability, prolonged hospital length of stay, extended recovery periods, and death. As older adults make up a continually growing proportion of hospitalized patients, critical care nurses need to understand how to recognize frailty and be familiar with related clinical practice implications. Such knowledge underpins effective organization and delivery of care strategies aimed at minimizing harm and maximizing positive outcomes for frail older adults. Drawing from recent literature, this article explores frailty and critical illness by discussing 2 dominant models of the concept. Using a clinical case study, links between frailty and critical care nursing practices are highlighted and clinical considerations are explored.

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)0.004
metaresearch head score (Gemma)0.015
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.007
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.015
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.005
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.506
GPT teacher head0.612
Teacher spread0.106 · 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
GenreReview

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

Citations8
Published2018
Admission routes1
Has abstractyes

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