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Record W2806860937 · doi:10.4037/ccn2018336

Frailty in Critical Care: Examining Implications for Clinical Practices

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

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

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.

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)0.096
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.955
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.096
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0020.002
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 head0.506
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