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Record W2143969618 · doi:10.1177/1054773805282299

Prevalence and Symptoms of Delirium Superimposed on Dementia

2006· article· en· W2143969618 on OpenAlexaff
Philippe Voyer, Martín G. Cole, Jane McCusker, Éric Belzile

Bibliographic record

VenueClinical Nursing Research · 2006
Typearticle
Languageen
FieldMedicine
TopicIntensive Care Unit Cognitive Disorders
Canadian institutionsSt Mary's Hospital CentreMcGill UniversityUniversité Laval
Fundersnot available
KeywordsDeliriumDementiaCognitive impairmentMedicineCognitionPsychiatryInternal medicineDisease

Abstract

fetched live from OpenAlex

Delirium is a frequent syndrome among patients who are elderly. People who are older with cognitive impairment who are institutionalized are at increased risk of developing delirium when hospitalized. In addition, their prior cognitive impairment makes detecting their delirium a challenge. This study goal was to describe the effect of severity of prior cognitive impairment on delirium prevalence and symptom presentation among patients who were older and were newly admitted to an acute care hospital. A total of 104 were included in this descriptive study and screened for delirium. The results showed that the prevalence of delirium increased according to the severity of the patients' prior cognitive impairment. Except for disorganized thinking, all symptoms of delirium were similar among patients with mild, moderate, and severe prior cognitive impairment. The study concluded that training nurses to recognize subtle changes in mental status among those patients who were older with prior cognitive impairment may prevent the underdetection of delirium.

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)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.078
GPT teacher head0.468
Teacher spread0.390 · 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 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

Citations90
Published2006
Admission routes1
Has abstractyes

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