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Accuracy of nurse documentation of delirium symptoms in medical charts

2008· article· en· W2171261904 on OpenAlexaff
Philippe Voyer, Martín G. Cole, Jane McCusker, Sylvie St‐Jacques, Johanne Laplante

Bibliographic record

VenueInternational Journal of Nursing Practice · 2008
Typearticle
Languageen
FieldMedicine
TopicIntensive Care Unit Cognitive Disorders
Canadian institutionsHôpital du Saint-SacrementMcGill UniversitySt Mary's Hospital CentreUniversité Laval
Fundersnot available
KeywordsDeliriumMedicineDocumentationMedical recordAcute careMEDLINEEmergency medicinePsychiatryHealth careInternal medicine

Abstract

fetched live from OpenAlex

The purpose of this study undertaken in an acute care hospital was to evaluate sensitivity and specificity of the documentation of nurse-reported delirium symptoms in medical charts. This is a descriptive study based on the clinical assessments of a study nurse and nursing notes in the medical charts of 226 delirious older patients newly admitted to an acute care hospital. The results of this prospective validation study indicated that documentation of delirium symptoms is poor. Disorientation, agitation and altered level of consciousness were the three symptoms yielding a higher level of sensitivity, but even so said symptoms were reported in less than a third of the medical charts. Univariate analysis suggested that higher comorbidity level, more severe symptoms of delirium and the use of physical restraints were associated with more valid documentation of delirium symptoms in medical charts. Lastly, this study corroborates results of previous studies, indicating that documentation of delirium symptoms in medical charts can be improved. Future study should target improving nurse documentation of delirium symptoms in medical charts.

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)0.040
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.603
Threshold uncertainty score0.968

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.040
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 science0.0000.000
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 head0.028
GPT teacher head0.410
Teacher spread0.383 · 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 designOther design
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

Citations48
Published2008
Admission routes1
Has abstractyes

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