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Record W2888370093 · doi:10.1097/ccm.0000000000003349

Delirium Monitoring in Neurocritically Ill Patients: A Systematic Review*

2018· review· en· W2888370093 on OpenAlex
Mayur B. Patel, Josef Bednařík, Patricia Lee, Yahya Shehabi, Jorge I. Salluh, Arjen J. C. Slooter, Kate Klein, Yoanna Skrobik, Alessandro Morandi, Peter E. Spronk, Andrew M. Naidech, Brenda T. Pun, Fernando A. Bozza, Annachiara Marra, Sayona John, Pratik P. Pandharipande, E. Wesley Ely

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 Medicine · 2018
Typereview
Languageen
FieldMedicine
TopicIntensive Care Unit Cognitive Disorders
Canadian institutionsMcGill University
FundersNational Heart, Lung, and Blood InstituteNational Institute on AgingCSL BehringNIH Clinical CenterAgency for Healthcare Research and QualityNational Institutes of HealthPfizerNational Institute of General Medical SciencesAbbott LaboratoriesU.S. Department of Veterans Affairs
KeywordsDeliriumMedicinePopulationInter-rater reliabilityMEDLINEInternal medicineIntensive care medicineEmergency medicineRating scale

Abstract

fetched live from OpenAlex

OBJECTIVES: The Society of Critical Care Medicine recommends routine delirium monitoring, based on data in critically ill patients without primary neurologic injury. We sought to answer whether there are valid and reliable tools to monitor delirium in neurocritically ill patients and whether delirium is associated with relevant clinical outcomes (e.g., survival, length of stay, functional independence, cognition) in this population. DATA SOURCES: We systematically reviewed Cumulative Index to Nursing and Allied Health Literature, Web of Science, and PubMed. STUDY SELECTION AND DATA EXTRACTION: Inclusion criteria allowed any study design investigating delirium monitoring in neurocritically ill patients (e.g., neurotrauma, ischemic, and/or hemorrhagic stroke) of any age. We extracted data relevant to delirium tool sensitivity, specificity, negative predictive value, positive predictive value, interrater reliability, and associated clinical outcomes. DATA SYNTHESIS: Among seven prospective cohort studies and a total of 1,173 patients, delirium was assessed in neurocritically patients using validated delirium tools after considering primary neurologic diagnoses and associated complications, finding a pooled prevalence rate of 12-43%. When able to compare against a common reference standard, Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, the test characteristics showed a sensitivity of 62-76%, specificity of 74-98%, positive predictive value of 63-91%, negative predictive value of 70-94%, and reliability kappa of 0.64-0.94. Among four studies reporting multivariable analyses, delirium in neurocritically patients was associated with increased hospital length of stay (n = 3) and ICU length of stay (n = 1), as well as worse functional independence (n = 1) and cognition (n = 2), but not survival. CONCLUSIONS: These data from studies of neurocritically ill patients demonstrate that patients with primary neurologic diagnoses can meet diagnostic criteria for delirium and that delirious features may predict relevant untoward clinical outcomes. There is a need for ongoing investigations regarding delirium in these complicated neurocritically ill patients.

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)0.378
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.378
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.378
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0070.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
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 head0.045
GPT teacher head0.387
Teacher spread0.342 · 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