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Pharmacological interventions for the treatment of delirium in critically ill adults

2019· review· en· W2972175093 on OpenAlexafffundabout
Lisa Burry, Brian Hutton, David Williamson, Sangeeta Mehta, Neill K. J. Adhikari, Wei Cheng, E. Wesley Ely, Ingrid Egerod, Dean Fergusson, Louise Rose

Bibliographic record

VenueCochrane Database of Systematic Reviews · 2019
Typereview
Languageen
FieldMedicine
TopicIntensive Care Unit Cognitive Disorders
Canadian institutionsSunnybrook Health Science CentreUniversité de MontréalHôpital du Sacré-Cœur de MontréalOttawa HospitalUniversity of TorontoHealth Sciences CentreMount Sinai Hospital
FundersCanadian Institutes of Health ResearchNational Institute for Health and Care ResearchAstraZeneca
KeywordsCritically illDeliriumIntensive care medicinePsychological interventionMedicineCritical illnessPsychologyPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Although delirium is typically an acute reversible cognitive impairment, its presence is associated with devastating impact on both short-term and long-term outcomes for critically ill patients. Advances in our understanding of the negative impact of delirium on patient outcomes have prompted trials evaluating multiple pharmacological interventions. However, considerable uncertainty surrounds the relative benefits and safety of available pharmacological interventions for this population. OBJECTIVES: Primary objective1. To assess the effects of pharmacological interventions for treatment of delirium on duration of delirium in critically ill adults with confirmed or documented high risk of deliriumSecondary objectivesTo assess the following:1. effects of pharmacological interventions on delirium-free and coma-free days; days with coma; delirium relapse; duration of mechanical ventilation; intensive care unit (ICU) and hospital length of stay; mortality; and long-term outcomes (e.g. cognitive; discharge disposition; health-related quality of life); and2. the safety of such treatments for critically ill adult patients. SEARCH METHODS: We searched the following databases from their inception date to 21 March 2019: Ovid MEDLINE®, Ovid MEDLINE® In-Process & Other Non-Indexed Citations, Embase Classic+Embase, and PsycINFO using the Ovid platform. We also searched the Cochrane Library on Wiley, the International Prospective Register of Systematic Reviews (PROSPERO) (http://www.crd.york.ac.uk/PROSPERO/), the Cumulative Index to Nursing and Allied Health Literature (CINAHL), and Web of Science. We performed a grey literature search of relevant databases and websites using the resources listed in Grey Matters developed by the Canadian Agency for Drugs and Technologies in Health (CADTH). We also searched trial registries and abstracts from annual scientific critical care and delirium society meetings. SELECTION CRITERIA: We sought randomized controlled trials (RCTs), including quasi-RCTs, of any pharmacological (drug) for treatment of delirium in critically ill adults. The drug intervention was to be compared to another active drug treatment, placebo, or a non-pharmacological intervention (e.g. mobilization). We did not apply any restrictions in terms of drug class, dose, route of administration, or duration of delirium or drug exposure. We defined critically ill patients as those treated in an ICU of any specialty (e.g. burn, cardiac, medical, surgical, trauma) or high-dependency unit. DATA COLLECTION AND ANALYSIS: Two review authors independently identified studies from the search results; four review authors (in pairs) performed data extraction and assessed risk of bias independently. We performed data synthesis through pairwise meta-analysis and network meta-analysis (NMA). Our hypothetical network structure was designed to be analysed at the drug class level and illustrated a network diagram of 'nodes' (i.e. drug classes) and 'edges' (i.e. comparisons between different drug classes from existing trials), thus describing a treatment network of all possible comparisons between drug classes. We assessed the quality of the body of evidence according to GRADE, as very low, low, moderate, or high. MAIN RESULTS: agonist dexmedetomidine was associated with a shorter duration of mechanical ventilation (RoM 0.55, 95% CrI 0.34 to 0.89; moderate-quality evidence), and the CHE inhibitor rivastigmine was associated with a longer ICU stay (RoM 2.19, 95% CrI 1.47 to 3.27; moderate-quality evidence). Adverse events often were not reported in these trials or, when reported, were rare; pair-wise analysis of QTc prolongation in seven studies did not show significant differences between antipsychotics, ondansetron, dexmedetomidine, and placebo. AUTHORS' CONCLUSIONS: agonists also ranked best for duration of mechanical ventilation and length of ICU stay, whereas the CHE inhibitor rivastigmine was associated with longer ICU stay. We found no evidence of a difference between placebo and any drug in terms of delirium-free and coma-free days, days with coma, physical restraint use, length of stay, long-term cognitive outcomes, or mortality. No studies reported delirium relapse, resolution of symptoms, or quality of life. The ten ongoing studies and the six studies awaiting classification that we identified, once published and assessed, may alter the conclusions of the review.

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)0.023
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.010
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.023
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0060.005
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0100.001

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 head0.220
GPT teacher head0.472
Teacher spread0.251 · 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 designSystematic review
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".

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Citations176
Published2019
Admission routes3
Has abstractyes

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