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Record W2167719907 · doi:10.1517/17425255.2013.799137

Drug absorption, distribution, metabolism and excretion considerations in critically ill adults

2013· review· en· W2167719907 on OpenAlexaff
Derek J. Roberts

Bibliographic record

VenueExpert Opinion on Drug Metabolism & Toxicology · 2013
Typereview
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmacogenetics and Drug Metabolism
Canadian institutionsQueen Elizabeth II Health Sciences CentreDalhousie UniversityUniversity of Calgary
Fundersnot available
KeywordsADMEPharmacokineticsDrugCritically illExcretionMedicineDistribution (mathematics)Drug metabolismPharmacologyMetabolic clearance rateIntensive care medicineInternal medicine

Abstract

fetched live from OpenAlex

INTRODUCTION: All critically ill patients require medication to treat organ dysfunction. However, the pharmacokinetics of drugs used to treat these patients is complex due to frequent alterations in drug absorption, distribution, metabolism, and excretion (ADME). AREAS COVERED: This review examines pharmacokinetic aspects of drug administration for adult intensive care unit (ICU) patients. Specifically, the authors examine the ADME changes that occur and which should be considered by clinicians when delivering drug therapy to critically ill patients. EXPERT OPINION: Dosage pharmacokinetics determined from single-dose or limited-duration administration studies in healthy volunteers may not apply to critically ill patients. Organ dysfunction among these patients may be due to pre-existing disease or the effects of a systemic or locoregional inflammatory response precipitated by their illness. Alterations in pharmacokinetics observed among the critically ill include altered bioavailability after enteral administration, increased volume of distribution and blood-brain barrier permeability and changes in P-glycoprotein and cytochrome P450 enzyme function. However, the effect of these changes on clinically important outcomes remains uncertain and poorly studied. Future investigations should examine not only pharmacokinetic changes among the critically ill, but also whether recognition of these changes and alterations in drug therapy directed as a consequence of their observation alters patient outcomes.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.875
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.001

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 head0.099
GPT teacher head0.438
Teacher spread0.340 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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".

Quick stats

Citations101
Published2013
Admission routes1
Has abstractyes

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