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Gentamicin pharmacokinetics in old age and frailty

2010· article· en· W1544592091 on OpenAlexaboutno aff
Sarah N. Hilmer, Kim Tran, Patrick Rubie, Jason D. Wright, Danijela Gnjidic, Slade Matthews, Peter R. Carroll

Bibliographic record

VenueBritish Journal of Clinical Pharmacology · 2010
Typearticle
Languageen
FieldMedicine
TopicAntibiotics Pharmacokinetics and Efficacy
Canadian institutionsnot available
Fundersnot available
KeywordsGentamicinRenal functionMedicinePharmacokineticsVolume of distributionCreatininePopulationAminoglycosideUrologyInternal medicineAntibioticsBiologyEnvironmental health

Abstract

fetched live from OpenAlex

WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT • Gentamicin pharmacokinetics show wide inter‐individual variability across all age groups and impaired gentamicin clearance is associated with impaired creatinine clearance in older people. • Changes in body composition and renal function with old age and frailty are likely to affect the pharmacokinetics of gentamicin. • There is current debate on whether the Modification of Diet in Renal Disease (MDRD) equation estimate of glomerular filtration rate (GFR) should replace the Cockcroft Gault equation estimate of creatinine clearance for calculation of doses of renally excreted drugs. WHAT THIS STUDY ADDS • The volume of distribution of gentamicin is not significantly lower in frail than in non frail older people. • The correlation between volume of distribution of gentamicin and actual bodyweight is poor in frail and moderate in non frail older people. • Gentamicin clearance is significantly lower in frail than in non frail older people. • The Cockcroft Gault calculation of creatinine clearance, calculated using ideal bodyweight, gave the best estimate of gentamicin clearance in this population of frail and non frail older people. • The MDRD estimate of GFR and Cockcroft Gault estimate of creatinine clearance, calculated using actual bodyweight, overestimate gentamicin clearance in frail and non frail older people. AIMS Frailty, a syndrome of decreased physiological reserve that is prevalent in old age, impacts on clinical pharmacology. The aims of the study were to (1) determine whether frailty affects the pharmacokinetics of gentamicin and (2) assess the accuracy of different estimates of body size and renal clearance as estimates of gentamicin pharmacokinetics in older inpatients. METHODS This was an observational study of gentamicin pharmacokinetics in a cohort of Australian hospital inpatients aged ≥65 years, who were administered prophylactic intravenous gentamicin. RESULTS Of the 31 participants, 14 were frail and 17 non frail on the Reported Edmonton Frail Scale. The mean volume of distribution of gentamicin was 14.8 ± 1.4 l in frail participants and 15.3 ± 2.2 l in non frail (NS). Volume of distribution correlated best with lean bodyweight. Gentamicin clearance was significantly lower in frail participants (46.6 ± 10.7 ml min −1 ) than in non frail (58.2 ± 12.4 ml min −1 , P = 0.01). The Cockcroft Gault estimate of creatinine clearance calculated using ideal bodyweight gave the best estimate of gentamicin clearance (mean error – 0.15 ml min −1 , 95% CI −2.67, 2.39). The Cockcroft Gault creatinine clearance calculated using actual bodyweight and the estimated glomerular filtration rate from the modified diet in renal disease equation overestimated gentamicin clearance, with mean errors of −10.15 ml min −1 (95%CI −13.60, −6.71) and −18.86 ml min −1 (95% CI −22.45, −15.27), respectively. The Cockcroft Gault creatinine clearance calculated using lean bodyweight underestimated gentamicin clearance (mean error 6.54 ml min −1 , 95% CI 4.18, 8.90). CONCLUSIONS Frail older people have significantly lower gentamicin clearance than non frail. The best estimate of gentamicin clearance is obtained from the Cockcroft Gault creatinine clearance calculated using ideal bodyweight.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.648
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.003
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 head0.058
GPT teacher head0.434
Teacher spread0.377 · 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 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

Citations54
Published2010
Admission routes1
Has abstractyes

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