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Record W2468132436

Prevention of ifosfamide nephrotoxicity by N-acetylcysteine: clinical pharmacokinetic considerations.

2007· review· en· W2468132436 on OpenAlexaff
Nancy Chen, Katarina Aleksa, Cindy Woodland, Michael Rieder, Gideon Koren

Bibliographic record

VenuePubMed · 2007
Typereview
Languageen
FieldMedicine
TopicChemotherapy-induced organ toxicity mitigation
Canadian institutionsWestern University
Fundersnot available
KeywordsIfosfamideNephrotoxicityPharmacokineticsMedicineAcetylcysteinePharmacologyIn vitroUrineIn vivoToxicityChemotherapyChemistryCisplatinInternal medicineBiochemistryBiologyAntioxidant
DOInot available

Abstract

fetched live from OpenAlex

BACKGROUND: Ifosfamide, which is routinely given to treat a variety of solid tumours in children, causes serious nephrotoxicity in treated children. Previous in vitro studies have shown that depletion of intracellular glutathione can enhance ifosfamide nephrotoxicity. Presently, there is no therapeutic agent that can prevent ifosfamide nephrotoxicity. We have recently shown that N-acetylcysteine (NAC) at 0.4 mM prevents ifosfamide-induced nephrotoxicity in vitro. However, this in vitro concentration of NAC needed to be compared to those used in human pharmacokinetic studies since the in vitro pharmacological effect of a compound is achieved at concentrations exceeding those used in clinical. OBJECTIVE: The aim of the present study was to verify whether the in vitro concentration of NAC, which was found to protect renal cells from ifosfamide-induced damages, is comparable to the currently used clinical concentrations. METHODS: A systematic literature review of all published papers reporting on the pharmacokinetics of NAC in humans was conducted. RESULTS: The steady state concentrations of NAC administered intravenously to humans ranged from 0.04 mM to 0.9 mM and the urine concentration of NAC was 2 mM. CONCLUSION: This suggests that the concentration chosen for in vitro studies is well within the range of clinical levels.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.981
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.179
GPT teacher head0.431
Teacher spread0.252 · 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 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

Citations8
Published2007
Admission routes1
Has abstractyes

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