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Filtering by: Creator Stringer, Kathleen A. Language English Discipline Health Sciences

Pharmacometabolomics of L-carnitine-Kaplan-Meier survival data: numbers at risk

Creator:

Stringer, Kathleen A.

Description:

These data were produced from the survival analysis of the pre-treatment metabolomics data generated from the Phase II clinical trial of L-carnitine treatment for septic shock (the RACE trial - see https://clinicaltrials.gov/ct2/show/NCT01665092). The results based on respective acetylcarnitine or valine concentration are presented (pdf). The csv files contain the at risk numbers from the Kaplan-Meier survival analysis. These findings described in our manuscript: Pharmacometabolomics Identifies Candidate Predictor Metabolites of an L-carnitine Treatment Mortality Benefit in Septic Shock. and All of the metabolomics data are available at the NIH Common Fund's National Metabolomics Data Repository (NMDR) website, the Metabolomics Workbench, https://www.metabolomicsworkbench.org which is supported by NIH grant U2C-DK119886 and where it has been assigned Project ID (accession number ST001319). The data can be accessed directly via its Project DOIs: (DOI: http://dx.doi.org/10.21228/M8VX0Z).

Keyword:

sepsis, septic shock, survival, mortality, metabolomics, and pharmacometabolomics

Citation to related publication:

Puskarich, M. A., Jennaro, T. S., Gillies, C. E., Evans, C. R., Karnovsky, A., McHugh, C. E., Flott, T. L., Jones, A. E., Stringer, K. A., & Investigators, O. behalf of the R. T. (2021). Pharmacometabolomics Identifies Candidate Predictor Metabolites of an L-carnitine Treatment Mortality Benefit in Septic Shock. (Preprint) https://doi.org/10.1101/2021.01.28.21250687

Discipline:

Health Sciences
Database Screening as a Strategy to Identify Endogenous Candidate Metabolites to Probe and Assess Mitochondrial Drug Toxicity

Creator:

George De la Rosa, Mery Vet, Patel, Dipali, McCann, Marc R., Stringer, Kathleen A., and Rosania, Gus R.

Description:

These data were produced from a study that employed a database strategy to identify candidate mitochondrial metabolites that could be clinically useful to identify individuals at increased risk of mitochondrial-related ADRs. The main candidate metabolite identified by the database strategy was evaluated using a mouse model of mitochondrial drug toxicity. These findings are described in our manuscript: Database Screening as a Strategy to Identify Endogenous Candidate Metabolites to Probe and Assess Mitochondrial Drug Toxicity. Data reported was supported by funding from the National Institute of General Medical Sciences (NIGMS) at the National Institutes of Health (NIH) under award numbers R01GM127787 (GRR) & R35GM136312 (KAS).

Keyword:

mitochondrial-realted metabolites, adverse drug reactions, and mitochondrial drug toxicity

Discipline:

Health Sciences

Pharmacometabolomics of L-carnitine-Kaplan-Meier survival data: numbers at risk

Database Screening as a Strategy to Identify Endogenous Candidate Metabolites to Probe and Assess Mitochondrial Drug Toxicity

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Pharmacometabolomics of L-carnitine-Kaplan-Meier survival data: numbers at risk

Database Screening as a Strategy to Identify Endogenous Candidate Metabolites to Probe and Assess Mitochondrial Drug Toxicity

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