Abstract
Objective
An early metabolic signature associated with the responsiveness to treatment can be useful in the better management of septic shock patients. This would help clinicians in designing personalized treatment protocols for patients showing non-responsiveness to treatment.
Methods
We analyzed the serum on Day 1 (n = 60), Day 3 (n = 47), and Day 5 (n = 26) of patients with septic shock under treatment using NMR-based metabolomics. Partial least square discriminant analysis (PLS-DA) was performed to generate the list of metabolites that can be identified as potential disease biomarkers having statistical significance (that is, metabolites that had a VIP score > 1, and p value < 0.05, False discovery rate (FDR) < 0.05).
Results
Common significant metabolites amongst the three time points were obtained that distinguished the patients being responsive (R) and non-responsive (NR) to treatments, namely 3 hydroxybutyrate, lactate, and phenylalanine which were lower, whereas glutamate and choline higher in patients showing responsiveness.
Discussion
The study gave these metabolic signatures identifying patients’ responsiveness to treatment. The results of the study will aid in the development of targeted therapy for ICU patients.
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Authors acknowledge Centre of Biomedical Research for providing the infrastructure and resources and Centre of Scientific and Industrial Research(CSIR), INDIA, for research fellowship.
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NS, AA and SP conceptualized and designed the methodology of the study. NS, AA and SP investigated the study. NS and AA provided the resources and supervised the study. NS and AA administered the project. NS provided financial support for the project. Formal analysis using software, data curation and validation was performed by SP. Patient sample and clinical data collection by MAS and SP. Visualization and original draft preparation by SP. Final draft review and editing by SP, MAS, AA and NS. All authors approved the final submission.
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The study was approved by the Institutional Ethical Committee of Sanjay Gandhi Post Graduate Institute of Medical Sciences with IEC code:2018-170-PhD-107 and approval code: PEG/BI/37/2019 and date of approval 28.01.19.
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Pandey, S., Siddiqui, M.A., Azim, A. et al. Metabolic fingerprint of patients showing responsiveness to treatment of septic shock in intensive care unit. Magn Reson Mater Phy 36, 659–669 (2023). https://doi.org/10.1007/s10334-022-01049-9
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DOI: https://doi.org/10.1007/s10334-022-01049-9