TY - JOUR
T1 - Early Mortality Prediction in Intensive Care Unit Patients Based on Serum Metabolomic Fingerprint
AU - Araújo, Rúben
AU - Ramalhete, Luís
AU - Von Rekowski, Cristiana P.
AU - Fonseca, Tiago A.H.
AU - Bento, Luís
AU - R. C. Calado, Cecília
N1 - Funding Information:
This research was funded by project grant DSAIPA/DS/0117/2020 supported by Funda\u00E7\u00E3o para a Ci\u00EAncia e a Tecnologia, Portugal. The present work was conducted in Instituto Polit\u00E9cnico de Lisboa and in the Engineering & Health Laboratory, which resulted from a collaboration protocol established between Universidade Cat\u00F3lica Portuguesa and Instituto Polit\u00E9cnico de Lisboa. Additionally, R. Ara\u00FAjo, T. Fonseca, and C. Rekowski acknowledge their PhD grants from FCT (references: 2021.05553.BD, 2024.02043.BD, and 2023.01951.BD, respectively).
Publisher Copyright:
© 2024 by the authors.
PY - 2024/12
Y1 - 2024/12
N2 - Predicting mortality in intensive care units (ICUs) is essential for timely interventions and efficient resource use, especially during pandemics like COVID-19, where high mortality persisted even after the state of emergency ended. Current mortality prediction methods remain limited, especially for critically ill ICU patients, due to their dynamic metabolic changes and heterogeneous pathophysiological processes. This study evaluated how the serum metabolomic fingerprint, acquired through Fourier-Transform Infrared (FTIR) spectroscopy, could support mortality prediction models in COVID-19 ICU patients. A preliminary univariate analysis of serum FTIR spectra revealed significant spectral differences between 21 discharged and 23 deceased patients; however, the most significant spectral bands did not yield high-performing predictive models. By applying a Fast-Correlation-Based Filter (FCBF) for feature selection of the spectra, a set of spectral bands spanning a broader range of molecular functional groups was identified, which enabled Naïve Bayes models with AUCs of 0.79, 0.97, and 0.98 for the first 48 h of ICU admission, seven days prior, and the day of the outcome, respectively, which are, in turn, defined as either death or discharge from the ICU. These findings suggest FTIR spectroscopy as a rapid, economical, and minimally invasive diagnostic tool, but further validation is needed in larger, more diverse cohorts.
AB - Predicting mortality in intensive care units (ICUs) is essential for timely interventions and efficient resource use, especially during pandemics like COVID-19, where high mortality persisted even after the state of emergency ended. Current mortality prediction methods remain limited, especially for critically ill ICU patients, due to their dynamic metabolic changes and heterogeneous pathophysiological processes. This study evaluated how the serum metabolomic fingerprint, acquired through Fourier-Transform Infrared (FTIR) spectroscopy, could support mortality prediction models in COVID-19 ICU patients. A preliminary univariate analysis of serum FTIR spectra revealed significant spectral differences between 21 discharged and 23 deceased patients; however, the most significant spectral bands did not yield high-performing predictive models. By applying a Fast-Correlation-Based Filter (FCBF) for feature selection of the spectra, a set of spectral bands spanning a broader range of molecular functional groups was identified, which enabled Naïve Bayes models with AUCs of 0.79, 0.97, and 0.98 for the first 48 h of ICU admission, seven days prior, and the day of the outcome, respectively, which are, in turn, defined as either death or discharge from the ICU. These findings suggest FTIR spectroscopy as a rapid, economical, and minimally invasive diagnostic tool, but further validation is needed in larger, more diverse cohorts.
KW - FTIR spectroscopy
KW - ICU mortality prediction
KW - omics
KW - serum biomarkers
UR - http://www.scopus.com/inward/record.url?scp=85213222840&partnerID=8YFLogxK
U2 - 10.3390/ijms252413609
DO - 10.3390/ijms252413609
M3 - Article
AN - SCOPUS:85213222840
SN - 1661-6596
VL - 25
JO - International Journal of Molecular Sciences
JF - International Journal of Molecular Sciences
IS - 24
M1 - 13609
ER -