Early Mortality Prediction in Intensive Care Unit Patients Based on Serum Metabolomic Fingerprint DOI Open Access
Rúben Araújo, Luís Ramalhete, Cristiana P. Von Rekowski

et al.

International Journal of Molecular Sciences, Journal Year: 2024, Volume and Issue: 25(24), P. 13609 - 13609

Published: Dec. 19, 2024

Predicting mortality in intensive care units (ICUs) is essential for timely interventions and efficient resource use, especially during pandemics like COVID-19, where high persisted even after the state of emergency ended. Current prediction methods remain limited, critically ill ICU patients, due to their dynamic metabolic changes heterogeneous pathophysiological processes. This study evaluated how serum metabolomic fingerprint, acquired through Fourier-Transform Infrared (FTIR) spectroscopy, could support models COVID-19 patients. A preliminary univariate analysis FTIR spectra revealed significant spectral differences between 21 discharged 23 deceased patients; however, most bands did not yield high-performing predictive models. By applying a Fast-Correlation-Based Filter (FCBF) feature selection spectra, set spanning broader range molecular functional groups was identified, which enabled Naïve Bayes with AUCs 0.79, 0.97, 0.98 first 48 h admission, seven days prior, day outcome, respectively, are, turn, defined as either death or discharge from ICU. These findings suggest spectroscopy rapid, economical, minimally invasive diagnostic tool, but further validation needed larger, more diverse cohorts.

Language: Английский

The Role of Monocyte Distribution Width (MDW) in the Prediction of Death in Adult Patients with Sepsis DOI Creative Commons
Dimitrios Theodoridis, Angeliki Tsifi, Emmanouil Magiorkinis

et al.

Microorganisms, Journal Year: 2025, Volume and Issue: 13(2), P. 427 - 427

Published: Feb. 15, 2025

Sepsis is a life-threatening condition; it major cause of hospital mortality worldwide and constitutes global health problem. This research investigates the use MDW as predictor for septic patients. was double-center prospective cohort study adult Septic patients were identified categorized into two categories: those who improved died. Blood drawn from three times, on first, third, fifth day their admission to hospital. evaluated biomarker predict patient outcome. In addition, existing inflammatory markers recorded in all The able patient's average found be significantly higher died records. For example, an value 28.4 first shown best cut-off determining fatal outcomes; receiver operating characteristic (ROC) analysis revealed area under curve 0.71 (95% Confidence Interval-CI: 0.57-0.84) with sensitivity 64.7% specificity 88.2%. conclusion, MDW, addition being marker that can quickly detect sepsis more effectively than other biomarkers, which proven by numerous studies, could also used indicator work attempt direction.

Language: Английский

Citations

0
Procalcitonin and interleukin- 6 in predicting prognosis of sepsis patients with cancer DOI

Yang Lyu,

Tao Han, Z. Zhang

et al.

Supportive Care in Cancer, Journal Year: 2025, Volume and Issue: 33(5)

Published: April 22, 2025

Language: Английский

Citations

0
Early Mortality Prediction in Intensive Care Unit Patients Based on Serum Metabolomic Fingerprint DOI Open Access
Rúben Araújo, Luís Ramalhete, Cristiana P. Von Rekowski

et al.

International Journal of Molecular Sciences, Journal Year: 2024, Volume and Issue: 25(24), P. 13609 - 13609

Published: Dec. 19, 2024

Predicting mortality in intensive care units (ICUs) is essential for timely interventions and efficient resource use, especially during pandemics like COVID-19, where high persisted even after the state of emergency ended. Current prediction methods remain limited, critically ill ICU patients, due to their dynamic metabolic changes heterogeneous pathophysiological processes. This study evaluated how serum metabolomic fingerprint, acquired through Fourier-Transform Infrared (FTIR) spectroscopy, could support models COVID-19 patients. A preliminary univariate analysis FTIR spectra revealed significant spectral differences between 21 discharged 23 deceased patients; however, most bands did not yield high-performing predictive models. By applying a Fast-Correlation-Based Filter (FCBF) feature selection spectra, set spanning broader range molecular functional groups was identified, which enabled Naïve Bayes with AUCs 0.79, 0.97, 0.98 first 48 h admission, seven days prior, day outcome, respectively, are, turn, defined as either death or discharge from ICU. These findings suggest spectroscopy rapid, economical, minimally invasive diagnostic tool, but further validation needed larger, more diverse cohorts.

Language: Английский

Citations

0