Impact of Persistent Inflammation, Immunosuppression, and Catabolism Syndrome during Intensive Care Admission on Each Post-Intensive Care Syndrome Component in a PICS Clinic

LASSO-Based Machine Learning Algorithm for Prediction of PICS Associated with Sepsis

Introduction

This study aims to establish a comprehensive, multi-level approach for tackling tropical diseases by proactively anticipating and managing Persistent Inflammation, Immunosuppression, and Catabolism Syndrome (PICS) within the initial 14 days of Intensive Care Unit (ICU) admission. The primary objective is to amalgamate a diverse array of indicators and pathogenic microbial data to pinpoint pivotal predictive variables, enabling effective intervention specifically tailored to the context of tropical diseases.

Methods

A focused analysis was conducted on 1733 patients admitted to the ICU between December 2016 and July 2019. Utilizing the Least Absolute Shrinkage and Selection Operator (LASSO) regression, disease severity and laboratory indices were scrutinized. The identified variables served as the foundation for constructing a predictive model designed to forecast the occurrence of PICS.

Results

Among the subjects, 13.79% met the diagnostic criteria for PICS, correlating with a mortality rate of 38.08%. Key variables, including red-cell distribution width coefficient of variation (RDW-CV), hemofiltration (HF), mechanical ventilation (MV), Norepinephrine (NE), lactic acidosis, and multiple-drug resistant bacteria (MDR) infection, were identified through LASSO regression. The resulting predictive model exhibited a robust performance with an Area Under the Curve (AUC) of 0.828, an accuracy of 0.862, and a specificity of 0.977. Subsequent validation in an independent cohort yielded an AUC of 0.848.

Discussion

The acquisition of RDW-CV, HF requirement, MV requirement, NE requirement, lactic acidosis, and MDR upon ICU admission emerges as a pivotal factor for prognosticating PICS onset in the context of tropical diseases. This study highlights the potential for significant improvements in clinical outcomes through the implementation of timely and targeted interventions tailored specifically to the challenges posed by tropical diseases.

Post-intensive care syndrome: Recent advances and future directions

Post-intensive care syndrome comprises physical, cognitive, and mental impairments in patients treated in an intensive care unit (ICU). It occurs either during the ICU stay or following ICU discharge and is related to the patients' long-term prognosis. The same concept also applies to pediatric patients, and it can greatly affect the mental status of family members. In the 10 years since post-intensive care syndrome was first proposed, research has greatly expanded. Here, we summarize the recent evidence on post-intensive care syndrome regarding its pathophysiology, epidemiology, assessment, risk factors, prevention, and treatments. We highlight new topics, future directions, and strategies to overcome post-intensive care syndrome among people treated in an ICU. Clinical and basic research are still needed to elucidate the mechanistic insights and to discover therapeutic targets and new interventions for post-intensive care syndrome.