Sepsis in the era of data-driven medicine: personalizing risks, diagnoses, treatments and prognoses

Abstract

Sepsis is a series of clinical syndromes caused by the immunological response to infection. The clinical evidence for sepsis could typically attribute to bacterial infection or bacterial endotoxins, but infections due to viruses, fungi or parasites could also lead to sepsis. Regardless of the etiology, rapid clinical deterioration, prolonged stay in intensive care units and high risk for mortality correlate with the incidence of sepsis. Despite its prevalence and morbidity, improvement in sepsis outcomes has remained limited. In this comprehensive review, we summarize the current landscape of risk estimation, diagnosis, treatment and prognosis strategies in the setting of sepsis and discuss future challenges. We argue that the advent of modern technologies such as in-depth molecular profiling, biomedical big data and machine intelligence methods will augment the treatment and prevention of sepsis. The volume, variety, veracity and velocity of heterogeneous data generated as part of healthcare delivery and recent advances in biotechnology-driven therapeutics and companion diagnostics may provide a new wave of approaches to identify the most at-risk sepsis patients and reduce the symptom burden in patients within shorter turnaround times. Developing novel therapies by leveraging modern drug discovery strategies including computational drug repositioning, cell and gene-therapy, clustered regularly interspaced short palindromic repeats -based genetic editing systems, immunotherapy, microbiome restoration, nanomaterial-based therapy and phage therapy may help to develop treatments to target sepsis. We also provide empirical evidence for potential new sepsis targets including FER and STARD3NL. Implementing data-driven methods that use real-time collection and analysis of clinical variables to trace, track and treat sepsis-related adverse outcomes will be key. Understanding the root and route of sepsis and its comorbid conditions that complicate treatment outcomes and lead to organ dysfunction may help to facilitate identification of most at-risk patients and prevent further deterioration. To conclude, leveraging the advances in precision medicine, biomedical data science and translational bioinformatics approaches may help to develop better strategies to diagnose and treat sepsis in the next decade.

Integrated Analysis of Gene Co-Expression Network and Prediction Model Indicates Immune-Related Roles of the Identified Biomarkers in Sepsis and Sepsis-Induced Acute Respiratory Distress Syndrome

“…Sepsis has emerged as a life-threatening condition, and ARDS induced by sepsis has added massive destructions and posed a great threat worldwide for the unavailability of efficient risk prediction, accurate genetic diagnosis, and molecular intervention; thus, se-ARDS gave rise to poor outcome and prognosis and limited effective prevention and therapy ( 5 ). The early prediction, recognition, and diagnosis of sepsis/se-ARDS are critical for appropriate treatment, while bioinformatics analysis provides an ideal method to screen large-scale gene expression data to explore the underlying mechanism of sepsis/se-ARDS ( 10 ).…”

“…In the era of data-driven medicine, large numbers of analysisbased researches, especially bioinformatics analysis, have erupted and penetrated into the field of infection-related diseases, including sepsis/se-ARDS (10,11). However, most of these studies focused on the primary stages of simple differential expression and functional analysis (12)(13)(14)(15).…”

The diagnostic value of next-generation sequencing technology in sepsis

“…According recent studies ( Voiriot et al., 2016 ; Southeast Asia Infectious Disease Clinical Research Network, 2017 ; Liu et al., 2020 ), viruses should play an important role in sepsis. However, viruses were not considered as an important causative agent of sepsis in previous study ( Long et al., 2016 ).…”

A Novel Design For A COVID-19 Diagnosis System Using Machine Learning And Drone Technology (COVIDRONE-20)

“…This is especially important as high body temperature is not something unique to COVID-19. In conclusion, early identification of disease is vital for the prevention of possible future outbreaks, however current techniques and methods being used to monitor and diagnose potential patients in realtime lack versatility, efficiency, and accuracy [23,24]. Therefore a new system was needed, hence the development of COVIDRONE -20, a more efficient, more accurate, and more versatile diagnosis or monitoring system [25][26][27][28][29][30].…”