Understanding sepsis

Nagalingam, Karen

doi:10.12968/bjon.2018.27.20.1168

Cited by 5 publications

(3 citation statements)

References 10 publications

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“…Severity and prognosis evaluation can help design an early and effective clinical treatment plan [ 79 ]. Sepsis scoring tools are diverse and continuously evolving as the definition of sepsis is updated.…”

Section: Sepsismentioning

confidence: 99%

“…Accurate diagnosis of sepsis is difficult to achieve with any single biomarker, and the combination of multiple biomarkers and sepsis scores can improve the accuracy of sepsis diagnosis and prognosis determination [78]. Severity and prognosis evaluation can help design an early and effective clinical treatment plan [79]. Sepsis scoring tools are diverse and continuously evolving as the definition of sepsis is updated.…”

Section: Sepsismentioning

confidence: 99%

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Research Progress of DcR3 in the Diagnosis and Treatment of Sepsis

Su,

Tong,

et al. 2023

IJMS

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Decoy receptor 3 (DcR3), a soluble glycosylated protein in the tumor necrosis factor receptor superfamily, plays a role in tumor and inflammatory diseases. Sepsis is a life-threatening organ dysfunction caused by the dysregulation of the response to infection. Currently, no specific drug that can alleviate or even cure sepsis in a comprehensive and multi-level manner has been found. DcR3 is closely related to sepsis and considerably upregulated in the serum of those patients, and its upregulation is positively correlated with the severity of sepsis and can be a potential biomarker for diagnosis. DcR3 alone or in combination with other markers has shown promising results in the early diagnosis of sepsis. Furthermore, DcR3 is a multipotent immunomodulator that can bind FasL, LIGHT, and TL1A through decoy action, and block downstream apoptosis and inflammatory signaling. It also regulates T-cell and macrophage differentiation and modulates immune status through non-decoy action; therefore, DcR3 could be a potential drug for the treatment of sepsis. The application of DcR3 in the treatment of a mouse model of sepsis also achieved good efficacy. Here, we introduce and discuss the progress in, and suggest novel ideas for, research regarding DcR3 in the diagnosis and treatment of sepsis.

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Section: Sepsismentioning

confidence: 99%

Section: Sepsismentioning

confidence: 99%

Research Progress of DcR3 in the Diagnosis and Treatment of Sepsis

Su,

Tong,

et al. 2023

IJMS

View full text Add to dashboard Cite

show abstract

“…Research has been conducted in monitoring patients with sepsis using wearable sensor monitors in low-and middle-income countries [2]. Despite the fact that these techniques may give useful information, they may not always be adequate to provide an accurate diagnosis [3]. By examining a higher number of characteristics and using the power of data-driven decisionmaking, machine learning techniques, such as ensemble classifers, have the potential to increase the accuracy of sepsis diagnosis [4].…”

Section: Introductionmentioning

confidence: 99%

Conditional Tabular Generative Adversarial Net for Enhancing Ensemble Classifiers in Sepsis Diagnosis

Alfakeeh,

Sharif,

Zorto

et al. 2023

Applied Computational Intelligence and Soft Computing

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Antibiotic-resistant bacteria have proliferated at an alarming rate as a result of the extensive use of antibiotics and the paucity of new medication research. The possibility that an antibiotic-resistant bacterial infection would progress to sepsis is one of the major collateral problems affecting people with this condition. 31,000 lives were lost due to sepsis in England with costs about two billion pounds annually. This research aims to develop and evaluate several classification approaches to improve predicting sepsis and reduce the tendency of underdiagnosis in computer-aided predictive tools. This research employs medical datasets for patients diagnosed with sepsis, and it analyses the efficacy of ensemble machine learning techniques compared to nonensemble machine learning techniques and the significance of data balancing and conditional tabular generative adversarial nets for data augmentation in producing reliable diagnosis. The average F Score obtained by the nonensemble models trained in this paper is 0.83 compared to the ensemble techniques average of 0.94. Nonensemble techniques, such as Decision Tree, achieved an F score of 0.90, an AUC of 0.90, and an accuracy of 90%. Histogram-basedgradient boosting classification tree achieved an F score of 0.96, an AUC of 0.96, and an accuracy of 95%, surpassing the other models tested. Additionally, when compared to the current state-of-the-art sepsis prediction models, the models developed in this study demonstrated higher average performance in all metrics, indicating reduced bias and improved robustness through data balancing and conditional tabular generative adversarial nets for data augmentation. The study revealed that data balancing and augmentation on the ensemble machine learning algorithms boost the efficacy of clinical predictive models and can help clinics decide which data types are most important when examining patients and diagnosing sepsis early through intelligent human-machine interface.

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Early Recognition and Management of Sepsis in the Elderly

Onawola

2021

Critical Care Nursing Quarterly

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Sepsis is a life-threatening and debilitating sickness in the elderly. This case study explores the importance of adequate assessment of patients on their initial presentation to the emergency department, during hospitalization, and before discharge. The clinical evaluation, recognition, and management of sepsis continue to be essential for patient survival to prevent and decrease the mortality rate. Some changes go on in the elderly organ systems and can lead to delay in identifying and treatment implementation. The use of the Third International Consensus Definition for Sepsis and Septic Shock (Sepsis-3) to anticipate outcomes in septic patients and the use of the Survival Sepsis Campaign for treatment guidelines promptly to improve outcomes are crucial. This article aims to inform clinicians and nurses of the importance of early recognition of subtle signs and symptoms and the management of sepsis in the elderly.

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Understanding sepsis

Cited by 5 publications

References 10 publications

Research Progress of DcR3 in the Diagnosis and Treatment of Sepsis

Research Progress of DcR3 in the Diagnosis and Treatment of Sepsis

Conditional Tabular Generative Adversarial Net for Enhancing Ensemble Classifiers in Sepsis Diagnosis

Early Recognition and Management of Sepsis in the Elderly

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