Performance of Sofa Score in Predicting the Risk of Mortality in Children With Sepsis

BUI, Quang Nghia; HA, Thanh Hieu; DUONG, Linh My; TRAN, Duc Long; NGUYEN, Tien Dat; PHAM, Tin Trung; TRAN, Van De

doi:10.31688/abmu.2023.58.1.03

Arch Balk Med Union

2023

DOI: 10.31688/abmu.2023.58.1.03

|View full text |Cite

Performance of Sofa Score in Predicting the Risk of Mortality in Children With Sepsis

Quang Nghia BUI¹,

Thanh Hieu HA²,

Linh My DUONG³

et al.

Abstract: La performance du score SOFA dans la prévision du risque de mortalité chez les enfants atteints de sepsisIntroduction. La septicémie est une maladie clinique complexe et l'une des principales causes de décès chez les enfants. Le score SOFA (Sequential Organ Failure Assessment) est un outil utile pour évaluer le risque de décès chez les patients atteints de septicémie. L'objectif de l'étude était de déterminer l'utilité du score SOFA pour prédire la mortalité chez les enfants atteints de septicémie. Matériels e… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Article1

Relationship

Self Cite0

Independent1

Authors

Journals

Cited by 1 publication

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Utilizing Predictive Factors as a Screening Tool for Early-Onset Sepsis in Neonates

Tran,

Tran

et al. 2024

Cureus

View full text Add to dashboard Cite

Introduction: Neonatal early-onset sepsis (EOS) is a severe condition that affects newborns within the first three days of life, with high mortality rates, particularly in low- and middle-income countries (LMICs). In Vietnam, the diagnosis and management of EOS are challenged by ambiguous clinical signs and limited access to blood culture testing facilities. Early identification of at-risk neonates using a predictive risk factor model is crucial for improving neonatal care and reducing mortality. Objectives: This study aims to identify maternal and neonatal risk factors associated with EOS and develop a predictive screening tool to facilitate the early detection of at-risk neonates in Vietnam. Materials and methods: A nested case-control study was conducted on 225 neonates at the central neonatal unit in a principal tertiary hospital in southwestern Vietnam over a two-year period. Risk factors were identified using univariable and multivariable logistic regression analyses. A predictive nomogram was developed and evaluated for discrimination, calibration, and decision curve analysis (DCA). Results: The study identified eight significant risk factors for EOS, including maternal genital infections during the third trimester, urinary tract infections (UTIs) during pregnancy, hypertension during pregnancy, insufficient maternal weight gain, rupture of membranes (ROM) ≥18 hours, meconium-stained amniotic fluid, first-minute APGAR score <7, and preterm birth <34 weeks. The predictive model demonstrated excellent discrimination with an area under the curve (AUC) of 0.913 (95% CI: 0.876-0.95, p<0.001) and good calibration (Hosmer-Lemeshow test with χ²(df)=5.496 (5), p=0.358). The model-based nomogram showed high sensitivity (82.7%) and specificity (83.3%) at an optimal cutoff of 0.25. The DCA illustrates the model's good clinical utility, providing a higher net benefit across most threshold probability ranges (0.0-0.96). Conclusions: This study presents a robust predictive model for the early identification of neonates at risk of EOS in Vietnam, based on key maternal and neonatal risk factors. The model, with demonstrated accuracy and reliability, holds significant potential for improving neonatal outcomes through timely interventions. Future research should aim at external validation and inclusion of broader clinical data to enhance the model's applicability and generalizability.

show abstract

Utilizing Predictive Factors as a Screening Tool for Early-Onset Sepsis in Neonates

Tran,

Tran

et al. 2024

Cureus

View full text Add to dashboard Cite

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Performance of Sofa Score in Predicting the Risk of Mortality in Children With Sepsis

Cited by 1 publication

References 21 publications

Utilizing Predictive Factors as a Screening Tool for Early-Onset Sepsis in Neonates

Utilizing Predictive Factors as a Screening Tool for Early-Onset Sepsis in Neonates

Contact Info

Product

Resources

About