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Comparison of NEWS2 and Machine Learning for Early Sepsis Warning

NCT07734480 · Status: ACTIVE_NOT_RECRUITING · Type: OBSERVATIONAL · Enrollment: 100

Last updated 2026-08-13

No results posted yet for this study

Summary

This prospective observational study aims to objectively measure the lead-time (the time from the first KDS alert to sepsis diagnosis) of the NEWS2-based clinical decision support system (KDS) and compare its early warning performance with a machine learning model trained on 2000 patients and externally validated. The study seeks to answer the following main questions:

How early does the NEWS2-based KDS provide an alert before sepsis diagnosis?

Does a machine learning model, developed using logistic regression and externally validated in a prospective cohort, offer superior specificity and comparable sensitivity to KDS?

Participants who are already receiving routine clinical care at Kocaeli City Hospital will have their vital signs and laboratory data monitored as part of standard practice. NEWS2 scores will be calculated automatically and the time of the first alert (T0) will be recorded. Sepsis diagnosis will be confirmed by an increase in SOFA score ≥ 2 (T1), evaluated by two independent and blinded physicians. Lead-time will be calculated as the difference between T1 (hours×60) and T0 (minutes). The machine learning model will be tested prospectively on this cohort, and its performance will be compared with KDS using sensitivity, specificity, F1 score, ROC-AUC, and accuracy.

Conditions

  • Sepsis
  • News-2
  • Machine Learning

Interventions

OTHER

Observational Study - No Intervention

Observational Study - No Intervention

Sponsors & Collaborators

  • Kocaeli Derince Education and Research Hospital

    lead OTHER

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2026-07-22
Primary Completion
2026-08-11
Completion
2026-08-13

Countries

  • Turkey (Türkiye)

Study Locations

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Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07734480 on ClinicalTrials.gov