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Sepsis prediction software at the point-of-care in ICU

NAVOY® is CE-marked and clinically validated1

Uses ICU data
through EHR/PDMS integration
Autonomous
3-hour foresight 24/7

Provides actionable insights at your fingertips

Benefits with NAVOY® in intensive and critical care

Augments ICU teams with actionable information

By leveraging machine learning technologies validated using data from over 60,000 ICU stays, NAVOY® can forecast patients’ risk of sepsis 3 hours before rule based scoring systems. Our software supports confident clinical decisions that allows earlier interventions which improve outcomes and helps reducing healthcare costs.2

Clinical decision support without  clinician fatigue

Intelligent care augmentation which can be adjusted to fit the caregiver’s preferences with regards to sensitivity and specificity.

24/7 proactive support to reduce caregiver burden 

By forecasting sepsis with 3 hours foresight, NAVOY®  surfaces actionable, contextualized clinical inferences within EHR workflows, allowing providers to react and intervene in a timely manner.

Real-time prediction via AlgoDx platform integration

NAVOY® tracks a selection of vital parameters, blood tests and other patient information already collected at the ICU, to deliver real-time insights.3

Clinical parameters used by NAVOY® for sepsis predictions

  • Age
  • Gender
  • Heart rate
  • Respiratory rate
  • Temperature
  • Systolic blood pressure
  • Diastolic blood pressure
  • Vasopressor use
  • Serum creatinine
  • Glucose
  • Lactate
  • Platelets
  • White blood cell count
  • Blood urea nitrogen
  • Bilirubin
  • pH
  • Oxygen saturation pulse oximetry
  • Fraction of inspired oxygen
  • International Normalized Ratio
  • Glasgow Coma Scale

AlgoDx products in the clinical workflow – case study: NAVOY® 

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You’re in good company

AlgoDx – proud to partner with renowned stakeholders in healthcare

GE Healthcare
Philips Healthcare
Cone Health
  1. Sjövall F, Persson I. Poster presentation at SCCM Society of Critical Care Medicine, San Francisco, January 21-24 2023. 
  2. Ericson O, Hjelmgren J, Sjövall F, Söderberg J, Persson I. The Potential Cost and Cost-Effectiveness Impact of Using a Machine Learning Algorithm for Early Detection of Sepsis in Intensive Care Units in Sweden. JHEOR. 2022;9(1):101-110. doi:10.36469/jheor.2022.33951
  3.  Persson I, Östling A, Arlbrandt M, Söderberg J, Becedas D. A Machine Learning Sepsis Prediction Algorithm for Intended Intensive Care Unit Use (NAVOY Sepsis): Proof-of-Concept Study. JMIR Form Res 2021;5(9):e28000. DOI: 10.2196/28000
  4. Persson I, Macura A, Becedas D, Sjövall F. Early prediction of sepsis in intensive care patients using the machine learning algorithm NAVOY® Sepsis, a prospective randomized clinical validation study. J Crit Care. 2024 Apr;80:154400. doi: 10.1016/j.jcrc.2023.154400.