The clinical use of measurements of inflammatory markers for diagnosing and monitoring different disease types is now routine. However, many inflammatory markers (e.g. CRP, IL-6, TNF-α, etc.) are non-specific and provide just little or ambiguous information about the exact cause, the progress and the severity of the inflammation. Variability among patients is also high due to influences of co-factors such as age, gender, genomic disposition and individual health conditions. Rather than relying solely on measured values, clinicians must consider the entire clinical picture of the patient, including the medical history, other diagnostic tests, nutritional state and current treatment of the patient. In practice it may not be feasible to obtain these informations at the right time, and besides, point-of-care tests for inflammatory markers could be expensive or unavailable. In conclusion, inflammatory pathways are well understood and “markers” of inflammation widely used, but there exists a large potential and need for specific just-in-time interpretation to give individual test results a greater value.

Glucosafe is a decision support system which wraps a mathematical compartment model of insulin and glucose metabolism. Parameters for the model include patient anthropometrics, gender and state of diabetes, and the model uses blood glucose measurements and previous data from insulin therapy and nutrition to estimate the patient-specific insulin sensitivity, a surrogate marker of inflammatory state and disease. The Glucosafe system then helps clinicians decide which nutrition and insulin therapy is optimal by applying the insulin sensitivity to predictions of the blood glucose response. The uniqueness of the tool lies in the intrinsic replicability of its calculations and decisions for treatment, making it an ideal tool to study both the inflammatory and the anti-inflammatory response in connection to measurements of relevant markers.

For illustration, a ficticious example is given: The calculated insulin sensitivity of a muscular male 35-year old non-diabetic patient with a height of 200 cm could be the same as the insulin sensitivity of a fragile diabetic 90-year old female with a height of 155 cm, because relative to their body composition both persons may experience a similar inflammatory state. Glucosafe’s model adapts to the inert differences (e.g: plasma volume, gender, etc.) and suggests nutrition and insulin treatment that may differ in quantity (male: 4 IU/h + 3000 kcal/d; female: 1.5 IU/h + 1800 kcal/d), but will result in very similar blood glucose responses. In this way, Glucosafe equalizes patients metabolically and removes the “noise” from important cofactors that are impacting inflammation, such as physiology, diabetes state, glycaemic treatment, and nutrition. For example, the types and amounts of nutrients consumed influence the body's inflammatory response in various ways. Likewise, insulin significantly exerts several anti-inflammatory effects. By removing the noise from metabolic cofactors, the Glucosafe tool enables us to study the quality of diagnostic signals of inflammation in humans under comparable and replicable metabolic conditions.

The Glucosafe model and system has so far been used for optimizing the nutrition and insulin treatment of critically ill patients. Safety and efficacy were demonstrated in 3 small pilot studies (N1=10, N2=12, N3=13), while results from a larger randomized controlled clinical trial (N=142) are expected by the end of 2024.

Critical illness engages the same inflammatory pathways as other medical conditions (e.g. type 2-diabetes, obesity, cancerous diseases). Glucosafe could be used in clinical experimental designs for the study of inflammatory marker types, their specificity, their importance, and their variability over the course of illness.

Envisioned project partners:

- industry partners specializing in developing diagnostic point-of-care test kits of inflammatory markers 

- university hospitals with experienced researchers in critical or severe illness

- research partners specializing in inflammatory diagnostics.