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Development of a Novel Algorithm for Real-Time Bedside Assessment of Insulin Resistance in Critically Ill Patients Based on Continuous Glucose Monitoring Data

Development of a Novel Algorithm for Real-Time Bedside Assessment of Insulin Resistance in Critically Ill Patients Based on Continuous Glucose Monitoring Data: A Multicenter, Observational, Prospective Study

Status
Completed
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT07385391
Enrollment
179
Registered
2026-02-04
Start date
2023-07-13
Completion date
2025-10-01
Last updated
2026-02-04

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Critical Illness, Insulin Resistance, Metabolism Disorders

Keywords

Metabolic Monitoring, Insulin Resistance, Prognosis

Brief summary

This study aims to develop and validate a novel algorithm for the real-time assessment of insulin resistance in critically ill patients using Continuous Glucose Monitoring (CGM). Current methods for assessing insulin resistance are often invasive or unfeasible in the intensive care setting. By analyzing the dynamic correlation between CGM readings and reference blood glucose fluctuations, the investigators seek to construct a new algorithmic metric. The study will further evaluate the association of this new metric with established insulin resistance indices, organ function, and patient clinical outcomes.

Detailed description

Insulin resistance (IR) is prevalent among critically ill patients, particularly those with sepsis, and is significantly associated with increased mortality, prolonged length of stay, and infectious complications. Consequently, real-time and accurate bedside monitoring of the degree of insulin resistance in this population is of paramount importance. Current clinical modalities for assessing insulin resistance (IR) in critical illness remain insufficient. The "gold standard" hyperinsulinemic-euglycemic clamp (HEC) is restricted by invasiveness, complexity, and cost, while its artificial steady-state fails to reflect glucose dynamics under acute stress. Alternatively, HOMA-IR is a static, hepatic-focused measure; its reliance on fasting baselines is often unfeasible due to continuous nutrition, precluding accurate assessment of peripheral glucose disposal. Similarly, the Oral Glucose Tolerance Test (OGTT) is limited by gastrointestinal dysmotility and confounded by stress-induced insulin dysregulation. Consequently, a novel strategy for real-time, dynamic, and bedside IR assessment is urgently required to overcome these limitations. This study aims to develop a novel algorithm for the real-time, bedside assessment of insulin resistance utilizing continuous glucose monitoring (CGM) data. A primary focus is the evaluation of the capability of CGM to capture dynamic glycemic fluctuations; specifically, the correlation between the magnitude of change in reference blood glucose between time points and the concurrent change in CGM readings will be analyzed. Based on the concordance of these dynamic variations, a new algorithmic metric is to be constructed. Subsequently, the association of this metric with established insulin resistance indices, organ function, and patient prognosis will be investigated to validate its clinical utility as a minimally invasive tool for monitoring metabolic status in critically ill patients.

Interventions

None listed

Sponsors

Chinese Medical Association
Lead SponsorNETWORK

Study design

Observational model
COHORT
Time perspective
PROSPECTIVE

Eligibility

Sex/Gender
ALL
Age
18 Years to 80 Years
Healthy volunteers
No

Inclusion criteria

* Age≥ 18 years and \< 80 years * ICU stay ≤48 hours * Expected ICU stay \> 24 hours * APACHE II score≥ 8

Exclusion criteria

* local infection within the sensor placement area * Laparotomy within lower abdomen * Participated in this study before * In other clinical trails

Design outcomes

Primary

MeasureTime frameDescription
ICU MortalityFrom date of study enrollment until the date of ICU discharge or date of death from any cause, whichever came first, assessed up to 60 daysThe incidence of all-cause death during the patient's stay in the Intensive Care Unit

Secondary

MeasureTime frameDescription
Incidence of HyperglycemiaFrom date of study enrollment until ICU discharge, assessed up to 30 days.The proportion of participants who experience at least one episode of hyperglycemia during the observation period. Hyperglycemia is defined as a blood glucose level greater than 180 mg/dL (10 mmol/L).
Incidence of HypoglycemiaFrom date of study enrollment until ICU discharge, assessed up to 30 days.The proportion of participants who experience at least one episode of hypoglycemia during the observation period. Hypoglycemia is defined as a blood glucose level less than 70 mg/dL (3.9 mmol/L). Severe hypoglycemia is defined as less than 40 mg/dL (2.2 mmol/L).
Duration of Vasopressor DependencyFrom date of study enrollment until the date of vasopressor cessation for at least 24 hours, assessed up to 30 days.The total length of time a patient requires continuous intravenous vasoactive drugs to maintain adequate blood pressure.
Duration of Invasive Mechanical VentilationFrom date of study enrollment until the date of successful extubation, tracheostomy, or death from any cause, whichever came first, assessed up to 30 daysThe total length of time a patient requires endotracheal intubation and support from a mechanical ventilator.
Duration of Continuous Renal Replacement Therapy (CRRT)From date of study enrollment until the date of CRRT discontinuation for at least 24 hours or death from any cause, whichever came first, assessed up to 30 days.The total length of time a patient requires continuous renal replacement therapy for acute kidney injury.

Countries

China

Contacts

PRINCIPAL_INVESTIGATORWenkui Yu, PhD, Professor

The Affiliated Nanjing Drum Tower Hospital of Nanjing University Medical School

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026