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NCT Number: NCT07385391

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

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.

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Key information

Conditions

Critical Illness Disease Attributes Glucose Metabolism Disorders Hyperinsulinism Insulin Resistance Metabolic Diseases Metabolism Disorders Nutritional and Metabolic Diseases Pathologic Processes Pathological Conditions, Signs and Symptoms

Age range

18 year–80 year

Sex eligibility

All sexes

Study type

Observational

Primary location

Nanjing Drum Tower Hospital

Nanjing, Jiangsu, 210000, China

About this study

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.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

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

Treatment and study plan

Primary outcomes

  1. ICU Mortality

    Time frame: From date of study enrollment until the date of ICU discharge or date of death from any cause, whichever came first, assessed up to 60 days

    The incidence of all-cause death during the patient's stay in the Intensive Care Unit

Secondary outcomes

  1. Incidence of Hyperglycemia

    Time frame: From 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).

  2. Incidence of Hypoglycemia

    Time frame: From 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).

  3. Duration of Vasopressor Dependency

    Time frame: From 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.

  4. Duration of Invasive Mechanical Ventilation

    Time frame: From date of study enrollment until the date of successful extubation, tracheostomy, or death from any cause, whichever came first, assessed up to 30 days

    The total length of time a patient requires endotracheal intubation and support from a mechanical ventilator.

  5. Duration of Continuous Renal Replacement Therapy (CRRT)

    Time frame: 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.

Sponsors and collaborators

Lead sponsor

Chinese Medical Association

Network

Registry information

Official study title

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

Important dates

Study start
2023
Primary completion
2024
Study completion
2025
First posted
Feb 4, 2026
Registry last updated
Feb 4, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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