Research on Risk Assessment and Early Warning Models for Adverse Clinical Outcomes in Critically Ill Patients

NCT07317817 | Completed

• 1 other identifier: 2024167
• Study Type: observational
• Target: 55,940
• Locations: 1 country
• Sites: 1

Brief Summary

This is a medical research study that uses information from past patient hospital records. It focuses on three serious conditions that often affect critically ill patients: sepsis (a life-threatening body-wide infection), ARDS (a severe lung injury that makes breathing very difficult), and acute kidney injury (sudden loss of kidney function). The goal is to better understand which patients in the ICU are at highest risk of developing these conditions or getting worse. Researchers will look at de-identified information from medical records of patients treated in the ICU . The study will use computer analysis to find patterns in the data that may help doctors predict these risks earlier. No new treatments are being tested, and no patients will be contacted or recruited for this study. All data used is anonymous to protect patient privacy.

Conditions

Sepsis; ARDS (Acute Respiratory Distress Syndrome); AKI - Acute Kidney Injury

Outcome Measures

Primary Outcomes (3)

• Area Under the Receiver Operating Characteristic Curve (AUROC) for predicting the composite outcome of Sepsis, ARDS, or Acute Kidney Injury

  The discriminatory power of the machine learning model will be assessed by the AUROC. The value ranges from 0 to 1, with a higher value indicating better ability to distinguish between patients who will and will not experience the composite outcome.

  From ICU admission to 7 days after admission (for outcome prediction)

• Calibration of predicted risk, measured by the Brier Score

  The accuracy of the model's predicted probabilities will be assessed using the Brier Score (range 0 to 1, lower scores indicate better calibration). A calibration plot will be presented to visualize the agreement between predicted and observed event rates.

  From ICU admission to 7 days after admission (for outcome assessment).

• Sensitivity (Recall) for the composite outcome at a pre-defined risk threshold

  Performance metric calculated after applying a pre-defined probability cut-off to classify patients as high-risk or low-risk.

  From ICU admission to 7 days after admission (for outcome assessment).

Interventions

No intervention (Observational study) OTHER

This is a non-interventional, observational study. The aim is to develop and validate a predictive model using existing clinical data. No medical interventions (such as drugs, devices, or procedures) are being administered, assigned, or compared as part of this research protocol. The "intervention" of interest is the application of the predictive model for risk assessment, which is an analytical procedure, not a patient-directed intervention.

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

A retrospective cohort of critically ill adult patients admitted to the intensive care unit (ICU). The study population will be derived from de-identified electronic health records.

You may qualify if:

• Adult patients (age ≥ 18 years).
• Admitted to the ICU with a length of stay ≥ 24 hours.
• Availability of key clinical variables within the first 24 hours of ICU admission (e.g., vital signs, laboratory results, admission diagnosis).

You may not qualify if:

• Patients with incomplete or missing key data for model variables (e.g., missing baseline creatinine, or missing Sequential Organ Failure Assessment (SOFA) score components).
• Patients admitted for palliative care or comfort measures only upon ICU admission.
• Readmissions during the same hospitalization (only the first ICU admission will be included).

Sponsors & Collaborators

• Chongqing Medical University: lead

Study Sites (1)

Chongqing Medical University

Chongqing, Chongqing Municipality, 400016, China

Location

MeSH Terms

Conditions

Sepsis; Acute Lung Injury; Acute Kidney Injury

Interventions

Observation

Condition Hierarchy (Ancestors)

Infections; Systemic Inflammatory Response Syndrome; Inflammation; Pathologic Processes; Pathological Conditions, Signs and Symptoms; Lung Injury; Lung Diseases; Respiratory Tract Diseases; Renal Insufficiency; Kidney Diseases; Urologic Diseases; Female Urogenital Diseases; Female Urogenital Diseases and Pregnancy Complications; Urogenital Diseases; Male Urogenital Diseases

Intervention Hierarchy (Ancestors)

Methods; Investigative Techniques

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Master's Student

Study Record Dates

• First Submitted: December 10, 2025
• First Posted: January 5, 2026
• Study Start: October 1, 2017
• Primary Completion: January 31, 2024
• Study Completion: January 31, 2024
• Last Updated: January 5, 2026

Record last verified: 2025-12

Data Sharing

• IPD Sharing: Will not share

Locations

CN (1)