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

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.

Study Overview

• Status: Completed
• Conditions: Sepsis; ARDS (Acute Respiratory Distress Syndrome); AKI - Acute Kidney Injury
• Intervention / Treatment: Other: No intervention (Observational study)

• Study Type: Observational
• Enrollment (Actual): 55940

Contacts and Locations

Study Locations

• China
  • Chongqing Municipality
    • Chongqing, Chongqing Municipality, China, 400016
      • Chongqing Medical University

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: No

• 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.

Description

Inclusion Criteria:

• 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).

Exclusion Criteria:

• 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).

Study Plan

How is the study designed?

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
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).

Collaborators and Investigators

• Sponsor: Chongqing Medical University

Study record dates

Study Major Dates

• Study Start (Actual): October 1, 2017
• Primary Completion (Actual): January 31, 2024
• Study Completion (Actual): January 31, 2024

Study Registration Dates

• First Submitted: December 10, 2025
• First Submitted That Met QC Criteria: December 24, 2025
• First Posted (Actual): January 5, 2026

Study Record Updates

• Last Update Posted (Actual): January 5, 2026
• Last Update Submitted That Met QC Criteria: December 24, 2025
• Last Verified: December 1, 2025

More Information

Terms related to this study

• Additional Relevant MeSH Terms: Urogenital Diseases; Pathologic Processes; Male Urogenital Diseases; Kidney Diseases; Urologic Diseases; Female Urogenital Diseases; Female Urogenital Diseases and Pregnancy Complications; Infections; Respiratory Tract Diseases; Systemic Inflammatory Response Syndrome; Inflammation; Lung Diseases; Renal Insufficiency; Lung Injury; Pathological Conditions, Signs and Symptoms; Acute Kidney Injury; Sepsis; Acute Lung Injury; Investigative Techniques; Methods; Observation
• Other Study ID Numbers: 2024167

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO
• IPD Plan Description: The individual participant data (IPD) underlying the results of this study cannot be made publicly available due to restrictions imposed by Chinese data protection laws and regulations, as well as the data use agreements with the source hospital(s). The data contain sensitive clinical information, and public sharing would compromise patient privacy and confidentiality. Aggregated data or analysis results will be made available in the published manuscript. Requests for specific analyses can be directed to the corresponding author.

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No