Research on Risk Assessment and Early Warning Models for Adverse Clinical Outcomes in Critically Ill Patients
Trial Snapshot
- Phase
- Not Applicable
- Status
- Completed
- Sponsor
- Enrollment
- 55,940
- Locations
- 1
- Primary Endpoint
- Area Under the Receiver Operating Characteristic Curve (AUROC) for predicting the composite outcome of Sepsis, ARDS, or Acute Kidney Injury
Study Overview
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.
Study Design
- Study Type
- Observational
- Observational Model
- Cohort
- Time Perspective
- Retrospective
Eligibility Criteria
- Ages
- 18 Years to — (Adult, Older Adult)
- Sex
- All
- Accepts Healthy Volunteers
- No
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).
Outcomes
Primary Outcomes
Area Under the Receiver Operating Characteristic Curve (AUROC) for predicting the composite outcome of Sepsis, ARDS, or Acute Kidney Injury
Time Frame: From ICU admission to 7 days after admission (for outcome prediction)
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.
Calibration of predicted risk, measured by the Brier Score
Time Frame: From ICU admission to 7 days after admission (for outcome assessment).
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.
Sensitivity (Recall) for the composite outcome at a pre-defined risk threshold
Time Frame: From ICU admission to 7 days after admission (for outcome assessment).
Performance metric calculated after applying a pre-defined probability cut-off to classify patients as high-risk or low-risk.
Secondary Outcomes
No secondary outcomes reported
Investigators
Yalin Dong
Master's Student
Chongqing Medical University