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

C

Chongqing Medical University

Status

Completed

Conditions

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

Treatments

Other: No intervention (Observational study)

Study type

Observational

Funder types

Other

Identifiers

NCT07317817
2024167

Details and patient eligibility

About

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.

Enrollment

55,940 patients

Sex

All

Ages

18+ years old

Volunteers

No Healthy Volunteers

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).

Trial contacts and locations

1

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Data sourced from clinicaltrials.gov

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