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Study on Machine Learning-Based Diagnosis and Risk Stratification Model for Acute Alcohol Intoxication

Study on Machine Learning-Based Diagnosis and Risk Stratification Model for Acute Alcohol Intoxication

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2600126236
Enrollment
Unknown
Registered
2026-06-05
Start date
2026-06-20
Completion date
Unknown
Last updated
2026-06-08

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Acute alcohol intoxication, symptoms

Interventions

Non-acute alcohol intoxication group:None
Acute alcohol intoxication group:None

Sponsors

The First Affiliated Hospital of Army Medical University
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to 65 Years

Inclusion criteria

Inclusion criteria: 1. Age 18-65 years old; 2. Patients who have previously visited the emergency department of each center; 3. Outpatient or discharge diagnoses include "alcohol poisoning/ethanol poisoning/alcohol overdose/ethanol overdose/drunkenness"; 4. Complete routine laboratory tests (such as blood routine, biochemical indicators, coagulation function, electrolytes, or blood gas analysis, etc.) within 6 hours of visit; 5. Complete clinical data records available for research analysis.

Exclusion criteria

Exclusion criteria: 1. Severe combined trauma (such as severe craniocerebral injury or multiple injuries) that may significantly affect laboratory indicators; 2. Clear presence of other toxins or drug poisoning (such as sedative-hypnotic drugs, pesticides, or drug abuse); 3. History of severe liver failure, end-stage renal disease, or other serious underlying diseases that may affect study indicators; 4. Critical clinical data are seriously missing, making statistical analysis impossible; 5. Pregnant patients; 6. Patients who received diagnosis and treatment at another hospital before visiting;

Design outcomes

Primary

MeasureTime frame
Area Under the Curve (AUC);

Secondary

MeasureTime frame
Sensitivity and Specificity;Accuracy and F1-score;

Countries

China

Contacts

Public ContactXiang Qiang

The First Affiliated Hospital of Army Medical University

xqiang163@163.com+86 23 68765650

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Jun 11, 2026