Development of Clinical Decision Support System for Severe Patients With Polytrauma

NCT06323096 | Recruiting DMC

• 1 other identifier: AR13067824
• Study Type: observational
• Target: 500
• Locations: 1 country
• Sites: 1

Brief Summary

The goal of this observational study is to develop a Clinical Decision Support System for severe patients with polytrauma. The main questions it aims to answer are:

• Is it possible to predict the development of systemic inflammatory response syndrome for the next 24 h after admission?
• Is it possible to predict the development of blood loss \>25% of blood volume for the next 24 h after admission?
• Is it possible to predict the development of acute traumatic coagulopathy for the next 24 h after admission?
• Is it possible to predict the development of pneumonia in polytrauma patients?
• Is it possible to predict the outcome in polytrauma patients? No intervention is planned for this study.

Conditions

Polytrauma

Keywords

severe polytrauma; clinical decision support system

Outcome Measures

Primary Outcomes (4)

• Prediction of SIRS

  Rate of SIRS prediction in the 24 h after admission using the developed CDSS.

  By the end of January 2024

• Rate of ATC prediction in the 24 h after admission using the developed CDSS.

  Rate of ATC prediction in the 24 h after admission using the developed CDSS.

  By the end of January 2024

• Rate of hemorrage prediction in the 24 h after admission using the developed CDSS.

  Rate of hemorrage prediction in the 24 h after admission using the developed CDSS.

  By the end of January 2024

• Rate of pneumonia prediction using the developed CDSS.

  Rate of pneumonia prediction within all period of admission using the developed CDSS.

  By the end of January 2024

Study Arms (4)

Polytrauma with SIRS

No intervention(s) to be administered.

Polytrauma with Bloodloss

No intervention(s) to be administered.

Polytrauma with ATC

No intervention(s) to be administered.

Polytrauma with Pneumonia

No intervention(s) to be administered.

Eligibility Criteria

• Age: 28 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

According to the World Health Organization (WHO forecast, by 2030 trauma is one of the five leading causes of death. In the Republic of Kazakhstan, road traffic injuries rank 7th among all causes of death (14.7 \[the 10-year average is 16.9\] per 100,000 population per year). Considering geographical and epidemiological factors, we chose two regional medical centers and the National Scientific Center of Traumatology and Orthopedics in the Republic of Kazakhstan, providing emergency medical care to patients with polytrauma (the serviced population is 610,000, 1,135,000, and 1,400,000 people, respectively).

You may qualify if:

• Availability of informed consent, signed by the patient or his legal representative;
• Patients over 18 years of age;
• Expanded criteria of the new Berlin definition of polytrauma: patients who comply with three conditions:
• Presence of damage to one area of the body with an AIS score ≥3 points.
• Presence of damage to ≥2 areas of the body with an AIS score of ≥2.
• Presence of ≥1 physiological risk factors and/or primary hospitalization in the ICU.
• Completeness of the medical record in terms of laboratory and instrumental studies and protocol of therapeutic and surgical treatment.

You may not qualify if:

• Refusal to participate in the study at any stage.
• Death within one hour after hospitalization.
• Missing data.
• Patients who seek primary care 24 hours after injury.
• Patients requiring transfer between profiles and hospitals for implementation of rehabilitation or other stages of therapy.
• Patients with prematurely interrupted treatment.
• Trauma combined with suffocation, drowning, frostbite, electrical trauma, or chemical and/or thermal burns.
• Patients with pathological fractures.
• Pregnant women.
• Cases with predominantly severe craniocephalic (GCS \<7 points) or spinal injury (deep paresis and plegias).

Sponsors & Collaborators

• Semey State Medical University: lead
• Ministry of Science and Higher Education of the Republic of Kazakhstan: collaborator

Study Sites (1)

Emergency Hospital

Semey, Abai, 071400, Kazakhstan

RECRUITING

Related Publications (1)

• Prokazyuk A, Tlemissov A, Zhanaspayev M, Aubakirova S, Mussabekov A. Development and validation of a machine learning-based model to assess probability of systemic inflammatory response syndrome in patients with severe multiple traumas. BMC Med Inform Decis Mak. 2024 Aug 27;24(1):235. doi: 10.1186/s12911-024-02640-x.

  PMID: 39192291 DERIVED

MeSH Terms

Conditions

Multiple Trauma

Condition Hierarchy (Ancestors)

Wounds and Injuries

Study Design

• Study Type: observational
• Observational Model: CASE CONTROL
• Time Perspective: OTHER
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: MD, Anesthesiology and ICU specialist

Study Record Dates

• First Submitted: March 14, 2024
• First Posted: March 21, 2024
• Study Start: December 1, 2020
• Primary Completion: September 1, 2024
• Study Completion: December 31, 2024
• Last Updated: March 21, 2024

Record last verified: 2024-03

Locations

KA (1)