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CT-based Model for Predicting Prolonged Weaning in Patients With Abdominal Trauma

Completed
Conditions
Wounds and Injuries
Ventilation Therapy; Complications
Registration Number
NCT06339073
Lead Sponsor
Jinling Hospital, China
Brief Summary

Critically ill patients often require tracheal intubation for mechanical ventilation, and timely weaning is crucial for airway management and reducing complications. However, there is currently a lack of an effective tool to predict weaning time in critically ill patients. This retrospective study established an effective nomogram model for predicting the time of weaning from mechanical ventilation in abdominal trauma patients by considering multiple perspectives. The model has been validated and demonstrated good performance in terms of discrimination, calibration, and clinical utility. Moreover, the model can effectively predict the prognosis of critically ill patients. The findings of this study have important implications for guiding respiratory management in clinically critically ill patients, particularly trauma patients.

Detailed Description

Not available

Recruitment & Eligibility

Status
COMPLETED
Sex
All
Target Recruitment
1023
Inclusion Criteria
  • (1) with information on survival status and time;
  • (2) aged 18-80 years;
  • (3) admitted to ICU;
  • (4) with abdominal CT performed within 1-week post-trauma;
  • (5) use of mechanical ventilation.
Exclusion Criteria
  • (1) low-quality CT images;
  • (2) history of mental illness.

Study & Design

Study Type
OBSERVATIONAL
Study Design
Not specified
Primary Outcome Measures
NameTimeMethod
Prolonged mechanical ventilationthrough whole hospitalization of each participant, an average of 25 days

Prolonged mechanical ventilation was defined as length of mechanical ventilation \>7 days

Secondary Outcome Measures
NameTimeMethod

Trial Locations

Locations (1)

the General Surgical Department of Jinling Hospital

🇨🇳

Nanjing, Jiangsu, China

the General Surgical Department of Jinling Hospital
🇨🇳Nanjing, Jiangsu, China
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