A Predictive Tool for Predicting Adverse Outcomes in Acute Pulmonary Embolism Patients Using CTPA.
- Conditions
- Deterioration, ClinicalPulmonary Embolism and Thrombosis
- Registration Number
- NCT05098769
- Lead Sponsor
- Shengjing Hospital
- Brief Summary
This study collected clinical, laboratory, and CT parameters of acute patients with acute pulmonary embolism from admission to predict adverse outcomes within 30 days after admission into hospital.
- Detailed Description
This study collected clinical, laboratory, and CT parameters of acute patients with acute pulmonary embolism from admission. The outcomes of interest were defined as the occurrence of adverse outcomes within 30 days after admission into hospital.
Eligible patients were randomized in some ratio into derivation and validation cohorts. The derivation cohort was used to develop and evaluate a multivariable logistic regression model for predicting the outcomes of interest. The discriminatory power was evaluated by comparing the nomogram to the established risk stratification systems. The consistency of the nomogram was evaluated using the validation cohort.
Recruitment & Eligibility
- Status
- RECRUITING
- Sex
- All
- Target Recruitment
- 300
- age of ≥ 18 years and a PE diagnosis based on CT pulmonary angiography
- pregnancy
- reception of reperfusion treatment before admission
- missing data regarding CT parameters, echocardiography, cardiac troponin I (c-Tn I), and N-terminal-pro brain natriuretic peptide (NT-pro BNP) levels.
Study & Design
- Study Type
- OBSERVATIONAL
- Study Design
- Not specified
- Primary Outcome Measures
Name Time Method Adverse outcomes 30 days The outcomes of interest were defined as the occurrence of adverse outcomes within 30 days after admission. Adverse outcomes were defined as PE-related deaths, the need for mechanical ventilation, the need for cardiopulmonary resuscitation, and the need for life-saving vasopressor and reperfusion treatment.
- Secondary Outcome Measures
Name Time Method
Trial Locations
- Locations (1)
Shenjing Hospital of CHINA MEDICAL UNIVERSITY
🇨🇳Shenyang, Liaoning, China