Adverse Outcome of Acute Pulmonary Embolism by Artificial Intelligence System Based on CT Pulmonary Angiography

Study Overview
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Brief Summary
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The investigators aim to build a predictive tool for Adverse Outcome of Acute Pulmonary Embolism by Artificial Intelligence System Based on CT Pulmonary Angiography.

Detailed Description
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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. The investigators aim to build a predictive tool for Adverse Outcome of Acute Pulmonary Embolism by Artificial Intelligence System Based on CT Pulmonary Angiography. 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.

Official Title
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Prediction of Adverse Outcome of Acute Pulmonary Embolism by Artificial Intelligence System Based on CT Pulmonary Angiography

Conditions
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Pulmonary Embolism and Thrombosis, Deterioration, Clinical, Artificial Intelligence

Intervention / Treatment
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* Other: no intervention


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: age of ≥ 18 years and a pulmonary embolism diagnosis based on CT pulmonary angiography Exclusion Criteria: 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.

Ages Eligible for Study
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Minimum Age: 18 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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Arms and Interventions

| Intervention/Treatment |
| --- |
|Other: no intervention|no intervention|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Incidence of Treatment-Emergent Adverse Events | The outcomes of interest were defined as the occurrence of adverse outcomes within 30 days after admission. Adverse outcomes were defined as deaths, the need for mechanical ventilation, the need for cardiopulmonary resuscitation, and the need for life-saving vasopressor and reperfusion treatment. | 30 days | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Incidence of Treatment-Emergent Adverse Events | The outcomes of interest were defined as the occurrence of adverse outcomes within 2 years after admission. Adverse outcomes were defined as deaths, the need for mechanical ventilation, the need for cardiopulmonary resuscitation, and the need for life-saving vasopressor and reperfusion treatment. | 2 years | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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Pulmonary Embolism and Thrombosis, Deterioration, Clinical, Artificial Intelligence