Artificial Intelligence, Deterioration, Clinical, Pulmonary Embolism and Thrombosis
Conditions
Keywords
Pulmonary Embolism and Thrombosis, Deterioration, Clinical, Artificial Intelligence
Brief summary
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
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.
Interventions
OTHERno intervention
no intervention
Sponsors
Shengjing Hospital
Study design
Observational model
COHORT
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
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.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Incidence of Treatment-Emergent Adverse Events | 30 days | 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. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Incidence of Treatment-Emergent Adverse Events | 2 years | 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. |
Countries
China
Contacts
CONTACTDONG JIA
CONTACTYIZHUO GAO
PRINCIPAL_INVESTIGATORDONG JIA
Shengjing Hospital
Outcome results
None listed