The purpose of this study is to prospectively validate the first PUMCH model for acute PE severity and prognosis prediction based on multi-center data constructed in the pre-project period based on national population data, and to optimize the PUMCH model based on artificial intelligence clustering algorithm.

Patients with pulmonary embolism and aged 18 years or older were enrolled in this study.Patient demographic characteristics(age, sex, department, diagnosis), basic vital signs, symptoms at their admissions (hemoptysis, dyspnea, chest pain, syncope, laboratory examinations (blood lab routines, blood gas, liver and kidney function, myocardial marker), and imaging examinations (vascular ultrasonography, computed tomographic angiography, echocardiography, chest CT,CTPA, pulmonary perfusion imaging, pulmonary angiography, PET/CT) were prospectively collected. Patients were followed up every 1/3/6 months to obtain survival outcomes.

Inclusion Criteria:

• age ≥ 18 years

• Inpatients with acute PTE diagnosed by imaging (CTPA, enhanced CT, V/Q imaging suggesting a high probability of PE, pulmonary angiography, MRPA) containing any of the following conditions.

  1. primary acute PTE combined with or without DVT
  2. recurrent acute PTE with a history of previous PTE or DVT

• signed informed consent form

Exclusion Criteria:

• blinded to any diagnostic or therapeutic test (VTE or other conditions)
• unable to complete follow-up (due to cognitive or behavioral limitations, etc.)

Inpatients with acute PTE diagnosed by imaging (CTPA, enhanced CT, V/Q imaging suggesting a high probability of PE, pulmonary angiography, MRPA).