RecruitingNCT06183944

Data Clustering Study With Artificial Intelligence and Phenotyping of Patients With Acute Pulmonary Embolism

Data Clustering Study With Artificial Intelligence and Phenotyping of Patients Who Presented With Acute Pulmonary Embolism

Sponsor

Centre Hospitalier Intercommunal de Toulon La Seyne sur Mer

Enrollment

2,500 participants

Start Date

Dec 11, 2023

Study Type

OBSERVATIONAL

Conditions

Pulmonary Embolism

Summary

The aim will be to identify clinically relevant phenotypes in patients with acute pulmonary embolism. Hierarchical clustering methods combined with unsupervised learning (machine learning) will be used to obtain groups of patients who are homogeneous at diagnosis. Evaluating their prognosis at 6 months (recurrence or chronic thromboembolic pulmonary hypertension), account the first 3 months of anticoagulant treatment, would provide an aid to medical decision-making. This research will include a retrospective and a prospective parts. The retrospective part will include patients who have been admitted to CHITS for acute pulmonary embolism since 2019. For the prospective part, it is planned to include patients with same characteristics over the years 2024 and 2025. More than 2,500 patients are expected to be included. This research will have no impact on current patient care. Data from consultations and various examinations carried out as part of care will be collected for six months post-diagnosis in order to meet the research objectives.

Eligibility

Min Age: 18 Years

Inclusion Criteria2

Age ≥ 18 years;
Patient with acute pulmonary embolism in CHITS (hospitalised or not).

Exclusion Criteria2

Sub-segmental pulmonary embolisms ;
Patient opposition.

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Interventions

OTHERHierarchical clustering methods

Hierarchical clustering methods will be used to form homogeneous groups of patients based on their data at diagnosis: presence or absence of symptoms, clinical and biological data, and presence or absence of favouring factors. Patient evolution at 6 months can fall into categories: stable, aggravation or progress, which are determined by events such as recurrence, hemorrhage, functional sequelae or death.