VTE Risk Prevention System Based on Big Data Analysis and Multimodule System

NCT ID: NCT05969951

Last Updated: 2023-08-01

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

RECRUITING

Total Enrollment

100000 participants

Study Classification

OBSERVATIONAL

Study Start Date

2021-04-14

Study Completion Date

2026-04-30

Brief Summary

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Venous thromboembolism (VTE) is one of the most common complications in perioperative period and the most common cause of postoperative death. VTE includes deep vein thrombosis (DVT) and acute pulmonary thromboembolism (PTE). Since the embolus of PTE comes from the deep vein thrombosis, and not all PE patients can present obvious clinical symptoms, VTE is currently considered as a disease for research, prevention, diagnosis and treatment at home and abroad. Therefore, we urgently need to develop a more comprehensive and reliable perioperative VTE risk prevention system based on medical big data and multi-module computer in current clinical practice, so as to effectively guide the prevention of DVT/PE, and thus reduce the perioperative mortality.

Detailed Description

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Venous thromboembolism (VTE) is one of the most common complications in perioperative period and the most common cause of postoperative death. VTE includes deep vein thrombosis (DVT) and acute pulmonary thromboembolism (PTE). Since the embolus of PTE comes from the deep vein thrombosis, and not all PE patients can present obvious clinical symptoms, VTE is currently considered as a disease for research, prevention, diagnosis and treatment at home and abroad. Therefore, we urgently need to develop a more comprehensive and reliable perioperative VTE risk prevention system based on medical big data and multi-module computer in current clinical practice, so as to effectively guide the prevention of DVT/PE, and thus reduce the perioperative mortality.

As early as 1991, Caprini et al. collated and published the clinical scale of VTE risk assessment based on the study data of 538 patients. In 2010, Caprini et al. conducted retrospective verification of this scale again among 8216 patients, thus making this scale an important reference for many medical institutions to assess the risk of VTE occurrence in perioperative patients, and it has been used ever since. However, over the past 30 years, the disease spectrum, surgical methods, anesthesia methods and the cognition of thrombus formation susceptibility of surgical patients have all undergone great changes. Perioperative patients who are evaluated by Caprini scale and take preventive measures according to its suggested measures will still have postoperative VTE. Therefore, in recent years, scholars have published new VTE risk prediction methods, such as Kucher model, Padua model and so on. However, the study cases established by the model are almost only about 1000 cases, and the included research indicators are limited.

The new technology realizes for the first time the identification, reading and integration of VTE-related risk indicators under the guidance of informatization and digitalization, providing technical support for big data analysis; To realize forward-looking, big data, multi-variable, multi-module VTE-related risk assessment and prediction; The existing scoring system should be improved to provide a more reliable and operable scoring model for perioperative VTE prevention and treatment.

Conditions

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Recruiting

Study Design

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Observational Model Type

CASE_CONTROL

Study Time Perspective

PROSPECTIVE

Study Groups

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New scoring mode group

Patients were evaluated for VTE risk in the perioperative period using a new scoring system

No interventions assigned to this group

Caprini group

Patients were evaluated for VTE risk in the perioperative period using Caprini scoring system

No interventions assigned to this group

Eligibility Criteria

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Inclusion Criteria

1. perioperative patients;
2. Age range from 10 to 90 years old, gender unlimited;
3. Sign informed consent.

Exclusion Criteria

* (1) non-operative patients; (2) have developed deep vein thrombosis and/or pulmonary embolism before surgery; (3) emergency operation patients; (4) Patients considered unsuitable for inclusion in the study.
Minimum Eligible Age

10 Years

Maximum Eligible Age

90 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Shengjing Hospital

OTHER

Sponsor Role lead

Responsible Party

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LI ZHAO

LI ZHAO

Responsibility Role PRINCIPAL_INVESTIGATOR

Locations

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Shengjing Hospital of China Medical University

Shenyang, Liaoning, China

Site Status RECRUITING

Countries

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China

Central Contacts

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Chuming Zhou, master

Role: CONTACT

+8602496615-21111

Yu Li, master

Role: CONTACT

+8602496615-21111

Facility Contacts

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Yu Li, master

Role: primary

+8602496615-21111

Chuming Zhou, master

Role: backup

+8602496615-21111

References

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Cronin M, Dengler N, Krauss ES, Segal A, Wei N, Daly M, Mota F, Caprini JA. Completion of the Updated Caprini Risk Assessment Model (2013 Version). Clin Appl Thromb Hemost. 2019 Jan-Dec;25:1076029619838052. doi: 10.1177/1076029619838052.

Reference Type BACKGROUND
PMID: 30939900 (View on PubMed)

Other Identifiers

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ShengjingH

Identifier Type: -

Identifier Source: org_study_id

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