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

Construction of Perioperative Venous Thromboembolism Risk Prevention System Based on Big Data Analysis and Multimodule System

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.

Study Overview

• Status: Recruiting
• Conditions: Recruiting

Detailed Description

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.

• Study Type: Observational
• Enrollment (Estimated): 100000

Contacts and Locations

• Study Contact: Name: Yu Li, master; Phone Number: +8602496615-21111; Email: sundy_liyu@163.com
• Study Contact Backup: Name: Chuming Zhou, master; Phone Number: +8602496615-21111; Email: zcm_06@163.com

Study Locations

• China
  • Liaoning
    • Shenyang, Liaoning, China, 110004
      • Recruiting
      • Shengjing Hospital of China Medical University
      • Contact: Yu Li, master; Phone Number: +8602496615-21111; Email: sundy_liyu@163.com
      • Principal Investigator: Li Zhao, Doctor
      • Sub-Investigator: Yu Li, Master
      • Contact: Chuming Zhou, master; Phone Number: +8602496615-21111; Email: zcm_06@163.com
      • Sub-Investigator: Chuming Zhou, Master

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Child; Adult; Older Adult
• Accepts Healthy Volunteers: No

• Sampling Method: Non-Probability Sample

Study Population

All patients in the perioperative period between 10-90

Description

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.

Study Plan

How is the study designed?

Number of groups / cohorts

2

Cohorts and Interventions

Group / Cohort
New scoring mode group; Patients were evaluated for VTE risk in the perioperative period using a new scoring system
Caprini group; Patients were evaluated for VTE risk in the perioperative period using Caprini scoring system

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
DVT incidence rate	Incidence of perioperative deep venous thromboembolism	7±2days after operation
PE incidence rate	Incidence of perioperative acute pulmonary thromboembolism	7±2days after operation

Collaborators and Investigators

• Sponsor: Shengjing Hospital

Publications and helpful links

General Publications

• 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.

Study record dates

Study Major Dates

• Study Start (Actual): April 14, 2021
• Primary Completion (Estimated): December 1, 2025
• Study Completion (Estimated): April 1, 2026

Study Registration Dates

• First Submitted: July 23, 2023
• First Submitted That Met QC Criteria: July 23, 2023
• First Posted (Actual): August 1, 2023

Study Record Updates

• Last Update Posted (Actual): August 1, 2023
• Last Update Submitted That Met QC Criteria: July 23, 2023
• Last Verified: April 1, 2023

More Information

Terms related to this study

• Other Study ID Numbers: ShengjingH

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: UNDECIDED

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No