OC 04.2 - Prediction of venous thromboembolic risk in hospitalized medically ill Thai patients with a novel DDC10 risk assessment model

Saturday, June 22, 2024

13:15 – 13:30 ICT

Room: Ballroom B4

Presenting Author(s)

Bundarika Suwanawiboon, MD

Assistant Professor
Department of Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University
Bangkok, Krung Thep, Thailand

Co-Author(s)

PA

Peemai Amornkanjanawat

Doctor
Department of Medicine, Faculty of Medicine, Chulalongkorn University
Bangkok, Krung Thep, Thailand
BS

Bunchoo Suntornopas

Staff Hematologist
Bangkok Metropolitan Administration General Hospital
Bangkok, Krung Thep, Thailand
NS

Natthaporn Sasijareonrat

Staff Hematologist
Bangkok Metropolitan Administration General Hospital
Bangkok, Krung Thep, Thailand
CP

Chavada Piyabun-yanon

Staff Hematologist
Pranangklao hospital
Bangkok, Krung Thep, Thailand
PS

Pirun Saelue

Assistant Professor
Department of Internal Medicine, Faculty of Medicine, Prince Songkla University
Hadyai, Songkhla, Thailand
Tarinee Rungjirajittranon

Lecturer
Department of Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University
Bangkok, Krung Thep, Thailand
YN

Yupa Nakkinkun

Technician
Faculty of Medicine Siriraj Hospital, Mahidol Univerisity
Bangkok, Krung Thep, Thailand
YC

Yingyong Chinthammitr

Assistant Professor
Siriraj hospital
Bangkok, Krung Thep, Thailand
TR

Theera Ruchutrakool

Associate Professor
Department of Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
Bangkok, Krung Thep, Thailand

Background: Prediction of hospitalized medically ill patients who are at risk of venous thromboembolism (VTE) is crucial for proper thromboprophylaxis. However, previous risk assessment models (RAM), including the Padua prediction score and IMPROVE score, did not accurately predict VTE risk in Thai medically ill inpatients.

Aims: To develop a RAM to predict VTE risk in medically ill patients.

Methods: A prospective multicenter cohort study was conducted on patients aged ≥ 18 years admitted to general medicine wards due to acute medical illness. Symptomatic VTE events were determined within 90 days after enrollment. Patients with a length of stay < 72 hours, ongoing anticoagulant therapy, non-acute medical conditions, and pregnancy were excluded. Backward stepwise regression was performed to select the best prediction model. The performances of this model were analyzed by the calibration plot and Area Under the Curve (AUC).

Results: A total of 1192 patients participated in the study; 578 (48.5%) were female. Two (0.2%) and 258 (21.7%) patients had prior VTE and active malignancies, respectively. The mean age was 62.4 ± 18.5 years. The median BMI and length of stay were 22.0 (IQR 19.1-25.1) and 9 days (IQR 6-15), respectively. None of the patients received mechanical or pharmacological thromboprophylaxis. Fifteen patients (1.3%, 95%CI 0.7-2.1) developed VTE within 90 days after enrollment. Diabetic ketoacidosis (D), prior deep vein thrombosis (D), central venous catheter placement (C), and length of stay >10 days (10) were significantly associated with increased risk of VTE (Table 1). We developed the DDC10 model as a nomogram to predict the probability of VTE in hospitalized medical patients (Figure 1). The calibration plot and the AUC of 0.77 confirmed the good performance of this model.

Conclusion(s): A novel RAM was developed to predict VTE risk in hospitalized medically ill patients with reasonable accuracy. Additional validation of the model is currently underway before implementation.