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Journal of Peking University (Health Sciences) ›› 2023, Vol. 55 ›› Issue (4): 625-630. doi: 10.19723/j.issn.1671-167X.2023.04.009

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Application of Padua prediction score and serum albumin level in evaluating venous thromboembolism in rheumatic inpatients

Qing PENG1,2,Jia-jun LIU2,Yan LIU2,Hua SHANG2,Guo TANG3,Ya-xin HAN4,Li LONG2,5,*()   

  1. 1. Department of Rheumatology and Immunology, Chengdu Second People's Hospital, Chengdu 610000, China
    2. Zunyi Medical University, Zunyi 563000, Guizhou, China
    3. Department of Rheumatology and Immunology, The Bishan Hospital of Chongqing, Chongqing 402760, China
    4. Department of Rheumatology and Immunology, The Wenjiang Hospital of Chengdu, Chengdu 610000, China
    5. Department of Rheumatology and Immunology, Sichuan Provincial People's Hospital, Chengdu 610000, China
  • Received:2020-07-30 Online:2023-08-18 Published:2023-08-03
  • Contact: Li LONG E-mail:llllyyyy2012@sina.com
  • Supported by:
    Chengdu Technology R&D Project of Benefiting People with Science and Technology(2015-HM01-00165-SF)

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Abstract:

Objective: To investigate the status of venous thromboembolism (VTE) in rheumatic inpatients, and to explore the efficiency of Padua prediction score (PPS) in the patient population. In addition, to analyze the relationship between serum albumin and VTE in rheumatic inpatients. Methods: Data of inpatients with rheumatology were retrospectively collected and analyzed at Sichuan Provincial People's Hospital from September 2018 to September 2019. Occurrence of VTE was compared between high (PPS≥4) and low (PPS < 4) risk groups. PPS were analyzed in the VTE and non-VTE patients. Multivariate Logistic regression model was used to analyze the risk factors in PPS and the relationship between serum albumin and VTE. Results: A total of 1 547 patients were included in this study, and 27 (1.7%) had symptomatic VTE. Among the symptomatic VTE cases, 19 (1.2%) had deep vein thrombosis (DVT) only, 6 (0.4%) had pulmonary thromboembolism (PTE) only, and 2 (0.1%) were diagnosed with DVT and PTE. PPS in the VTE and non-VTE groups were 3.33±1.78 and 1.80±0.97 respectively (P < 0.05).The number of patients with PPS≥4 in the VTE group and non-VTE group was 37.0% and 4.3% respectively (P < 0.01). The average serum albumin level in the VTE group was lower than that in non-VTE group [(29.79±6.36) g/L vs. (35.17±6.31) g/L, P < 0.001]. Seventy-six cases was divided into high-risk group of VTE, while 1 471 cases were in the low-risk group, and the incidence of VTE was 13.2% and 1.2% respectively (P < 0.001). Logistic regression analysis showed that ongoing hormonal treatment, age≥70 years, trauma and/or surgery ≤30 d, reduced mobility and previous VTE were risk factors of VTE in the rheumatology patients, OR values were 7.11, 7.07, 3.40, 2.40 and 2.00, respectively. Lower serum albumin level was the risk factor of VTE in the rheumatology patients [OR=0.88 (95%CI: 0.82-0.94)]. Conclusion: The incidence of VTE was relatively higher in the hospitalized patients in Department of Rheumatology and Immunology. Glucocorticoid therapy was the highest risk factor of VTE and lower serum albumin level also was the risk factor. Although the PPS can reflect the risk of VTE in rheumatic inpatients to some extent, its effectiveness is limited. PPS can be optimized for quantitative VTE risk assessment of rheumatic inpatients in the future.

Key words: Venous thromboembolism, Padua prediction score, Rheumatic diseases

CLC Number: 

  • R593.2

Table 1

Risk factors for Padua predictive score"

Component Score
Active cancer 3
Previous VTE 3
Reduced mobility 3
Known thrombophilic condition 3
Trauma/surgery < 30 d 2
Age≥70 years 1
Heart/respiratory failure 1
Acute MI or ischemic stroke 1
Acute infection/rehum disorder 1
Obesity (BMI≥30 kg/m2) 1
Ongoing hormonal treatment 1

Table 2

Types and number of diseases of 1 547 patients"

Disease type n (%)
Rheumatoid arthritis 335 (21.7)
Primary Sjögren’s syndrome 249 (16.1)
Systemic lupus erythematosus 244 (15.8)
Osteoarthritis 195 (12.6)
Idiopathic inflammatory myositis 108 (7.0)
Spondyloarthritis 107 (6.9)
Gout 101 (6.5)
Overlap syndrome 84 (5.4)
Vasculitis 51 (3.3)
Systemic sclerosis 34 (2.2)
Adult Still’s disease 24 (1.6)
Panniculitis 15 (0.9)

Table 3

Comparison of general conditions of VTE and non-VTE group"

Items VTE group (n=27) Non-VTE group (n=1 520) P
Gender, n(%) 0.19
  Male 10 (37.0) 394 (25.9)
  Female 17 (63.0) 1 126 (74.1)
Age, n(%) 0.01
  ≥60 years 16 (59.3) 480 (31.6)
   < 60 years 11 (40.7) 1 041 (68.4)
Hypertension, n(%) 6 (13.9) 211 (16.0) 0.33
Diabetes, n(%) 3 (11.1) 91 (6.0) 0.48
BMI/(kg/m2), ${\bar x}$±s 23.24±4.56 22.50±3.46 0.15
Hospitalization days, ${\bar x}$±s 15.35±6.64 11.47±4.89 0.03
PPS, ${\bar x}$±s 3.33±1.78 1.80±0.97 < 0.001
Serum albumin/(g/L), ${\bar x}$±s 29.79±6.36 35.17±6.31 < 0.001

Table 4

Association of PPS with risk of VTE in binomial Logistic regression models"

PPS VTE (n=27), n (%) Non-VTE (n=1 520), n (%) OR (95%CI) P
0-1 2 (7.4) 580 (38.1) 1 (reference category)
2 11 (40.8) 718 (47.2) 4.43 (0.98, 20.12) 0.053
3 4 (14.8) 156 (10.3) 7.43 (1.35, 40.97) 0.021
4 2 (7.4) 32 (2.1) 18.12 (2.47, 132.86) 0.004
5 3 (11.1) 25 (1.7) 34.8 (5.56, 217.68) 0.001
≥6 5 (18.5) 9 (0.6) 161.11 (27.52, 943.07) 0.001

Table 5

Analysis of risk factors in PPS by Logistic regression model"

Risk factor OR(95%CI) P
Ongoing hormonal treatment 7.11 (2.13, 23.73) 0.001
Age≥70 years 2.40 (1.00, 5.76) 0.049
Trauma/surgery < 30 d 7.07 (1.55，32.24) 0.012
Reduced mobility 3.40 (2.37, 4.87) < 0.001
Previous VTE 2.00 (1.20, 3.33) 0.008

Table 6

Association of serum albumin categories with risk of incidence VTE in Logistic regression models"

Serum albumin categories VTE (n=27) Non-VTE (n=1 520) OR (95%CI) P
Serum albumin ≥ 40.0 g/L 1 29 1 (reference category)
30.00 g/L ≤ Serum albumin < 40.00 g/L 15 77 6.05 (0.79, 45.98) 0.08
25.00 g/L ≤ Serum albumin < 30.00 g/L 6 179 11.89 (1.42, 99.59) 0.02
20.00 g/L ≤ Serum albumin < 25.00 g/L 3 880 13.83 (1.42, 134.77) 0.02
Serum albumin < 20.00 g/L 2 355 24.48 (2.16, 278.13) 0.01
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