Single factor analysis of risk warning indicators of venous thromboembolism risk
According to relevant literature and clinical practice, the VTE risk warning indicators which are not included in the Caprini score scale mainly include four parts: (1) General indicators, mainly including gender, patient origin, nationality, payment methods, length of stay (days); (2) Related indicators of current medical history, including 17 variables such as cough, expectoration, hemoptysis, dyspnea, pleural chest pain, cyanosis, pain in the precardiac area, palpitations, shortness of breath after exertion, chest tightness, shortness of breath, syncope with unknown cause, pleural effusion, unilateral lower limb Pain, deep venous tenderness in the lower limbs, pigmentation in the lower limbs, walking fatigue in the lower limbs, and increased local skin temperature in the lower limbs; (3) Relevant indicators of previous history, mainly including 7 variables such as hypertension, diabetes, smoking, systemic connective tissue disease, renal insufficiency, liver disease (hepatitis or liver damage), anemia; (4) The relevant indexes of the laboratory inspection items, mainly including 11 variables such as prothrombin time (PT), thrombin time (TT), activated partial thrombin time (APTT), Fibrinogen (FIB), Fibrinogen Degradation Product (FDP), International Normalized Ratio (INR), D-Dimerization , Albumin, platelet count, white blood cell count, number of red blood cells. In addition, we included the Caprini score as a risk warning indicator in the univariate analysis. The detailed results are shown in Table 1.
Multivariate analysis of early risk warning indicators of venous thromboembolism
Univariate analysis was performed on 41 variables, of which there were 15 variables with statistical significance of P <0.05. In order to not omit possible VTE risk early warning related variables, increase the sensitivity of the risk early warning model and allow more possible variables to be included in the variable, the variables with P <0.3 in the univariate analysis or consistented with literature reports and clinical experience were included in the subsequent multivariate analysis. Therefore, a total of 28 variables were included. After colinear analysis, all variables had VIF less than 3, it can be considered that there is no co-linearity among VTE risk warning indicators, which can be included in multi-factor logistic regression analysis, as shown in Table 2.
The above 28 variables with P <0.3 were included in Logistic regression analysis, and a total of 7 independent risk warning indicators were screened out, which were pleural chest pain X10 (P <0.001), shortness of breath after exercise X14 (P = 0.045), and shortness of breath X15 (P <0.001), unilateral lower extremity pain X18 (P <0.001), smoking X25 (P = 0.005), fibrinogen degradation product X34 (P <0.001), Caprini score X41 (P = 0.004). The logistic regression was used to obtain the regression coefficient, standard error, Wald chi-square value, P value, its corresponding OR value, and its 95% confidence interval of the independent risk warning indicators, as shown in Table 3.
Construction of VTE Risk Warning Model
According to the above results The model independent variable assignment method is shown in Table 4. The final VTE risk warning model is as follows:
p = ex / ( 1+ ex ) ,
x = -4.840 + 2.557 • X10(1) + 1.432 • X14(1) + 2.977 • X15(1) + 3.445 • X18(1) + 1.086 • X25(1) + 0.249 • X34 + 0.282 • X41
Where e is the logarithm of natural numbers;
Pleural chest pain X10, shortness of breath after exercise X14, chest tightness shortness of breath X15, unilateral lower extremity pain X18, smoking X25 and other variables are binary values (not specific medical history, 1 for yes, 0 for none). The unit of fibrinogen degradation product (X34) was (μg/ml). Caprini score (X41) is based on Caprini risk assessment scale, with no unit.
Evaluation and comparison of test efficacy of VTE Risk Warning Model
According to the formula of the VTE risk warning model, the predicted probability of VTE occurrence was calculated useing ROC curve analysis. The area under the ROC curve (AUC) was 0.960 (95% CI: 0.940, 0.976), the standard error was 0.009, and Z = 52.279. The Hosmer-Lemeshow test (H-L test) was performed on the VTE risk warning model, and the c2 was 55.441.
Caprini risk assessment scale and VTE risk warning model were used to predict the truncation value (95% CI ) of VTE, which were 5 (4,5), 0.438 (0.263, 0.504), respectively. The sensitivity, specificity, accuracy and Youden index of VTE were predicted as 26.1%, 96.5%, 61.3%, 0.23 and 92.6%, 91.8%, 92.2% , 0.84 respectively. The AUC values were 0.596 ( 95%CI: 0.552, 0.638 ) and 0.960 ( 95%CI: 0.940, 0.976 ), respectively. The difference between the two groupd was statistically significant (Z= 14.521, P <0.0001), as shown in Figure 1.
External validation of VTE Risk Warning Model
The validation data set included 63 patients with VTE and 85 patients without VTE. There was no significant difference in the distribution of general clinical variables between validation data set and modeling data set (P>0.05), which avoided the deviation of the results due to the uneven distribution of clinical variables.
The validation data set was substituted into the established VTE risk warning model formula to calculate the prediction probability of the occurrence of VTE in each patient, and the truncation value of the model was used to evaluate the prediction efficiency of the validated data set. The sensitivity, specificity, accuracy and Youden index were 77.8%, 84.7%, 81.8% and 0.625, respectively. It indicated that the VTE risk warning model had a higher prediction efficiency both in the external population and external population.