Applicability of the Padua scale for Chinese rheumatic in-patients with venous thromboembolism

Comparison of the PADUA and IMPROVE scores in assessing venous thromboembolism risk in 42,257 medical inpatients in China

Venous thromboembolism (VTE) is a major contributor to hospital mortality and disability-adjusted life-year (DALY) loss. Multiple guidelines recommend using the Padua or IMPROVE scores to stratify VTE risk in hospitalized medical patients. However, the IMPROVE score is not recommended in Chinese guidelines, and there is very little evaluation of its clinical application and effectiveness in the Chinese population. The objective of this study is to compare the efficacy of the Padua and IMPROVE scoring models for assessing VTE risk in Chinese medical inpatients. We conducted a retrospective analysis of the clinical characteristics and thrombotic risk of 42,257 medical inpatients at a tertiary hospital in Guangdong, China, between 2021 and 2022. Logistic regression was used to assess thrombotic risk factors. The Receiver Operating Characteristic (ROC) curves, Area Under the Curve (AUC), sensitivity, and specificity were employed to evaluate the performance of the two models. Of the 42,257 patients included, 948 (2.24%) experienced VTE during hospitalization. According to the Padua score, 3,7513 (88.78%) of patients were considered low risk, while 4,744 (18.22%) were classified as high risk. The IMPROVE score identified 20,744 (49.09%) of patients as low risk, 20799(49.22%) as intermediate risk, and 714(1.69%) as high risk. The AUC for the Padua score was 0.735 (95% CI: 0.717-0.753), with a sensitivity of 49.4% and specificity of 89.6%. For the IMPROVE score, the AUC was 0.711 (95% CI: 0.693-0.729), with a sensitivity of 32.5% and specificity of 99.0%. The DeLong test, used to compare the AUCs, yielded a z-value of 1.886 with a P-value of 0.059, indicating no statistical difference. When assessing VTE risk in patients with stroke, cancer, nephrotic syndrome, and critical illness (ICU/CCU stay), both scoring models showed comparable predictive performance with AUCs ranging between 0.7 and 0.8. Both the Padua score and IMPROVE score have good predictive ability for VTE events during hospitalization in medical patients. Among them, the IMPROVE score has objective assessment items, simpler operation, and more detailed risk stratification, which is beneficial for clinicians to take physical and pharmacological preventive measures at different levels.ChiCTR2200056903, February 22, retrospectively registered.

Nomogram for hospital-acquired venous thromboembolism among patients with cardiovascular diseases

BACKGROUND

Identifying venous thromboembolism (VTE) is challenging for patients with cardiovascular diseases due to similar clinical presentation. Most hospital-acquired VTE events are preventable, whereas the implementation of VTE prophylaxis in clinical practice is far from sufficient. There is a lack of hospital-acquired VTE prediction models tailored specifically designed for patients with cardiovascular diseases. We aimed to develop a nomogram predicting hospital-acquired VTE specifically for patients with cardiovascular diseases.

MATERIAL AND METHODS

Consecutive patients with cardiovascular diseases admitted to internal medicine of Fuwai hospital between September 2020 and August 2021 were included. Univariable and multivariable logistic regression were applied to identify risk factors of hospital-acquired VTE. A nomogram was constructed according to multivariable logistic regression, and internally validated by bootstrapping.

RESULTS

A total of 27,235 patients were included. During a median hospitalization of four days, 154 (0.57%) patients developed hospital-acquired VTE. Multivariable logistic regression identified that female sex, age, infection, pulmonary hypertension, obstructive sleep apnea, acute coronary syndrome, cardiomyopathy, heart failure, immobility, central venous catheter, intra-aortic balloon pump and anticoagulation were independently associated with hospital-acquired VTE. The nomogram was constructed with high accuracy in both the training set and validation (concordance index 0.865 in the training set, and 0.864 in validation), which was further confirmed in calibration. Compared to Padua model, the Fuwai model demonstrated significantly better discrimination ability (area under curve 0.865 vs. 0.786, net reclassification index 0.052, 95% confidence interval 0.012-0.091, P = 0.009; integrated discrimination index 0.020, 95% confidence interval 0.001-0.039, P = 0.051).

CONCLUSION

The incidence of hospital-acquired VTE in patients with cardiovascular diseases is relatively low. The nomogram exhibits high accuracy in predicting hospital-acquired VTE in patients with cardiovascular diseases.

Evaluating of Existing VTE Risk Scales in Glioma Patients

INTRODUCTION

Postoperative venous thromboembolism (VTE) is a frequently occurring complication among glioma patients. Several risk assessment models (RAMs), including the Caprini RAM, the IMPROVE Risk Score, the IMPROVED VTE Risk Score, and the Padua Prediction Score, have not been validated within the glioma patient population. The purpose of this study was to assess the predictive accuracy of established VTE risk scales in patients with glioma.

MATERIALS AND METHODS

A single-center, retrospective, observational cohort study was conducted on 265 glioma patients who underwent surgery at the Almazov Medical and Research Centre between 2021 and 2022. VTE detection followed the current clinical guidelines. Threshold values for the Caprini, IMPROVE VTE, IMPROVEDD, and Padua scales were determined using ROC analysis methods, with cumulative weighting for sensitivity and specificity in predicting VTE development. The areas under the ROC curves (AUC) were calculated, and comparisons were made using the DeLong test.

RESULTS

The area under the curve for the Caprini risk assessment model was 80.41, while the IMPROVEDD VTE risk score was 75.38, the Padua prediction score was 76.9, and the IMPROVE risk score was 72.58. No significant differences were observed in the AUC values for any of the scales. The positive predictive values of all four scales were low, with values of 50 (28-72) for Caprini, 48 (28-69) for IMPROVEDD VTE, 50 (30-70) for Padua, and 64 (35-87) for IMPROVE RAM. No significant differences were found in terms of PPV, NPV, positive likelihood ratio, and negative likelihood ratio among the analyzed scales.

CONCLUSIONS

The Caprini Risk Assessment Model, the IMPROVE Risk Score, the IMPROVED VTE Risk Score, and the Padua Prediction Score exhibit acceptable specificity and sensitivity for glioma patients. However, their low positive predictive ability, coupled with the complexity of interpretation, limits their utility in neurosurgical practice.

MiR-128-3p promotes the progression of deep venous thrombosis through binding SIRT1

OBJECTIVES

This research aimed to study the effect of microRNA-128-3p (miR-128-3p) on deep venous thrombosis (DVT).

METHOD

The 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay, Transwell chamber method, and flow cytometry technique were used in the cell experiments. Potential interconnection between miR-128-3p and silent information regulator sirtuin 1 (SIRT1) was revealed by luciferase activity. The concentration of miR-128-3p and mRNA SIRT1 was assessed by quantitative reverse transcription polymerase chain reaction (qRT-PCR). The receiver operating characteristic (ROC) curve was used to test the predictive effect of miR-128-3p in DVT.

RESULTS

Decreased miR-128-3p expression was beneficial to cell proliferation and migration and inhibited inflammation, apoptosis, and adhesion of human umbilical vein endothelial cells (HUVECs). The impacts of miR-128-3p on HUVECs were achieved by targeting SIRT1. MiR-128-3p was upregulated in patients with DVT, and it was of great significance in differentiating patients with DVT.

CONCLUSION

Overexpression of miR-128-3p might become a biomarker for patients with DVT.