Influence of Lower Extremity Deep Venous Thrombosis in Cerebral Infarction on Coagulation Index and Thromboelastogram and Its Risk Factors

Cerebral infarction is a serious brain injury disease, which is mainly caused by the blockage of blood circulation in patients’ brains; thus, the patient’s brain appears ischemia and hypoxia state, and large-scale nerve cell death occurs immediately. The aim of this study was to explore the influence of lower extremity deep venous thrombosis (LEDVT) on coagulation indexes and thromboelastogram (TEG) after cerebral infarction. Altogether, 67 patients with cerebral infarction complicated with LEDVT in our hospital from April 2017 to August 2019 were collected as the observation group (OG) and 58 patients with cerebral infarction without lower extremity deep venous thrombosis as the control group (CG). The R, K, angle, and MA values in PT, APTT, TT, FIB, and TEG indexes were compared between the two groups. The ROC curve was applied to analyze the diagnostic value of R value, K value, angle value, and MA value in the occurrence of LEDVT in patients with cerebral infarction. Logistic regression analysis was applied to analyze the independent risk factors of lower extremity deep venous thrombosis in cerebral infarction. PT, APTT, and TT in the OG were evidently lower than those in the CG, while FIB in the OG was evidently higher than that in the CG, R value and K value of the OG were evidently lower than those of the CG, and angle and MA values were higher than those in the CG. The AUC of R value, K value, angle value, and MA value of the ROC curve of LEDVT in patients with cerebral infarction was 0.735, 0.713, 0.790, and 0.819. Multivariate analysis showed that high FIB, angle, and MA were risk factors, while R and K values were protective factors. PT, APTT, and TT are lower and FIB is higher in patients with cerebral infarction with LEDVT. TEG has a certain diagnostic value. FIB value, angle value, and MA value are independent risk factors of LEDVT in patients with cerebral infarction, while R value and K value are protective factors.

Functional Status and Its Related Factors Among Stroke Survivors in Rehabilitation Departments of Hospitals in Shenzhen, China

Background: Many stroke survivors have multiple chronic diseases and complications, coupled with various other factors which may affect their functional status. We aimed to investigate the factors associated with poor functional status in hospitalized patients with stroke in Shenzhen, China.Methods: This is a cross-sectional study. Data on 646 patients with stroke were recruited from four urban hospitals using cluster sampling. The Longshi Scale was used to assess the functional status of stroke survivors. Explanatory variables, i.e. factors affecting functional status, included demographic, lifestyle factors, complications, and chronic conditions. The ordinal logistic regression model was used to investigate factors associated with poor functional status. Results: Stroke survivors with poor functional status accounted for 72.14% and were assessed as the bedridden group based on the Longshi scale, 21.67% of patients with moderate functional limitation were assessed as the domestic group and 6.19% of the patients with mild functional restriction was assessed as the community group. The highest dependence was noted for feeding (73.39%), bowel and bladder management (69.74%), and bedtime entertainment (69.53%) among the bedridden group, and housework (74.29%) among the domestic group. In the adjusted model, patients who were in older age groups (odds ratio [OR] = 2.39, 95% CI: 1.55–3.80), female (OR = 1.73, 95% CI: 1.08–2.77), duration of stroke more than 12 months (OR = 1.94, 95% CI: 1.28–2.95), with pulmonary infection (OR = 10.91, 95% CI: 5.81–20.50), and with deep venous thrombosis (OR = 3.00, 95% CI: 1.28–7.04) had almost or more than two times the risk of poorer functioning.Conclusions: Our study found that 72.14% of stroke survivors had poor functional status, 21.67% and 6.19% of stroke survivors had moderate functional limitations and mild functional restrictions in rehabilitation settings. The older age bracket (age ≥ 60) and females were more likely to exhibit poor functioning. Pulmonary infection and deep venous thrombosis, both common post-stroke complications, were related to the increased chance of dependence. Therefore, interventions aimed at treating or preventing pulmonary infection and deep vein thrombosis need to contribute to addressing these circumstances and subsequent dysfunction after stroke.

Deep Venous Thrombosis (DVT) risk assessment on routine hemodialysis patient using Padua prediction score

Introduction: Hemodialysis requires invasive vascular access (VA) procedure which could emerge deep venous thrombosis (DVT) complication. Apart from VA, other risk factors, either modifiable or unmodifiable, could increase DVT risk. Those factors can be assessed by Padua Prediction Score (PPS). This study aims to assess which risk factors in PPS increase the risk of developing DVT in routine hemodialysis patients at BHCC main clinic. Methods: This research is a descriptive observational study with simple random sampling. The participants were 58 routine hemodialysis patients in BHCC. The inclusion criteria of this study were the ages above 17 years old, had history hemodialysis more than one, the patient willing to become of the sample subject. The patient that incompletely fulfills the questionnaire were already treated with anticoagulation were admitted for VTE, and had a history of discontinuing hemodialysis were excluded. The data were gathered using a questionnaire according to PPS. The data was analyzed by using SPP 25.0. The descriptive data was provided in a table and pie chart. Results: Based on the results of the PPS, 11 patients (18.96%) were among the high risk, and 47 patients (81.04%) were at low risk. The most potent risk factor in increasing the risk of DVT is reduced mobility with a risk priority number (RPN) of 30 (severity=3, occurrence=10). Recent (≤one month) trauma and surgery entail on second with an RPN of 24 (severity=2, occurrence=12). The third is occupied by heart and/or respiratory failure with a RPN of 14 (severity=1, occurrence=14). Previous VTE history with a RPN of 12 (severity=3, occurrence=4) placed fourth, followed by age≥ 70 (RPN=8, severity=1, occurrence=8) and obesity (BMI>= 30) with a RPN of 4 (severity=1, occurrence=4) at fifth and sixth respectively. Conclusion: "Reduced mobility" is the most prominent risk factor to increase DVT risk in routine hemodialysis patients, followed by other risk factors. Reduced mobility and obesity are modifiable risk factors that should be eliminated by educating routine hemodialysis patients.