Dataset Information

Combination of D-dimer and Albumin in the Prediction of Deep Vein Thrombosis in Patients with Spontaneous Intracerebral Hemorrhage.

ABSTRACT:

Background and purpose

Deep venous thrombosis (DVT) makes spontaneous intracerebral hemorrhage (ICH) treatment more challenging. We aimed to determine the predictive ability of D-dimer combination with albumin for DVT in spontaneous ICH.

Methods

Spontaneous ICH patients were retrospectively included. Univariate and multivariate logistic regression analyses were performed. The restricted cubic spline (RCS) curve was adopted. Multivariate logistic regression analysis was further conducted to assess the predictive powers of D-dimer and albumin in different models. Besides, the incremental predictive ability of D-dimer combination with albumin was evaluated with areas under the curve (AUC), net reclassification improvement (NRI), and integrated discrimination index (IDI).

Results

D-dimer was significantly higher, while albumin was considerably lower in the DVT group than in the non-DVT group [D-dimer, 0.47 (0.29, 1.08) versus 0.98 (0.48, 2.49), P < .001; albumin, 39.45 ± 7.05 versus 36.93 ± 4.77, P < .001). The multivariate logistic regression analysis showed that higher D-dimer and lower albumin were independently related to DVT after controlling confounders (D-dimer, OR = 1.061, 95% CI = 1.012-1.112, P = .013; albumin, OR = 0.934, 95% CI = 0.895-0.973, P = .001). The best cut-off value of the D-dimer was 0.40, and the albumin was 37.15. Besides, D-dimer and albumin had good predictive abilities in different models. The AUC, NRI, and IDI revealed that models that included the D-dimer combination with albumin had better predictability than those without.

Conclusions

D-dimer combination with albumin has a good predictability of DVT in spontaneous ICH.

SUBMITTER: Chen L

PROVIDER: S-EPMC10034306 | biostudies-literature | 2023 Jan-Dec

REPOSITORIES: biostudies-literature

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Publications

Combination of D-dimer and Albumin in the Prediction of Deep Vein Thrombosis in Patients with Spontaneous Intracerebral Hemorrhage.

Chen Lingli L Zhang Wanli W Liu Chunfeng C

Clinical and applied thrombosis/hemostasis : official journal of the International Academy of Clinical and Applied Thrombosis/Hemostasis 20230101

<h4>Background and purpose</h4>Deep venous thrombosis (DVT) makes spontaneous intracerebral hemorrhage (ICH) treatment more challenging. We aimed to determine the predictive ability of D-dimer combination with albumin for DVT in spontaneous ICH.<h4>Methods</h4>Spontaneous ICH patients were retrospectively included. Univariate and multivariate logistic regression analyses were performed. The restricted cubic spline (RCS) curve was adopted. Multivariate logistic regression analysis was further con ...[more]

PMID: 36946100

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Project description:BackgroundMisdiagnosis of hemorrhage secondary to cerebral venous sinus thrombosis (CVST-ICH) as arterial-origin spontaneous intracerebral hemorrhage (sICH) can lead to inappropriate treatment and the potential for severe adverse outcomes. The current practice for identifying CVST-ICH involves venography, which, despite being increasingly utilized in many centers, is not typically used as the initial imaging modality for ICH patients. The study aimed to develop an explainable deep learning model to quickly identify ICH caused by CVST based on non-contrast computed tomography (NCCT).MethodsThe study population included patients diagnosed with CVST-ICH and other spontaneous ICH from January 2016 to March 2023 at the Second Affiliated Hospital of Zhejiang University, Taizhou First People's Hospital, Taizhou Hospital, Quzhou Second People's Hospital, and Longyan First People's Hospital. A transfer learning-based 3D U-Net with segmentation and classification was proposed and developed only on admission plain CT. Model performance was assessed using the area under the curve (AUC), sensitivity, and specificity metrics. For further evaluation, the average diagnostic performance of nine doctors on plain CT was compared with model assistance. Interpretability methods, including Grad-CAM++, SHAP, IG, and occlusion, were employed to understand the model's attention.FindingsAn internal dataset was constructed using propensity score matching based on age, initially including 102 CVST-ICH patients (median age: 44 [29, 61] years) and 683 sICH patients (median age: 65 [52, 73] years). After matching, 102 CVST-ICH patients and 306 sICH patients (median age: 50 [40, 62] years) were selected. An external dataset consisted of 38 CVST-ICH and 119 sICH patients from four other hospitals. Validation showed AUC 0·94, sensitivity 0·96, and specificity 0·8 for the internal testing subset; AUC 0·85, sensitivity 0·87, and specificity 0·82 for the external dataset, respectively. The discrimination performance of nine doctors interpreting CT images significantly improved with the assistance of the proposed model (accuracy 0·79 vs 0·71, sensitivity 0·88 vs 0·81, specificity 0·75 vs 0·68, p < 0·05). Interpretability methods highlighted the attention of model to the features of hemorrhage edge appearance.InterpretationThe present model demonstrated high-performing and robust results on discrimination between CVST-ICH and spontaneous ICH, and aided doctors' diagnosis in clinical practice as well. Prospective validation with larger-sample size is required.FundingThe work was funded by the National Key R&D Program of China (2023YFE0118900), National Natural Science Foundation of China (No.81971155 and No.81471168), the Science and Technology Department of Zhejiang Province (LGJ22H180004), Medical and Health Science and Technology Project of Zhejiang Province (No.2022KY174), the 'Pioneer' R&D Program of Zhejiang (No. 2024C03006 and No. 2023C03026) and the MOE Frontier Science Center for Brain Science & Brain-Machine Integration, Zhejiang University.

Project description:BackgroundThere is substantial evidence to support the use of several methods for preventing deep-vein thrombosis (DVT) following intracerebral hemorrhage (ICH). However, the extent to which these measures are implemented in clinical practice and the factors influencing patients' receipt of preventive measures remain unclear. Therefore, we aimed to evaluate the rate of the early implementation of DVT prophylaxis and the factors associated with its success in patients with ICH.MethodsThis study enrolled 49,950 patients with spontaneous ICH from the Chinese Stroke Center Alliance (CSCA) between August 2015 and July 2019. Early DVT prophylaxis implementation was defined as an intervention occurring within 48 h after admission. Univariate and multivariate logistic regression analyses were conducted to identify the rate and factors associated with the implementation of early prophylaxis for DVT in patients with ICH.ResultsAmong the 49,950 ICH patients, the rate of early DVT prophylaxis implementation was 49.9%, the rate of early mobilization implementation was 29.49%, and that of pharmacological prophylaxis was 2.02%. Factors associated with an increased likelihood of early DVT prophylaxis being administered in the multivariable model included receiving early rehabilitation therapy (odds ratio [OR], 2.531); admission to stroke unit (OR 2.231); admission to intensive care unit (OR 1.975); being located in central (OR 1.879) or eastern regions (OR 1.529); having a history of chronic obstructive pulmonary disease (OR 1.292), ischemic stroke (OR 1.245), coronary heart disease or myocardial infarction (OR 1.2); taking antihypertensive drugs (OR 1.136); and having a higher Glasgow Coma Scale (GCS) score (OR 1.045). Conversely, being male (OR 0.936), being hospitalized in tertiary hospitals (OR 0.778), and having a previous intracranial hemorrhage (OR 0.733) were associated with a lower likelihood of early DVT prophylaxis being administered in patients with ICH.ConclusionsThe implementation rate of early DVT prophylaxis among Chinese patients with ICH was subpar, with pharmacological prophylaxis showing the lowest prevalence. Various controllable factors exerted an impact on the implementation of early DVT prophylaxis in this population.

Dataset Information

Combination of D-dimer and Albumin in the Prediction of Deep Vein Thrombosis in Patients with Spontaneous Intracerebral Hemorrhage.

Background and purpose

Methods

Results

Conclusions

Publications

Combination of D-dimer and Albumin in the Prediction of Deep Vein Thrombosis in Patients with Spontaneous Intracerebral Hemorrhage.

Similar Datasets

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