Dataset Information

Clinical profile and risk factors of cerebral venous sinus thrombosis (CVST) in Sudan: A multicenter cross-sectional study.

ABSTRACT:

Background

Cerebral venous sinus thrombosis (CVST) is a relatively uncommon cause of stroke that mainly affects young ladies, with a wide spectrum of symptoms severity, and prognosis. In this study, we aim to study the clinical profile and Risk Factors of CVST among Sudanese patients in Khartoum state hospitals.

Methods

This was a multi-center cross-sectional hospital-based study that covered 37 participants in three major hospitals in Khartoum, with radiologically confirmed Cerebral Venous Sinus Thrombosis (CVST).

Results

About 37 patients were included in this study. The median age was 35 years; the range was 52 years, with a minimum age of 23 years and a maximum of 75 years. The commonest presenting feature was headache (n = 35; 94.6%), followed by blurring of vision (n = 25; 67.6%), while seizures is a presenting symptom in nearly half of the patients (n = 17; 45.9%), on examination papilledema was present in 83.8%. In this study 13.8% were pregnant, 31.0% were postpartum and OCPS users account for 27%. Regarding the involved sinus; Sagittal Venous Sinus and the transverse sinus were the most affected sinuses. Regarding treatment options: "low molecular weight heparin followed with warfarin" was found in 81.1%, followed by heparin in only 10.8%, while the new agents NOACs comprised only 8.1%.

Conclusion

Cerebral Venous Sinus Thrombosis is mainly a disease of child-bearing women, although significant proportions of men were affected. Cerebral Venous Sinus Thrombosis presents in a wide variety of signs and symptoms.

SUBMITTER: Ibrahim EAA

PROVIDER: S-EPMC9758368 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Clinical profile and risk factors of cerebral venous sinus thrombosis (CVST) in Sudan: A multicenter cross-sectional study.

Ibrahim Etedal Ahmed A EAA Hassan Mohamed Rofiedah Eisa RE Hussien Mohamed Ahmed Khabab Abbasher KA Haroun Mazin S MS Abdalla Yassin Abdelrahim YA Abdalla Omer Mohammed Eltahier ME Mahmmoud Fadelallah Eljack Mohammed M

Annals of medicine and surgery (2012) 20221117

<h4>Background</h4>Cerebral venous sinus thrombosis (CVST) is a relatively uncommon cause of stroke that mainly affects young ladies, with a wide spectrum of symptoms severity, and prognosis. In this study, we aim to study the clinical profile and Risk Factors of CVST among Sudanese patients in Khartoum state hospitals.<h4>Methods</h4>This was a multi-center cross-sectional hospital-based study that covered 37 participants in three major hospitals in Khartoum, with radiologically confirmed Cereb ...[more]

PMID: 36536723

Similar Datasets

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.

Dataset Information

Clinical profile and risk factors of cerebral venous sinus thrombosis (CVST) in Sudan: A multicenter cross-sectional study.

Background

Methods

Results

Conclusion

Publications

Clinical profile and risk factors of cerebral venous sinus thrombosis (CVST) in Sudan: A multicenter cross-sectional study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets