Diagnostic and Treatment Features of Stroke Patients Based on RAPID Artificial Intelligent (RAPID AI) Software Analysis in Phu Tho Provincial General Hospital in Vietnam (Preprint)
Authors: Nguyen Ngoc Huy , Hoang Minh Van , Nguyen An Quang , Nguyen Thong Van , Tran Luc Quang , Nguyen Minh Anh , Ha Quyet Manh 
Published: May 2021

BACKGROUND

Stroke is the second leading cause of death and the leading cause of permanent disability global-ly. Vietnam is a developing country with a high prevalence of stroke. This study was conducted from October 2019 to October 2020 at Phu Tho Provincial General Hospital, Vietnam.

OBJECTIVE

The study aimed to determine and describe the characteristics of 54 acute ischemic stroke patients for whom Rapid AI technology was used for imaging analysis for diagnosis and treatment.

METHODS

This study was a case series based on data from the electronic medical records of stroke patients admitted to Phu Tho Provincial General Hospital between October 2019 and October 2020, for whom Rapid AI was used to analyze images of stroke.

RESULTS

The highlighted results showed that the mean age of patients was 73.39 ± 12.46 years and males comprised 57.4 of the sample. The most common risk factor identified was hypertension (75.9%), followed by atrial fibrillation (24.1%), diabetes (20.4%), alcohol habits (14.8%), and smoking (9.3%). The most common clinical signs were hemiparesis, observed in 75.9% of the patients, fol-lowed by dysphasia in 50.0% and memory loss in 27.8% of the sample. Small numbers of stroke patients had clinical presentations of dizziness (7.4%) and headache (7.4%). In total, 5.6% of stroke patients had a bad prognosis, presenting with unconsciousness and near death. The sub-clinical characteristics included high blood pressure in 48 (88.9%) patients, and the median score for blood pressure was 151.22 ± 22.89 mmHg. The red blood cells and triglyceride were mostly at normal concentrations. The prevalence of elevated blood glucose was 40.7%, while the preva-lence of high cholesterol was 33.3%. A small number of patients showed an abnormal platelet count (5.6%) and INR (3.7%). ASPECTS evaluation showed that 24 (44.4%) patients had good ASPECTS scores of 8–10, 17 (31.5%) patients had bad ASPECTS scores of 5–7, and 13 (24.1%) patients had the worst ASPECTS scores of 0–4. The number of patients with an infarct core vol-ume <70 mL was 50 (92.6%), while a mismatch volume of >15 mL was observed in 31 (54.7%) patients and 22 (40.7%) patients had a mismatch ratio >1.8. The assessment of CT imaging of thrombi showed 51 cases of anterior cerebral circulation, including 13 (24.07%) cases diagnosed as ICA, 30 (75.93%) cases diagnosed as MCA, and 8 (14.81%) cases diagnosed as SA. There were 10 cases of MCA-M1 (18.52%), 7 cases of MCA-M2 and MCA-M4 (12.96%) cases and 6 cases of MCA-M3 (11.11%), respectively. There were only three cases of posterior cerebral circulation, comprising one (1.85%) case of PCA and two (3.72%) cases of BA.

CONCLUSIONS

These are the first results regarding the clinical and subclinical features of patients with stroke investigated using Rapid AI for diagnosis and treatment in Vietnam in general, and specifically in Phu Tho Provincial General Hospital.