Abstract
We aimed to investigate the efficacy of an objective method using AI-based retinal characteristic analysis to automatically differentiate between two traditional Chinese syndromes that are associated with ischemic stroke. Inpatient clinical and retinal data were retrospectively retrieved from the archive of our hospital. Patients diagnosed with cerebral infarction in the department of acupuncture and moxibustion between 2014 and 2018 were examined. Of these, the patients with Qi deficiency blood stasis syndrome (QDBS) and phlegm stasis in channels (PSIC) syndrome were selected. Those without retinal photos were excluded. To measure and analyze the patients' retinal vessel characteristics, we applied a patented AI-assisted automated retinal image analysis system developed by the Chinese University of Hong Kong. The demographic, clinical, and retinal information was compared between the QDBS and PSIC patients. The t-test and chi-squared test were used to analyze continuous data and categorical data, respectively. All the selected clinical information and retinal vessel measures were used to develop different discriminative models for QDBS and PSIC using logistic regression. Discriminative efficacy and model performances were evaluated by plotting a receiver operating characteristic curve. As compared to QDBS, the PSIC patients had a lower incidence of insomnia problems (46% versus 29% respectively, p=0.023) and a higher tortuosity index (0.45 ± 0.07 versus 0.47 ± 0.07, p=0.027). Moreover, the area under the curve of the logistic model showed that its discriminative efficacy based on both retinal and clinical characteristics was 86.7%, which was better than the model that employed retinal or clinical characteristics individually. Thus, the discriminative model using AI-assisted retinal characteristic analysis showed statistically significantly better performance in QDBS and PSIC syndrome differentiation among stroke patients. Therefore, we concluded that retinal characteristics added value to the clinical differentiation between QDBS and PSIC.
Highlights
Since 2012, stroke has been a leading cause of death and disability in China, and its incidence has been increasing at a rate of 8.7% per year [1]. e most common subtype of stroke in China is ischemic stroke, accounting for 43–79% of all stroke patients [2]
One of the basic features of Traditional Chinese medicine (TCM) for stroke is a treatment plan based on syndrome differentiation [4], that is, every TCM physician makes a diagnosis of stroke and individually prescribes medication based on each patient’s syndrome differentiation. erefore, the accuracy of the differentiation is the key to efficiently treating this disease
We focused on the clinical risks of ischemic stroke and demonstrated that a history of insomnia or drinking could indicate the presence the two TCM syndromes, Qi deficiency and blood stasis syndrome (QDBS) and phlegm stasis in channels syndrome (PSIC)
Summary
Since 2012, stroke has been a leading cause of death and disability in China, and its incidence has been increasing at a rate of 8.7% per year [1]. e most common subtype of stroke in China is ischemic stroke, accounting for 43–79% of all stroke patients [2]. According to the “Guidelines for the Diagnosis and Treatment of Common Diseases in the Traditional Chinese. Medicine” [5], the syndromes (“ZHENG” in Chinese) of stroke are described in six aspects: wind pattern (Feng Zheng), heat pattern (Huo Re Zheng), phlegm pattern (Tan Zheng), blood stasis pattern (Xue Yu Zheng), qi deficiency pattern (Qi Xu Zheng), and yin deficiency pattern (Yin Xu Zheng). According to these syndromes, we arranged and combined them into seven syndrome types [6]. The Qi deficiency and blood stasis syndrome (QDBS) and the phlegm stasis in channels syndrome (PSIC) are most common syndrome types in ischemic stroke patients, occurring in about 53.6% of cases [7]
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