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OBJECTIVE: To derive the Chinese medicine (CM) syndrome classification and subgroup syndrome characteristics of ischemic stroke patients. METHODS: By extracting the CM clinical electronic medical records (EMRs) of 7,170 hospitalized patients with ischemic stroke from 2016 to 2018 at Weifang Hospital of Traditional Chinese Medicine, Shandong Province, China, a patient similarity network (PSN) was constructed based on the symptomatic phenotype of the patients. Thereafter the efficient community detection method BGLL was used to identify subgroups of patients. Finally, subgroups with a large number of cases were selected to analyze the specific manifestations of clinical symptoms and CM syndromes in each subgroup. RESULTS: Seven main subgroups of patients with specific symptom characteristics were identified, including M3, M2, M1, M5, M0, M29 and M4. M3 and M0 subgroups had prominent posterior circulatory symptoms, while M3 was associated with autonomic disorders, and M4 manifested as anxiety; M2 and M4 had motor and motor coordination disorders; M1 had sensory disorders; M5 had more obvious lung infections; M29 had a disorder of consciousness. The specificity of CM syndromes of each subgroup was as follows. M3, M2, M1, M0, M29 and M4 all had the same syndrome as wind phlegm pattern; M3 and M0 both showed hyperactivity of Gan (Liver) yang pattern; M2 and M29 had similar syndromes, which corresponded to intertwined phlegm and blood stasis pattern and phlegm-stasis obstructing meridians pattern, respectively. The manifestations of CM syndromes often appeared in a combination of 2 or more syndrome elements. The most common combination of these 7 subgroups was wind-phlegm. The 7 subgroups of CM syndrome elements were specifically manifested as pathogenic wind, pathogenic phlegm, and deficiency pathogens. CONCLUSIONS: There were 7 main symptom similarity-based subgroups in ischemic stroke patients, and their specific characteristics were obvious. The main syndromes were wind phlegm pattern and hyperactivity of Gan yang pattern.
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AVC Isquêmico , Humanos , Síndrome , Medicina Tradicional Chinesa , Fígado , FenótipoRESUMO
Cerebral palsy is one of the most prevalent neurological disorders and the most frequent cause of disability. Identifying the syndrome by patients' symptoms is the key to traditional Chinese medicine (TCM) cerebral palsy treatment. Artificial intelligence (AI) is advancing quickly in several sectors, including TCM. AI will considerably enhance the dependability and precision of diagnoses, expanding effective treatment methods' usage. Thus, for cerebral palsy, it is necessary to build a decision-making model to aid in the syndrome diagnosis process. While the recurrent neural network (RNN) model has the potential to capture the correlation between symptoms and syndromes from electronic medical records (EMRs), it lacks TCM knowledge. To make the model benefit from both TCM knowledge and EMRs, unlike the ordinary training routine, we begin by constructing a knowledge-based RNN (KBRNN) based on the cerebral palsy knowledge graph for domain knowledge. More specifically, we design an evolution algorithm for extracting knowledge in the cerebral palsy knowledge graph. Then, we embed the knowledge into tensors and inject them into the RNN. In addition, the KBRNN can benefit from the labeled EMRs. We use EMRs to fine-tune the KBRNN, which improves prediction accuracy. Our study shows that knowledge injection can effectively improve the model effect. The KBRNN can achieve 79.31% diagnostic accuracy with only knowledge injection. Moreover, the KBRNN can be further trained by the EMRs. The results show that the accuracy of fully trained KBRNN is 83.12%.
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METHODS: Individualized treatment of traditional Chinese medicine (TCM) provides a theoretical basis for the study of the personalized classification of complex diseases. Utilizing the TCM clinical electronic medical records (EMRs) of 7170 in patients with IS, a patient similarity network (PSN) with shared symptoms was constructed. Next, patient subgroups were identified using community detection methods and enrichment analyses were performed. Finally, genetic data of symptoms, herbs, and drugs were used for pathway and GO analysis to explore the characteristics of pathways of subgroups and to compare the similarities and differences in genetic pathways of herbs and drugs from the perspective of molecular pathways of symptoms. RESULTS: We identified 34 patient modules from the PSN, of which 7 modules include 98.48% of the whole cases. The 7 patient subgroups have their own characteristics of risk factors, complications, and comorbidities and the underlying genetic pathways of symptoms, drugs, and herbs. Each subgroup has the largest number of herb pathways. For specific symptom pathways, the number of herb pathways is more than that of drugs. CONCLUSION: The research of disease classification based on community detection of symptom-shared patient networks is practical; the common molecular pathway of symptoms and herbs reflects the rationality of TCM herbs on symptoms and the wide range of therapeutic targets.
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OBJECTIVE: To explore the rule of point selection in treatment of cerebral palsy with acupuncture in preschool children. METHODS: Based on the electronic medical records of Xi'an Encephalopathy Hospital of TCM, through structuring medical record text, acupuncture prescriptions were extracted. Using the data mining tools of the ancient and modern medical record cloud platform V2.2.3 and the clinical effective prescription and molecular mechanism analysis system of traditional Chinese medicine V2.0, the cluster analysis and complex network analysis were conducted on acupuncture prescriptions. RESULTS: Of 1584 acupuncture prescriptions for cerebral palsy in children, there were 84 acupoints and stimulating areas of scalp acupuncture, of which, foot-motor-sensory area, balance area and Sanyinjiao (SP 6) were the top 3 acupoints with the highest use rate. With cluster analysis, 5 groups of common supplementary acupoints and stimulating areas were found, named, Weizhong (BL 40) and Waiguan (TE 5), Shousanli (LI 10), Xingjian (LR 2), Xuanzhong (GB 39) and Chengfu (BL 36), foot-motor-sensory area, balance area and Sanyinjiao (SP 6), Xuehai (SP 10) and Fenglong (ST 40), Pishu (BL 20), motor area and Yanglingquan (GB 34). With complex network analysis on core prescriptions, 13 core acupoints and stimulating areas of scalp acupuncture were obtained, including 3 core main points, i.e. Sanyinjiao (SP 6), balance area and foot-motor-sensory area and 10 sub-core points, i.e. Taichong (LR 3), motor area, Xuehai (SP 10), Ganshu (BL 18), Pishu (BL 20), Yanglingquan (GB 34), Sishencong (EX-HN 1), Baihui (GV 20), Fengchi (GB 20) and Shenshu (BL 23). CONCLUSION: In treatment of acupuncture for cerebral palsy in preschool children, the core prescriptions reveal the simultaneous treatment of exterior and interior, the mutual regulation of yin and yang and the combination of acupoints with stimulating ares of scalp acupuncture for both encephalopathy and paralysis.
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Terapia por Acupuntura , Paralisia Cerebral , Pontos de Acupuntura , Paralisia Cerebral/terapia , Pré-Escolar , Mineração de Dados , Registros Eletrônicos de Saúde , HumanosRESUMO
Purpose. To conduct a meta-analysis evaluating the efficacy of Shenfu injection for treating patients with septic shock when compared with conventional therapy. Methods. Eight databases including Pubmed, EMBASE, Cochrane Library, ISI Web of Science, CNKI, Wanfang, VIP, and CBM were searched up to October 2014. Randomized controlled trials assessing the efficacy of Shenfu injection were identified. Mean arterial pressure, heart rate, lactate, and mortality were included as outcome measurements. Results. We analyzed data from 12 randomized controlled trials involving 904 participants. Compared with conventional therapy, Shenfu injection could further increase the mean arterial pressure at 1 hour (SMD 0.38; 95% CI, 0.01-0.74) and 6 hours (SMD 0.82; 95% CI, 0.03-1.61). Shenfu injection could further normalize heart rate at 6 hours (SMD -0.90; 95% CI, -1.47-0.33) and clear serum lactate at 6 hours (SMD -0.51; 95% CI, -0.70-0.32) and 24 hours (SMD, 0.52; 95% CI, -0.77-0.26). As the endpoint of mortality was not unified, it was not meta-analyzed. Conclusions. Based on the findings in present review, Shenfu injection is more effective than conventional therapy in increasing mean arterial pressure, normalizing heart rate, clearing serum lactate, and reducing mortality. These results should be confirmed in higher level clinical trials in the future.