Sivakumar Jayanth, Ahmed Saba, Begdache Lina, Jain Swati, Won Daehan
Department of Systems Science and Industrial Engineering, The State University of New York at Binghamton, Binghamton, NY 13902, USA.
Department of Biological Sciences, The State University of New York at Binghamton, Binghamton, NY 13902, USA.
J Pers Med. 2020 Nov 9;10(4):214. doi: 10.3390/jpm10040214.
Comorbidities, dietary supplement use, and prescription drug use may negatively (or positively) affect mental health in cardiovascular patients. Although the significance of mental illnesses, such as depression, anxiety, and schizophrenia, on cardiovascular disease is well documented, mental illnesses resulting from heart disease are not well studied. In this paper, we introduce the risk factors of mental illnesses as an exploratory study and develop a prediction framework for mental illness that uses comorbidities, dietary supplements, and drug usage in heart disease patients. Particularly, the data used in this study consist of the records of 68,647 patients with heart disease, including the patient's mental illness information and the patient's intake of dietary supplements, antibiotics, and comorbidities. Patients in age groups <61, gender differences, and drug intakes, such as Azithromycin, Clarithromycin, Vitamin B6, and Coenzyme Q10, were associated with mental illness. For predictive modeling, we consider applying various state-of-the-art machine learning techniques with tuned parameters and finally obtain the following: Depression: 78.01% accuracy, 79.13% sensitivity, 72.65% specificity, and 86.26% Area Under the Curve (AUC). Anxiety: 82.93% accuracy, 82.86% sensitivity, 83.35% specificity, and 88.45% AUC. Schizophrenia: 87.59% accuracy, 87.70% sensitivity, 85.14% specificity, and 92.73% AUC. Disease: 86.63% accuracy, 95.50% sensitivity, 77.76% specificity, and 91.59% AUC. From the results, we conclude that using heart disease information, comorbidities, dietary supplement use, and antibiotics enables us to accurately predict the mental health outcome.
合并症、膳食补充剂的使用和处方药的使用可能对心血管疾病患者的心理健康产生负面影响（或正面影响）。虽然抑郁症、焦虑症和精神分裂症等精神疾病对心血管疾病的影响已有充分记录，但由心脏病导致的精神疾病却未得到充分研究。在本文中，我们作为一项探索性研究介绍精神疾病的风险因素，并为精神疾病开发一个预测框架，该框架使用合并症、膳食补充剂和心脏病患者的药物使用情况。具体而言，本研究使用的数据包括68647名心脏病患者的记录，其中包括患者的精神疾病信息以及患者对膳食补充剂、抗生素和合并症的摄入情况。年龄组<61岁的患者、性别差异以及阿奇霉素、克拉霉素、维生素B6和辅酶Q10等药物的摄入与精神疾病有关。对于预测建模，我们考虑应用各种经过参数调整的先进机器学习技术，最终得到以下结果：抑郁症：准确率78.01%，灵敏度79.13%，特异度72.65%，曲线下面积（AUC）86.26%。焦虑症：准确率82.93%，灵敏度82.86%，特异度83.35%，AUC 88.45%。精神分裂症：准确率87.59%，灵敏度87.70%，特异度85.14%，AUC 92.73%。疾病：准确率86.63%，灵敏度95.50%，特异度77.76%，AUC 91.59%。从结果中我们得出结论，利用心脏病信息、合并症、膳食补充剂的使用和抗生素能够准确预测心理健康结果。
