Predicting new-onset post-stroke depression from real-world data using machine learning algorithm

IntroductionPost-stroke depression (PSD) is a serious mental disorder after ischemic stroke. Early detection is important for clinical practice. This research aims to develop machine learning models to predict new-onset PSD using real-world data.MethodsWe collected data for ischemic stroke patients from multiple medical institutions in Taiwan between 2001 and 2019. We developed models from 61,460 patients and used 15,366 independent patients to test the models’ performance by evaluating their specificities and sensitivities. The predicted targets were whether PSD occurred at 30, 90, 180, and 365 days post-stroke. We ranked the important clinical features in these models.ResultsIn the study’s database sample, 1.3% of patients were diagnosed with PSD. The average specificity and sensitivity of these four models were 0.83–0.91 and 0.30–0.48, respectively. Ten features were listed as important features related to PSD at different time points, namely old age, high height, low weight post-stroke, higher diastolic blood pressure after stroke, no pre-stroke hypertension but post-stroke hypertension (new-onset hypertension), post-stroke sleep-wake disorders, post-stroke anxiety disorders, post-stroke hemiplegia, and lower blood urea nitrogen during stroke.DiscussionMachine learning models can provide as potential predictive tools for PSD and important factors are identified to alert clinicians for early detection of depression in high-risk stroke patients

Women with endometriosis have higher comorbidities: Analysis of domestic data in Taiwan

AbstractEndometriosis, defined by the presence of viable extrauterine endometrial glands and stroma, can grow or bleed cyclically, and possesses characteristics including a destructive, invasive, and metastatic nature. Since endometriosis may result in pelvic inflammation, adhesion, chronic pain, and infertility, and can progress to biologically malignant tumors, it is a long-term major health issue in women of reproductive age. In this review, we analyze the Taiwan domestic research addressing associations between endometriosis and other diseases. Concerning malignant tumors, we identified four studies on the links between endometriosis and ovarian cancer, one on breast cancer, two on endometrial cancer, one on colorectal cancer, and one on other malignancies, as well as one on associations between endometriosis and irritable bowel syndrome, one on links with migraine headache, three on links with pelvic inflammatory diseases, four on links with infertility, four on links with obesity, four on links with chronic liver disease, four on links with rheumatoid arthritis, four on links with chronic renal disease, five on links with diabetes mellitus, and five on links with cardiovascular diseases (hypertension, hyperlipidemia, etc.). The data available to date support that women with endometriosis might be at risk of some chronic illnesses and certain malignancies, although we consider the evidence for some comorbidities to be of low quality, for example, the association between colon cancer and adenomyosis/endometriosis. We still believe that the risk of comorbidity might be higher in women with endometriosis than that we supposed before. More research is needed to determine whether women with endometriosis are really at risk of these comorbidities

An Efficient Essential Secret Image Sharing Scheme Using Derivative Polynomial

As a popular technology in information security, secret image sharing is a method to guarantee the secret image’s security. Usually, the dealer would decompose the secret image into a series of shadows and then assign them to a number of participants, and only a quorum of participants could recover the secret image. Generally, it is assumed that every participant is equal. Actually, due to their position in many practical applications, some participants are given special privileges. Therefore, it is desirable to give an approach to generate shadows with different priorities shadows. In this paper, an efficient essential secret image sharing scheme using a derivative polynomial is proposed. Compared with existing related works, our proposed scheme can not only create the same-sized shadows with smaller size but also removes the concatenation operation in the sharing phase. Theoretical analysis and simulations confirm the security and effectiveness of the proposed scheme

The Impact of Clinical Prognosis of Viral Hepatitis in Head and Neck Cancer Patients Receiving Concurrent Chemoradiotherapy

This study evaluated the clinical characteristics of head and neck cancer (HNC) patients with hepatitis B (HBV) or hepatitis C (HCV) who underwent concurrent chemoradiotherapy (CCRT) and examined the prognostic impact of antiviral therapies. In a 19-year retrospective analysis of 8224 HNC patients treated with CCRT, 29.8% (2452) were diagnosed with HBV or HCV, of whom 714 received antiviral therapy. For non-metastatic HNC patients on CCRT, factors such as gender, Charlson Comorbidity Index (CCI), liver cirrhosis markers (Fibrosis-4, APRI), and initial tumor stage were significant determinants of their overall survival. However, the presence of HBV or HCV and the administration of antiviral treatments did not yield distinct survival outcomes. In summary, antiviral therapy for HBV or HCV did not affect the 5-year survival rates of non-metastatic HNC patients undergoing CCRT, while gender, tumor stage, CCI, and liver cirrhosis were notable prognostic indicators