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Persistent somatic symptoms (PSS) are a diagnostic core criterion of the somatic symptom disorder. This longitudinal study aims to determine the frequency of PSS in patients with cardiac disease, identify potential predictive factors, and investigate its impact on healthcare utilization. Somatic symptoms were assessed with the Somatic Symptom Scale-8 four times over the course of three months in consecutively approached cardiac outpatients. Patients were grouped having PSS vs. not having PSS following a psychometric-driven approach based on the SSS-8 cut-off score and a data-driven approach applying cluster analysis. T-tests were performed to compare the characteristics between patients having vs. not having PSS. To identify predictors of group affiliation, we conducted multivariable logistic regressions. Additionally, analyses of covariance were used to further examine associations between healthcare utilization and group affiliation. The study included 95 patients (30.5% female) with a mean age of 60.5 years (SD = 8.7). All patients had at least one of the following cardiac diseases recorded in their medical history: coronary heart disease (n = 51), myocardial infarction (n = 21), valve disease (n = 22), cardiomyopathy (n = 15), cardiac dysrhythmia (n = 43), and heart failure (n = 12). 30 (32%) were grouped having PSS according to the psychometric-driven approach and 27 (28%) according to the data-driven approach. For both approaches, patients with PSS were more likely to be female, unemployed, reporting angina pectoris, having higher depression, and higher anxiety severity (for all: p ≤ 0.05). Predictors of PSS group affiliation were female gender, higher age, depression severity, and angina pectoris (for all: p ≤ 0.015). Patients with PSS more frequently visited general practitioners and cardiologists compared to patients without PSS (p ≤ 0.013). Enhancing our knowledge of PSS in patients with cardiac disease could help to improve identification of patients’ specific needs and the factors to consider in diagnosis and individualized treatment.
Persistent somatic symptoms (PSS) are a diagnostic core criterion of the somatic symptom disorder. This longitudinal study aims to determine the frequency of PSS in patients with cardiac disease, identify potential predictive factors, and investigate its impact on healthcare utilization. Somatic symptoms were assessed with the Somatic Symptom Scale-8 four times over the course of three months in consecutively approached cardiac outpatients. Patients were grouped having PSS vs. not having PSS following a psychometric-driven approach based on the SSS-8 cut-off score and a data-driven approach applying cluster analysis. T-tests were performed to compare the characteristics between patients having vs. not having PSS. To identify predictors of group affiliation, we conducted multivariable logistic regressions. Additionally, analyses of covariance were used to further examine associations between healthcare utilization and group affiliation. The study included 95 patients (30.5% female) with a mean age of 60.5 years (SD = 8.7). All patients had at least one of the following cardiac diseases recorded in their medical history: coronary heart disease (n = 51), myocardial infarction (n = 21), valve disease (n = 22), cardiomyopathy (n = 15), cardiac dysrhythmia (n = 43), and heart failure (n = 12). 30 (32%) were grouped having PSS according to the psychometric-driven approach and 27 (28%) according to the data-driven approach. For both approaches, patients with PSS were more likely to be female, unemployed, reporting angina pectoris, having higher depression, and higher anxiety severity (for all: p ≤ 0.05). Predictors of PSS group affiliation were female gender, higher age, depression severity, and angina pectoris (for all: p ≤ 0.015). Patients with PSS more frequently visited general practitioners and cardiologists compared to patients without PSS (p ≤ 0.013). Enhancing our knowledge of PSS in patients with cardiac disease could help to improve identification of patients’ specific needs and the factors to consider in diagnosis and individualized treatment.
Ancient Chinese porcelain occupies an important position in Chinese cultural relics, and the development process of ceramics in various periods has played a great role in promoting the development of society. To explore the historical evolution path of Chinese ceramic technology, this paper proposes a data mining approach. The first step is to list the data mining tools, and then a distributed data crawler is deployed to crawl textual information related to Chinese ceramics in the Cultural Collection by defining keywords related to Chinese porcelain. Then, the incomplete data duplication, semantic ambiguity, and low-value and unclear pointing information that existed in the original text data were deleted. By setting thresholds and sorting, keywords with higher weights were filtered after scanning the cleaned texts. To compare data from different periods and subjects, the data was normalized. Correlation analysis was used to extract historical changes in Chinese ceramic technology in the time dimension, and then the components of ceramics in the historical evolution were analyzed by K-mean-based principal component analysis. Ceramic manufacturing technology mainly developed during the Five Dynasties and Two Songs, formed during the Yuan Dynasty, matured during the Ming Dynasty, flourished during the Qing Dynasty, and declined during the Republic of China. The first six principal components were extracted because their cumulative variance contribution exceeded 85%. In detail, the samples were divided into four categories according to each principal component, and the classification results reflect the differences in the content of pottery-making raw materials. Side by side, it reflects that pottery-making technology is changing with the advancement of history.
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