Medicine
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Diabetes is a chronic disease caused by absolute or relative insufficiency of insulin secretion and impaired insulin utilization. CDH1 and DVL1 role in diabetes and its nursing care is unclear. The diabetes dataset GSE21321 and GSE19790 profiles were downloaded from the gene expression omnibus (GEO) database. ⋯ Core gene expression heatmap showed that core genes (CTNNB1, CDH1, DVL1) were highly expressed in diabetes samples. CTD analysis showed thatCTNNB1, CDH1, DVL1were associated with weight gain, inflammation, and necrosis. CDH1 and DVL1 are highly expressed in diabetes and may become molecular targets for diabetes and its care.
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Comparative Study Observational Study
Exploring the Relationship between Sleep Pattern and Quality of Life in the Middle-aged Population Based on Fuzzy-set Qualitative Comparative Analysis.
This study aims to investigate the effects of 7 factors (subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleeping medications, and daytime dysfunction), as measured by the Pittsburgh Sleep Quality Index, on the quality of life (QOL) in middle-aged individuals. A total of 194 middle-aged individuals aged 45 to 59 years participated in this study. The Chinese version of the medical outcomes study 36-item short-form health survey and the Pittsburgh Sleep Quality Index were used to assess the QOL and sleep quality, respectively. ⋯ Three configurations of sleep patterns negatively influence QOL: the "low-quality type" with non-high-level subjective sleep quality, sleep duration, and habitual sleep efficiency as core conditions; the "barrier type" with high level of sleep disturbances, non-high-level sleep latency, and non-high-level subjective sleep quality/sleep duration as core conditions; and the "drug-based type" with high level of use of sleeping medications and subjective sleep quality as core conditions. Using the fuzzy-set qualitative comparative analysis method, this study initially reveals that the influence of sleep patterns on QOL in middle-aged individuals is a holistic effect combining multiple elements. This deepens and enriches the understanding of the relationship between sleep patterns and QOL and expands new perspectives for more in-depth research on how to improve the QOL of middle-aged individuals through sleep interventions.
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Previous research on physical activity (PA) has mostly concentrated on a single or small number of activities, with scant coverage of the effects of PA on hypertension (HTN) and all-cause mortality. Most studies examining HTN in the elderly have been too small or shown contradictory findings. We conducted a cross-sectional study using 10 cycles of the National Health and Nutrition Examination Survey data from 1999 to 2018. ⋯ The present study underscores the significant benefits of PA in patients aged 65 years and older with HTN. Notably, it was found to reduce systolic blood pressure and have a positive impact on the decrease of all-cause and hypertensive mortality. These findings highlight the crucial role of PA in the health and longevity of aged patients with HTN.
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The aim of this study was to develop a machine-learning prediction model for AKI after craniotomy and evacuation of hematoma in craniocerebral trauma. We included patients who underwent craniotomy and evacuation of hematoma due to traumatic brain injury in our hospital from January 2015 to December 2020. Ten machine learning methods were selected to model prediction, including XGBoost, Logistic Regression, Light GBM, Random Forest, AdaBoost, GaussianNB, ComplementNB, Support Vector Machines, and KNeighbors. ⋯ The AdaBoost model showed an AUC of 0.909 (95% CI, 0.849-0.970) in the validation cohort. Although there was an underestimated acute kidney injury risk for the model in the calibration curve, there was a net benefit for the AdaBoost model in the decision curve. Our machine learning model was evaluated to have a good performance in the validation cohorts and could be a useful tool in the clinical practice.
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Postoperative cognitive deficits frequently occur in patients undergoing cardiac surgery, leaving them with reduced cognitive function. Cognitive training has been shown to improve cognitive function, however, the role in patients after cardiac surgery is unclear. In this study, we aimed to evaluate the effectiveness and safety of cognitive training in patients undergoing cardiac surgery. ⋯ The present study, based on a low to moderate quality of evidence, suggests that cognitive training improves cognitive functioning, reduces the incidence of postoperative cognitive dysfunction, and has a positive impact on anxiety and depression in patients undergoing cardiac surgery. However, current evidence does not allow for the determination of effects on quality of life, postoperative delirium, and postoperative length of stay.