Computer neural networks

计算机神经网络
  • 文章类型: Journal Article
    背景:关于COVID-19的研究很多,但关于其对戊型肝炎的影响却很少。我们旨在评估COVID-19对策对戊型肝炎发病模式的影响,并探讨时间序列模型在分析该模式中的应用。
    方法:我们的关键想法是将COVID-19爆发前的模型与COVID-19爆发前的数据进行拟合,并使用预测值与实际值之间的偏差来反映COVID-19对策的效果。我们分析了2013-2018年中国戊型肝炎的发病模式。我们在COVID-19爆发前评估了3种方法的拟合和预测能力。此外,我们采用这些方法构建了COVID-19前的发病率模型,并将COVID-19后的预测与现实进行了比较.
    结果:在COVID-19爆发之前,中国戊型肝炎发病模式总体呈固定和季节性,在三月的高峰,十月的低谷,冬季和春季的水平高于夏季和秋季,每年。然而,来自前COVID-19模型的后COVID-19预测在截面上与现实截然不同,但在其他时期则一致。
    结论:自COVID-19大流行以来,中国戊型肝炎的发病模式已经发生了很大的变化,发病率大大降低。COVID-19对策对戊型肝炎发病模式的影响是暂时的。预计戊型肝炎的发病率将逐渐恢复到COVID-19之前的模式。
    BACKGROUND: There are abundant studies on COVID-19 but few on its impact on hepatitis E. We aimed to assess the effect of the COVID-19 countermeasures on the pattern of hepatitis E incidence and explore the application of time series models in analyzing this pattern.
    METHODS: Our pivotal idea was to fit a pre-COVID-19 model with data from before the COVID-19 outbreak and use the deviation between forecast values and actual values to reflect the effect of COVID-19 countermeasures. We analyzed the pattern of hepatitis E incidence in China from 2013 to 2018. We evaluated the fitting and forecasting capability of 3 methods before the COVID-19 outbreak. Furthermore, we employed these methods to construct pre-COVID-19 incidence models and compare post-COVID-19 forecasts with reality.
    RESULTS: Before the COVID-19 outbreak, the Chinese hepatitis E incidence pattern was overall stationary and seasonal, with a peak in March, a trough in October, and higher levels in winter and spring than in summer and autumn, annually. Nevertheless, post-COVID-19 forecasts from pre-COVID-19 models were extremely different from reality in sectional periods but congruous in others.
    CONCLUSIONS: Since the COVID-19 pandemic, the Chinese hepatitis E incidence pattern has altered substantially, and the incidence has greatly decreased. The effect of the COVID-19 countermeasures on the pattern of hepatitis E incidence was temporary. The incidence of hepatitis E was anticipated to gradually revert to its pre-COVID-19 pattern.
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  • 文章类型: Journal Article
    骨矿物质密度(BMD)降低会损害骨小梁中的螺钉购买,并可能导致脊柱器械后螺钉松动。现有的计算机断层扫描(CT)扫描可用于机会性骨质疏松症筛查,以降低BMD。这项病例对照研究的目的是研究机会性评估的BMD与使用半刚性器械进行腰椎退行性不稳的脊柱手术后的结果之间的关系。
    我们回顾了在我们医院接受半刚性器械初次手术的连续患者。随访影像学显示螺钉松动的患者以病例为准。未显示螺钉松动的患者,或者-如果没有随访影像学检查(n=8)-报告了初次手术后≥6个月的手术获益,可作为对照。匹配标准是性别,年龄,和外科构造。在围手术期CT扫描中,通过自动脊柱分割和异步校准,在L1至L4进行机会性BMD筛查。这种深度学习驱动方法的处理步骤可以使用免费提供的在线工具Anduin(https://anduin。骨屏。de).计算BMD的曲线下面积(AUC)作为螺钉松动的预测因子。
    纳入46例老年患者(69.9±9.1岁)-23例和23例对照。大多数手术涉及三个脊柱运动节段(n=34)。20例骨量低,13例骨质疏松BMD。病例的平均BMD(86.5±29.5mg/cm3)明显低于对照组(118.2±32.9mg/cm3,p=0.001),即螺钉松动患者BMD降低。螺钉松动最好通过BMD<81.8mg/cm²来预测(灵敏度=91.3%,特异性=56.5%,AUC=0.769,p=0.002)。
    在接受脊柱手术的老年患者组中,骨质疏松症或低骨量(BMD≤120mg/cm²)的患病率相对较高。螺钉松动与骨密度接近骨质疏松阈值(<80mg/cm3)相关。使用所提出的方法进行机会性BMD筛查是可行的,并且可以指导外科医生采取措施以防止螺钉松动并增加有利的结果。
    Decreased bone mineral density (BMD) impairs screw purchase in trabecular bone and can cause screw loosening following spinal instrumentation. Existing computed tomography (CT) scans could be used for opportunistic osteoporosis screening for decreased BMD. Purpose of this case-control study was to investigate the association of opportunistically assessed BMD with the outcome after spinal surgery with semi-rigid instrumentation for lumbar degenerative instability.
    We reviewed consecutive patients that had primary surgery with semi-rigid instrumentation in our hospital. Patients that showed screw loosening in follow-up imaging qualified as cases. Patients that did not show screw loosening or-if no follow-up imaging was available (n = 8)-reported benefit from surgery ≥ 6 months after primary surgery qualified as controls. Matching criteria were sex, age, and surgical construct. Opportunistic BMD screening was performed at L1 to L4 in perioperative CT scans by automatic spine segmentation and using asynchronous calibration. Processing steps of this deep learning-driven approach can be reproduced using the freely available online-tool Anduin (https://anduin.bonescreen.de). Area under the curve (AUC) was calculated for BMD as a predictor of screw loosening.
    Forty-six elderly patients (69.9 ± 9.1 years)-23 cases and 23 controls-were included. The majority of surgeries involved three spinal motion segments (n = 34). Twenty patients had low bone mass and 13 had osteoporotic BMD. Cases had significantly lower mean BMD (86.5 ± 29.5 mg/cm³) compared to controls (118.2 ± 32.9 mg/cm³, p = 0.001), i.e. patients with screw loosening showed reduced BMD. Screw loosening was best predicted by a BMD < 81.8 mg/cm³ (sensitivity = 91.3%, specificity = 56.5%, AUC = 0.769, p = 0.002).
    Prevalence of osteoporosis or low bone mass (BMD ≤ 120 mg/cm³) was relatively high in this group of elderly patients undergoing spinal surgery. Screw loosening was associated with BMD close to the threshold for osteoporosis (< 80 mg/cm³). Opportunistic BMD screening is feasible using the presented approach and can guide the surgeon to take measures to prevent screw loosening and to increase favorable outcomes.
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