Ventricular rate smoothing for atrial fibrillation: a quantitative comparison study.

AIMS: To quantitatively compare the ventricular rate-smoothing (VRS) effects of different ventricular pacing (VP) protocols for atrial fibrillation (AF). METHODS AND RESULTS: Using a recently developed open-source model that can simulate the ventricular response in AF and VP, the performance of fixed-rate pacing and four previously published VRS algorithms were assessed by the mean RR (mRR), the root mean square of successive RR differences (RMSSD), the percentage of ventricular senses (VS%), and the percentage of short RR intervals (sRR%). All pacing protocols cause rate-dependent reduction of RMSSD, VS%, and sRR% with or without shortening of mRR compared to spontaneous AF. Fixed-rate pacing was more sensitive to the intrinsic rate than the VRS algorithms. The performance was generally comparable between different VRS algorithms, although higher mRR and VS% can be achieved at the expense of larger RMSSD and sRR%. CONCLUSION: The effect of VP on ventricular rhythm in AF depends on both intrinsic rate and the aggressiveness of the pacing protocol. Adequate rate control is necessary for effective operation of the VRS algorithm. Choosing VRS algorithm should balance between the beneficial effects of rate regularization and the negative effects of increasing heart rate and percentage of VP.     

Effects of sino-aortic denervation on spectral characteristics of blood pressure and pulse interval variability: a wide-band approach

Sino-aortic denervation (SAD) is employed in cats to evaluate the baroreflex influence on blood pressure (BP) and pulse interval (PI) spectral components from 0·00008 to 0·9 Hz as assessed by FFT wide-band spectra and their 1/f modelling; and the linear coupling between BP and PI and between systolic and diastolic BP as assessed by coherence analysis. Specific procedures have been developed to obtain an effective smoothing of spectra and coherence functions. SAD induced an increase in BP powers from 0·03 to 0·0006 Hz and a power reduction of most of the remaining BP components; a reduction of PI powers at all frequencies; marked deviations of BP spectra from the 1/f trend; a reduction of the coherence between BP and PI from 0·12 to 0·5 Hz and a coherence enhancement at lower frequencies. These findings indicate that the arterial baroreflex modulates both fast and slow spectral components of BP and PI; homogeneously enhances PI fluctuations at all frequencies; produces differentiated effects on BP fluctuations along the frequency axis; and at low frequencies exerts the buffering action on BP through strategies which reduce the BP-PI linear link.     

Characteristics of\dot V_A /\dot Q distributions recovered from inert gas elimination datadistributions recovered from inert gas elimination data

The resolving powers of the enforced smoothing and log-normal parametric estimation techniques in recovering ventilation/perfusion ratio distributions were evaluated using noisy inert gas elimination data simulated from hypothetical distribution functions representing various degrees of heterogeneity. The resolving powers were assessed in terms of the statistical recoverabilities of the shunt, dead space, modality, and modal moments characterizing the perfusion distribution. For all distributions tested, both modal mean and shunt were estimated by either technique with sufficient accuracies. Modal dispersions (σ) were consistently overestimated by up to 0.15 decade for narrow distributions, but the mean errors became negligible for σ greater than 0.2 decade. As compared with the shunt, the dead space estimates were more variable and biased, probably due to their indirect estimation from the perfusion distribution, which was imperfectly recovered. Both broad unimodal and widely separated bimodal or trimodal distributions (σ>0.6 decade) were recovered as bimodal distributions of similar forms, so that detection of modality was difficult. The recoveries by both techniques were comparable in most cases studied, except that parametric estimation generally tended to be more sensitive to measurement errors and was computationally less efficient. These results provide a useful basis for the interpretation of distributions obtained from empirical inert gas data.     

Detecting antibodies with similar reactivity patterns in the HLDA8 blind panel of flow cytometry data

The blind panel collected for the 8th Human Leucocyte Differentiation Antigens Workshop (HLDA8; ) included 49 antibodies of known CD specificities and 76 antibodies of unknown specificity. We have identified groups of antibodies showing similar patterns of reactivity that need to be investigated by biochemical methods to evaluate whether the antibodies within these groups are reacting with the same molecule. Our approach to data analysis was based on the work of Salganik et al. (in press) [Salganik, M.P., Milford E.L., Hardie D.L., Shaw, S., Wand, M.P., in press. Classifying antibodies using flow cytometry data: class prediction and class discovery. Biometrical Journal].     

调任通督治疗失眠症实施护理干预的临床观察

目的 探讨调任通督治疗并实施护理干预对失眠患者睡眠的影响.方法 将57例失眠患者随机分为对照组28例和干预组29例,对照组给予调任通督针剌治疗,干预组在调任通督治疗基础上实施护理干预,观察两组心理健康状况、睡眠质量、临床疗效及治疗依从性,并进行比较.结果 干预组治愈率明显高于对照组,心理健康状况、睡眠质量指标及对治疗的依从性亦明显优于对照组.结论 调任通督针刺并实施护理干预是治疗失眠症的有效方法.     

Global Analysis of Methylation Profiles From High Resolution CpG Data

New high throughput technologies are now enabling simultaneous epigenetic profiling of DNA methylation at hundreds of thousands of CpGs across the genome. A problem of considerable practical interest is identification of large scale, global changes in methylation that are associated with environmental variables, clinical outcomes, or other experimental conditions. However, there has been little statistical research on methods for global methylation analysis using technologies with individual CpG resolution. To address this critical gap in the literature, we develop a new strategy for global analysis of methylation profiles using a functional regression approach wherein we approximate either the density or the cumulative distribution function (CDF) of the methylation values for each individual using B‐spline basis functions. The spline coefficients for each individual are allowed to summarize the individual's overall methylation profile. We then test for association between the overall distribution and a continuous or dichotomous outcome variable using a variance component score test that naturally accommodates the correlation between spline coefficients. Simulations indicate that our proposed approach has desirable power while protecting type I error. The method was applied to detect methylation differences, both genome wide and at LINE1 elements, between the blood samples from rheumatoid arthritis patients and healthy controls and to detect the epigenetic changes of human hepatocarcinogenesis in the context of alcohol abuse and hepatitis C virus infection. A free implementation of our methods in the R language is available in the Global Analysis of Methylation Profiles (GAMP) package at http://research.fhcrc.org/wu/en.html .     

季节性指数平滑法在预测某院儿科门诊人次中的应用

目的应用季节性指数平滑法预测某院儿科门诊人次,为儿科合理调配医疗资源提供科学依据。方法基于2013年1月1日-2018年12月31日某院儿科门诊人次数据,使用SPSS22.0软件建立季节性指数平滑模型,采用2016年1月1日-2018年12月31日各季度儿科门诊人次数据进行验证,并对2019年1月1日-2020年12月31日儿科门诊人次进行预测。结果季节性指数平滑法的最优预测模型为Winters相加模型,该模型在Gamma(趋势)、Delta(季节)均有统计学意义,平稳的R^2分别为0.76,R^2值为0.79,标准化的BIC为20.69,模型残差为白噪声序列,平均相对误差为8.85%;2019年1月1日-2020年12月31日某院儿科门诊人次的预测仍呈现出持续上升的季节性和周期性趋势。结论季节性指数平滑法的Winters相加模型能够较好的拟合该院儿科门诊人次的实际值,可用于儿科门诊量及变化趋势的预测,值得推广应用。     

Nonparametric analysis of dependently interval‐censored failure time data

Failure time studies based on observational cohorts often have to deal with irregular intermittent observation of individuals, which produces interval‐censored failure times. When the observation times depend on factors related to a person's failure time, the failure times may be dependently interval censored. Inverse‐intensity‐of‐visit weighting methods have been developed for irregularly observed longitudinal or repeated measures data and recently extended to parametric failure time analysis. This article develops nonparametric estimation of failure time distributions using weighted generalized estimating equations and monotone smoothing techniques. Simulations are conducted for examination of the finite sample performance of proposed estimators. This research is motivated in part by the Toronto Psoriatic Arthritis Cohort Study, and the proposed methodology is applied to this study.     

Spatiotemporal incidence rate data analysis by nonparametric regression

To monitor the incidence rates of cancers, AIDS, cardiovascular diseases, and other chronic or infectious diseases, some global, national, and regional reporting systems have been built to collect/provide population‐based data about the disease incidence. Such databases usually report daily, monthly, or yearly disease incidence numbers at the city, county, state, or country level, and the disease incidence numbers collected at different places and different times are often correlated, with the ones closer in place or time being more correlated. The correlation reflects the impact of various confounding risk factors, such as weather, demographic factors, lifestyles, and other cultural and environmental factors. Because such impact is complicated and challenging to describe, the spatiotemporal (ST) correlation in the observed disease incidence data has complicated ST structure as well. Furthermore, the ST correlation is hidden in the observed data and cannot be observed directly. In the literature, there has been some discussion about ST data modeling. But, the existing methods either impose various restrictive assumptions on the ST correlation that are hard to justify, or ignore partially or entirely the ST correlation. This paper aims to develop a flexible and effective method for ST disease incidence data modeling, using nonparametric local smoothing methods. This method can properly accommodate the ST data correlation. Theoretical justifications and numerical studies show that it works well in practice.