Real-time refinement of subthalamic nucleus targeting using Bayesian decision-making on the root mean square measure.

The subthalamic nucleus (STN) is a major target for treatment of advanced Parkinson's disease patients undergoing deep brain stimulation surgery. Microelectrode recording (MER) is used in many cases to identify the target nucleus. A real-time procedure for identifying the entry and exit points of the STN would improve the outcome of this targeting procedure. We used the normalized root mean square (NRMS) of a short (5 seconds) MER sampled signal and the estimated anatomical distance to target (EDT) as the basis for this procedure. Electrode tip location was defined intraoperatively by an expert neurophysiologist to be before, within, or after the STN. Data from 46 trajectories of 27 patients were used to calculate the Bayesian posterior probability of being in each of these locations, given RMS-EDT pair values. We tested our predictions on each trajectory using a bootstrapping technique, with the rest of the trajectories serving as a training set and found the error in predicting the STN entry to be (mean +/- SD) 0.18 +/- 0.84, and 0.50 +/- 0.59 mm for STN exit point, which yields a 0.30 +/- 0.28 mm deviation from the expert's target center. The simplicity and computational ease of RMS calculation, its spike sorting-independent nature and tolerance to electrode parameters of this Bayesian predictor, can lead directly to the development of a fully automated intraoperative physiological procedure for the refinement of imaging estimates of STN borders.     

Is the apparent U-shape of well-being over the life course a result of inappropriate use of control variables? A commentary on Blanchflower and Oswald (66: 8, 2008, 1733–1749)

In their article in this journal “Is well-being U-shaped over the life cycle?” Blanchflower and Oswald (Blanchflower, D.G., & Oswald, A.J. (2008). Is well-being U-shaped over the life cycle? Social Science & Medicine, 66, 1733–1749) report the results of an ambitious cross-national study of age and well-being and conclude that in most societies studied the well-being of adults tends to be high in young adulthood and old age and lowest around age 40. I argue that the appearance of this U-shaped curve of well-being is the result of the use of inappropriate and questionable control variables. The most clearly inappropriate control variable is marital status, the control of which to a large extent accounts for the U-shaped curve. Most researchers who have studied the relationship between being married and being happy believe that happiness affects marital status (happier people are more likely to marry and stay married), and of course a variable that is affected by the dependent variable should not be included as a control variable in a simple recursive model. Such control variables as income and education are suspect because the relationship between them and well-being is likely to be partially spurious, and such variables as race and whether or not persons lived with both parents at age 16 should not be controlled, because they cannot affect or be affected by age. Finally, year of survey should not be controlled because of the age-period-cohort conundrum, which makes including age, period, and cohort all as predictor variables in a regression inappropriate (and impossible if the three variables are measured precisely and comparably). The only clearly appropriate control variable is birth cohort, and when only it is controlled, the regression data become estimates of how the well-being of persons has actually changed as they have gone through the life course. I argue that such estimates are much more useful than the counterfactual abstractions provided by Blanchflower and Oswald (Blanchflower, D.G., & Oswald, A.J. (2008). Is well-being U-shaped over the life cycle? Social Science & Medicine, 66, 1733–1749), and I conclude that those authors (or someone else) could make a very important contribution by redoing their analyses with birth cohort as the only control variable. I do that with the American happiness data and find that the results do not come close to the U-shaped pattern.     

Causal models of attention-deficit/hyperactivity disorder: from common simple deficits to multiple developmental pathways.

Until recently, causal models of attention-deficit/hyperactivity disorder (ADHD) have tended to focus on the role of common, simple, core deficits. One such model highlights the role of executive dysfunction due to deficient inhibitory control resulting from disturbances in the frontodorsal striatal circuit and associated mesocortical dopaminergic branches. An alternative model presents ADHD as resulting from impaired signaling of delayed rewards arising from disturbances in motivational processes, involving frontoventral striatal reward circuits and mesolimbic branches terminating in the ventral striatum, particularly the nucleus accumbens. In the present article, these models are elaborated in two ways. First, they are each placed within their developmental context by consideration of the role of person x environment correlation and interaction and individual adaptation to developmental constraint. Second, their relationship to one another is reviewed in the light of recent data suggesting that delay aversion and executive functions might each make distinctive contributions to the development of the disorder. This provides an impetus for theoretical models built around the idea of multiple neurodevelopmental pathways. The possibility of neuropathologic heterogeneity in ADHD is likely to have important implications for the clinical management of the condition, potentially impacting on both diagnostic strategies and treatment options.     

Use of current situational information and causal inference: Do dysphoric individuals make “unwarranted” causal inferences?

According to Beck's original theory, depressives make unwarranted negatively biased personal inferences. Specifically, Beck suggested that depressives ignore current positive situational information and are unduly influenced by current negative situational information in making inferences. To test Beck's theory, we used Kelley's normative model of causal inference to examine the utilization of causally relevant situational information by dysphoric, nondepressed, and very nondepressed subjects in making causal attributions for personal success and failure. We used Stevens and Jones' classic method from social psychology and embedded the relevant causal information in the natural flow of events. Results showed that dysphoric, nondepressed, and very nondepressed subjects did, to an equal degree, use such information to make causal attributions. Although dysphoric and both groups of nondepressed subjects used current situational information consistently with Kelley's model, clear-cut baseline differences in the content of their causal attributions existed. Thus, the results supported the reformulations of Beck's theory that emphasize content, rather than process, differences between depressive and nondepressive cognition for dysphoria.Preparation of this article was supported by a Vilas Award, a University of Wisconsin Graduate School Grant, a Romnes Fellowship, a Biomedical Grant, and NIMH Grant R01MH43866 to Lyn Y. Abramson.     

基于两样本孟德尔随机化方法探讨睡眠与痛风的关联

[目的] 通过两样本孟德尔随机化设计,探讨睡眠与痛风之间的关联。[方法] 从一项包含763 813名参与者的全基因组关联研究(genome-wide association study,GWAS)中获取痛风遗传关联数据。以与打鼾、睡眠时间、睡眠类型、失眠及白日困倦程度等睡眠表型相关的单核苷酸多态性(single nucleotide polymorphism,SNP)作为工具变量,采用逆方差加权(inverse variance weighted,IVW)评估遗传学预测的不同睡眠表型与痛风发生风险的关系。采用MR-Egger回归和孟德尔随机多态性残差和离群值(MR pleiotropy residual sum and outlier,MR-PRESSO)检验进行敏感性分析,以评估工具变量的多效性。进一步采用加权中位数法、简单中位数法、最大似然比法等分析方法检验结果的稳健性与可靠性。[结果] IVW结果显示,遗传学预测的打鼾[优势比(odds ratio,OR)=3.12,95%置信区间(confidence interval,CI)(1.21～8.05),PFDR=0.045]和失眠[OR=1.09,95%CI(1.04～1.15),PFDR=0.005]与痛风发生风险呈正相关,而睡眠时间、睡眠类型及白日困倦程度与痛风发生之间不存在统计学关联。MR-Egger回归提示上述因果关联未受到水平多效性影响,加权中位数法、简单中位数法、最大似然比法得出与IVW相似的结果。[结论] 打鼾、失眠与痛风发生风险呈正相关,纠正打鼾和失眠可能对痛风有一定的预防作用。     

多参数信息融合实现非脑电的睡眠结构分期

目前临床睡眠分析的主要手段是多导睡眠图（Polysomnograph,PSG）,用仪器记录被测者整晚的脑电、眼动电和颏肌电等生理参数,计算机进行自动睡眠分期,再由技术人员依据国际标准进行校正.几十年来PSG保持着睡眠分期金标准的地位.提出在不使用脑电的条件下,利用较易获得的心动周期、呼吸、体动等基本生理参数,提取其中与睡眠过程及其变化有关的规律和信息,建立知识规则库,采用不确定推理的证据理论进行多参数睡眠信息融合计算,实现睡眠结构分期.50余例与PSG对照试验结果表明：醒睡的平均符合率达90%以上,基本睡眠结构的平均符合率达75%以上,证明该技术达到了应用的要求.     

长期未转阴新型冠状病毒肺炎患者 血清白蛋白水平与病毒转阴的因果关系探索

[摘要]　目的　初步探索血清白蛋白水平与新型冠状病毒肺炎长期阳性患者病毒转阴之间的因果关系。方法?以病程超过30 d的轻型新型冠状病毒肺炎住院患者为研究对象,采集人口学信息、治疗策略、合并疾病、实验室检查指标信息,以发病后45 d内病毒累积转阴率为因变量,以发病后（30±3）d时的血清白蛋白水平为主要分析变量,以人口学信息、治疗策略、合并疾病、实验室检查结果等其他信息为协变量,采用限制立方样条回归-Cox比例风险回归模型探讨血清白蛋白水平对累积转阴率的影响。结果?共有189例患者纳入分析,其中101例在45 d内实现了病毒转阴。进一步分析发现,30 d时的血清白蛋白水平与45 d病毒累积转阴率之间存在相关性（P = 0.027）。当血清白蛋白＜39 g/L时,低血清白蛋白水平是病毒转阴的危险因素,且血清白蛋白水平越低,风险比（hazard ritio, HR）越高,血清白蛋白越接近39 g/L,HR则越接近1;当血清白蛋白≥39 g/L时,血清白蛋白水平不再是病毒转阴的危险因素。结论?血清白蛋白水平与患者的病毒转阴密切相关,当血清白蛋白＜39 g/L时,血清白蛋白水平越低,越不利于病毒转阴。因此,治疗过程中关注血清白蛋白变化,及时给予干预,可能有利于病毒转阴。     

Working conditions and health behavior as causes of educational inequalities in self-rated health: an inverse odds weighting approach

Objective:Using a novel mediation method that presents unbiased results even in the presence of exposure–mediator interactions, this study estimated the extent to which working conditions and health behaviors contribute to educational inequalities in self-rated health in the workforce.Methods:Respondents of the longitudinal Survey of Health, Ageing, and Retirement in Europe (SHARE) in 16 countries were selected, aged 50–64 years, in paid employment at baseline and with information on education and self-rated health (N=15 028). Education, health behaviors [including body mass index (BMI)] and working conditions were measured at baseline and self-rated health at baseline and two-year follow-up. Causal mediation analysis with inverse odds weighting was used to estimate the total effect of education on self-rated health, decomposed into a natural direct effect (NDE) and natural indirect effect (NIE).Results:Lower educated workers were more likely to perceive their health as poor than higher educated workers [relative risk (RR) 1.48, 95% confidence interval (CI) 1.37–1.60]. They were also more likely to have unfavorable working conditions and unhealthy behaviors, except for alcohol consumption. When all working conditions were included, the remaining NDE was RR 1.30 (95% CI 1.15–1.44). When BMI and health behaviors were included, the remaining NDE was RR 1.40 (95% CI 1.27–1.54). Working conditions explained 38% and health behaviors and BMI explained 16% of educational inequalities in health. Including all mediators explained 64% of educational inequalities in self-rated health.Conclusions:Working conditions and health behaviors explain over half of the educational inequalities in self-rated health. To reduce health inequalities, improving working conditions seems to be more important than introducing health promotion programs in the workforce.     

Microcomputer-based automatic regulation of extracorporeal circulation: a trial for the application of fuzzy inference

Since its establishment many researchers have been trying to automate the process of extracorporeal circulation (ECC). We developed a preliminary experimental model of an automatic regulatory system for ECC. The purpose of the system was to regulate basic hemodynamic parameters such as pump flow and withdrawal blood volume. It was divided into three main components: data sampling unit, central processing unit, and controlling unit. Based on this model we were able to achieve autoregulation of ECC using minimum configuration; however, the system lacked smoothness. This was partly because it was based on a "static" regulation system which used conditional statements having multiple parameters. In this study, we applied fuzzy logic to the former model to achieve more accurate and reliable regulation. We report experimental results for the new system and compare the data between clinical circulation in 13 infants (mean body weight, 13.32 +/- 5.99 kg) and experimental regulation in 7 mongrel dogs (mean body weight, 11.9 +/- 2.53 kg). The comparative study revealed no statistical difference between the two groups. This result suggests that the automatic regulation of ECC may be an alternative to manual operation by a professional perfusionist in the near future.     

Risk stratification for mortality in cardiovascular disease survivors: A survival conditional inference tree analysis

Background and aimsEfficient analysis strategies for complex network with cardiovascular disease (CVD) risk stratification remain lacking. We sought to identify an optimized model to study CVD prognosis using survival conditional inference tree (SCTREE), a machine-learning method.Methods and resultsWe identified 5379 new onset CVD from 2006 (baseline) to May, 2017 in the Kailuan I study including 101,510 participants (the training dataset). The second cohort composing 1,287 CVD survivors was used to validate the algorithm (the Kailuan II study, n = 57,511). All variables (e.g., age, sex, family history of CVD, metabolic risk factors, renal function indexes, heart rate, atrial fibrillation, and high sensitivity C-reactive protein) were measured at baseline and biennially during the follow-up period. Up to December 2017, we documented 1,104 deaths after CVD in the Kailuan I study and 170 deaths in the Kailuan II study. Older age, hyperglycemia and proteinuria were identified by the SCTREE as main predictors of post-CVD mortality. CVD survivors in the high risk group (presence of 2–3 of these top risk factors), had higher mortality risk in the training dataset (hazard ratio (HR): 5.41; 95% confidence Interval (CI): 4.49–6.52) and in the validation dataset (HR: 6.04; 95%CI: 3.59–10.2), than those in the lowest risk group (presence of 0–1 of these factors).ConclusionOlder age, hyperglycemia and proteinuria were the main predictors of post-CVD mortality.Trial registrationChiCTR-TNRC-11001489.