Impact of sampling rate on statistical significance for single subject fMRI connectivity analysis

A typical time series in functional magnetic resonance imaging (fMRI) exhibits autocorrelation, that is, the samples of the time series are dependent. In addition, temporal filtering, one of the crucial steps in preprocessing of functional magnetic resonance images, induces its own autocorrelation. While performing connectivity analysis in fMRI, the impact of the autocorrelation is largely ignored. Recently, autocorrelation has been addressed by variance correction approaches, which are sensitive to the sampling rate. In this article, we aim to investigate the impact of the sampling rate on the variance correction approaches. Toward this end, we first derived a generalized expression for the variance of the sample Pearson correlation coefficient (SPCC) in terms of the sampling rate and the filter cutoff frequency, in addition to the autocorrelation and cross‐covariance functions of the time series. Through simulations, we illustrated the importance of the variance correction for a fixed sampling rate. Using the real resting state fMRI data sets, we demonstrated that the data sets with higher sampling rates were more prone to false positives, in agreement with the existing empirical reports. We further demonstrated with single subject results that for the data sets with higher sampling rates, the variance correction strategy restored the integrity of true connectivity.     

Which behaviours are first to emerge during recovery of consciousness after severe brain injury?

BackgroundEarly detection of consciousness after severe brain injury is critical for establishing an accurate prognosis and planning appropriate treatment.ObjectivesTo determine which behavioural signs of consciousness emerge first and to estimate the time course to recovery of consciousness in patients with severe acquired brain injury.MethodsRetrospective observational study using the Coma Recovery Scale-Revised and days to recovery of consciousness in 79 patients (51 males; 34 with traumatic brain injury; median [IQR] age 48 [26–61] years; median time since injury 26 [20–36] days) who transitioned from coma or unresponsive wakefulness syndrome (UWS)/vegetative state (VS) to the minimally conscious state (MCS) or emerged from MCS during inpatient rehabilitation.ResultsVisual pursuit was the most common initial sign of MCS (41% of patients; 95% CI [30–52]), followed by reproducible command-following (25% [16–35]) and automatic movements (24% [15–33]). Ten other behaviours emerged first in less than 16% of cases. Median [IQR] time to recovery of consciousness was 44 [33–59] days. Etiology did not significantly affect time to recovered consciousness.ConclusionRecovery of consciousness after severe brain injury is most often signalled by reemergence of visual pursuit, reproducible command-following and automatic movements. Clinicians should use assessment measures that are sensitive to these behaviours because early detection of consciousness is critical for accurate prognostication and treatment planning.     

Improved dynamic connection detection power in estimated dynamic functional connectivity considering multivariate dependencies between brain regions

To estimate dynamic functional connectivity (dFC), the conventional method of sliding window correlation (SWC) suffers from poor performance of dynamic connection detection. This stems from the equal weighting of observations, suboptimal time scale, nonsparse output, and the fact that it is bivariate. To overcome these limitations, we exploited the kernel‐reweighted logistic regression (KELLER) algorithm, a method that is common in genetic studies, to estimate dFC in resting state functional magnetic resonance imaging (rs‐fMRI) data. KELLER can estimate dFC through estimating both spatial and temporal patterns of functional connectivity between brain regions. This paper compares the performance of the proposed KELLER method with current methods (SWC and tapered‐SWC (T‐SWC) with different window lengths) based on both simulated and real rs‐fMRI data. Estimated dFC networks were assessed for detecting dynamically connected brain region pairs with hypothesis testing. Simulation results revealed that KELLER can detect dynamic connections with a statistical power of 87.35% compared with 70.17% and 58.54% associated with T‐SWC (p‐value = .001) and SWC (p‐value <.001), respectively. Results of these different methods applied on real rs‐fMRI data were investigated for two aspects: calculating the similarity between identified mean dynamic pattern and identifying dynamic pattern in default mode network (DMN). In 68% of subjects, the results of T‐SWC with window length of 100 s, among different window lengths, demonstrated the highest similarity to those of KELLER. With regards to DMN, KELLER estimated previously reported dynamic connection pairs between dorsal and ventral DMN while SWC‐based method was unable to detect these dynamic connections.     

手术室心理护理对手术患者精神状态的影响

目的探讨手术室心理护理对手术患者焦虑、抑郁状态及护理满意度的影响。方法以医院2017年1月—2019年4月在医院接受手术治疗的1200例患者展开研究,随机将其划分为研究组(n=600)与对照组(n=600),分别接受常规基础上的心理护理以及单纯常规护理,对比分析患者抑郁、焦虑评分、护理满意度。结果治疗后,与对照组比,观察组抑郁、焦虑评分均更低;且研究组(97.0%)患者护理满意度高于对照组(83.7%),差异有统计学意义(P<0.05)。结论心理护理干预对于手术患者精神干预结果比较好,不仅可以改善患者的抑郁、焦虑情况,也能提升其护理满意度。     

经前侧入路达芬奇机器人辅助肺段切除术的临床分析

目的总结经前侧入路达芬奇机器人辅助肺段切除术治疗肺部结节的临床价值。方法回顾性分析2018年6月至2019年10月于我科行前侧入路达芬奇机器人辅助肺段切除术77例患者的临床资料,其中男22例、女55例,年龄53(30~71)岁。对患者症状、一般情况、术前影像学资料、切除肺段分布、手术时间、出血量、淋巴结清扫数、术后带管时间、引流量、术后住院时间、术后并发症以及围术期死亡等指标进行分析。结果所有患者均顺利完成手术,无中转开胸,无严重并发症,无围术期死亡。术后病理48例为早期肺癌,29例为良性肿瘤。机器人Docking时间4(1~30)min,机器人腔内操作时间76(30~170)min,出血量30(20~400)mL,术后胸腔闭式引流管引流时间4(2~15)d,术后总引流量780(200~3980)mL;术后住院时间7(3~19)d。结论经前侧入路机器人辅助肺段切除治疗肺部结节安全、便捷和有效,值得临床推广应用。     

伊布利特联合胺碘酮转复持续性房颤的有效性及安全性研究

目的 探讨运用循证护理模式对脑卒中恢复期患者在社区家庭康复中的干预效果。 方法 选取80例首发脑卒中患者作为研究对象，采用随机数字表法分为常规组和观察组各40例。常规组采用常规社区家庭康复护理方法，而观察组实施循证护理模式，即采用循证护理路径制定出适合患者的最佳社区家庭康复护理方案。评估2组患者干预前后的心理状态、神经功能缺损程度、日常生活能力和运动功能，比较2组患者干预后的总有效率、生活质量、疾病复发率和护理满意度。 结果 观察组干预后的总有效率高于常规组（P＜0.05）；观察组干预后的DSI评分、CSS评分、Barthel指数和MAS评分均优于常规组（P＜0.05）；观察组患者干预后的复发率低于常规组，护理满意度高于常规组（P＜0.05）。 结论 在脑卒中恢复期患者的社区家庭康复中，实施循证护理模式能够改善患者的心理状况及运动功 和日常生活能力，降低复发率，提高患者生活质量；能够增进护患间信任及和谐关系。     

Hubs disruption in mesial temporal lobe epilepsy. A resting‐state fMRI study on a language‐and‐memory network

Mesial temporal lobe epilepsy (mTLE) affects the brain networks at several levels and patients suffering from mTLE experience cognitive impairment for language and memory. Considering the importance of language and memory reorganization in this condition, the present study explores changes of the embedded language‐and‐memory network (LMN) in terms of functional connectivity (FC) at rest, as measured with functional MRI. We also evaluate the cognitive efficiency of the reorganization, that is, whether or not the reorganizations support or allow the maintenance of optimal cognitive functioning despite the seizure‐related damage. Data from 37 patients presenting unifocal mTLE were analyzed and compared to 48 healthy volunteers in terms of LMN‐FC using two methods: pairwise correlations (region of interest [ROI]‐to‐ROI) and graph theory. The cognitive efficiency of the LMN‐FC reorganization was measured using correlations between FC parameters and language and memory scores. Our findings revealed a large perturbation of the LMN hubs in patients. We observed a hyperconnectivity of limbic areas near the dysfunctional hippocampus and mainly a hypoconnectivity for several cortical regions remote from the dysfunctional hippocampus. The loss of FC was more important in left mTLE (L‐mTLE) than in right (R‐mTLE) patients. The LMN‐FC reorganization may not be always compensatory and not always useful for patients as it may be associated with lower cognitive performance. We discuss the different connectivity patterns obtained and conclude that interpretation of FC changes in relation to neuropsychological scores is important to determine cognitive efficiency, suggesting the concept of “connectome” would gain to be associated with a “cognitome” concept.     

藏药珊瑚七十味丸中重金属含量及Hg元素化学形态研究＊

目的 测定珊瑚七十味丸（Ratanasampil，RNSP）中5种重金属元素的含量，并确定Hg元素存在的各种化学形态，为名贵藏药重金属含量及元素形态的确定提供准确的新型研究方法。方法 采用强酸消解法处理珊瑚七十味丸，利用电感耦合等离子体原子发射光谱（Inductively coupled plasma atomic emission spectrometry，ICP-OES）测定样品中不同重金属元素的含量，同时采用X射线光电子能谱技术（X-ray photoelectron spectroscopy，XPS）对样品中的Hg元素进行价态分析。结果 不同批次的珊瑚七十味丸中Hg、As、Cr、Cd及Cu这5种重金属元素含量存在一定的差异；Hg元素存在游离Hg2+、HgS、HgO共3种形式，且差异较大。结论 ICP-OES和XPS对药物中的5种重金属含量和Hg元素的价态进行的检测和分析，得到的数据较为准确、可靠，能够为珊瑚七十味丸的临床使用提供数据上的参考依据，也为传统道地藏药材中的重金属含量检测及价态分析提供了一种新的研究思路和方法。