熊磊教授基于“脾为痰源”辨治儿童癫痫临证思路探赜

熊磊教授以理脾为本，将治痰贯穿始终。根据小儿脾常不足、肾常虚、肝常有余的生理特点，癫痫发作期治疗主以涤痰开窍，辅以理气健脾，同时配合活血化瘀通窍与平肝息风潜阳。主要选方为柴芍温胆汤、天麻钩藤饮、桃红四物汤加减；缓解期则以补肾养肝为主，兼以健脾化痰，主要选方为杞菊地黄丸合定痫丸加减，取得较好临床疗效。     

EEG functional connectivity contributes to outcome prediction of postanoxic coma

ObjectiveTo investigate the additional value of EEG functional connectivity features, in addition to non-coupling EEG features, for outcome prediction of comatose patients after cardiac arrest.MethodsProspective, multicenter cohort study. Coherence, phase locking value, and mutual information were calculated in 19-channel EEGs at 12 h, 24 h and 48 h after cardiac arrest. Three sets of machine learning classification models were trained and validated with functional connectivity, EEG non-coupling features, and a combination of these. Neurological outcome was assessed at six months and categorized as “good” (Cerebral Performance Category [CPC] 1–2) or “poor” (CPC 3–5).ResultsWe included 594 patients (46% good outcome). A sensitivity of 51% (95% CI: 34–56%) at 100% specificity in predicting poor outcome was achieved by the best functional connectivity-based classifier at 12 h after cardiac arrest, while the best non-coupling-based model reached a sensitivity of 32% (0–54%) at 100% specificity using data at 12 h and 48 h. Combination of both sets of features achieved a sensitivity of 73% (50–77%) at 100% specificity.ConclusionFunctional connectivity measures improve EEG based prediction models for poor outcome of postanoxic coma.SignificanceFunctional connectivity features derived from early EEG hold potential to improve outcome prediction of coma after cardiac arrest.     

老年下肢骨折患者行手术室人性化护理的效果

目的评价手术室人性化护理干预对老年下肢骨折患者手术以及术后恢复情况的影响,以加速老年骨折患者康复。方法选择我院近年来收治手术治疗的老年下肢骨折患者,总计100例。结合手术室护理方法进行对照组和研究组随机分组,对照组老年下肢骨折患者采取常规护理,研究组老年下肢骨折患者采取手术室人性化护理干预。比较两组老年下肢骨折患者的手术情况,包括情绪评分、生活质量评分、术后并发症以及护理满意度。结果研究组老年下肢骨折患者SAS、SDS、SF-36评分均明显优于对照组,且安全性和护理满意度均明显高于对照组,观察指标数据差异有统计学意义,P<0.05。结论予以老年下肢骨折患者手术室人性化护理干预满足了患者的护理需求,进一步稳定了患者的情绪、身体,从而提高了患者手术安全性。     

Motor dysfunction in mild cognitive impairment as tested by kinematic analysis and transcranial magnetic stimulation

ObjectivePrevious studies have demonstrated voluntary movement alterations as well as motor cortex excitability and plasticity changes in patients with mild cognitive impairment (MCI). To investigate the pathophysiology of movement abnormalities in MCI, we tested possible relationships between movement abnormalities and primary motor cortex alterations in patients.MethodsFourteen amnestic MCI (aMCI) patients and 16 healthy controls were studied. Cognitive assessment was performed using clinical scales. Finger tapping was recorded by a motion analysis system. Transcranial magnetic stimulation was used to test the input/output curve of motor evoked potentials, intracortical inhibition, and short-latency afferent inhibition. Primary motor cortex plasticity was probed by theta burst stimulation. We investigated correlations between movement abnormalities, clinical scores, and cortical neurophysiological parameters.ResultsMCI patients showed less rhythmic movement but no other movement abnormalities. Cortical excitability measures were normal in patients, whereas plasticity was reduced. Movement rhythm abnormalities correlated with frontal dysfunction scores.ConclusionOur study in MCI patients demonstrated abnormal voluntary movement and plasticity changes, with no correlation between the two. Altered rhythm correlated with frontal dysfunction.SignificanceOur results contribute to the understanding of pathophysiological mechanisms of motor impairment in MCI.     

Automated assessment of the substantia nigra on susceptibility map-weighted imaging using deep convolutional neural networks for diagnosis of Idiopathic Parkinson's disease

ObjectivesDespite its use in determining nigrostriatal degeneration, the lack of a consistent interpretation of nigrosome 1 susceptibility map-weighted imaging (SMwI) limits its generalized applicability. To implement and evaluate a diagnostic algorithm based on convolutional neural networks for interpreting nigrosome 1 SMwI for determining nigrostriatal degeneration in idiopathic Parkinson's disease (IPD).MethodsIn this retrospective study, we enrolled 267 IPD patients and 160 control subjects (125 patients with drug-induced parkinsonism and 35 healthy subjects) at our institute, and 24 IPD patients and 27 control subjects at three other institutes on approval of the local institutional review boards. Dopamine transporter imaging served as the reference standard for the presence or absence of abnormalities of nigrosome 1 on SMwI. Diagnostic performance was compared between visual assessment by an experienced neuroradiologist and the developed deep learning-based diagnostic algorithm in both internal and external datasets using a bootstrapping method with 10000 re-samples by the “pROC” package of R (version 1.16.2).ResultsThe area under the receiver operating characteristics curve (AUC) (95% confidence interval [CI]) per participant by the bootstrap method was not significantly different between visual assessment and the deep learning-based algorithm (internal validation, .9622 [0.8912–1.0000] versus 0.9534 [0.8779-0.9956], P = .1511; external validation, 0.9367 [0.8843-0.9802] versus 0.9208 [0.8634-0.9693], P = .6267), indicative of a comparable performance to visual assessment.ConclusionsOur deep learning-based algorithm for assessing abnormalities of nigrosome 1 on SMwI was found to have a comparable performance to that of an experienced neuroradiologist.