PBL联合CBL教学法在中医院校影像教学中应用的优势

随着影像技术的快速发展,影像检查已发展为临床诊断疾病的主要手段之一。所以作为未来医疗工作者的医学生,学好影像学变得越来越重要。目前影像教学大多采用传统的“满堂灌”的授课方式,学生处于学习的被动状态,效果并不尽人意。如何才能让学生真正掌握影像学知识,是值得每位任教老师深思的问题。作者结合多年的教学经验与实践,并针对中医院校医学生西医知识相对薄弱,课时少这一特点,认为PBL联合CBL教学法不但可以激发学生学习的主观能动性,培养学生的自学能力,增强学生解决问题的能力,提升临床思维能力,还可以提高课堂效率,有利于学生更好地学习、掌握影像知识,并学会将所学理论知识应用于临床实践。     

基于神经网络和支持向量机的中医体质辨识模型研究＊

目的 提出基于舌象和形体特征的中医体质辨识模型，探讨中医以舌辨质客观化、规范化方法。方法 提取客观化的舌象特征（舌质与舌苔的色度和饱和度、舌苔纹理的平均亮度、平滑度以及齿痕特征）和形体特征，建立基于神经网络和支持向量机的客观化舌象和形体特征的辅助中医体质识别模型。结果 对平和质、气虚质、阴虚质和气淤质四种体质进行模型的训练和测试，结果表明融合舌象特征和形体特征的中医体质辨识模型能有效地辅助中医体质识别，且支持向量机对四种体质辨识效果总体上优于神经网络。结论 基于客观化的舌象特征和形体特征辅助中医体质辨识有利于提高中医体质辨识的客观化水平，合理选择机器学习算法可以提高中医体质辨识的准确性。     

翻转课堂联合CBL教学在中医辨证见习中的应用

目的探讨翻转课堂联合CBL教学法应用于中医学辨证见习教学中的效果。方法将60名学生随机分为两组,每组30名,学生均来自于中南大学湘雅医学院临床医学专业2016级五年制本科。翻转课堂联合CBL教学法被应用于试验组,传统教学模式被应用于对照组,教学效果评价采用理论知识考核与学生满意度调查的双向评价模式。结果试验组的见习内容知识考核卷面成绩和满意度调查得分均高于对照组,差异均有统计学意义(P <0.05)。结论在中医学辨证见习课中,翻转课堂联合CBL教学法的教学效果优于传统教学模式。     

The risk of fractures,acute myocardial infarction,atrial fibrillation and ventricular arrhythmia in geriatric patients exposed to promethazine

ABSTRACT

Objectives: This study aimed to compare the risk of fractures, acute myocardial infarction, atrial fibrillation, and ventricular arrhythmia among Danish citizens aged ≥ 65 which were new users of promethazine or domperidone, triazolam, loratadine, and betahistine. Secondly, the study aimed to perform a risk stratification to identify the most relevant predictors for the study outcomes.

Methods: The study period was 01/01/2015 to 31/12/2016. The data sources were the Danish registers. Each patient was followed for 90 days. A logistic regression model was used to compute the unadjusted and adjusted odds ratios (OR), and a conditional inference tree was used to identify the most relevant predictors for the study outcomes.

Results: Promethazine had a higher risk of hospitalization for atrial fibrillation than loratadine and betahistine (OR 1.58; 95% CI 1.07–2.63 and OR 3.22; 95% CI 1.69–7.14, respectively). For fractures, acute myocardial infarction, and ventricular arrhythmia hospitalizations, no statistically significant differences were found among drugs under investigation. The medical history of cardiac arrhythmia (OR 4.14; 95% CI 2.94–5.78, p < 0.0001) was the most relevant predictor for atrial fibrillation hospitalizations.

Conclusion: This study found an increased risk of atrial fibrillation hospitalization among promethazine users, and the risk was higher among patients with prior cardiac arrhythmia.     

CBL联合PACS教学模式在本科生骨科临床带教中的应用

目的探索Case-based learning(CBL)联合PACS (Picture Achieving & Communication System)、影像存档与传输系统教学模式在本科生临床带教中的应用效果。方法选取广西中医药大学第一附属医院骨科接受临床带教的80名本科生,随机分为2组。试验组为结合PACS的CBL教学组;对照组为PBL(Problem-based learning)组,通过2组学生的客观考核成绩与主观效果评价,对比2种方法在“股骨粗隆间骨折”教学中的应用效果。结果与对照组相比,试验组在客观考核成绩及主观效果评价的多个指标中均优于对照组,二者差异具有统计学意义(P<0.05)。结论结合了PACS的CBL模式教学可有效提高临床带教的效率,提升临床带教效果,具有很好的推广潜力。     

How to master endoscopic submucosal dissection in the USA

Endoscopic submucosal dissection (ESD) is an established technique for the endoscopic therapy of dysplastic and early cancerous lesions throughout the gastrointestinal tract. The procedure requires both a sophisticated knowledge for lesion characterization and high‐level endoscopic skills. As a result, the learning curve is very steep and, in Japan, it takes years to gain proficiency under the traditional Master‐Apprentice teaching model. At present, as a result of multiple limitations, this training model is not applicable to the USA. Nevertheless, a unique, multipronged, stepwise approach has emerged as a viable pathway to train US endoscopists in ESD. Although this approach deserves refinement, it has already led to the expansion of ESD in the USA, has contributed to the widening of the indications for ESD, and has further developed ESD techniques. Multiple challenges remain, but they can be overcome by active collaboration between Japanese and US endoscopists and professional societies. The robust interest in ESD in the USA has drawn industry attention with a few innovations already coming to fruition and many more in development.     

Source imaging of seizure onset predicts surgical outcome in pediatric epilepsy

ObjectiveTo assess whether ictal electric source imaging (ESI) on low-density scalp EEG can approximate the seizure onset zone (SOZ) location and predict surgical outcome in children with refractory epilepsy undergoing surgery.MethodsWe examined 35 children with refractory epilepsy. We dichotomized surgical outcome into seizure- and non-seizure-free. We identified ictal onsets recorded with scalp and intracranial EEG and localized them using equivalent current dipoles and standardized low-resolution magnetic tomography (sLORETA). We estimated the localization accuracy of scalp EEG as distance of scalp dipoles from intracranial dipoles. We also calculated the distances of scalp dipoles from resection, as well as their resection percentage and compared between seizure-free and non-seizure-free patients. We built receiver operating characteristic curves to test whether resection percentage predicted outcome.ResultsResection distance was lower in seizure-free patients for both dipoles (p = 0.006) and sLORETA (p = 0.04). Resection percentage predicted outcome with a sensitivity of 57.1% (95% CI, 34–78.2%), a specificity of 85.7% (95% CI, 57.2–98.2%) and an accuracy of 68.6% (95% CI, 50.7–83.5%) (p = 0.01).ConclusionIctal ESI performed on low-density scalp EEG can delineate the SOZ and predict outcome.SignificanceSuch an application may increase the number of children who are referred for epilepsy surgery and improve their outcome.     

The discrepancy between verbal and visuoperceptual IQ in children with a specific learning disorder: An analysis of 1624 cases

Children with a specific learning disorder (SLD) are often characterized by marked intellectual strengths and weaknesses. In the last few years, research has focused on a common discrepancy between low working memory and processing speed on the one hand, and high verbal and visuoperceptual intelligence on the other. SLD profiles featuring a specific discrepancy between verbal and visuoperceptual abilities have been only marginally considered, however, and their systematic comparison vis-à-vis typically-developing (TD) populations has yet to be conducted. The present study examined a dataset of 1624 WISC-IV profiles of children with a diagnosis of SLD. It emerged that the proportion of children with a Verbal Comprehension Index (VCI) at least 1.5 SD (22 standardized points) lower than their scores on the Perceptual Reasoning Index (PRI) was larger than the proportion of SLD children with the opposite discrepant profile; it was also larger than the same proportion found among TD children. Comparing the two discrepant profiles revealed that the children also differed by type of learning difficulty, gender, and performance in the WISC-IV Symbol search task. Further examination suggested that children who were discrepant and also distinctly poor in visuoperceptual intelligence were particularly slow in general processing.     

Development of a Simulation-Based Mastery Learning Curriculum for Breaking Bad News

Introduction

Physician communication impacts patient outcomes. However, communication skills, especially around difficult conversations, remain suboptimal, and there is no clear way to determine the validity of entrustment decisions. The aims of this study were to 1) describe the development of a simulation-based mastery learning (SBML) curriculum for breaking bad news (BBN) conversation skills and 2) set a defensible minimum passing standard (MPS) to ensure uniform skill acquisition among learners.

Human subjects exploit a cognitive map for credit assignment

An influential reinforcement learning framework proposes that behavior is jointly governed by model-free (MF) and model-based (MB) controllers. The former learns the values of actions directly from past encounters, and the latter exploits a cognitive map of the task to calculate these prospectively. Considerable attention has been paid to how these systems interact during choice, but how and whether knowledge of a cognitive map contributes to the way MF and MB controllers assign credit (i.e., to how they revaluate actions and states following the receipt of an outcome) remains underexplored. Here, we examine such sophisticated credit assignment using a dual-outcome bandit task. We provide evidence that knowledge of a cognitive map influences credit assignment in both MF and MB systems, mediating subtly different aspects of apparent relevance. Specifically, we show MF credit assignment is enhanced for those rewards that are related to a choice, and this contrasted with choice-unrelated rewards that reinforced subsequent choices negatively. This modulation is only possible based on knowledge of task structure. On the other hand, MB credit assignment was boosted for outcomes that impacted on differences in values between offered bandits. We consider mechanistic accounts and the normative status of these findings. We suggest the findings extend the scope and sophistication of cognitive map-based credit assignment during reinforcement learning, with implications for understanding behavioral control.

An extensive body of psychological and neuroscientific literature on dual-system reinforcement learning (RL) indicates that behavior is governed by two distinct systems (1–17)—a rigid, retrospective model-free (MF) system (18, 19) and a flexible, prospective model-based (MB) system (18, 20). Unlike an MF system, which tends to repeat actions with a past history of success, an MB system relies on a cognitive map (CM) (21), that is, a model detailing the structure of a decision-making environment, including how states, actions, observations, and rewards are linked, to predict the impact of action choice on potential future rewards. Recent research highlights competitive and cooperative interactions between these systems, including speed accuracy trade-offs (22), reliability-based arbitration (1, 23), and a plan-to-habit strategy (24), with a focus on a prospective-planning role served by the MB system during choice. Recently, we demonstrated another influence of a CM (and thus, as we described it there, MB processes) in guiding credit assignment (CA) to MF action-values (i.e., affecting how MF values of actions and states are updated as reward-outcomes are received) (25). However, by design, this influence was limited to unraveling the resolution of state uncertainty for MF purposes, leaving broader aspects of the contribution of CM-based processes to CA unexplored.Here, we consider two potential complementary CM-based modulators of CA. Both concern the causal structure of the relationship between options and outcomes. One involves the “relatedness” of actual outcomes to an enacted choice, a retrospective effect of a CM on MF CA. The second involves the “importance” of potential outcomes during the deliberation process preceding a choice, a prospective effect of a CM on MB CA.“Relatedness” arises out of a complexity in assigning credit when information about streams of rewards is provided that depends only partly on the actions taken (unlike situations that involve simple lotteries, for instance, when an action is directly followed by the reward it occasions). An MF system, lacking structural causal knowledge, is disposed to assign credit naively to a choice based on the entire collection of ensuing outcomes, irrespective of whether these outcomes were caused by, or related to, an actual initiating action choice. By contrast, knowledge stored as a CM can guide MF CA to favor action-related outcomes.Take an example of a trader who deliberates purchasing one of two available mutual funds: X, which invests in companies A and B, or Y, which invests in companies A and C. Assume the trader opts for X and then later receives positive information about companies B and D. The trader might assign credit in an MF manner to her/his past action (“buy X”), updating the action’s cached value on the basis that positive consequences followed that choice. However, only one component of those positive consequences (that concerning company B) actually related to the choice of fund X. We propose that MF CA is modulated by a CM such that a change in the action’s value will be affected mostly by information about company B. More generally, relatedness depends on a causal attribution of rewards to actions (26).We consider a second modulator of CA, termed “importance,” as a form of attentional effect. When deliberating between several choice options, and taking into account their prospective outcomes, it is often the case that certain outcomes (which we dub “unimportant”) should not determine choice, as they are common to all choice options. In contrast, other (“important”) outcomes are distinctive to some choice options but not to others, and these should be the main determinants of choice. A CM will contain this type of information and direct attention to the latter alone. We consider the possibility that when the outcomes of the choice are observed, those that garnered more attention at choice are favored in learning.Consider our previous example where information about companies B and D triggers a CA process that leads to positive revaluation of these companies—a process useful for future MB financial decisions related to these companies. We propose this CA process can be biased by CM-based deliberations during choice. Notably, the values of companies B and C were “important” in the trader’s MB deliberation process (choosing a fund), as each is unique to one fund. The values of companies A and D, on the other hand, are less important, as these are either common to both choice options (A) or altogether absent (D). We hypothesize that representations of “important” components in a CM are activated more strongly during choice, leading to them being revalued more when information about choice outcomes are subsequently realized. Thus, ceteris paribus, the increase in the trader’s evaluation of company B will be higher than for company D, given the positive information. This evaluation is then exploited by MB planning processes for future choices.To test these hypotheses, we developed a variant of our previously described dual-outcome bandit task (25). Participants chose between pairs of bandits (i.e., lotteries) that led to different outcomes and received a stream of reward feedback pertaining to choice-related, choice-unrelated, important, and unimportant outcomes. Critically, there are two ways to value bandits in this task. An MF controller treats each bandit holistically, and, as described above, an MB controller predicts the values of the bandits from knowledge of the outcomes to which the bandits lead as provided by a putative CM. This distinction in the structure of evaluations can then be generalized to the apportioning of credit. We consider CA to a bandit to take the form of an MF credit assignment (MFCA; since the MF system makes decisions directly based on these values). Similarly, we consider CA to the outcomes associated with the bandits to be an MB credit assignment (MBCA). To put this another way, the main distinction between MFCA and MBCA in our task is that the former pertains to a revaluation of actions, while the latter pertains to a revaluation of latent causes for these actions (i.e., the ensuing outcomes).In support of our hypothesis that MFCA is guided by a CM, we found evidence that credit for choice-related and -unrelated outcomes is assigned to actions in a different manner. We show information about rewards actually related to chosen actions alone positively impact on the value of those actions. Information about rewards not related to chosen actions, on the other hand, have an opposite effect. Second, we found that MBCA was greater for choice outcomes that were “important” compared to “unimportant” during choice deliberations. We discuss mechanistic and normative accounts of these results.