《医疗机构病历管理规定（2013年版）》立法技术缺陷初探

通过以立法技术角度对《医疗机构病历管理规定（2013年版）》进行分析,与2002年下发的《医疗机构病历管理规定》进行对比,从立法依据、适当的立法技术、条与款的关系、法律责任、与上位法的关系等方面入手,结合其他法律的规定和学者的研究成果,在对该规定给与充分肯定的基础上,深入探讨其在立法技术方面存在的缺陷,以期对其有更加深入、全面的认识;同时也希望促使立法者对立法技术给予应有的重视,在立法技术方面少犯错误,以利于立法工作更加完善。     

Software-assisted decision support in digital histopathology

Tissue diagnostics is the world of pathologists, and it is increasingly becoming digitalised to leverage the enormous potential of personalised medicine and of stratifying patients, enabling the administration of modern therapies. Therefore, the daily task for pathologists is changing drastically and will become increasingly demanding in order to take advantage of the development of modern computer technologies. The role of pathologist has rapidly evolved from exclusively describing the morphology and phenomenology of a disease, to becoming a gatekeeper for novel and most effective treatment options. This is possible based on the retrieval and management of a wide range of complex information from tissue or a group of cells and associated meta-data. Intelligent and self-learning software solutions can support and guide pathologists to score clinically relevant decisions based on the accurate and robust quantification of multiple target molecules or surrogate biomarker as companion or complimentary diagnostics along with relevant spatial relationships and contextual information from digital H&E and multiplexed images. With the availability of multiplex staining techniques on a single slide, high-resolution image analysis tools, and high-end computer hardware, machine and deep learning solutions now offer diagnostic rulesets and algorithms that still require clinical validation in well-designed studies. Before entering the clinical practice, the ‘human factor’ pathologist needs to develop trust in the output coming from the ‘digital black box of computational pathology’, including image analysis solutions and artificial intelligence algorithms to support critical clinical decisions which otherwise would not be available. © 2020 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.     

COVID-19疫情中的生物力学问题

新型冠状病毒肺炎自爆发以来,已成为全球关注的焦点。由于疫情来势迅猛,给医疗制度体系、医疗资源、应急处置、医疗器械等提出了严峻的挑战,也暴露出其中诸多不足。以病毒的体外活性规律研究、气溶胶传播的生物力学问题、呼吸性疾病对心血管疾病影响的研究、公共交通和公共场所中通风方式的改进、医疗器械的生物力学研究为例,应用生物力学的原理、观点和方法,认识和剖析其中所存在和亟待改进的问题,期望生物力学能在疫情防控中发挥学科优势和力量,以此促进生物力学学科发展。     

Relative stability of alexithymia and openness to emotions in one psychiatric day hospital setting

Alexithymia (literally, difficulty finding words for emotions) and openness to emotions (OE: referring to the cognitive representation, communication, regulation, perception of internal and external bodily sensations, and social restriction of emotions) are strongly linked to psychopathology. The absolute and relative stability hypotheses were tested in order to determine whether significant changes occurred on these constructs after therapy, a condition where changes were expected for both constructs. Negative attitudes toward treatment (NTI) and perceived social support (PSS) were expected to significantly predict alexithymia and OE. Patients (N = 179) who participated in this longitudinal study filled in the Toronto Alexithymia Scale, the Dimensions of Openness to Emotions Scale, the NTI subscale, the Multidimensional Scale of Perceived Social Support, and the Social Desirability Scale. After treatment, we observed significant decrease of all alexithymia scores and significant increases of three OE scores, that is, cognitive representation, communication, and regulation of emotions. Regression analyses revealed that gender, age, NTI, and PSS were significant predictors of alexithymia and OE. NTI strongly predicted lower OE levels and higher alexithymia levels, whereas PSS had opposite predicting effects on these constructs. In conclusion, the significant changes, and the moderate to high correlational levels observed between before and after alexithymia and OE scores, strengthen the relative stability hypothesis for both constructs. In addition, PSS represents a protective factor and NTI a vulnerability indicator for therapists. Our aim is to optimize treatment by providing therapists treating emotion difficulties a more concrete array of variables that potentially either promote or subvert recovery.