Systematic Review of Health Economic Evaluations Focused on Artificial Intelligence in Healthcare: The Tortoise and the Cheetah

ObjectivesThis study aimed to systematically review recent health economic evaluations (HEEs) of artificial intelligence (AI) applications in healthcare. The aim was to discuss pertinent methods, reporting quality and challenges for future implementation of AI in healthcare, and additionally advise future HEEs.MethodsA systematic literature review was conducted in 2 databases (PubMed and Scopus) for articles published in the last 5 years. Two reviewers performed independent screening, full-text inclusion, data extraction, and appraisal. The Consolidated Health Economic Evaluation Reporting Standards and Philips checklist were used for the quality assessment of included studies.ResultsA total of 884 unique studies were identified; 20 were included for full-text review, covering a wide range of medical specialties and care pathway phases. The most commonly evaluated type of AI was automated medical image analysis models (n = 9, 45%). The prevailing health economic analysis was cost minimization (n = 8, 40%) with the costs saved per case as preferred outcome measure. A total of 9 studies (45%) reported model-based HEEs, 4 of which applied a time horizon >1 year. The evidence supporting the chosen analytical methods, assessment of uncertainty, and model structures was underreported. The reporting quality of the articles was moderate as on average studies reported on 66% of Consolidated Health Economic Evaluation Reporting Standards items.ConclusionsHEEs of AI in healthcare are limited and often focus on costs rather than health impact. Surprisingly, model-based long-term evaluations are just as uncommon as model-based short-term evaluations. Consequently, insight into the actual benefits offered by AI is lagging behind current technological developments.     

Bench to bedside: recent advances in lung cancer pathological research with implications for diagnostic clinical practice

After decades of relative stagnation lung cancer is emerging as a disease type where rapid progress is being made in diagnosis and therapy, as well as in our understanding of disease biology. Much of this progress is of immediate impact to diagnosticians, and more is likely to affect diagnostic practice in the near future. In this review we seek to briefly summarize several key areas of active research of immediate or probable imminent value to trainee and consultant pulmonary pathologists alike. We cover some major changes in tumour classification, grading, and patient stratification, as well as considering the state of the art in machine-assisted interpretation of lung cancer histology, and the use of genetically modified lung cancer models.     

复发性流产患者易栓症指标筛检的意义

目的探讨易栓症相关指标与不明原因复发性流产(URSA)的相关性,为URSA患者的病因排查和治疗提供参考。方法选取2016年11月—2018年3月上海交通大学医学院附属国际和平妇幼保健院104例流产次数≥2次的URSA患者作为URSA组,以45例健康经产妇作为对照组,检测所有研究对象血浆狼疮抗凝物(LA)阳性率、抗心磷脂抗体(ACA)阳性率、蛋白C(PC)活性、蛋白S(PS)活性、抗凝血酶(AT)活性、凝血因子Ⅻ(FⅫ)活性和D-二聚体(DD)水平。结果URSA组LA阳性率、PC活性、PS活性、AT活性、FⅫ活性、DD水平与对照组比较差异均有显著统计学意义(P<0.05)。结论LA阳性、PS缺陷、FⅫ缺陷和DD增高与URSA密切相关。LA、PS、FⅫ、DD是URSA患者体内高凝状态较好的筛查指标,联合检测AT、PC,对预测URSA血栓形成有临床指导意义。     

近端胃切除人工三角瓣成形抗反流术的力学机理仿真分析

目的:对食管胃结合部腺癌近端胃切除术（PG）人工三角瓣成形后残胃食糜进行流体动力学数值模拟，并计算不同性质胃内食糜的流动特征。方法:构建常规PG和人工三角瓣成形术术后胃仿真模型，运用Fluent软件对不同粘度胃内食糜反流问题进行数值模拟。结果:站立位姿态时，相对常规PG方案，人工三角瓣成形手术方案表现出较好的抗反流作用；卧位姿态时，当胃内食糜粘度大于0.145 2 Pa[?s，且胃内食糜不超过人工三角瓣情况下，人工三角瓣成形抗反流手术表现出较好的抗反流效果；人工三角瓣抗反流成形手术方案数值模拟结果与临床上患者表现一致。结论:本研究仿真分析为人工三角瓣成形抗反流手术方案的有效性机理分析、临床患者术后饮食及手术方案的进一步改进提供理论及数值依据。 【关键词】食管胃结合部腺癌；抗反流；人工三角瓣；计算流体力学     

Louisiana's “Medically Futile” Unborn Child List: Ethical Lessons at the Post-Dobbs Intersection of Reproductive and Disability Justice

Ableist attitudes and structures are increasingly recognized across all sectors of health care delivery. After Dobbs, novel questions arose in the United States concerning how to protect reproductive autonomy while avoiding discrimination against and devaluation of disabled persons. In this essay, we examine the Louisiana Department of Health's emergency declaration, “List of Conditions That Shall Deem an Unborn Child ‘Medically Futile,’” issued August 1, 2022. We raise a number of medical, ethical, and public health concerns that lead us to argue that the declaration should be rescinded. Analysis of this ethically objectionable declaration provides valuable lessons about how to uphold both reproductive and disability justice in a post-Dobbs landscape.     

Empowering the Nurse Practitioner With the Reproductive Justice Framework

On June 24, 2022, the Supreme Court of the United States ruled to strike down Roe v. Wade (1973), a landmark decision that legalized access to abortion under the right to privacy. By overturning Roe, the decision now leaves the regulation of abortion up to each individual state. Consideration of the consequences that will affect vulnerable populations is paramount now that Roe v. Wade is overturned. Nurse practitioners who are impartial toward abortion should be introduced to Reproductive Justice, which can help them better understand the lived experiences of people with the capacity for pregnancy and the complexities surrounding abortion.     

A Review of Machine Learning Techniques for Keratoconus Detection and Refractive Surgery Screening

ABSTRACT

Various machine learning techniques have been developed for keratoconus detection and refractive surgery screening. These techniques utilize inputs from a range of corneal imaging devices and are built with automated decision trees, support vector machines, and various types of neural networks. In general, these techniques demonstrate very good differentiation of normal and keratoconic eyes, as well as good differentiation of normal and form fruste keratoconus. However, it is difficult to directly compare these studies, as keratoconus represents a wide spectrum of disease. More importantly, no public dataset exists for research purposes. Despite these challenges, machine learning in keratoconus detection and refractive surgery screening is a burgeoning field of study, with significant potential for continued advancement as imaging devices and techniques become more sophisticated.