Calcification of coronary artery

In June, Aidoc announced a partnership with University Hospitals to deploy its AI imaging solution in hospitals and outpatient clinics. Ohio-based University Hospitals Health System (UH) has teamed up with healthcare AI company Aidoc to catch conditions like pulmonary embolism, coronary artery calcification and intracranial hemorrhage expediently.Aidoc’s platform has more than 30 care pathways and the company has 17 FDA-cleared algorithms, which it claims is the most clinical algorithms of any company. By partnering with Aidoc, hospitals and health systems can rapidly ramp up the use of AI in their practices, so it can make a large-scale impact.This is what UH has done. The health system has deployed Aidoc’s AI platform, aiOS, across 13 hospitals and dozens of outpatient facilities.“When a patient arrives at a UH facility and undergoes a CT scan for an injury or pain, Aidoc's AI analyzes the scan using its comprehensive algorithms,” a press release by Aidoc says. “The technology identifies both expected and unexpected findings, helps physicians prioritize urgent cases and ensures all flagged conditions are reviewed by the care team.”"Today's care delivery is incredibly complex with numerous moving parts," Donna Plecha, M.D., chair of radiology at UH, said in a statement. "Aidoc’s AI technology assists our radiologists in evaluating various patient images, allowing our clinicians to access precise, actionable data quickly. The AI technology enables our care teams to be more accurate and efficient leading to even more exceptional care for our patients.”Elad Walach, founder and CEO of Aidoc, said that from the get-go, UH had a vision for AI to make a big impact on clinical care. Walach said the health system wanted to be strategic in picking an AI partner that would solve more than one problem at a time. With Aidoc, UH has been able to launch over a dozen AI solutions in a matter of months. “UH has been very strategic in how they looked at the AI space because a lot of health systems … they run after one shiny point solution at a time,” Walach said. “But because of the adoption time and scaling time, it takes them, let's say, one year to adopt one AI solution, and then another year to adopt the second.”UH thought about AI acceleration from the get-go, which Walach said is unique.Scalability is one of the goals of Aidoc, but it also focuses on outcomes. For example, in the partnership with one of UH’s clinical innovation centers, Aidoc will study how the deployment of its platform affects quality and cost of care.One of UH’s goals in bringing in an AI partner was to solve the long wait times for outpatient and ambulatory visits. In time-critical cases, waiting weeks to visit a doctor after a chest CT could have major adverse consequences. With Aidoc, existing chest CT scans, for example, can instantly be evaluated by an algorithm that can detect a pulmonary embolism. A patient can then be elevated to the proper level of care and be saved from waiting weeks for a diagnosis.Aidoc said the deployment of its AI solutions is expected to markedly enhance patient safety and care quality.Walach said about half of hospitals and health systems are using some type of AI in their radiology practices. Aidoc accounts for a large portion of them. Aidoc is partnering with more than 150 hospitals and health systems in the U.S., which Walach said is about 25% of the market. Aidoc is also used by the top three radiology practices in the U.S., he noted.“The biggest problem of the AI space today is fragmentation, right? Because if you fix one problem, you create three others because you create even more siloes with data,” Walach explained.Walach said AI has the potential to solve interoperability challenges in healthcare, but the deployment of one AI solution isn’t going to fix health IT. Health systems need a platform that can bring data silos together rather than create yet another data silo, he noted.Founded in 2016, Aidoc has raised $264 million to date, according to Crunchbase, including a $110 million series D round in 2022. Its backers include TCV, Alpha Intelligence Capital and CDIB Capital.

点击上方“蓝字”关注我们吧！ 迄今为止，“可治疗特质（TTs，Treatable traits）”已被应用于确诊后的疾病管理。TTs指可在临床和/或生物学上确定的临床特征和危险因素，若存在则具有重大的临床治疗意义。随着对TTs认识的不断深入，研究发现在临床诊断疾病前对现有的TTs采取及时干预措施可有效防止疾病的进展，应将识别TTs从确诊疾病后扩展到确诊疾病前。以慢性阻塞性肺疾病（COPD）为例，“COPD前期”是指无气流受限但有呼吸道症状和/或结构或功能异常的患者，他们最终可能会随着时间的推移而出现气流受限，而在COPD前期可能已具有TTs。发表于2024年7月《Respirology》（IF 6.6）的文章[1]总结了COPD前期患者潜在的多种TTs，并对未来临床实践和研究提出相关建议以减轻未来疾病负担。 COPD前期的诊断标准和人群定义 COPD前期是指出现慢性呼吸道症状、肺部结构改变和（或）病理生理学改变，但未达到慢阻肺诊断标准［吸入支气管舒张剂后第1秒用力呼气容积（FEV1）/用力肺活量（FVC）<0.70］，在后续随访中更易进展为慢阻肺的人群（图1）。 在既往的慢阻肺全球创议（GOLD）中被称为GOLD 0，后参照高血压前期和糖尿病前期的概念称为COPD前期。COPD基因队列中约12%的参与者在无气流受限的情况下FEV1<80%预计值，临床使用保留比值受损肺功能（PRISm）术语进行识别。 此外，研究发现，低肺功能轨迹，无论是否与肺生长不良和/或加速衰退有关，都在未来观察到发生COPD。由此，研究认为COPD前期包括GOLD 0、PRISm和低肺功能轨迹，尤其是肺功能加速下降的患者，甚至可能是从高于正常峰值的肺功能（即异常轨迹）开始并加速下降的患者（图2）。 COPD前期的可治疗特质 肺部特质（症状、结构和生理功能） 1.症状 COPD前期患者可能会出现呼吸困难、咳嗽咳痰，有时还会出现“症状恶化”。一项探索双联支气管扩张剂（LABA-LAMA）与安慰剂对照治疗COPD前期症状的研究显示，LABA-LAMA治疗未减少呼吸道症状，尽管可有效改善肺功能。这是一项重要的研究，但需要仔细考虑几个潜在的问题。第一，接近60%接受安慰剂的受试者在3个月内症状和健康状况有显著改善，表明这种COPD前期表型可能是不稳定的。其次，参与者的主要症状是咳嗽咳痰，而不是劳力性呼吸困难，所以支扩剂治疗不太可能对此产生影响。第三，试验仅持续12周，无法观察到对症状加重发作的显著影响。最后，研究未排除导致呼吸困难的肺外因素（例如心血管疾病），这些因素不太可能受到LABA-LAMA的影响。 另一项RCT纳入了年龄更小（25-55岁）的正在吸烟者，无气流受限，但存在小气道功能障碍（多次呼吸氮冲洗异常），研究持续12个月，LABA-LAMA组20例，安慰剂组17例。结果显示，在6个月和12个月时，两组之间使用支气管扩张剂后FEV1下降（主要结局）或次要结局（症状、强制振荡法或DLco）均未发现显著差异。此外，部分COPD患者存在T2炎症，此类患者接受吸入性类固醇和/或生物疗法或可实现临床获益，在COPD前期患者中或可得到类似结果。 2.肺结构异常 尽管既往暂无研究专门调查COPD前期患者，但COPD患者的胸部CT扫描可以发现许多不同的潜在TTs，既存在于肺内（肺气肿、支气管扩张、粘液堵塞、肺癌、肺动脉扩张），也存在于肺外（心脏增大、冠状动脉钙化、骨质疏松和胸肌重量减少）。其中一些结果也可能在COPD前期患者中发现。尽管目前缺少相关依据，但发现上述潜在TTs的COPD前期患者也可能应给予治疗。因此，胸部CT为检测COPD患者和COPD前期患者的TTs提供了崭新可能，值得开展前瞻性、设计良好的研究。 3.肺功能异常 COPD前期患者无气流受限，但可存在许多其他肺功能异常，包括一氧化碳弥散量（DLco）减少、过度充气、小气道阻塞和/或FEV1加速下降。在此情况下，有必要考虑以下因素： （1）DLco减少最常见的原因为肺气肿，即使无气流受限； （2）肺过度充气和气体滞留可能是由于FEV1/FVC无法识别的小气道功能障碍； （3）FEV1加速下降是某些肺功能轨迹的一部分。 目前尚无随机对照试验研究如何管理COPD前期患者的此类TTs，但作者推测，在等待该人群的具体证据时，使用与COPD患者相同的策略治疗可能是可接受的。 肺外和行为特质/生活方式/环境特质 目前这两个领域尚缺乏COPD前期患者的信息，但COPD患者的肺外和行为特质、生活方式和环境特质已有研究作出相关阐述[2]： 肺外特质主要与合并症有关，如抑郁、焦虑、超重/肥胖、失能、鼻窦炎、声带功能障碍、全身性炎症、贫血、心血管疾病、胃食道反流病、阻塞性睡眠呼吸暂停、运动耐力下降等。研究显示肥胖和心血管疾病在PRISm和低肺功能轨迹患者中较为常见。 行为特质、生活方式和环境特质包括吸烟、缺乏运动、久坐不动、骨密度降低和骨质疏松症等，行为特质主要为与疾病自我管理问题相关特质，如吸入器技术与依从性不佳、缺乏书面行动计划以及对疾病缺乏了解。如上均为极其重要的特质，会影响其他特质，且可能恶化症状、干预效果和疾病结局。 总结 鉴于COPD的临床前阶段较长以及目前关于其潜在TTs的证据，研究建议对COPD前期患者的TTs进行有效干预以阻止最终进展为COPD。然而，未来仍需进一步研究以确定更为详细的COPD前期TTs，并确定干预治疗的可行性和成本效益，更好推动临床实践。目前已有研究证实N-乙酰半胱氨酸（NAC）可改善呼吸困难、咳嗽咳痰等呼吸道症状，显著降低COPD急性加重风险，或可成为干预COPD前期TTs的有效利器。 参考文献 [1] Dharmage SC, Faner R, Agustí A. Treatable traits in pre-COPD: Time to extend the treatable traits paradigm beyond established disease. Respirology. 2024 Jul;29(7):551-562. [2] Papi A, Faner R, Pavord I, et al. From treatable traits to GETomics in airway disease: moving towards clinical practice[J]. European Respiratory Review, 2024, 33(171). 提示：本材料仅供医疗卫生专业人士进行医学科学交流，不用于推广目的。 *乙酰半胱氨酸在中国上市剂型为口服及吸入制剂。乙酰半胱氨酸片0.6g在中国上市的适应症为“用于分泌大量粘稠痰液的慢性阻塞性肺病（COPD）、慢性支气管炎(CB)、肺气肿(PE)等慢性呼吸系统感染的祛痰治疗。”该药品在全球各国所获得的上市许可内容和条件有不同。

Being near and having more exposure to urban green space and blue (water) space is linked to lower odds of having coronary artery calcification in middle age, which is an early marker of cardiovascular disease. The associations were more pronounced among Black individuals and those living in neighborhoods with lower socioeconomic status, with the strongest effects observed in Black individuals in economically deprived neighborhoods. Being near and having more exposure to urban green space and blue (water) space is linked to lower odds of having coronary artery calcification in middle age, which is an early marker of cardiovascular disease. The associations were more pronounced among Black individuals and those living in neighborhoods with lower socioeconomic status, with the strongest effects observed in Black individuals in economically deprived neighborhoods. Specifically, Black participants with the highest accessibility to a river had 32% lower odds of coronary artery calcification compared to those with the lowest accessibility. Black participants with greater access to green spaces had up to 35% lower odds of calcification. For each 10%-point increase in green space, the odds of having coronary artery calcification decreased by 15% on average. The study was published today June 27 Circulation. Coronary artery calcification (CAC) is when calcium builds up in the plaque found in the walls of the coronary arteries. It can be a sign of early coronary artery disease, which can cause a heart attack. "The protective effect of having access to urban blue and green spaces with coronary artery calcification highlighted in our study underscore the potential benefits of such infrastructure, particularly for underserved populations at higher risk for cardiovascular disease," said corresponding author Dr. Lifang Hou, a professor of preventive medicine at Northwestern University Feinberg School of Medicine. "Our findings provide quantitative evidence supporting environmental policies to enhance the accessibility and quality of residential blue and green spaces, which can promote public health benefit and address racial and neighborhood-related health disparities." Why do green and blue spaces improve health? "Having more green and blue spaces may provide increased opportunities for physical activities, social interactions, stress relief and restoration, all of which have been linked to improved metabolic and cardiovascular health," Hou said. "Additionally, exposure to green and blue spaces has been shown to boost people's immune system, reduce chronic inflammation and slow down the biological aging process, all of which are biologically important in people's overall health and cardiovascular health. More studies are needed to fully understand the role of urban natural environments in pathways related to human health." Conversely, the study also showed shorter distances to parks were associated with higher odds of CAC in these neighborhoods, with individuals having the highest park accessibility showing 29% higher odds of CAC compared to those with the lowest accessibility. "The poor condition of parks and/or safety concerns in underserved urban neighborhoods might deter park use and prevent residents from fully benefiting from these spaces," said study first author Kyeezu Kim, adjunct assistant professor of preventive medicine at Feinberg and assistant professor at Sungkyunkwan University School of Medicine in South Korea. "From a public health perspective, the results suggest the need for quality control and management of the surrounding environment in neighborhoods with disadvantaged social determinants of health. More data is warranted to fully explain this observation." How the study was conducted The study included 2,960 Black and white men and women (average age of 50 years) from Birmingham, Ala., Chicago, Ill., Minneapolis, Minn., and Oakland, Calif., who were followed for 25 years (from 1985-1986 to 2010-2011). While proximity to urban blue and green spaces has been linked to better cardiovascular health, few studies have examined the role of social determinants of health, such as race and neighborhoods with lower socioeconomic status in these associations, particularly with long-term observational data. Data for this study were drawn from the Coronary Artery Risk Development in Young Adults (CARDIA) study, a multi-center prospective cohort study across four urban cities in the U.S. The CARDIA study began in 1985-1986 with 5,115 self-reported Black and white individuals in early adulthood (mean age 24.8). For blue and green spaces, researchers included percent blue space cover, distance to the nearest river, percent green space cover and distance to the nearest major park within 5 km of the participants' residential addresses. The presence of CAC was measured using a CT (computed tomography) scan when participants were about 50 years old. Researchers examined the associations between each blue and green space and CAC by race and neighborhood socioeconomic status. The CARDIA study is conducted and supported by the National Heart, Lung, and Blood Institute (NHLBI) in collaboration with the University of Alabama at Birmingham grants HHSN268201800005I and HHSN268201800007I, Northwestern University grant HHSN268201800003I, University of Minnesota grant HHSN268201800006I and Kaiser Foundation Research Institute grant HHSN268201800004I. The research is also supported by NHLBI grant R01HL114091 and National Institute on Aging grant R01AG081244, all of the National Institutes of Health. It is also supported by the American Heart Association.