The digital phenotype of vaccination.
Ontology highlight
ABSTRACT:
SUBMITTER: Quer G
PROVIDER: S-EPMC9362685 | biostudies-literature | 2022 Aug
REPOSITORIES: biostudies-literature
Publications
The digital phenotype of vaccination.
Quer Giorgio G Topol Eric J EJ Steinhubl Steven R SR
Nature biotechnology 20220801 8
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Project description:ObjectiveWe aimed to establish a comprehensive digital phenotype for postpartum hemorrhage (PPH). Current guidelines rely primarily on estimates of blood loss, which can be inaccurate and biased and ignore complementary information readily available in electronic medical records (EMR). Inaccurate and incomplete phenotyping contributes to ongoing challenges in tracking PPH outcomes, developing more accurate risk assessments, and identifying novel interventions.Materials and methodsWe constructed a cohort of 71 944 deliveries from the Mount Sinai Health System. Estimates of postpartum blood loss, shifts in hematocrit, administration of uterotonics, surgical interventions, and diagnostic codes were combined to identify PPH, retrospectively. Clinical features were extracted from EMRs and mapped to common data models for maximum interoperability across hospitals. Blinded chart review was done by a physician on a subset of PPH and non-PPH patients and performance was compared to alternate PPH phenotypes. PPH was defined as clinical diagnosis of postpartum hemorrhage documented in the patient's chart upon chart review.ResultsWe identified 6639 PPH deliveries (9% prevalence) using our phenotype-more than 3 times as many as using blood loss alone (N = 1,747), supporting the need to incorporate other diagnostic and intervention data. Chart review revealed our phenotype had 89% accuracy and an F1-score of 0.92. Alternate phenotypes were less accurate, including a common blood loss-based definition (67%) and a previously published digital phenotype (74%).ConclusionWe have developed a scalable, accurate, and valid digital phenotype that may be of significant use for tracking outcomes and ongoing clinical research to deliver better preventative interventions for PPH.
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Project description:To understand how evolving systems bring forth novel and useful phenotypes, it is essential to understand the relationship between genotypic and phenotypic change. Artificial evolving systems can help us understand whether the genotype-phenotype maps of natural evolving systems are highly unusual, and it may help create evolvable artificial systems. Here we characterize the genotype-phenotype map of digital organisms in Avida, a platform for digital evolution. We consider digital organisms from a vast space of 10141 genotypes (instruction sequences), which can form 512 different phenotypes. These phenotypes are distinguished by different Boolean logic functions they can compute, as well as by the complexity of these functions. We observe several properties with parallels in natural systems, such as connected genotype networks and asymmetric phenotypic transitions. The likely common cause is robustness to genotypic change. We describe an intriguing tension between phenotypic complexity and evolvability that may have implications for biological evolution. On the one hand, genotypic change is more likely to yield novel phenotypes in more complex organisms. On the other hand, the total number of novel phenotypes reachable through genotypic change is highest for organisms with simple phenotypes. Artificial evolving systems can help us study aspects of biological evolvability that are not accessible in vastly more complex natural systems. They can also help identify properties, such as robustness, that are required for both human-designed artificial systems and synthetic biological systems to be evolvable.
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Project description:In this study, we explore the recent setup of a digital vaccination record in Austria. Working from a social-scientific perspective, we find that the introduction of the electronic vaccination pass was substantially accelerated by the COVID-19 pandemic. Our interviews with key stakeholders (n = 16) indicated that three main factors drove this acceleration. The pandemic (1) sidelined historical conflicts regarding data ownership and invoked a shared sense of the value of data, (2) accentuated the need for enhanced administrative efficiency in an institutionally fragmented system, and (3) helped invoke the national vaccination registry as an indispensable infrastructure for public health governance with the potential to innovate its healthcare system in the long term.
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Project description:IntroductionCognition is reduced at low and high glucose, reflecting cognitive vulnerability to glucose (CVG) fluctuations. The impact of glucose fluctuations on the aging brain remains unclear. We examined whether CVG is associated with plasma biomarkers of Alzheimer's disease (AD) pathology and neurodegeneration.MethodsParticipants included N = 114 adults with type 1 diabetes assessed for processing speed and sustained attention using ecological momentary assessment (EMA) combined with continuous glucose monitoring (CGM). We characterized associations between CVG and amyloid beta (Aβ) 42/40, phosphorylated tau (p-tau) 181 and 217, neurofilament light chain, and glial fibrillary acidic protein.ResultsCVG was associated with all plasma biomarkers, except Aβ 42/40. CVG for sustained attention exhibited strong associations with p-tau biomarkers that persisted across covariate specifications.DiscussionCVG may be a useful digital phenotype of AD. It remains unclear whether CVG contributes to versus arises from neurodegeneration. We consider possible mechanisms linking cognitive vulnerability and long-term glucose variability to the development of neuropathology.HighlightsCognitive vulnerability to glucose (CVG) may be a useful digital phenotype of neurodegeneration. We used cognitive ecological momentary assessment and continuous glucose monitoring to investigate CVG's associations with plasma biomarkers. Associations of CVG for sustained attention and phosphorylated tau 181 remained significant across covariates. We discuss possible mechanisms relating glucose variability, cognition, and neurodegeneration.
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Project description:Digital technologies are being increasingly utilized in healthcare to provide pertinent and timely information for primary prevention, such as vaccination. This study aimed to conduct a systematic review to describe and assess current digital health interventions to promote HPV vaccination among adolescents and parents of adolescents, and to recommend directions for future interventions of this kind. Using appropriate medical subject headings and keywords, we searched multiple databases to identify relevant studies published in English between 1 January 2017 and 31 July 2022. We screened and selected eligible studies for inclusion in the final analysis. We reviewed a total of 24 studies, which included interventions using text messages (4), mobile apps (4), social media and websites (8), digital games (4), and videos (4). The interventions generally improved determinants of HPV vaccination, such as HPV-related knowledge, vaccine-related conversations, and vaccination intentions. In particular, text message and social media interventions targeted improved vaccine uptake behaviors, but little meaningful change was observed. In conclusion, digital health interventions can cost-effectively provide education about HPV vaccination, offer interactive environments to alleviate parental vaccine hesitancy, and ultimately help adolescents engage in HPV vaccine uptake.
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Project description:Contemporary communication requires both a supply of content and a digital information infrastructure. Modern campaigns of misinformation are especially dependent on that back-end infrastructure for tracking and targeting a sympathetic audience and generating revenue that can sustain the campaign financially-if not enable profiteering. However, little is known about the political economy of misinformation, particularly those campaigns spreading misleading or harmful content about public health guidelines and vaccination programs. To understand the political economy of health misinformation, we analyze the content and infrastructure networks of 59 groups involved in communicating misinformation about vaccination programs. With a unique collection of tracker and communication infrastructure data, we demonstrate how the political economy of misinformation depends on platform monetization infrastructures. We offer a theory of communication resource mobilization that advances understanding of the communicative context, organizational interactions, and political outcomes of misinformation production.
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Project description:BackgroundSocial media and digital technologies have played essential roles in disseminating information and promoting vaccination during the COVID-19 pandemic. There is a need to summarize the applications and analytical techniques of social media and digital technologies in monitoring vaccine attitudes and administering COVID-19 vaccines.ObjectiveWe aimed to synthesize the global evidence on the applications of social media and digital technologies in COVID-19 vaccination and to explore their avenues to promote COVID-19 vaccination.MethodsWe searched 6 databases (PubMed, Scopus, Web of Science, Embase, EBSCO, and IEEE Xplore) for English-language articles from December 2019 to August 2022. The search terms covered keywords relating to social media, digital technology, and COVID-19 vaccines. Articles were included if they provided original descriptions of applications of social media or digital health technologies/solutions in COVID-19 vaccination. Conference abstracts, editorials, letters, commentaries, correspondence articles, study protocols, and reviews were excluded. A modified version of the Appraisal Tool for Cross-Sectional Studies (AXIS tool) was used to evaluate the quality of social media-related studies. The review was undertaken with the guidance of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews.ResultsA total of 178 articles were included in our review, including 114 social media articles and 64 digital technology articles. Social media has been applied for sentiment/emotion analysis, topic analysis, behavioral analysis, dissemination and engagement analysis, and information quality analysis around COVID-19 vaccination. Of these, sentiment analysis and topic analysis were the most common, with social media data being primarily analyzed by lexicon-based and machine learning techniques. The accuracy and reliability of information on social media can seriously affect public attitudes toward COVID-19 vaccines, and misinformation often leads to vaccine hesitancy. Digital technologies have been applied to determine the COVID-19 vaccination strategy, predict the vaccination process, optimize vaccine distribution and delivery, provide safe and transparent vaccination certificates, and perform postvaccination surveillance. The applied digital technologies included algorithms, blockchain, mobile health, the Internet of Things, and other technologies, although with some barriers to their popularization.ConclusionsThe applications of social media and digital technologies in addressing COVID-19 vaccination-related issues represent an irreversible trend. Attention should be paid to the ethical issues and health inequities arising from the digital divide while applying and promoting these technologies.
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