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Age, Multiple Chronic Conditions, and COVID-19: A Literature Review.

ABSTRACT:

Background

Various patient demographic and clinical characteristics have been associated with poor outcomes for individuals with coronavirus disease 2019 (COVID-19). To describe the importance of age and chronic conditions in predicting COVID-19-related outcomes.

Methods

Search strategies were conducted in PubMed/MEDLINE. Daily alerts were created.

Results

A total of 28 studies met our inclusion criteria. Studies varied broadly in sample size (n = 21 to more than 17,000,000). Participants' mean age ranged from 48 years to 80 years, and the proportion of male participants ranged from 44% to 82%. The most prevalent underlying conditions in patients with COVID-19 were hypertension (range: 15%-69%), diabetes (8%-40%), cardiovascular disease (CVD) (4%-61%), chronic pulmonary disease (1%-33%), and chronic kidney disease (range 1%-48%). These conditions were each associated with an increased in-hospital case fatality rate (CFR) ranging from 1% to 56%. Overall, older adults have a substantially higher case fatality rate (CFR) as compared to younger individuals affected by COVID-19 (42% for those <65 vs 65% > 65 years). Only one study examined the association of chronic conditions and the risk of dying across different age groups; their findings suggested similar trends of increased risk in those < 65 years and those > 65 years as compared to those without these conditions.

Conclusions

There has been a traditional, single-condition approach to consideration of how chronic conditions and advancing age relate to COVID-19 outcomes. A more complete picture of the impact of burden of multimorbidity and advancing patient age is needed.

SUBMITTER: Tisminetzky M

PROVIDER: S-EPMC7799222 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature

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Publications

Age, Multiple Chronic Conditions, and COVID-19: A Literature Review.

Tisminetzky Mayra M Delude Christopher C Hebert Tara T Carr Catherine C Goldberg Robert J RJ Gurwitz Jerry H JH

The journals of gerontology. Series A, Biological sciences and medical sciences 20220401 4

<h4>Background</h4>Various patient demographic and clinical characteristics have been associated with poor outcomes for individuals with coronavirus disease 2019 (COVID-19). To describe the importance of age and chronic conditions in predicting COVID-19-related outcomes.<h4>Methods</h4>Search strategies were conducted in PubMed/MEDLINE. Daily alerts were created.<h4>Results</h4>A total of 28 studies met our inclusion criteria. Studies varied broadly in sample size (n = 21 to more than 17,000,000 ...[more]

PMID: 33367606

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Project description:BackgroundA rising number of conversational agents or chatbots are equipped with artificial intelligence (AI) architecture. They are increasingly prevalent in health care applications such as those providing education and support to patients with chronic diseases, one of the leading causes of death in the 21st century. AI-based chatbots enable more effective and frequent interactions with such patients.ObjectiveThe goal of this systematic literature review is to review the characteristics, health care conditions, and AI architectures of AI-based conversational agents designed specifically for chronic diseases.MethodsWe conducted a systematic literature review using PubMed MEDLINE, EMBASE, PyscInfo, CINAHL, ACM Digital Library, ScienceDirect, and Web of Science. We applied a predefined search strategy using the terms "conversational agent," "healthcare," "artificial intelligence," and their synonyms. We updated the search results using Google alerts, and screened reference lists for other relevant articles. We included primary research studies that involved the prevention, treatment, or rehabilitation of chronic diseases, involved a conversational agent, and included any kind of AI architecture. Two independent reviewers conducted screening and data extraction, and Cohen kappa was used to measure interrater agreement.A narrative approach was applied for data synthesis.ResultsThe literature search found 2052 articles, out of which 10 papers met the inclusion criteria. The small number of identified studies together with the prevalence of quasi-experimental studies (n=7) and prevailing prototype nature of the chatbots (n=7) revealed the immaturity of the field. The reported chatbots addressed a broad variety of chronic diseases (n=6), showcasing a tendency to develop specialized conversational agents for individual chronic conditions. However, there lacks comparison of these chatbots within and between chronic diseases. In addition, the reported evaluation measures were not standardized, and the addressed health goals showed a large range. Together, these study characteristics complicated comparability and open room for future research. While natural language processing represented the most used AI technique (n=7) and the majority of conversational agents allowed for multimodal interaction (n=6), the identified studies demonstrated broad heterogeneity, lack of depth of reported AI techniques and systems, and inconsistent usage of taxonomy of the underlying AI software, further aggravating comparability and generalizability of study results.ConclusionsThe literature on AI-based conversational agents for chronic conditions is scarce and mostly consists of quasi-experimental studies with chatbots in prototype stage that use natural language processing and allow for multimodal user interaction. Future research could profit from evidence-based evaluation of the AI-based conversational agents and comparison thereof within and between different chronic health conditions. Besides increased comparability, the quality of chatbots developed for specific chronic conditions and their subsequent impact on the target patients could be enhanced by more structured development and standardized evaluation processes.

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Dataset Information

Age, Multiple Chronic Conditions, and COVID-19: A Literature Review.

Background

Methods

Results

Conclusions

Publications

Age, Multiple Chronic Conditions, and COVID-19: A Literature Review.

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