Long COVID Characteristics and Experience: A Descriptive Study from the Yale LISTEN Research Cohort.

OBJECTIVE: To describe the experience of people with long COVID symptomatology and characterize the psychological, social, and financial challenges they experience. BACKGROUND: The experience of people with long COVID needs further amplification, especially with a comprehensive focus on symptomatology, treatments, and impact on daily life and finances. METHODS: We collected data from individuals aged 18 and older reporting long COVID as participants in the Yale Listen to Immune, Symptom and Treatment Experiences Now (LISTEN) Study. The sample population included 441 participants surveyed between May 2022 and July 2023. We evaluated their demographic characteristics, socioeconomic and psychological status, index infection period, health status, quality of life, symptoms, treatments, pre-pandemic comorbidities, and new-onset conditions. RESULTS: Overall, the median age of the participants with long COVID was 46 years (IQR: 38 to 57 years); 74% were women, 86% were Non-Hispanic White, and 93% were from the United States. Participants reported low health status measured by the Euro-QoL visual analogue scale, with a median score of 49 (IQR: 32 to 61). Participants documented a diverse range of symptoms, with all 96 possible symptom choices being reported. Additionally, participants had tried many treatments (median number of treatments: 19, IQR: 12 to 28). They were also experiencing psychological distress, social isolation, and financial stress. CONCLUSIONS: Despite having tried numerous treatments, participants with long COVID continued to experience an array of health and financial challenges-findings that underscore the failure of the healthcare system to address the medical needs of people with long COVID. These insights highlight the need for crucial medical, mental health, financial, and community support services, as well as further scientific investigation, to address the complex impact of long COVID.

Testing Race Differences in Risk of Gestational Diabetes Mellitus Associated with Household Food Insecurity (Using NHANES 2007-2018).

OBJECTIVE: This study aimed to estimate the association of household food insecurity with gestational diabetes mellitus (GDM) risk by race and ethnic group. STUDY DESIGN: The study was a secondary analysis from the National Health and Nutrition Examination Survey from 2007 to 2018. A survey-weighted logistic regression model was constructed with self-reported GDM as the response. The primary independent variable was a four-level food security indicator, defined as the inability to obtain food in a socially acceptable way due to the lack of financial resources and controlled for several established risk factors. Analyses were stratified by race (White and Black) and ethnicity (Hispanic) to provide insight into how gestational diabetes risk differs by subpopulation. RESULTS: Results indicated that family history of diabetes is a risk factor across all races (adjusted odds ratio [aOR]: 4.22-16.26), while household food insecurity is a significant risk factor for only Hispanic women living with a partner (aOR: 8.50 for very low food security). CONCLUSION: In the United States, Hispanic women's GDM risk may be uniquely impacted by food insecurity. KEY POINTS: · This study provides a national estimate of the GDM risk from food insecurity by race and ethnicity.. · The results in this study suggest a statistically significant relationship between household food insecurity and an increasing risk of developing GDM for Hispanic individuals.. · White women who live alone (without spouse or partner) were also at elevated risk of GDM.. · Age at delivery, poverty ratio, and family history of diabetes are also risk factors for the disease..

Post-Vaccination Syndrome: A Descriptive Analysis of Reported Symptoms and Patient Experiences After Covid-19 Immunization.

Introduction: A chronic post-vaccination syndrome (PVS) after covid-19 vaccination has been reported but has yet to be well characterized. Methods: We included 241 individuals aged 18 and older who self-reported PVS after covid-19 vaccination and who joined the online Yale Listen to Immune, Symptom and Treatment Experiences Now (LISTEN) Study from May 2022 to July 2023. We summarized their demographics, health status, symptoms, treatments tried, and overall experience. Results: The median age of participants was 46 years (interquartile range [IQR]: 38 to 56), with 192 (80%) identifying as female, 209 (87%) as non-Hispanic White, and 211 (88%) from the United States. Among these participants with PVS, 127 (55%) had received the BNT162b2 [Pfizer-BioNTech] vaccine, and 86 (37%) received the mRNA-1273 [Moderna] vaccine. The median time from the day of index vaccination to symptom onset was three days (IQR: 1 day to 8 days). The time from vaccination to symptom survey completion was 595 days (IQR: 417 to 661 days). The median Euro-QoL visual analogue scale score was 50 (IQR: 39 to 70). The five most common symptoms were exercise intolerance (71%), excessive fatigue (69%), numbness (63%), brain fog (63%), and neuropathy (63%). In the week before survey completion, participants reported feeling unease (93%), fearfulness (82%), and overwhelmed by worries (81%), as well as feelings of helplessness (80%), anxiety (76%), depression (76%), hopelessness (72%), and worthlessness (49%) at least once. Participants reported a median of 20 (IQR: 13 to 30) interventions to treat their condition. Conclusions: In this study, individuals who reported PVS after covid-19 vaccination had low health status, high symptom burden, and high psychosocial stress despite trying many treatments. There is a need for continued investigation to understand and treat this condition.

Uncovering heterogeneous cardiometabolic risk profiles in US adults: the role of social and behavioral determinants of health.

INTRODUCTION: Social and behavioral determinants of health (SBDH) have been linked to diabetes risk, but their role in explaining variations in cardiometabolic risk across race/ethnicity in US adults is unclear. This study aimed to classify adults into distinct cardiometabolic risk subgroups using SBDH and clinically measured metabolic risk factors, while comparing their associations with undiagnosed diabetes and pre-diabetes by race/ethnicity. RESEARCH DESIGN AND METHODS: We analyzed data from 38,476 US adults without prior diabetes diagnosis from the National Health and Nutrition Examination Survey (NHANES) 1999-2018. The k-prototypes clustering algorithm was used to identify subgroups based on 16 SBDH and 13 metabolic risk factors. Each participant was classified as having no diabetes, pre-diabetes or undiagnosed diabetes using contemporaneous laboratory data. Logistic regression was used to assess associations between subgroups and diabetes status, focusing on differences by race/ethnicity. RESULTS: Three subgroups were identified: cluster 1, primarily middle-aged adults with high rates of smoking, alcohol use, short sleep duration, and low diet quality; cluster 2, mostly young non-white adults with low income, low health insurance coverage, and limited healthcare access; and cluster 3, mostly older males who were the least physically active, but with high insurance coverage and healthcare access. Compared with cluster 2, adjusted ORs (95% CI) for undiagnosed diabetes were 14.9 (10.9, 20.2) in cluster 3 and 3.7 (2.8, 4.8) in cluster 1. Clusters 1 and 3 (vs cluster 2) had high odds of pre-diabetes, with ORs of 1.8 (1.6, 1.9) and 2.1 (1.8, 2.4), respectively. Race/ethnicity was found to modify the relationship between identified subgroups and pre-diabetes risk. CONCLUSIONS: Self-reported SBDH combined with metabolic factors can be used to classify adults into subgroups with distinct cardiometabolic risk profiles. This approach may help identify individuals who would benefit from screening for diabetes and pre-diabetes and potentially suggest effective prevention strategies.

Association of SGLT-2 Inhibitors With Treatment Satisfaction and Diabetes-Specific and General Health Status in Adults With Cardiovascular Disease and Type 2 Diabetes.

Background It is unknown if initiation of a sodium-glucose cotransporter-2 inhibitor (SGLT-2i) is associated with changes in patient-reported health status outside of clinical trials. Methods and Results Using a prospective observational study design, adults with type 2 diabetes and cardiovascular disease were recruited from 14 US hospitals between November 2019 and December 2021 if they were new users of noninsulin antidiabetic medications. The primary outcome was change in 6-month diabetes treatment satisfaction. Secondary outcomes included diabetes-related symptom distress, diabetes-specific quality of life, and general health status for all patients and based on cardiovascular disease type. Inverse probability of treatment weight using propensity score was performed to compare outcome changes based on medication use. Of 887 patients (SGLT-2i: n=242) included in the inverse probability of treatment weight analyses, there was no difference in changes in treatment satisfaction in SGLT-2i users compared with other diabetes medication users (0.99 [95% CI, -0.14 to 2.13] versus 1.54 [1.08 to 2.00], P=0.38). Initiating an SGLT-2i versus other diabetes medications was associated with a greater reduction in ophthalmological symptoms (-3.09 [95% CI, -4.99 to -1.18] versus -0.38 [-1.54 to 0.77], P=0.018) but less improvement in hyperglycemia (1.08 [-2.63 to 4.79] versus -3.60 [-5.34 to -1.86], P=0.026). In subgroup analyses by cardiovascular disease type, SGLT-2i use was associated with a greater reduction in total diabetes symptom burden and neurological sensory symptoms in patients with heart failure. Conclusions Among patients with type 2 diabetes and cardiovascular disease, initiating an SGLT-2i was not associated with changes in diabetes treatment satisfaction, total diabetes symptoms, diabetes-specific quality of life, or general health status.

Impact of Mediterranean Dietary Education on Symptoms for Adults at Risk for Nonalcoholic Fatty Liver Disease.

This 2-month quasi-experimental study focused on the impact of education regarding the Mediterranean diet on symptoms for adults who are at risk for nonalcoholic fatty liver disease (NAFLD). The study was conducted on a sample of 28 adults who presented to Pinnacle clinical research for NAFLD screening via a fibroscan. These individuals who are at risk for NAFLD received a single 15-minute one-on-one in person education regarding the Mediterranean diet. The diet encourages fruits, vegetables, whole grains, legumes, nuts, seeds, fish, and olive oil. The results of the study showed that the Mediterranean diet education was associated with significant improvement of abdominal symptoms ( t = 3.34, p = .03), improvement of fatigue symptoms ( t = 5.88, p < .001), and decrease in hepatic steatosis ( t = 5.77, p < .001). Our study suggests that the education on the Mediterranean diet may be associated with improvement of self-reported abdominal symptoms, fatigue, and steatosis score.

Examining changes in knowledge and practice in nurse practitioners after an online educational module on obstructive sleep apnea.

AIMS: The purpose of this study is to investigate primary care nurse practitioner (NP) knowledge and knowledge retention on obstructive sleep apnea (OSA) screening after an educational in-service. BACKGROUND: The prevalence of OSA is high and continues to rise amid the obesity epidemic. Approximately 75-90 % of individuals with moderate to severe OSA remain undiagnosed. Continuing education of OSA risk factors among primary care providers may increase screening rates, leading to early diagnosis and treatment. METHODS: An educational module was presented to NPs (n = 30) during a mandatory NP in-service at two sets of outpatient clinics. Knowledge was assessed with a pre-test and post-test survey consisting of 23 items. A 25-item follow-up test was administered five weeks after to assess knowledge retention. RESULTS: An increase in total knowledge scores was demonstrated between the pre-test and post-test with a decrease in knowledge observed at follow-up. Follow-up test total mean scores remained above pre-test levels, indicating potential long-term learning. CONCLUSIONS: While learning was demonstrated, NPs acknowledged continued barriers to screening for OSA such as time and having no OSA screening tool available in the electronic medical record (EMR).

A mixed-methods approach to understand university students' perceived impact of returning to class during COVID-19 on their mental and general health.

PURPOSE: This study investigated the prevalence and risk factors of mental and general health symptoms among university students attending in-person and online classes during COVID-19. We also explored their experiences returning to in-person classes and their views on the university's COVID-19-related policies. METHODS: In this sequential explanatory mixed-methods study (2020-2021), U.S. university student respondents (N = 1030; 603 women [58.5%], 907 [88.1%] aged 18-24 years) completed a quantitative, cross-sectional survey assessing their mental and general health symptoms experienced while taking classes during the COVID-19 pandemic. The survey link was distributed through social media and email invitations. Three separate follow-up focus groups (n = 27), consisting of an average of nine focus group respondents who had completed the quantitative survey per group, were conducted using a semi-structured interview guide. Focus group respondents provided qualitative responses on their experiences returning to class during COVID-19 and adhering to COVID-19-related policies. RESULTS: The prevalence of mental health symptoms among survey respondents were 57.6% (n = 593) for depression, 41.5% (n = 427) for anxiety, and 40.8% (n = 420) for stress. Over 90% of respondents reported perceptions of good general health. Female respondents and respondents identified as non-binary gender had an increased risk for mental health symptoms compared to male respondents. Respondents with preexisting medical conditions had an increased risk for worse general health. Themes identified through qualitative analysis included (1) attending class during COVID-19 is associated with unhealthy behaviors, and poor health, (2) perceived challenges of online learning and increased feelings of isolation, (3) demand for COVID-19 policy reform and greater transparency of COVID-19 statistics; (4) difficulties in adhering to COVID-19 policies; and (5) concerns about acquiring and transmitting COVID-19. CONCLUSIONS: Our findings indicate that university students attending classes during the pandemic are experiencing negative mental health impacts. Although students were aware of COVID-19-related policies, many found it challenging to comply. Broad acceptance of COVID-19 policies will require greater transparency and information sharing.

Sex-specific impact of diabetes on all-cause mortality among adults with acute myocardial infarction: An updated systematic review and meta-analysis, 1988-2021.

Background: The prevalence of diabetes and its impact on mortality after acute myocardial infarction (AMI) are well-established. Sex-specific analyses of the impact of diabetes on all-cause mortality after AMI have not been updated and comprehensively investigated. Objective: To conduct a systematic review and meta-analysis that examined sex-specific short-term, mid-term and long-term all-cause mortality associated with diabetes among AMI survivors (diabetes versus non-diabetes patients in men and women separately), using up-to-date data. Methods: We systematically searched Embase and MEDLINE for studies that were published from inception to November 14, 2021. Studies were included if (1) they studied post-AMI all-cause-mortality in patients with and without diabetes, (2) sex-specific all-cause mortality at short-term (in-hospital or within 90 days after discharge), mid-term (>90 days and within 5 years), and/or long-term (>5 years) were reported. From eligible studies, we used random effects meta-analyses models to estimate pooled unadjusted and adjusted sex-specific risk ratio (RR) of all-cause mortality at short-, mid-, and long-term follow-up for adults with diabetes compared with those without diabetes. Results: Of the 3647 unique studies identified, 20 studies met inclusion criteria. In the unadjusted analysis (Total N=673,985; women=34.2%; diabetes patients=19.6%), patients with diabetes were at a higher risk for all-cause mortality at short-term (men: RR, 2.06; women: RR, 1.83); and mid-term follow-up (men: RR, 1.69; women: RR, 1.52) compared with those without diabetes in both men and women. However, when adjusted RRs were used (Total N=7,144,921; women=40.0%; diabetes patients=28.4%), the associations between diabetes and all-cause mortality in both men and women were attenuated, but still significantly elevated for short-term (men: RR, 1.16; 95% CI, 1.12-1.20; women: RR, 1.29; 95% CI, 1.15-1.46), mid-term (men: RR, 1.39; 95% CI, 1.31-1.46; women: RR, 1.38; 95% CI, 1.20-1.58), and long-term mortality (men: RR, 1.58; 95% CI, 1.22-2.05; women: RR, 1.76; 95% CI, 1.25-2.47). In men, all-cause mortality risk associated with diabetes tended to increase with the duration of follow-up (p<0.0001). Conclusions: Diabetes has substantial and sustained effects on post-AMI all-cause mortality at short-term, mid-term and long-term follow-up, regardless of sex. Tailoring AMI treatment based on patients' diabetes status, duration of follow-up and sex may help narrow the gap in all-cause mortality between patients with diabetes and those without diabetes.

Interventions to mitigate COVID-19 misinformation: protocol for a scoping review.

BACKGROUND: The duration and impact of the COVID-19 pandemic depends in a large part on individual and societal actions which is influenced by the quality and salience of the information to which they are exposed. Unfortunately, COVID-19 misinformation has proliferated. To date, no systematic efforts have been made to evaluate interventions that mitigate COVID-19-related misinformation. We plan to conduct a scoping review that seeks to fill several of the gaps in the current knowledge of interventions that mitigate COVID-19-related misinformation. METHODS: A scoping review focusing on interventions that mitigate COVID-19 misinformation will be conducted. We will search (from January 2020 onwards) MEDLINE, EMBASE, CINAHL, PsycINFO, Web of Science Core Collection, Africa-Wide Information, Global Health, WHO Global Literature on Coronavirus Disease Database, WHO Global Index Medicus, and Sociological Abstracts. Gray literature will be identified using Disaster Lit, Google Scholar, Open Science Framework, governmental websites, and preprint servers (e.g., EuropePMC, PsyArXiv, MedRxiv, JMIR Preprints). Study selection will conform to Joanna Briggs Institute Reviewers' Manual 2020 Methodology for JBI Scoping Reviews. Only English language, original studies will be considered for inclusion. Two reviewers will independently screen all citations, full-text articles, and abstract data. A narrative summary of findings will be conducted. Data analysis will involve quantitative (e.g., frequencies) and qualitative (e.g., content and thematic analysis) methods. DISCUSSION: Original research is urgently needed to design interventions to mitigate COVID-19 misinformation. The planned scoping review will help to address this gap. SYSTEMATIC REVIEW REGISTRATIONS: Systematic Review Registration: Open Science Framework (osf/io/etw9d).

Tracking Self-reported Symptoms and Medical Conditions on Social Media During the COVID-19 Pandemic: Infodemiological Study.

BACKGROUND: Harnessing health-related data posted on social media in real time can offer insights into how the pandemic impacts the mental health and general well-being of individuals and populations over time. OBJECTIVE: This study aimed to obtain information on symptoms and medical conditions self-reported by non-Twitter social media users during the COVID-19 pandemic, to determine how discussion of these symptoms and medical conditions changed over time, and to identify correlations between frequency of the top 5 commonly mentioned symptoms post and daily COVID-19 statistics (new cases, new deaths, new active cases, and new recovered cases) in the United States. METHODS: We used natural language processing (NLP) algorithms to identify symptom- and medical condition-related topics being discussed on social media between June 14 and December 13, 2020. The sample posts were geotagged by NetBase, a third-party data provider. We calculated the positive predictive value and sensitivity to validate the classification of posts. We also assessed the frequency of health-related discussions on social media over time during the study period, and used Pearson correlation coefficients to identify statistically significant correlations between the frequency of the 5 most commonly mentioned symptoms and fluctuation of daily US COVID-19 statistics. RESULTS: Within a total of 9,807,813 posts (nearly 70% were sourced from the United States), we identified a discussion of 120 symptom-related topics and 1542 medical condition-related topics. Our classification of the health-related posts had a positive predictive value of over 80% and an average classification rate of 92% sensitivity. The 5 most commonly mentioned symptoms on social media during the study period were anxiety (in 201,303 posts or 12.2% of the total posts mentioning symptoms), generalized pain (189,673, 11.5%), weight loss (95,793, 5.8%), fatigue (91,252, 5.5%), and coughing (86,235, 5.2%). The 5 most discussed medical conditions were COVID-19 (in 5,420,276 posts or 66.4% of the total posts mentioning medical conditions), unspecified infectious disease (469,356, 5.8%), influenza (270,166, 3.3%), unspecified disorders of the central nervous system (253,407, 3.1%), and depression (151,752, 1.9%). Changes in posts in the frequency of anxiety, generalized pain, and weight loss were significant but negatively correlated with daily new COVID-19 cases in the United States (r=-0.49, r=-0.46, and r=-0.39, respectively; P<.05). Posts on the frequency of anxiety, generalized pain, weight loss, fatigue, and the changes in fatigue positively and significantly correlated with daily changes in both new deaths and new active cases in the United States (r ranged=0.39-0.48; P<.05). CONCLUSIONS: COVID-19 and symptoms of anxiety were the 2 most commonly discussed health-related topics on social media from June 14 to December 13, 2020. Real-time monitoring of social media posts on symptoms and medical conditions may help assess the population's mental health status and enhance public health surveillance for infectious disease.

Prevalence of Dyslipidemia and Availability of Lipid-Lowering Medications Among Primary Health Care Settings in China.

Importance: Dyslipidemia, the prevalence of which historically has been low in China, is emerging as the second leading yet often unaddressed factor associated with the risk of cardiovascular diseases. However, recent national data on the prevalence, treatment, and control of dyslipidemia are lacking. Objective: To assess the prevalence, treatment, and control of dyslipidemia in community residents and the availability of lipid-lowering medications in primary care institutions in China. Design, Setting, and Participants: This cross-sectional study used data from the China-PEACE (Patient-Centered Evaluative Assessment of Cardiac Events) Million Persons Project, which enrolled 2 660 666 community residents aged 35 to 75 years from all 31 provinces in China between December 2014 and May 2019, and the China-PEACE primary health care survey of 3041 primary care institutions. Data analysis was performed from June 2019 to March 2021. Exposures: Study period. Main Outcomes and Measures: The main outcome was the prevalence of dyslipidemia, which was defined as total cholesterol greater than or equal to 240 mg/dL, low-density lipoprotein cholesterol (LDL-C) greater than or equal to 160 mg/dL, high-density lipoprotein cholesterol (HDL-C) less than 40 mg/dL, triglycerides greater than or equal to 200 mg/dL, or self-reported use of lipid-lowering medications, in accordance with the 2016 Chinese Adult Dyslipidemia Prevention Guideline. Results: This study included 2 314 538 participants with lipid measurements (1 389 322 women [60.0%]; mean [SD] age, 55.8 [9.8] years). Among them, 781 865 participants (33.8%) had dyslipidemia. Of 71 785 participants (3.2%) who had established atherosclerotic cardiovascular disease (ASCVD) and were recommended by guidelines for lipid-lowering medications regardless of LDL-C levels, 10 120 (14.1%) were treated. The overall control rate of LDL-C (≤70 mg/dL) among adults with established ASCVD was 26.6% (19 087 participants), with the control rate being 44.8% (4535 participants) among those who were treated and 23.6% (14 552 participants) among those not treated. Of 236 579 participants (10.2%) with high risk of ASCVD, 101 474 (42.9%) achieved LDL-C less than or equal to 100 mg/dL. Among participants with established ASCVD, advanced age (age 65-75 years, odds ratio [OR], 0.63; 95% CI, 0.56-0.70), female sex (OR, 0.56; 95% CI, 0.53-0.58), lower income (reference category), smoking (OR, 0.89; 95% CI, 0.85-0.94), alcohol consumption (OR, 0.87; 95% CI, 0.83-0.92), and not having diabetes (reference category) were associated with lower control of LDL-C. Among participants with high risk of ASCVD, younger age (reference category) and female sex (OR, 0.58; 95% CI, 0.56-0.59) were associated with lower control of LDL-C. Of 3041 primary care institutions surveyed, 1512 (49.7%) stocked statin and 584 (19.2%) stocked nonstatin lipid-lowering drugs. Village clinics in rural areas had the lowest statin availability. Conclusions and Relevance: These findings suggest that dyslipidemia has become a major public health problem in China and is often inadequately treated and uncontrolled. Statins were available in less than one-half of the primary care institutions. Strategies aimed at detection, prevention, and treatment are needed.

Polysomnographic Phenotypes of Obstructive Sleep Apnea and Incident Type 2 Diabetes: Results from the DREAM Study.

Rationale: Obstructive sleep apnea (OSA) is associated with cardiovascular disease and incident type 2 diabetes (T2DM). Seven OSA phenotypes, labeled on the basis of their most distinguishing polysomnographic features, have been shown to be differentially associated with incident cardiovascular disease. However, little is known about the relevance of polysomnographic phenotypes for the risk of T2DM. Objectives: To assess whether polysomnographic phenotypes are associated with incident T2DM and to compare the predictive value of baseline polysomnographic phenotypes with the Apnea-Hypopnea Index (AHI) for T2DM. Methods: The study included 840 individuals without baseline diabetes from a multisite observational U.S. veteran cohort who underwent OSA evaluation between 2000 and 2004, with follow-up through 2012. The primary outcome was incident T2DM, defined as no diagnosis at baseline and a new physician diagnosis confirmed by fasting blood glucose >126 mg/dL during follow-up. Relationships between the seven polysomnographic phenotypes (1. mild, 2. periodic limb movements of sleep [PLMS], 3. non-rapid eye movement and poor sleep, 4. rapid eye movement and hypoxia, 5. hypopnea and hypoxia, 6. arousal and poor sleep, and 7. combined severe) and incident T2DM were investigated using Cox proportional hazards regression and competing risk regression models with and without adjustment for baseline covariates. Likelihood ratio tests were conducted to compare the predictive value of the phenotypes with the AHI. Results: During a median follow-up period of 61 months, 122 (14.5%) patients developed incident T2DM. After adjustment for baseline sociodemographics, fasting blood glucose, body mass index, comorbidities, and behavioral risk factors, hazard ratios among persons with "hypopnea and hypoxia" and "PLMS" phenotypes as compared with persons with "mild" phenotype were 3.18 (95% confidence interval [CI], 1.53-6.61] and 2.26 (95% CI, 1.06-4.83) for incident T2DM, respectively. Mild OSA (5 ⩽ AHI < 15) (vs. no OSA) was directly associated with incident T2DM in both unadjusted and multivariable-adjusted regression models. The addition of polysomnographic phenotypes, but not AHI, to known T2DM risk factors greatly improved the predictive value of the computed prediction model. Conclusions: Polysomnographic phenotypes "hypopnea and hypoxia" and "PLMS" independently predict risk of T2DM among a predominantly male veteran population. Polysomnographic phenotypes improved T2DM risk prediction comared with the use of AHI.

Engagement With COVID-19 Public Health Measures in the United States: A Cross-sectional Social Media Analysis from June to November 2020.

BACKGROUND: COVID-19 has continued to spread in the United States and globally. Closely monitoring public engagement and perceptions of COVID-19 and preventive measures using social media data could provide important information for understanding the progress of current interventions and planning future programs. OBJECTIVE: The aim of this study is to measure the public's behaviors and perceptions regarding COVID-19 and its effects on daily life during 5 months of the pandemic. METHODS: Natural language processing (NLP) algorithms were used to identify COVID-19-related and unrelated topics in over 300 million online data sources from June 15 to November 15, 2020. Posts in the sample were geotagged by NetBase, a third-party data provider, and sensitivity and positive predictive value were both calculated to validate the classification of posts. Each post may have included discussion of multiple topics. The prevalence of discussion regarding these topics was measured over this time period and compared to daily case rates in the United States. RESULTS: The final sample size included 9,065,733 posts, 70% of which were sourced from the United States. In October and November, discussion including mentions of COVID-19 and related health behaviors did not increase as it had from June to September, despite an increase in COVID-19 daily cases in the United States beginning in October. Additionally, discussion was more focused on daily life topics (n=6,210,255, 69%), compared with COVID-19 in general (n=3,390,139, 37%) and COVID-19 public health measures (n=1,836,200, 20%). CONCLUSIONS: There was a decline in COVID-19-related social media discussion sourced mainly from the United States, even as COVID-19 cases in the United States increased to the highest rate since the beginning of the pandemic. Targeted public health messaging may be needed to ensure engagement in public health prevention measures as global vaccination efforts continue.

Interventions to Mitigate COVID-19 Misinformation: A Systematic Review and Meta-Analysis.

The duration and impact of the COVID-19 pandemic depends largely on individual and societal actions which are influenced by the quality and salience of the information to which they are exposed. Unfortunately, COVID-19 misinformation has proliferated. Despite growing attempts to mitigate COVID-19 misinformation, there is still uncertainty regarding the best way to ameliorate the impact of COVID-19 misinformation. To address this gap, the current study uses a meta-analysis to evaluate the relative impact of interventions designed to mitigate COVID-19-related misinformation. We searched multiple databases and gray literature from January 2020 to September 2021. The primary outcome was COVID-19 misinformation belief. We examined study quality and meta-analysis was used to pool data with similar interventions and outcomes. 16 studies were analyzed in the meta-analysis, including data from 33378 individuals. The mean effect size of interventions to mitigate COVID-19 misinformation was positive, but not statistically significant [d = 2.018, 95% CI (-0.14, 4.18), p = .065, k = 16]. We found evidence of publication bias. Interventions were more effective in cases where participants were involved with the topic, and where text-only mitigation was used. The limited focus on non-U.S. studies and marginalized populations is concerning given the greater COVID-19 mortality burden on vulnerable communities globally. The findings of this meta-analysis describe the current state of the literature and prescribe specific recommendations to better address the proliferation of COVID-19 misinformation, providing insights helpful to mitigating pandemic outcomes.

Newly diagnosed diabetes and outcomes after acute myocardial infarction in young adults.

OBJECTIVE: To examine prevalence and characteristics of newly diagnosed diabetes (NDD) in younger adults hospitalised with acute myocardial infarction (AMI) and investigate whether NDD is associated with health status and clinical outcomes over 12-month post-AMI. METHODS: In individuals (18-55 years) admitted with AMI, without established diabetes, we defined NDD as (1) baseline or 1-month HbA1c≥6.5%; (2) discharge diabetes diagnosis or (3) diabetes medication initiation within 1 month. We compared baseline characteristics of NDD, established diabetes and no diabetes, and their associations with baseline, 1-month and 12-month health status (angina-specific and non-disease specific), mortality and in-hospital complications. RESULTS: Among 3501 patients in Variation in Recovery: Role of Gender on Outcomes of Young AMI Patients study, 14.5% met NDD criteria. Among 508 patients with NDD, 35 (6.9%) received discharge diagnosis, 91 (17.9%) received discharge diabetes education and 14 (2.8%) initiated pharmacological treatment within 1 month. NDD was more common in non-White (OR 1.58, 95% CI 1.23 to 2.03), obese (OR 1.72, 95% CI 1.39 to 2.12), financially stressed patients (OR 1.27, 95% CI 1.02 to 1.58). Compared with established diabetes, NDD was independently associated with better disease-specific health status and quality of life (p≤0.04). No significant differences were found in unadjusted in-hospital mortality and complications between NDD and established or no diabetes. CONCLUSIONS: NDD was common among adults≤55 years admitted with AMI and was more frequent in non-White, obese, financially stressed individuals. Under 20% of patients with NDD received discharge diagnosis or initiated discharge diabetes education or pharmacological treatment within 1 month post-AMI. NDD was not associated with increased risk of worse short-term health status compared with risk noted for established diabetes. TRIAL REGISTRATION NUMBER: NCT00597922.

Effects of Mobile Text Messaging on Glycemic Control in Patients With Coronary Heart Disease and Diabetes Mellitus: A Randomized Clinical Trial

BACKGROUND: Mobile health interventions may support risk factor management and are readily scalable in healthcare systems. We aim to evaluate the efficacy of a text messaging-based intervention to improve glycemic control in patients with coronary heart disease and diabetes mellitus in China. METHODS AND RESULTS: The CHAT-DM study (Cardiovascular Health and Texting-Diabetes Mellitus) was a parallel-group, single-blind, randomized clinical trial that included 502 patients with both coronary heart disease and diabetes mellitus from 34 hospitals in China. The intervention group (n=251) received 6 text messages per week for 6 months in addition to usual care. Messages were theory driven and culturally tailored to provide educational and motivational information on glucose monitoring, blood pressure control, medication adherence, physical activity, and lifestyle. The control group (n=251) received usual care and 2 thank you messages per month. The primary outcome was change in glycated hemoglobin (HbA1C [hemoglobin A1C]) from baseline to 6 months. Secondary outcomes were change in proportion of patients achieving HbA1C <7%, fasting blood glucose, systolic blood pressure, LDL (low-density lipoprotein) cholesterol, body mass index, and physical activity from baseline to 6 months. The end points were assessed using analyses of covariance. The follow-up rate was 99%. When compared with control group at 6 months, the intervention group had a greater reduction in HbA1C (-0.2% versus 0.1%; P=0.003) and a greater proportion of participants who achieved HbA1C <7% (69.3% versus 52.6%; P=0.004). Change in fasting blood glucose was larger in the intervention group (between-group difference: -0.6 mmol/L; 95% CI, -1.1 to -0.2; P=0.011), but no other outcome differences were observed. Nearly all participants reported that messages were easy to understand (97.1%) and useful (94.1%). CONCLUSIONS: A text message intervention resulted in better glycemic control in patients with diabetes mellitus and coronary heart disease. While the mechanism of this benefit remains to be determined, the results suggest that a simple, culturally sensitive mobile text messaging program may provide an effective and feasible way to improve disease self-management. CLINICAL TRIAL REGISTRATION: URL: http://www.clinicaltrials.gov. Unique identifier: NCT02883842.

Association of Diabetes Mellitus With Health Status Outcomes in Young Women and Men After Acute Myocardial Infarction: Results From the VIRGO Study.

Background Diabetes mellitus increases the risk of mortality after acute myocardial infarction (AMI). However, little is known about the association of diabetes mellitus with post-AMI health status outcomes (symptoms, functioning, and quality of life) in younger adults. Methods and Results We investigated the association between diabetes mellitus and health status during the first 12 months after AMI, using data from 3501 adults with AMI (42.6% with diabetes mellitus) aged 18 to 55 years enrolled in the VIRGO (Variation in Recovery: Role of Gender on Outcomes of Young AMI Patients) study. Health status was measured with Seattle Angina Questionnaire (SAQ), 12-item Short-Form Health Survey, and EuroQol-Visual Analogue Scale at baseline hospitalization, 1-month, and 12-months post-AMI. At baseline, patients with diabetes mellitus had significantly worse SAQ-angina frequency (81±22 versus 86±19), SAQ-physical limitations (77±28 versus 85±23), SAQ-quality of life (55±25 versus 57±23), 12-item Short-Form Health Survey mental (44±13 versus 46±12)/physical functioning (41±12 versus 46±12), and EuroQol-Visual Analogue Scale (61±22 versus 66±21) than those without diabetes mellitus. Over time, both groups (with and without diabetes mellitus) improved considerably and the differences in health status scores progressively narrowed (except for 12-item Short-Form Health Survey physical functioning). In the linear-mixed effects models, adjusted for sociodemographics, cardiovascular risk factors, comorbidities, clinical characteristics, psychosocial factors, healthcare use, and AMI treatment, diabetes mellitus was associated with worse health status at baseline but not after discharge, and the association did not vary by sex. Conclusions At baseline, young adults with diabetes mellitus had poorer health status than those without diabetes mellitus. After AMI, however, they experienced significant improvements and diabetes mellitus was not associated with worse angina, SAQ-physical limitations, mental functioning, and quality of life, after adjustment for baseline covariates. Clinical Trial Registration URL: https://www.clinicaltrials.gov/. Unique identifier: NCT00597922.