Mortality among people who have experienced homelessness: protocol for a systematic review and meta-analysis.

INTRODUCTION: Homelessness is a major contributor to health inequalities. People who experience homelessness are at markedly increased risk of multiple and complex health morbidities which likely increase their susceptibility to early, preventable death. Despite this, the mortality burden in this group remains poorly understood, limited in part by insufficient synthesis of data at a global level. This systematic review will synthesise international literature examining rates of risk and protective factors for mortality among people who have experienced homelessness. METHODS AND ANALYSIS: We will search MEDLINE, PsycINFO, Embase and PubMed for peer-reviewed cohort studies examining mortality among people who have experienced homelessness. No study eligibility restrictions will be placed on the date, country of origin, or language of publications, or age of the sample. We will assess the quality of included studies using the Methodological Standards for Epidemiological Research scale. Our measures of mortality will include: (A) incidence-all cause and cause specific, expressed as a crude mortality rate (CMR) per 1000 person-years, with 95% CI and (B) all cause and cause specific, indirectly standardised mortality ratios (SMRs) with 95%CI. Associations between risk and protective factors and all-cause and cause-specific mortality will be reported using pooled relative risk ratios with 95% CI. Where there are sufficient data, the influence of subgroup and methodological factors on CMRs, SMRs and predictive factors will be examined using meta-regression. ETHICS AND DISSEMINATION: This study does not require institutional ethics review or approval as it will synthesise findings from published studies that have previously been granted relevant ethics approvals. Study findings will be disseminated through a peer-reviewed journal article, conference and seminar presentations. A plain language summary will be distributed through the authors' academic and professional networks. PROSPERO REGISTRATION NUMBER: CRD42021272937.

Mitigation behavior prior to COVID-19 vaccination availability is associated with COVID-19 infection and time to vaccination.

BACKGROUND: Mitigation behaviors reduce the incidence of COVID-19 infection. Determining characteristics of groups defined by mitigation behaviors compliance may be useful to inform targeted public health policies and interventions. This study aimed to identify groups of individuals according to self-reported compliance with COVID-19 mitigation behaviors, define compliance class characteristics, and explore associations between compliance classes and important study and public health outcomes. METHODS AND FINDINGS: We studied 1,410 participants in the Cabarrus County COVID-19 Prevalence and Immunity longitudinal cohort study (June 2020 to December 2021) who were asked 10 questions regarding compliance with recommended COVID-19 mitigation behaviors. By Latent Class Analysis, 1,381 participants were categorized into 3 classes (most [49.4%], moderately [45.0%], and least [5.6%] compliant). Compared with the most compliant class, the least and moderately compliant classes were younger (mean = 61.9 v. 59.0 v. 53.8 years), had fewer medical conditions per individual (1.37 v. 1.08 v. 0.77), and differed in Hispanic ethnicity (6.2% v. 2.8% v. 9.1%) and COVID-19 vaccine intention (65.8% v. 59.8% v. 35.1%). Compared to the most compliant class, the least compliant class had fewer women (54.6% v. 76.3%), fewer insured individuals (92.2% v. 97.4%), and more withdrew from study participation early (28.6% v. 16.0%). Relative to the most compliant class, the least compliant class had a higher likelihood of COVID-19 infection (OR = 2.08 [95% CI 1.13, 3.85]), lower rate of COVID-19 vaccination (72.6% v. 95.1%), and longer time to 50% COVID-19 vaccination following eligibility (8-9 vs 16 days). CONCLUSIONS: Classes defined by mitigation behaviors compliance had distinct characteristics, including age, sex, medical history, and ethnicity, and were associated with important study and public health outcomes. Targeted public health policies and interventions according to the compliance group characteristics may be of value in current and future pandemic responses to increase compliance.

Reasons for Receiving or Not Receiving Bivalent COVID-19 Booster Vaccinations Among Adults - United States, November 1-December 10, 2022.

Bivalent COVID-19 booster vaccines, developed to protect against both ancestral and Omicron BA.4/BA.5 variants, are recommended to increase protection against SARS-CoV-2 infection and severe disease* (1,2). However, relatively few eligible U.S. adults have received a bivalent booster dose (3), and reasons for low coverage are unclear. An opt-in Internet survey of 1,200 COVID-19-vaccinated U.S. adults was conducted to assess reasons for receiving or not receiving a bivalent booster dose. Participants could select multiple reasons from a list of suggested reasons to report why they had or had not received a bivalent booster dose. The most common reasons cited for not receiving the bivalent booster dose were lack of awareness of eligibility for vaccination (23.2%) or of vaccine availability (19.3%), and perceived immunity against infection (18.9%). After viewing information about eligibility and availability, 67.8% of participants who had not received the bivalent booster dose indicated that they planned to do so; in a follow-up survey 1 month later, 28.6% of these participants reported having received the dose. Among those who had planned to receive the booster dose but had not yet done so, 82.6% still intended to do so. Participants who had still not received the booster dose most commonly reported being too busy to get vaccinated (35.6%). To help increase bivalent booster dose coverage, health care and public health professionals should use evidence-based strategies to convey information about booster vaccination recommendations and waning immunity (4), while also working to increase convenient access.

Association of Guideline Complexity With Individuals' Ability to Determine Eligibility for COVID-19 Vaccination.

This cross-sectional study examines the association between the complexity of consumer guidelines for COVID-19 vaccination and identification of eligibility.

The association between non-English primary language and COVID-19 clinical trial eligibility and enrollment: A retrospective cohort study.

BACKGROUND: Establishing equitable access to COVID-19 clinical trials is an important step in mitigating outcomes disparities. Historically, language has served as a barrier to equitable clinical trial participation. METHODS: A centralized research infrastructure was established at our institution to screen potential trial participants and to promote efficient and equitable access to COVID-19 clinical trials. Rates of eligibility and enrollment in COVID-19 clinical trials by primary language between April 9 and July 31, 2020 (during the first regional COVID-19 surge) were evaluated using logistic regression. Estimates were adjusted for potential confounders including age, sex, and time. RESULTS: A total of 1245 patients were admitted to the hospital with COVID-19 during the study period and screened for clinical trial eligibility. Among all screened patients, 487 (39%) had a non-English primary language. After adjustment, patients with a non-English primary language had 1.98 times higher odds (CI 1.51 to 2.59) of being eligible for 1 or more COVID-19 clinical trials. Among eligible patients, those with a non-English primary language had 1.83 times higher odds (CI 1.36 to 2.47) of enrolling in COVID-19 clinical trials than patients with English as the primary language. CONCULSION: These findings suggest that there are modifiable barriers that can be addressed to lessen the impact of language discordance on access to clinical trials and provide an opportunity to further investigate factors associated with clinical trial participation for patients whose primary language is not English.

Combining human and machine intelligence for clinical trial eligibility querying.

OBJECTIVE: To combine machine efficiency and human intelligence for converting complex clinical trial eligibility criteria text into cohort queries. MATERIALS AND METHODS: Criteria2Query (C2Q) 2.0 was developed to enable real-time user intervention for criteria selection and simplification, parsing error correction, and concept mapping. The accuracy, precision, recall, and F1 score of enhanced modules for negation scope detection, temporal and value normalization were evaluated using a previously curated gold standard, the annotated eligibility criteria of 1010 COVID-19 clinical trials. The usability and usefulness were evaluated by 10 research coordinators in a task-oriented usability evaluation using 5 Alzheimer's disease trials. Data were collected by user interaction logging, a demographic questionnaire, the Health Information Technology Usability Evaluation Scale (Health-ITUES), and a feature-specific questionnaire. RESULTS: The accuracies of negation scope detection, temporal and value normalization were 0.924, 0.916, and 0.966, respectively. C2Q 2.0 achieved a moderate usability score (3.84 out of 5) and a high learnability score (4.54 out of 5). On average, 9.9 modifications were made for a clinical study. Experienced researchers made more modifications than novice researchers. The most frequent modification was deletion (5.35 per study). Furthermore, the evaluators favored cohort queries resulting from modifications (score 4.1 out of 5) and the user engagement features (score 4.3 out of 5). DISCUSSION AND CONCLUSION: Features to engage domain experts and to overcome the limitations in automated machine output are shown to be useful and user-friendly. We concluded that human-computer collaboration is key to improving the adoption and user-friendliness of natural language processing.

Metastatic gastroesophageal cancer in older patients - is this patient cohort represented in clinical trials?

BACKGROUND: Older patients are underrepresented in the clinical trials that determine the standards of care for oncological treatment. We conducted a review to identify whether there have been age-restrictive inclusion criteria in clinical trials over the last twenty five years, focusing on patients with metastatic gastroesophageal cancer. METHODS: A search strategy was developed encompassing Embase, PubMed and The Cochrane Library databases. Completed phase III randomised controlled trials evaluating systemic anti-cancer therapies in metastatic gastroesophageal malignancies from 1st January 1995 to 18th November 2020 were identified. These were screened for eligibility using reference management software (Covidence; Veritas Health Innovation Ltd). Data including age inclusion/exclusion criteria and median age of participants were recorded. The percentage of patients ≥ 65 enrolled was collected where available. The change over time in the proportion of studies using an upper age exclusion was estimated using a linear probability model. RESULTS: Three hundred sixty-three phase III studies were identified and screened, with 66 trials remaining for final analysis. The majority of trials were Asian (48%; n = 32) and predominantly evaluated gastric malignancies, (86%; n = 56). The median age of participants was 62 (range 18-94). Thirty-two percent (n = 21) of studies specified an upper age limit for inclusion and over half of these were Asian studies. The median age of exclusion was 75 (range 65-80). All studies prior to 2003 used an upper age exclusion (n = 12); whereas only 9 that started in 2003 or later did (17%). Among later studies, there was a very modest downward yearly-trend in the proportion of studies using an upper age exclusion (-0.02 per year; 95%CI -0.05 to 0.01; p = 0.31). Fifty-two percent (n = 34) of studies specified the proportion of their study population who were ≥ 65 years. Older patients represented only 36% of the trial populations in these studies (range 7-60%). CONCLUSIONS: Recent years have seen improvements in clinical trial protocols, with many no longer specifying restrictive age criteria. Reasons for poor representation of older patients are complex and ongoing efforts are needed to broaden eligibility criteria and prioritise the inclusion of older adults in clinical trials.

ACA Marketplaces Became Less Affordable Over Time For Many Middle-Class Families, Especially The Near-Elderly.

The Affordable Care Act provides tax credits for Marketplace insurance, but before 2021, families with incomes above four times the federal poverty level did not qualify for tax credits and could face substantial financial burdens when purchasing coverage. As a measure of affordability, we calculated potential Marketplace premiums as a percentage of family income among families with incomes of 401-600 percent of poverty. In 2015 half of this middle-class population would have paid at least 7.7 percent of their income for the lowest-cost bronze plan; in 2019 they would have paid at least 11.3 percent of their income. By 2019 half of the near-elderly ages 55-64 would have paid at least 18.9 percent of their income for the lowest-cost bronze plan in their area. The American Rescue Plan Act temporarily expanded tax credit eligibility for 2021 and 2022, but our results suggest that families with incomes of 401-600 percent of poverty will again face substantial financial burdens after the temporary subsidies expire.

A Playbook for Implementing Medicaid Expansion: Louisiana's Experience.

Policy Points Twelve states have yet to expand Medicaid under the Affordable Care Act (ACA). Louisiana offers a model of steps that states and counties can take to rapidly enroll eligible persons while balancing eligibility integrity and doing so within a limited administrative budget. In a post-COVID-19 health care landscape, Medicaid expansion can improve and protect population health and boost state economies, even amid budget shortfalls. Even though Louisiana compares well with other states in eligibility and enrollment efforts, future expansions may integrate other social support programs into their implementation strategies.

Evaluation of the Association Between Medicare Eligibility and Excess Deaths During the COVID-19 Pandemic in the US.

This cross-sectional regression discontinuity analysis compares deaths slightly younger and older than 65 years to examine the relationship between access to health insurance coverage and COVID-19 mortality.

Equity in vaccine trials for higher weight people? Protocol for a rapid review of inclusion and exclusion criteria for higher weight people in clinical trials for COVID-19.

INTRODUCTION: Vaccination is a public health strategy that aims to reduce the burden of viral illness, especially important for populations known or likely to be at increased risk for inequitable outcomes due to the disease itself or disparities in care accessed and received. The role of weight status in COVID-19 susceptibility and disease burden remains unclear. Despite this, higher weight is frequently described as a definitive risk factor for both susceptibility and disease severity. Therefore, COVID-19 vaccine trials should recruit a study group representative of the full weight spectrum, and undertake appropriate subgroup analysis by weight status to evaluate response and titrate dose regimes where indicated to ensure equitable outcomes for higher weight people. METHODS AND ANALYSIS: We aim to review inclusion and exclusion criteria of clinical trial protocols registered with ClinicalTrials.gov, ISRCTN Register, the WHO official vaccine trial register, and 'The COVID-19 Vaccine Tracker'. To determine the number of trials including higher weight (body mass index >30 kg/m2) individuals and the number of trials conducting efficacy subgroup analyses by weight status. Screening, data extraction and quality appraisal of trial protocols will be completed independently by a minimum of two reviewers. Clinical trials will be assessed for risk of bias using the Risk of Bias-2 tool. We will conduct a descriptive analysis of extracted data. The following subsets are proposed: participation of higher weight people in COVID-19 vaccine trials by trial phase, country and vaccine platform. ETHICS AND DISSEMINATION: Ethical approval was not required for this review. The results of this rapid review will be presented at appropriate conferences and published in a suitable peer reviewed journal. PROSPERO REGISTRATION NUMBER: CRD42020226573.

Race and ethnicity do not impact eligibility for remdesivir: A single-center experience.

As the Coronavirus-2019 (COVID-19) pandemic continues, multiple therapies are rapidly being evaluated for efficacy in clinical trials. Clinical trials should be racially and ethnically representative of the population that will eventually benefit from these medications. There are multiple potential barriers to racial and ethnic minority enrollment in clinical trials, one of which could be that inclusion and exclusion criteria select for certain racial or ethnic groups disproportionately. In this observational cohort study at a single health care system, we examined if there were differences in eligibility for treatment with remdesivir based on clinical trial criteria for racial and ethnic minorities compared to non-Hispanic Whites. 201 electronic medical record charts were reviewed manually. Self-identified Whites were older than other racial or ethnic groups. At the time of presentation, Black, Latinx, and White participants met inclusion criteria for remdesivir at similar rates (72%, 80%, and 73% respectively), and exclusion criteria at similar rates (43%, 38% and 49% for Black, Latinx and White participants respectively). In this study, there was no difference in eligibility for remdesivir based on race or ethnicity alone.

Building an OMOP common data model-compliant annotated corpus for COVID-19 clinical trials.

Clinical trials are essential for generating reliable medical evidence, but often suffer from expensive and delayed patient recruitment because the unstructured eligibility criteria description prevents automatic query generation for eligibility screening. In response to the COVID-19 pandemic, many trials have been created but their information is not computable. We included 700 COVID-19 trials available at the point of study and developed a semi-automatic approach to generate an annotated corpus for COVID-19 clinical trial eligibility criteria called COVIC. A hierarchical annotation schema based on the OMOP Common Data Model was developed to accommodate four levels of annotation granularity: i.e., study cohort, eligibility criteria, named entity and standard concept. In COVIC, 39 trials with more than one study cohorts were identified and labelled with an identifier for each cohort. 1,943 criteria for non-clinical characteristics such as "informed consent", "exclusivity of participation" were annotated. 9767 criteria were represented by 18,161 entities in 8 domains, 7,743 attributes of 7 attribute types and 16,443 relationships of 11 relationship types. 17,171 entities were mapped to standard medical concepts and 1,009 attributes were normalized into computable representations. COVIC can serve as a corpus indexed by semantic tags for COVID-19 trial search and analytics, and a benchmark for machine learning based criteria extraction.

Inclusion of pregnant women in COVID-19 treatment trials: a review and global call to action.

Inclusion of pregnant women in COVID-19 clinical trials would allow evaluation of effective therapies that might improve maternal health, pregnancy, and birth outcomes, and avoid the delay of developing treatment recommendations for pregnant women. We explored the inclusion of pregnant women in treatment trials of COVID-19 by reviewing ten international clinical trial registries at two timepoints in 2020. We identified 155 COVID-19 treatment studies of non-biological drugs for the April 7-10, 2020 timepoint, of which 124 (80%) specifically excluded pregnant women. The same registry search for the July 10-15, 2020 timepoint, yielded 722 treatment studies, of which 538 (75%) specifically excluded pregnant women. We then focused on studies that included at least one of six drugs (remdesivir, lopinavir-ritonavir, interferon beta, corticosteroids, chloroquine and hydroxychloroquine, and ivermectin) under evaluation for COVID-19. Of 176 such studies, 130 (74%) listed pregnancy as an exclusion criterion. Of 35 studies that evaluated high-dose vitamin treatment for COVID-19, 27 (77%) excluded pregnant women. Despite the surge in treatment studies for COVID-19, the proportion excluding pregnant women remains consistent. Exclusion was not well justified as many of the treatments being evaluated have no or low safety concerns during pregnancy. Inclusion of pregnant women in clinical treatment trials is urgently needed to identify effective COVID-19 treatment for this population.

Who should be vaccinated first? Comparing vaccine prioritization strategies in Israel and European countries using the Covid-19 Health System Response Monitor.

The rapid rollout of Israel's vaccination program has led to considerable international interest. In this brief commentary we consider how the criteria for vaccination priority groups differ between Israel and selected European countries. We argue that following the Israeli approach of using broad criteria for prioritization- i.e. having fewer groups and a lower age threshold- could have several beneficial effects, including more manageable logistics and fewer roll out delays, as well as potentially reducing pressure on hospitals. With an increasing supply of vaccines becoming available rapidly in much of Europe, countries could consider following the approach of Israel and adopting broader priority criteria going forward.

Towards clinical data-driven eligibility criteria optimization for interventional COVID-19 clinical trials.

OBJECTIVE: This research aims to evaluate the impact of eligibility criteria on recruitment and observable clinical outcomes of COVID-19 clinical trials using electronic health record (EHR) data. MATERIALS AND METHODS: On June 18, 2020, we identified frequently used eligibility criteria from all the interventional COVID-19 trials in ClinicalTrials.gov (n = 288), including age, pregnancy, oxygen saturation, alanine/aspartate aminotransferase, platelets, and estimated glomerular filtration rate. We applied the frequently used criteria to the EHR data of COVID-19 patients in Columbia University Irving Medical Center (CUIMC) (March 2020-June 2020) and evaluated their impact on patient accrual and the occurrence of a composite endpoint of mechanical ventilation, tracheostomy, and in-hospital death. RESULTS: There were 3251 patients diagnosed with COVID-19 from the CUIMC EHR included in the analysis. The median follow-up period was 10 days (interquartile range 4-28 days). The composite events occurred in 18.1% (n = 587) of the COVID-19 cohort during the follow-up. In a hypothetical trial with common eligibility criteria, 33.6% (690/2051) were eligible among patients with evaluable data and 22.2% (153/690) had the composite event. DISCUSSION: By adjusting the thresholds of common eligibility criteria based on the characteristics of COVID-19 patients, we could observe more composite events from fewer patients. CONCLUSIONS: This research demonstrated the potential of using the EHR data of COVID-19 patients to inform the selection of eligibility criteria and their thresholds, supporting data-driven optimization of participant selection towards improved statistical power of COVID-19 trials.