Latent class analysis of health, social, and behavioral profiles associated with psychological distress among pregnant and postpartum women during the COVID-19 pandemic in the United States.

BACKGROUND: There is a growing body of literature documenting negative mental health impacts from the COVID-19 pandemic. The purpose of this study was to identify risk and protective factors associated with mental health and well-being among pregnant and postpartum women during the pandemic. METHODS: This was a cross-sectional, anonymous online survey study distributed to pregnant and postpartum (within 6 months) women identified through electronic health records from two large healthcare systems in the Northeastern and Midwestern United States. Survey questions explored perinatal and postpartum experiences related to the pandemic, including social support, coping, and health care needs and access. Latent class analysis was performed to identify classes among 13 distinct health, social, and behavioral variables. Outcomes of depression, anxiety, and stress were examined using propensity-weighted regression modeling. RESULTS: Fit indices demonstrated a three-class solution as the best fitting model. Respondents (N = 616) from both regions comprised three classes, which significantly differed on sleep- and exercise-related health, social behaviors, and mental health: Higher Psychological Distress (31.8%), Moderate Psychological Distress (49.8%), and Lower Psychological Distress (18.4%). The largest discriminatory issue was support from one's social network. Significant differences in depression, anxiety, and stress severity scores were observed across these three classes. Reported need for mental health services was greater than reported access. CONCLUSIONS: Mental health outcomes were largely predicted by the lack or presence of social support, which can inform public health decisions and measures to buffer the psychological impact of ongoing waves of the COVID-19 pandemic on pregnant and postpartum women. Targeted early intervention among those in higher distress categories may help improve maternal and child health.

Treatment with stimulants and the risk of COVID-19 complications in adults with ADHD.

Adults with attention deficit hyperactivity disorder (ADHD) have shown higher infection rates and worse outcomes from COVID-19. Stimulant medications are prescribed as the first-line treatment for ADHD in adults and mitigate risk of negative ADHD-related health outcomes, but little is known about the association between stimulant medications and COVID-19 outcomes. The objective of this study was to assess the risks of severe COVID-19 outcomes among people with ADHD who were prescribed stimulant medications versus those who were not. This retrospective cohort study used electronic health records in the TriNetX research database. We assessed records of adults with ADHD diagnosed with COVID-19 between January 1, 2020 and June 30, 2021. The stimulant cohort consisted of 28,011 people with at least one stimulant prescription; the unmedicated cohort comprised 42,258 people without prescribed stimulants within 12 months prior to their COVID infection. Multiple logistic regression modeling was utilized to assess the presence of critical care services or death within 30 days after the onset of COVID diagnoses, controlling for patient demographics, and comorbid medical and mental health conditions. The stimulant cohort was less likely to utilize emergency department, hospital, and intensive care services than the unmedicated cohort, and had significantly lower 30-day mortality. Further research, including prospective studies, is needed to confirm and refine these findings.

External Validation of the COVID-NoLab and COVID-SimpleLab Prognostic Tools.

Our objective was to externally validate 2 simple risk scores for mortality among a mostly inpatient population with COVID-19 in Canada (588 patients for COVID-NoLab and 479 patients for COVID-SimpleLab). The mortality rates in the low-, moderate-, and high-risk groups for COVID-NoLab were 1.1%, 9.6%, and 21.2%, respectively. The mortality rates for COVID-SimpleLab were 0.0%, 9.8%, and 20.0%, respectively. These values were similar to those in the original derivation cohort. The 2 simple risk scores, now successfully externally validated, offer clinicians a reliable way to quickly identify low-risk inpatients who could potentially be managed as outpatients in the event of a bed shortage. Both are available online (https://ebell-projects.shinyapps.io/covid_nolab/ and https://ebell-projects.shinyapps.io/COVID-SimpleLab/).

Risks of Severe COVID-19 Outcomes Among Patients With Diabetic Polyneuropathy in the United States.

CONTEXT: Diabetic neuropathy (DN) affects more than 50% of diabetic patients who are also likely to have compromised immune system and respiratory function, both of which can make them susceptible to the SARS-CoV-2 virus. OBJECTIVE: To assess the risk of severe COVID-19 illness among adults with DN, compared with those with no DN and those with no diabetes. SETTING: The analysis utilized electronic health records from 55 US health care organizations in the TriNetX research database. DESIGN: A retrospective cohort study. PARTICIPANTS: The analysis included 882 650 adults diagnosed with COVID-19 in January 2020 to June 2021, including 16 641 with DN, 81 329 with diabetes with no neuropathy, and 784 680 with no diabetes. OUTCOME MEASURES: The presence of health care utilization (admissions to emergency department, hospital, intensive care unit), 30-day mortality, clinical presentation (cough, fever, hypoxemia, dyspnea, or acute respiratory distress syndrome), and diagnostic test results after being infected affected by COVID-19. RESULTS: The DN cohort was 1.19 to 2.47 times more likely than the non-DN cohorts to utilize care resources, receive critical care, and have higher 30-day mortality rates. Patients with DN also showed increased risk (1.13-2.18 times) of severe symptoms, such as hypoxemia, dyspnea, and acute respiratory distress syndrome. CONCLUSIONS: Patients with DN had a significantly greater risk of developing severe COVID-19-related complications than those with no DN. It is critical for the public health community to continue preventive measures, such as social distancing, wearing masks, and vaccination, to reduce infection rates, particularly in higher risk groups, such as those with DN.

Mindfulness-Based Stress Reduction Live Online During the COVID-19 Pandemic: A Mixed Methods Feasibility Study.

Objectives: To assess the feasibility, acceptability, and effects of Mindfulness Based Stress Reduction (MBSR) live online during the COVID-19 shutdown. Design: Mixed-methods study using a sequential explanatory design. Settings/location: Cohorts 1-4 took place in-person and Cohorts 5-6 took place over Zoom following the onset of the COVID-19 pandemic. Subjects: Participants were paying members of the general public enrolled in one of six live MBSR courses. Interventions: All MBSR courses followed the standard 8-week MBSR curriculum, led by experienced instructors. Outcome measures: Feasibility measured via class attendance, acceptability measured via the adapted Treatment Satisfaction Survey, and MBSR course effects measured by a focus group with Cohort 5, and the following assessments completed by all cohorts: Perceived Stress Scale-10, Generalized Anxiety Disorder-7, Patient Health Questionnaire-9 and the 36-item Short Form Survey. Results: 73 adults participated in six live MBSR courses (48 in the four in-person courses; 25 in the two online courses). Most of the participants identified as white, non-Hispanic, middle-aged females, with annual household income >$100,000. Course completion, defined as at least 6/8 classes attended, did not differ between in-person and online cohorts (84.1% versus 67.6%, respectively, p = 0.327). Participants in Cohort 5 who completed the course (n = 10) rated it as very important and useful for stress coping, and reported high likelihood of continuing their mindfulness practice (all ratings: between 8 and 10 on a 1-10 Likert scale), with open-ended responses corroborating their numerical ratings. Focus group (n = 6) responses indicated that online MBSR was positively received, reduced perceived loss of control, and improved quality of life and morale during the pandemic. Conclusions: Delivering MBSR live online can be feasible and acceptable for the general public, and is potentially beneficial, including during the social upheaval of the COVID-19 pandemic. Online delivery could help expand access to MBSR and address health inequities.

Adjunctive osteopathic therapy for hospitalized COVID-19 patients: A feasibility-oriented chart review study with matched controls.

Background: Osteopathic manipulative treatment (OMT) may improve outcomes during COVID-related respiratory distress - the most common cause of death from novel coronavirus (SARS-CoV-2). Outcomes from OMT treatments of respiratory distress during the COVID-19 pandemic have not been reported. Objective: Assess adjunctive OMT in hospitalized patients with SARS-CoV-2 and respiratory distress. Design: Feasibility oriented retrospective observational cohort study. Setting: COVID-19 (non-ICU) ward in a tertiary academic medical center. Methods: Inpatients received daily OMT treatments of rib raising, abdominal diaphragm doming, thoracic pump and pedal pump. Primary outcomes were procedural acceptance, satisfaction, side effects, and adverse events. Secondary outcomes were patient-reported clinical change after therapy; number of hospital days; need during hospitalization for high-flow oxygen, C-PAP/BiPAP or intensive care; need for supplementary oxygen at discharge; and discharge disposition. Participants: Hospitalized adults with SARS-CoV-2 infection and respiratory distress. Results: OMT (n = 27) and Control (n = 152) groups were similar in demographics and most laboratory studies. 90% of patients accepted OMT and reported high satisfaction (4.26/±0.71 (maximum 5)), few negative effects, no adverse events, and positive clinical change (5.07 ± 0.96 (maximum 7)). Although no significant differences were found in secondary outcomes, OMT patients trended towards fewer hospital days than Controls (p = 0.053; Cohen's d = 0.22), a relationship that trended towards correlation with number of co-morbidities (p = 0.068). Conclusion: Hospitalized patients with respiratory distress and COVID-19 reported acceptance, satisfaction, and greater ease of breathing after a four-part OMT protocol, and appear to have a shorter length of hospitalization. Randomized controlled trials are needed to confirm these results.

Development and Validation of a Two-Step Predictive Risk Stratification Model for Coronavirus Disease 2019 In-hospital Mortality: A Multicenter Retrospective Cohort Study.

Objectives: An accurate prognostic score to predict mortality for adults with COVID-19 infection is needed to understand who would benefit most from hospitalizations and more intensive support and care. We aimed to develop and validate a two-step score system for patient triage, and to identify patients at a relatively low level of mortality risk using easy-to-collect individual information. Design: Multicenter retrospective observational cohort study. Setting: Four health centers from Virginia Commonwealth University, Georgetown University, the University of Florida, and the University of California, Los Angeles. Patients: Coronavirus Disease 2019-confirmed and hospitalized adult patients. Measurements and Main Results: We included 1,673 participants from Virginia Commonwealth University (VCU) as the derivation cohort. Risk factors for in-hospital death were identified using a multivariable logistic model with variable selection procedures after repeated missing data imputation. A two-step risk score was developed to identify patients at lower, moderate, and higher mortality risk. The first step selected increasing age, more than one pre-existing comorbidities, heart rate >100 beats/min, respiratory rate ≥30 breaths/min, and SpO2 <93% into the predictive model. Besides age and SpO2, the second step used blood urea nitrogen, absolute neutrophil count, C-reactive protein, platelet count, and neutrophil-to-lymphocyte ratio as predictors. C-statistics reflected very good discrimination with internal validation at VCU (0.83, 95% CI 0.79-0.88) and external validation at the other three health systems (range, 0.79-0.85). A one-step model was also derived for comparison. Overall, the two-step risk score had better performance than the one-step score. Conclusions: The two-step scoring system used widely available, point-of-care data for triage of COVID-19 patients and is a potentially time- and cost-saving tool in practice.

'Us-Versus-Them': Othering in COVID-19 public health behavior compliance.

OBJECTIVE: We explored public perceptions about the COVID-19 pandemic to learn how those attitudes may affect compliance with health behaviors. METHODS: Participants were Central Pennsylvania adults from diverse backgrounds purposively sampled (based on race, gender, educational attainment, and healthcare worker status) who responded to a mixed methods survey, completed between March 25-31, 2020. Four open-ended questions were analyzed, including: "What worries you most about the COVID-19 pandemic?" We applied a pragmatic, inductive coding process to conduct a qualitative, descriptive content analysis of responses. RESULTS: Of the 5,948 respondents, 538 were sampled for this qualitative analysis. Participants were 58% female, 56% with ≥ bachelor's degree, and 50% from minority racial backgrounds. Qualitative descriptive analysis revealed four themes related to respondents' health and societal concerns: lack of faith in others; fears of illness or death; frustration at perceived slow societal response; and a desire for transparency in communicating local COVID-19 information. An "us-versus-them" subtext emerged; participants attributed non-compliance with COVID-19 behaviors to other groups, setting themselves apart from those Others. CONCLUSION: Our study uncovered Othering undertones in the context of the COVID-19 pandemic, occurring between groups of like-minded individuals with behavioral differences in 'compliance' versus 'non-compliance' with public health recommendations. Addressing the 'us-versus-them' mentality may be important for boosting compliance with recommended health behaviors.

Developing and testing an automated qualitative assistant (AQUA) to support qualitative analysis.

Qualitative research remains underused, in part due to the time and cost of annotating qualitative data (coding). Artificial intelligence (AI) has been suggested as a means to reduce those burdens, and has been used in exploratory studies to reduce the burden of coding. However, methods to date use AI analytical techniques that lack transparency, potentially limiting acceptance of results. We developed an automated qualitative assistant (AQUA) using a semiclassical approach, replacing Latent Semantic Indexing/Latent Dirichlet Allocation with a more transparent graph-theoretic topic extraction and clustering method. Applied to a large dataset of free-text survey responses, AQUA generated unsupervised topic categories and circle hierarchical representations of free-text responses, enabling rapid interpretation of data. When tasked with coding a subset of free-text data into user-defined qualitative categories, AQUA demonstrated intercoder reliability in several multicategory combinations with a Cohen's kappa comparable to human coders (0.62-0.72), enabling researchers to automate coding on those categories for the entire dataset. The aim of this manuscript is to describe pertinent components of best practices of AI/machine learning (ML)-assisted qualitative methods, illustrating how primary care researchers may use AQUA to rapidly and accurately code large text datasets. The contribution of this article is providing guidance that should increase AI/ML transparency and reproducibility.

COVID-19 outcomes among adult patients treated with long-term opioid therapy for chronic non-cancer pain in the USA: a retrospective cohort study.

OBJECTIVE: Patients treated with long-term opioid therapy (LTOT) are known to have compromised immune systems and respiratory function, both of which make them particularly susceptible to the SARS-CoV-2 virus. The objective of this study was to assess the risk of developing severe clinical outcomes among COVID-19 non-cancer patients on LTOT, compared with those without LTOT. DESIGN AND DATA SOURCES: A retrospective cohort design using electronic health records in the TriNetX research database. PARTICIPANTS AND SETTING: 418 216 adults diagnosed with COVID-19 in January-December 2020 from 51 US healthcare organisations: 9558 in the LTOT and 408 658 in the control cohort. They did not have cancer diagnoses; only a small proportion might have been treated with opioid maintenance for opioid use disorder. RESULTS: Patient on LTOT had a higher risk ratio (RR) than control patients to visit an emergency department (RR 2.04, 95% CI 1.93 to 2.16) and be hospitalised (RR 2.91, 95% CI 2.69 to 3.15). Once admitted, LTOT patients were more likely to require intensive care (RR 3.65, 95% CI 3.10 to 4.29), mechanical ventilation (RR 3.47, 95% CI 2.89 to 4.15) and vasopressor support (RR 5.28, 95% CI 3.70 to 7.53) and die within 30 days (RR 1.96, 95% CI 1.67 to 2.30). The LTOT group also showed increased risk (RRs from 2.06 to 3.98, all significant to 95% CI) of more-severe infection (eg, cough, dyspnoea, fever, hypoxaemia, thrombocytopaenia and acute respiratory distress syndrome). Statistically significant differences in several laboratory results and other vital signs appeared clinically negligible. CONCLUSION: COVID-19 patients on LTOT were at higher risk of increased morbidity, mortality and healthcare utilisation. Interventions to reduce the need for LTOT and to increase compliance with COVID-19 protective measures may improve outcomes and reduce healthcare cost in this population. Prospective studies need to confirm and refine these findings.

Lower Intent to Comply with COVID-19 Public Health Recommendations Correlates to Higher Disease Burden in Following 30 Days.

OBJECTIVES: We sought to determine whether self-reported intent to comply with public health recommendations correlates with future coronavirus disease 2019 (COVID-19) disease burden. METHODS: A cross-sectional, online survey of US adults, recruited by snowball sampling, from April 9 to July 12, 2020. Primary measurements were participant survey responses about their intent to comply with public health recommendations. Each participant's intent to comply was compared with his or her local COVID-19 case trajectory, measured as the 7-day rolling median percentage change in COVID-19 confirmed cases within participants' 3-digit ZIP code area, using public county-level data, 30 days after participants completed the survey. RESULTS: After applying raking techniques, the 10,650-participant sample was representative of US adults with respect to age, sex, race, and ethnicity. Intent to comply varied significantly by state and sex. Lower reported intent to comply was associated with higher COVID-19 case increases during the following 30 days. For every 3% increase in intent to comply with public health recommendations, which could be achieved by improving average compliance by a single point for a single item, we estimate a 9% reduction in new COVID-19 cases during the subsequent 30 days. CONCLUSIONS: Self-reported intent to comply with public health recommendations may be used to predict COVID-19 disease burden. Measuring compliance intention offers an inexpensive, readily available method of predicting disease burden that can also identify populations most in need of public health education aimed at behavior change.

Knowledge, Perceptions, and Preferred Information Sources Related to COVID-19 Among Central Pennsylvania Adults Early in the Pandemic: A Mixed Methods Cross-Sectional Survey.

PURPOSE: To explore public knowledge, understanding of public health recommendations, perceptions, and trust in information sources related to COVID-19. METHODS: A cross-sectional survey of central Pennsylvanian adults evaluated self-reported knowledge, and a convergent, mixed methods design was used to assess beliefs about recommendations, intended behaviors, perceptions, and concerns related to infectious disease risk, and trust of information sources. RESULTS: The survey was completed by 5,948 adults. The estimated probability of correct response for the basic knowledge score, weighted with confidence, was 0.79 (95% CI, 0.79-0.80). Knowledge was significantly higher in patients with higher education and nonminority race. While the majority of respondents reported that they believed following CDC recommendations would decrease the spread of COVID-19 in their community and intended to adhere to them, only 65.2% rated social isolation with the highest level of belief and adherence. The most trusted information source was federal public health websites (42.8%). Qualitative responses aligned with quantitative data and described concerns about illness, epidemiologic issues, economic and societal disruptions, and distrust of the executive branch's messaging. The survey was limited by a lack of minority representation, potential selection bias, and evolving COVID-19 information that may impact generalizability and interpretability. CONCLUSIONS: Knowledge about COVID-19 and intended adherence to behavioral recommendations were high. There was substantial distrust of the executive branch of the federal government, however, and concern about mixed messaging and information overload. These findings highlight the importance of consistent messaging from trusted sources that reaches diverse groups.

Norovirus Infections Drop 49% in the United States with Strict COVID-19 Public Health Interventions.

Norovirus is a substantial burden on the U.S. We compared norovirus outbreaks before and during COVID-19. There were fewer norovirus outbreaks during COVID-19 compared to a similar time period in 2019 (326 versus 638, P<0.001). CONCLUSION: COVID-19 public health interventions may be considered to decrease the burden of norovirus. This demonstrates the ability of more restrictive interventions to decrease other outbreaks of known or emerging viruses.

Development and Validation of the COVID-NoLab and COVID-SimpleLab Risk Scores for Prognosis in 6 US Health Systems.

PURPOSE: Develop and validate simple risk scores based on initial clinical data and no or minimal laboratory testing to predict mortality in hospitalized adults with COVID-19. METHODS: We gathered clinical and initial laboratory variables on consecutive inpatients with COVID-19 who had either died or been discharged alive at 6 US health centers. Logistic regression was used to develop a predictive model using no laboratory values (COVID-NoLab) and one adding tests available in many outpatient settings (COVID-SimpleLab). The models were converted to point scores and their accuracy evaluated in an internal validation group. RESULTS: We identified 1340 adult inpatients with complete data for nonlaboratory parameters and 741 with complete data for white blood cell (WBC) count, differential, c-reactive protein (CRP), and serum creatinine. The COVID-NoLab risk score includes age, respiratory rate, and oxygen saturation and identified risk groups with 0.8%, 11.4%, and 40.4% mortality in the validation group (AUROCC = 0.803). The COVID-SimpleLab score includes age, respiratory rate, oxygen saturation, WBC, CRP, serum creatinine, and comorbid asthma and identified risk groups with 1.0%, 9.1%, and 29.3% mortality in the validation group (AUROCC = 0.833). CONCLUSIONS: Because they use simple, readily available predictors, developed risk scores have potential applicability in the outpatient setting but require prospective validation before use.

Characteristics and Outcomes Among Hospitalized COVID-19-Positive Patients in a Nonurban Environment.

INTRODUCTION: Virtually all hospitalized coronavirus disease-2019 (COVID-19) outcome data come from urban environments. The extent to which these findings are generalizable to other settings is unknown. Coronavirus disease-2019 data from large, urban settings may be particularly difficult to apply in military medicine, where practice environments are often semi-urban, rural, or austere. The purpose of this study is compare presenting characteristics and outcomes of U.S. patients with COVID-19 in a nonurban setting to similar patients in an urban setting. MATERIALS AND METHODS: This is a retrospective case series of adults with laboratory-confirmed COVID-19 infection who were admitted to Hershey Medical Center (HMC), a 548-bed tertiary academic medical center in central Pennsylvania serving semi-urban and rural populations, from March 23, 2020, to April 20, 2020 (the first month of COVID-19 admissions at HMC). Patients and outcomes of this cohort were compared to published data on a cohort of similar patients from the New York City (NYC) area. RESULTS: The cohorts had similar age, gender, comorbidities, need for intensive care or mechanical ventilation, and most vital sign and laboratory studies. The NYC's cohort had shorter hospital stays (4.1 versus 7.2 days, P < .001) but more African American patients (23% versus 12%, P = .02) and higher prevalence of abnormal alanine (>60U/L; 39.0% versus 5.9%, P < .001) and aspartate (>40U/L; 58.4% versus 42.4%, P = .012) aminotransferase, oxygen saturation <90% (20.4% versus 7.2%, P = .004), and mortality (21% versus 1.4%, P < .001). CONCLUSIONS: Hospitalists in nonurban environments would be prudent to use caution when considering the generalizability of results from dissimilar regions. Further investigation is needed to explore the possibility of reproducible causative systemic elements that may help improve COVID-19-related outcomes. Broader reports of these relationships across many settings will offer military medical planners greater ability to consider outcomes most relevant to their unique settings when considering COVID-19 planning.

Public Intent to Comply with COVID-19 Public Health Recommendations.

Stay-at-home orders have been an essential component of coronavirus 2019 (COVID-19) management in the United States. As states start lifting these mandates to reopen the economy, voluntary public compliance with public health recommendations may significantly influence the extent of resurgence in COVID-19 infection rates. Population-level risk from reopening may therefore be predicted from public intent to comply with public health recommendations. We are conducting a global, convergent design mixed-methods survey on public knowledge, perceptions, preferred health information sources, and understanding of and intent to comply with public health recommendations. With over 9,000 completed surveys from every US state and over 70 countries worldwide, to our knowledge this is the largest pandemic messaging study to date. Although the study is still ongoing, we have conducted an analysis of 5,005 US surveys completed from April 9-15, 2020 on public intent to comply with public health recommendations and offer insights on the COVID-19 pandemic-related risk of reopening. We found marked regional differences in intent to follow key public health recommendations. Regional efforts are urgently needed to influence public behavior changes to decrease the risk of reopening, particularly in higher-risk areas with low public intent to comply with preventive health recommendations. [HLRP: Health Literacy Research and Practice. 2020;4(3):e160-e165.].