Patient preference for virtual versus in-person visits in neuromuscular clinical practice.

INTRODUCTION/AIMS: It is unknown if patients with neuromuscular diseases prefer in-person or virtual telemedicine visits. We studied patient opinions and preference on virtual versus in-person visits, and the factors influencing such preferences. METHODS: Telephone surveys, consisting of 11 questions, of patients from 10 neuromuscular centers were completed. RESULTS: Five hundred and twenty surveys were completed. Twenty-six percent of respondents preferred virtual visits, while 50% preferred in-person visits. Sixty-four percent reported physical interaction as "very important." For receiving a new diagnosis, 55% preferred in-person vs 35% reporting no preference. Forty percent were concerned about a lack of physical examination vs 20% who were concerned about evaluating vital signs. Eighty four percent reported virtual visits were sufficiently private. Sixty eight percent did not consider expenses a factor in their preference. Although 92% were comfortable with virtual communication technology, 55% preferred video communications, and 19% preferred phone calls. Visit preference was not significantly associated with gender, diagnosis, disease severity, or symptom management. Patients who were concerned about a lack of physical exam or assessment of vitals had significantly higher odds of selecting in-person visits than no preference. DISCUSSION: Although neither technology, privacy, nor finance burdened patients in our study, more patients preferred in-person visits than virtual visits and 40% were concerned about a lack of physical examination. Interactions that occur with in-person encounters had high importance for patients, reflecting differences in the perception of the patient-physician relationship between virtual and in-person visits.

The timing of geographic power.

In many studies on the spatial risk of disease, investigators use geographic locations at the time of disease diagnosis in spatial models to search for individual areas of elevated risk. However, these studies often fail to find a significant spatial signal. This may be due to the misspecification of the timing and location of pertinent exposures. Environmental exposures related to cancer risk vary over space and time, and many cancers have long latencies. When these factors are considered in conjunction with a mobile population, it is likely that the spatial signal related to relevant historic environmental exposures is obscured. To investigate this hypothesis, we conducted simulation studies to characterize the effect of residential mobility on the ability of generalized additive models to detect areas of significantly elevated historic environmental exposure. We generated data based on the residential histories of participants in the National Cancer Institute Surveillance, Epidemiology, and End Results non-Hodgkin lymphoma study, and varied the duration and intensity of the environmental exposure. Results showed that the probability of detection, mean spatial sensitivity, and mean spatial specificity of models decreased steadily as the time since relevant exposure increased. This suggests that for diseases with long latencies, spatial areas of high risk due to high-intensity exposure of relatively short duration will be difficult to detect over time when using residential locations at the time of diagnosis in mobile study populations.

The impact of population mobility on estimates of environmental exposure effects in a case-control study.

In many studies of environmental risk factors for disease, researchers use the location at diagnosis as a geographic reference for environmental exposures. However, many environmental pollutants change continuously over space and time. The dynamic characteristics of these pollutants coupled with population mobility in the United States suggest that for diseases with long latencies like cancer, historic exposures may be more relevant than exposure at the time of diagnosis. In this article, we evaluated to what extent the commonly used assumption of no population mobility results in increased bias in the estimates of the relationship between environmental exposures and long-latency health outcomes disease in a case-control study. We conducted a simulation study using the residential histories of a random sample from the National Institutes of Health-AARP (formerly American Association of Retired Persons) Diet and Health Study. We simulated case-control status based on subject exposure and true exposure effects that varied temporally. We compared estimates from models using only subject location at diagnosis to estimates where subjects were assumed to be mobile. Ignoring population mobility resulted in underestimates of subject exposure, with largest deviations observed at time points further away from study enrollment. In general, the effect of population mobility on the bias of the estimates of the relationship between the exposure and the outcome was more prominent with exposures that showed substantial spatial and temporal variability. Based on our results, we recommend using residential histories when environmental exposures and disease latencies span a long enough time period that mobility is important.

Prenatal Depression Severity and Postpartum Care Utilization in a Medicaid Population.

Background: Postpartum visits are a necessary continuum of medical care for women who are diagnosed with depression during pregnancy. However, postpartum care utilization is typically lower in populations who face adverse events and it is unclear to what extent having depression during pregnancy may compromise postpartum visit follow-up. Our study examined the association between severity of prenatal depression and postpartum care utilization among women on Medicaid. Materials and Methods: Data from a university-based, nonprofit managed care organization (2008-2012) were analyzed (N = 846). Prenatal depression severity and postpartum care utilization were determined using the International Classification of Diseases, Ninth Revision (ICD-9) codes, from medical claims records. Bivariate and multivariable logistic regression was conducted. Odds ratios and 95% confidence intervals (CIs) were calculated. Results: The majority (64.2%) of women received a mild/moderate prenatal depression diagnosis and 52.5% of the total sample attended their postpartum care visit. After adjusting for confounders, we found decreased odds of postpartum care utilization among women with less severe diagnoses. Women with a mild/moderate prenatal depression diagnosis were 12% less likely to attend the postpartum care visit compared with women with a severe prenatal depression diagnosis (adjusted odds ratio = 0.88, 95% CI = 0.65-1.19). However, this finding was not statistically significant. Conclusions: Our study did not yield evidence of a statistically significant relationship between prenatal depression severity and postpartum visit attendance among a sample of Medicaid beneficiaries. Additional research is needed to assess the association between prenatal depression severity and postpartum care use to enhance continuity of services for Medicaid-insured women into the postpartum period.

Cross-sectional analysis to explore the awareness, attitudes and actions of UK adults at high risk of severe illness from COVID-19.

OBJECTIVES: This study explored the impact of COVID-19 on people identified as at high risk of severe illness by UK government, and in particular, the impact of lockdown on access to healthcare, medications and use of technological platforms. DESIGN: Online survey methodology. SETTING: UK. PARTICIPANTS: 1038 UK adults were recruited who were either identified by UK government as at high risk of severe illness from COVID-19 or self-identified as at high risk with acute or other chronic health conditions not included in the UK government list. Participants were recruited through social media advertisements, health charities and patient organisations. MAIN OUTCOMES MEASURES: The awareness, attitudes and actions survey which explores the impact of COVID-19, on including access to healthcare, use of technology for health condition management, mental health, depression, well-being and lifestyle behaviours. RESULTS: Nearly half of the sample (44.5%) reported that their mental health had worsened during the COVID-19 lockdown. Management of health conditions changed including access to medications (28.5%) and delayed surgery (11.9%), with nearly half of the sample using telephone care (45.5%). Artificial Intelligence identified that participants in the negative cluster had higher neuroticism, insecurity and negative sentiment. Participants in this cluster reported more negative impacts on lifestyle behaviours, higher depression and lower well-being, alongside lower satisfaction with platforms to deliver healthcare. CONCLUSIONS: This study provides novel evidence of the impact of COVID-19 on people identified as at high risk of severe illness. These findings should be considered by policy-makers and healthcare professionals to avoid unintended consequences of continued restrictions and future pandemic responses.

Evaluation of Intravenous Vancomycin Pharmacokinetic Parameters in Patients With Acute Brain Injury.

BACKGROUND: Vancomycin is a glycopeptide antibiotic that is primarily cleared by renal elimination. Patients with acute brain injury often exhibit augmented renal clearance which has been associated with subtherapeutic vancomycin concentrations. OBJECTIVE: To determine whether population pharmacokinetics accurately predict vancomycin empiric dose frequency in patients with acute brain injury. METHODS: This was a single-center, retrospective cohort study conducted following institutional review board approval at Virginia Commonwealth University Health System. Data were collected from patients 18 years of age or older admitted with acute brain injury. The primary outcome was the difference in the elimination rate constant of vancomycin between population predicted pharmacokinetics and patient-specific pharmacokinetics. RESULTS: A total of 158 patients were included in the analysis. A test of the paired differences between the mean population predicted and patient-specific elimination rate constants showed that the mean population predicted elimination rate constant was larger by 0.0211 h-1 (95% confidence interval [CI]: -0.028 to -0.015). The difference between the mean population predicted and patient-specific half-lives showed that the mean population predicted half-life was shorter by 1.01 hours (95% CI: 0.7-1.3). Vancomycin was administered at a mean initial dose of 15.4 mg/kg (standard deviation [SD] = 2.2), with an average frequency of 12 hours (SD = 1.1). The average trough concentration at steady state was 9.9 µg/mL (SD = 4.9). CONCLUSIONS: The small clinical difference in population and patient-specific elimination rate constants demonstrates that population pharmacokinetics may be an accurate empiric dosing strategy for determining vancomycin dose frequency in patients with acute brain injury.

Prepregnancy Depression and Breastfeeding Duration: A Look at Maternal Age.

BACKGROUND: In the United States, major depressive disorder affects one in five women aged 20-40 years. During these childbearing years, depression can negatively impact maternal behaviors that are crucial for infant growth and development. This study examined the relationship between prepregnancy depression and breastfeeding duration by maternal age. METHODS: Data from Phase 7 (2012-2013) of the Pregnancy Risk Assessment Monitoring System (N=62,483) were analyzed. Prepregnancy depression was dichotomized while breastfeeding duration was categorized as never breastfed, breastfed 8 weeks or less, and breastfed more than 8 weeks. Maternal age was a significant effect modifier; therefore, results were stratified by maternal age. Multinomial logistic regression was used to obtain odds ratios and 95% confidence intervals (CI). RESULTS: For women aged 20-24, 25-29, and 30-34 years with prepregnancy depression, the odds of never breastfeeding and breastfeeding 8 weeks or less were significantly higher than in women with no history of prepregnancy depression. Notably, among women aged 25-29 with prepregnancy depression, the odds of never breastfeeding and breastfeeding 8 weeks or less were 93% (adjusted odds ratio (AOR) = 1.93, 95% CI =1.57-2.37) and 65% (AOR = 1.65, 95% CI = 1.37-1.99) higher compared to women with no history of prepregnancy depression, respectively. CONCLUSIONS: Having a history of poor mental health before pregnancy may increase the likelihood of premature breastfeeding cessation. A woman's mental health status before pregnancy should be considered in reproductive and prenatal care models. Efforts should be made to understand challenges women of specific age groups face when trying to breastfeed.