Tag: statistics

JMIR Mhealth Uhealth. 2023 Mar 7;11:e38506. doi: 10.2196/38506.

ABSTRACT

BACKGROUND: Chronic hand and foot eczema is a polyetiological dermatological condition. Patients experience pain, itching, and sleep disturbances and have a reduced quality of life. Skin care programs and patient education can improve the clinical outcome. eHealth devices offer a new opportunity to better inform and monitor patients.

OBJECTIVE: This study aimed to systematically analyze the effect of a monitoring smartphone app combined with patient education on the quality of life and clinical outcome of patients with hand and foot eczema.

METHODS: Patients in the intervention group received an educational program; attended study visits on weeks 0, 12, and 24; and had access to the study app. Patients in the control group attended the study visits only. The primary end point was a statistically significant reduction in Dermatology Life Quality Index, pruritus, and pain at weeks 12 and 24. The secondary end point was a statistically significant reduction in the modified Hand Eczema Severity Index (HECSI) score at weeks 12 and 24. This is an interim analysis at week 24 of the 60-week randomized controlled study.

RESULTS: In total, 87 patients were included in the study and randomized to the intervention group (n=43, 49%) or control group (n=44, 51%). Of the 87 patients, 59 (68%) completed the study visit at week 24. There were no significant differences between the intervention and control groups regarding quality of life, pain, itch, activity, and clinical outcome at weeks 12 and 24. Subgroup analysis revealed that, compared with the control group, the intervention group with an app use frequency of fewer than once every 5 weeks had a significant improvement in the Dermatology Life Quality Index at weeks 12 (P=.001) and 24 (P=.05), in pain measured on a numeric rating scale at weeks 12 (P=.02) and 24 (P=.02), and in the HECSI score at week 12 (P=.02). In addition, the HECSI scores assessed on the basis of pictures taken by the patients of their hands and feet correlated strongly with the HECSI scores recorded by physicians during regular personal visits (r=0.898; P=.002) even when the quality of the images was not that good.

CONCLUSIONS: An educational program combined with a monitoring app that connects patients with their treating dermatologists can improve quality of life if the app is not used too frequently. In addition, telemedical care can at least partially replace personal care in patients with hand and foot eczema because the analysis of the pictures taken by the patients correlates strongly with that of the in vivo images. A monitoring app such as the one presented in this study has the potential to improve patient care and should be implemented in daily practice.

TRIAL REGISTRATION: Deutsches Register Klinischer Studien DRKS00020963; https://drks.de/search/de/trial/DRKS00020963.

PMID:36881465 | DOI:10.2196/38506

Int J Radiat Biol. 2023 Mar 7:1-12. doi: 10.1080/09553002.2023.2181998. Online ahead of print.

ABSTRACT

BACKGROUND: Exposure to different forms of ionizing radiation occurs in diverse occupational, medical, and environmental settings. Improving the accuracy of the estimated health risks associated with exposure is therefore, essential for protecting the public, particularly as it relates to chronic low dose exposures. A key aspect to understanding health risks is precise and accurate modeling of the dose-response relationship. Toward this vision, benchmark dose (BMD) modeling may be a suitable approach for consideration in the radiation field. BMD modeling is already extensively used for chemical hazard assessments and is considered statistically preferable to identifying low and no observed adverse effects levels. BMD modeling involves fitting mathematical models to dose-response data for a relevant biological endpoint and identifying a point of departure (the BMD, or its lower bound). Recent examples in chemical toxicology show that when applied to molecular endpoints (e.g. genotoxic and transcriptional endpoints), BMDs correlate to points of departure for more apical endpoints such as phenotypic changes (e.g. adverse effects) of interest to regulatory decisions. This use of BMD modeling may be valuable to explore in the radiation field, specifically in combination with adverse outcome pathways, and may facilitate better interpretation of relevant in vivo and in vitro dose-response data. To advance this application, a workshop was organized on June 3rd, 2022, in Ottawa, Ontario that brought together BMD experts in chemical toxicology and the radiation scientific community of researchers, regulators, and policy-makers. The workshop’s objective was to introduce radiation scientists to BMD modeling and its practical application using case examples from the chemical toxicity field and demonstrate the BMDExpress software using a radiation dataset. Discussions focused on the BMD approach, the importance of experimental design, regulatory applications, its use in supporting the development of adverse outcome pathways, and specific radiation-relevant examples.

CONCLUSIONS: Although further deliberations are needed to advance the use of BMD modeling in the radiation field, these initial discussions and partnerships highlight some key steps to guide future undertakings related to new experimental work.

PMID:36881459 | DOI:10.1080/09553002.2023.2181998

JMIR Res Protoc. 2023 Mar 7;12:e42267. doi: 10.2196/42267.

ABSTRACT

BACKGROUND: HIV incidence estimates are published each year for all Ending the HIV Epidemic (EHE) counties, but they are not stratified by the demographic variables highly associated with risk of infection. Regularly updated estimates of HIV incident diagnoses available at local levels are required to monitor the epidemic in the United States over time and could contribute to background incidence rate estimates for alternative clinical trial designs for new HIV prevention products.

OBJECTIVE: We describe methods using existing, robust data sources within areas in the United States to reliably estimate longitudinal HIV incident diagnoses stratified by race and age categories among men who have sex with other men (MSM) eligible for pre-exposure prophylaxis (PrEP) but not taking it.

METHODS: This is a secondary analysis of existing data sources to develop new estimates of incident HIV diagnoses in MSM. We reviewed past methods used to estimate incident diagnoses and explored opportunities to improve these estimates. We will use existing surveillance data sources and population sizes of HIV PrEP-eligible MSM estimated from population-based data sources (eg, US Census data and pharmaceutical prescription databases) to develop metropolitan statistical area-level estimates of new HIV diagnoses among PrEP-eligible MSM. Required parameters are number of new diagnoses among MSM, estimates of MSM with an indication for PrEP, and prevalent PrEP use including median duration of use; these parameters will be stratified by jurisdiction and age group or race or ethnicity. Preliminary outputs will be available in 2023, and updated estimates will be produced annually thereafter.

RESULTS: Data to parameterize new HIV diagnoses among PrEP-eligible MSM are available with varying levels of public availability and timeliness. In early 2023, the most recent available data on new HIV diagnoses were from the 2020 HIV surveillance report, which reports 30,689 new HIV infections in 2020, and 24,724 of them occurred in an MSA with a population of ≥500,000. Updated estimates for PrEP coverage based on commercial pharmacy claims data through February 2023 will be generated. The rate of new HIV diagnoses among MSM can be estimated from new diagnoses within each demographic group (numerator) and the total person-time at risk of diagnosis for each group (denominator) by metropolitan statistical area and year. To estimate time at risk, the person-time of individuals on PrEP or person-time after incident HIV infection but before diagnosis should be removed from stratified population size estimates of the total number of person-years with indications for PrEP.

CONCLUSIONS: Reliable, serial, cross-sectional estimates for rates of new HIV diagnoses for MSM with PrEP indications can serve as benchmark community estimates of failures of HIV prevention and opportunities to improve services and will support public health epidemic monitoring and alternative clinical trial designs.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/42267.

PMID:36881450 | DOI:10.2196/42267

JMIR Form Res. 2023 Mar 7;7:e43296. doi: 10.2196/43296.

ABSTRACT

BACKGROUND: The experience sampling methodology (ESM) has long been considered as the gold standard for gathering data in everyday life. In contrast, current smartphone technology enables us to acquire data that are much richer, more continuous, and unobtrusive than is possible via ESM. Although data obtained from smartphones, known as mobile sensing, can provide useful information, its stand-alone usefulness is limited when not combined with other sources of information such as data from ESM studies. Currently, there are few mobile apps available that allow researchers to combine the simultaneous collection of ESM and mobile sensing data. Furthermore, such apps focus mostly on passive data collection with only limited functionality for ESM data collection.

OBJECTIVE: In this paper, we presented and evaluated the performance of m-Path Sense, a novel, full-fledged, and secure ESM platform with background mobile sensing capabilities.

METHODS: To create an app with both ESM and mobile sensing capabilities, we combined m-Path, a versatile and user-friendly platform for ESM, with the Copenhagen Research Platform Mobile Sensing framework, a reactive cross-platform framework for digital phenotyping. We also developed an R package, named mpathsenser, which extracts raw data to an SQLite database and allows the user to link and inspect data from both sources. We conducted a 3-week pilot study in which we delivered ESM questionnaires while collecting mobile sensing data to evaluate the app’s sampling reliability and perceived user experience. As m-Path is already widely used, the ease of use of the ESM system was not investigated.

RESULTS: Data from m-Path Sense were submitted by 104 participants, totaling 69.51 GB (430.43 GB after decompression) or approximately 37.50 files or 31.10 MB per participant per day. After binning accelerometer and gyroscope data to 1 value per second using summary statistics, the entire SQLite database contained 84,299,462 observations and was 18.30 GB in size. The reliability of sampling frequency in the pilot study was satisfactory for most sensors, based on the absolute number of collected observations. However, the relative coverage rate-the ratio between the actual and expected number of measurements-was below its target value. This could mostly be ascribed to gaps in the data caused by the operating system pushing away apps running in the background, which is a well-known issue in mobile sensing. Finally, some participants reported mild battery drain, which was not considered problematic for the assessed participants’ perceived user experience.

CONCLUSIONS: To better study behavior in everyday life, we developed m-Path Sense, a fusion of both m-Path for ESM and Copenhagen Research Platform Mobile Sensing. Although reliable passive data collection with mobile phones remains challenging, it is a promising approach toward digital phenotyping when combined with ESM.

PMID:36881444 | DOI:10.2196/43296

Psychol Health Med. 2023 Mar 7:1-14. doi: 10.1080/13548506.2023.2185643. Online ahead of print.

ABSTRACT

Engagement in recreation can positively impact the physical and mental health of those experiencing mental health challenges; however, the impact of engaging in other aspects of such recreation, such as volunteering, remain largely unexplored in this population. Volunteering is known to have a wealth of health and wellbeing benefits among the general population; therefore, the impact of recreational-based volunteering for those with mental health conditions deserves to be explored. The current study sought to examine the health, social and wellbeing impacts of parkrun engagement among runners and volunteers living with a mental health condition. Participants with a mental health condition (N = 1661, M(SD)_age = 43.4 (12.8) years, 66% female) completed self-reported questionnaires. A MANOVA was conducted to examine the differences in health and wellbeing impacts between those who run/walk vs. those who run/walk and volunteer, while chi-square analyses examined variables of perceived social inclusion. Findings suggest that there was a statistically significant multivariate effect of participation type on perceived parkrun impact (F (10, 1470) = 7.13; p < 0.001; Wilk’s Λ = 0.954, partial η² = 0.046). It was also found that for those who run/walk and volunteer, compared to those who only run/walk, parkrun made them more feel part of a community (56% v 29% respectively, X²(1) = 116.70, p < 0.001) and facilitated them meeting new people (60% v 24% respectively, X² (1) = 206.67, p < 0.001). These results suggest that the health, wellbeing, and social inclusion benefits of parkrun participation are different for those who run and volunteer, compared to those who only run. These findings may have public health implications and clinical implications for mental health treatment, as they convey that it is not simply the physical engagement in recreation that may play a role in one’s recovery, but also the volunteer aspect.

PMID:36881438 | DOI:10.1080/13548506.2023.2185643

JAMA Netw Open. 2023 Mar 1;6(3):e231860. doi: 10.1001/jamanetworkopen.2023.1860.

ABSTRACT

IMPORTANCE: Perceived stress can have long-term physiological and psychological consequences and has shown to be a modifiable risk factor for Alzheimer disease and related dementias.

OBJECTIVE: To investigate the association between perceived stress and cognitive impairment in a large cohort study of Black and White participants aged 45 years or older.

DESIGN, SETTING, AND PARTICIPANTS: The Reasons for Geographic and Racial Differences in Stroke (REGARDS) study is a national population-based cohort of 30 239 Black and White participants aged 45 years or older, sampled from the US population. Participants were recruited from 2003 to 2007, with ongoing annual follow-up. Data were collected by telephone, self-administered questionnaires, and an in-home examination. Statistical analysis was performed from May 2021 to March 2022.

EXPOSURES: Perceived stress was measured using the 4-item version of the Cohen Perceived Stress Scale. It was assessed at the baseline visit and during 1 follow-up visit.

MAIN OUTCOMES AND MEASURES: Cognitive function was assessed with the Six-Item Screener (SIS); participants with a score below 5 were considered to have cognitive impairment. Incident cognitive impairment was defined as a shift from intact cognition (SIS score >4) at the first assessment to impaired cognition (SIS score ≤4) at the latest available assessment.

RESULTS: The final analytical sample included 24 448 participants (14 646 women [59.9%]; median age, 64 years [range, 45-98 years]; 10 177 Black participants [41.6%] and 14 271 White participants [58.4%]). A total of 5589 participants (22.9%) reported elevated levels of stress. Elevated levels of perceived stress (dichotomized as low stress vs elevated stress) were associated with 1.37 times higher odds of poor cognition after adjustment for sociodemographic variables, cardiovascular risk factors, and depression (adjusted odds ratio [AOR], 1.37; 95% CI, 1.22-1.53). The association of the change in the Perceived Stress Scale score with incident cognitive impairment was significant in both the unadjusted model (OR, 1.62; 95% CI, 1.46-1.80) and after adjustment for sociodemographic variables, cardiovascular risk factors, and depression (AOR, 1.39; 95% CI, 1.22-1.58). There was no interaction with age, race, and sex.

CONCLUSIONS AND RELEVANCE: This study suggests that there is an independent association between perceived stress and both prevalent and incident cognitive impairment. The findings suggest the need for regular screening and targeted interventions for stress among older adults.

PMID:36881411 | DOI:10.1001/jamanetworkopen.2023.1860

JAMA Netw Open. 2023 Mar 1;6(3):e231864. doi: 10.1001/jamanetworkopen.2023.1864.

ABSTRACT

IMPORTANCE: Telemedicine can increase access to care, but uptake has been low among people living in rural areas. The Veterans Health Administration initially encouraged telemedicine uptake in rural areas, but telemedicine expansion efforts have broadened since the COVID-19 pandemic.

OBJECTIVE: To examine changes over time in rural-urban differences in telemedicine use for primary care and for mental health integration services among Veterans Affairs (VA) beneficiaries.

DESIGN, SETTING, AND PARTICIPANTS: This cohort study examined 63.5 million primary care and 3.6 million mental health integration visits across 138 VA health care systems nationally from March 16, 2019, to December 15, 2021. Statistical analysis took place from December 2021 to January 2023.

EXPOSURES: Health care systems with most clinic locations designated as rural.

MAIN OUTCOMES AND MEASURES: For every system, monthly visit counts for primary care and mental health integration specialties were aggregated from 12 months before to 21 months after pandemic onset. Visits were categorized as in person or telemedicine, including video. A difference-in-difference approach was used to examine associations in visit modality by health care system rurality and pandemic onset. Regression models also adjusted for health care system size as well as relevant patient characteristics (eg, demographic characteristics, comorbidities, broadband internet access, and tablet access).

RESULTS: The study included 63 541 577 primary care visits (6 313 349 unique patients) and 3 621 653 mental health integration visits (972 578 unique patients) (6 329 124 unique patients among the cohort; mean [SD] age, 61.4 [17.1] years; 5 730 747 men [90.5%]; 1 091 241 non-Hispanic Black patients [17.2%]; and 4 198 777 non-Hispanic White patients [66.3%]). In fully adjusted models for primary care services before the pandemic, rural VA health care systems had higher proportions of telemedicine use than urban ones (34% [95% CI, 30%-38%] vs 29% [95% CI, 27%-32%]) but lower proportions of telemedicine use than urban health care systems after pandemic onset (55% [95% CI, 50%-59%] vs 60% [95% CI, 58%-62%]), signifying a 36% reduction in the odds of telemedicine use (odds ratio [OR], 0.64; 95% CI, 0.54-0.76). The rural-urban telemedicine gap was even larger for mental health integration (OR, 0.49; 95% CI, 0.35-0.67) than for primary care services. Few video visits occurred across rural and urban health care systems (unadjusted percentages: before the pandemic, 2% vs 1%; after the pandemic, 4% vs 8%). Nonetheless, there were rural-urban divides for video visits in both primary care (OR, 0.28; 95% CI, 0.19-0.40) and mental health integration services (OR, 0.34; 95% CI, 0.21-0.56).

CONCLUSIONS AND RELEVANCE: This study suggests that, despite initial telemedicine gains at rural VA health care sites, the pandemic was associated with an increase in the rural-urban telemedicine divide across the VA health care system. To ensure equitable access to care, the VA health care system’s coordinated telemedicine response may benefit from addressing rural disparities in structural capacity (eg, internet bandwidth) and from tailoring technology to encourage adoption among rural users.

PMID:36881410 | DOI:10.1001/jamanetworkopen.2023.1864

JACC Heart Fail. 2023 Jan 12:S2213-1779(22)00721-1. doi: 10.1016/j.jchf.2022.11.026. Online ahead of print.

ABSTRACT

BACKGROUND: Initiation and up-titration of guideline-directed medical therapies (GDMTs) for heart failure with reduced ejection fraction (HFrEF) remains suboptimal, in part because of concerns regarding tolerability and adverse events (AEs).

OBJECTIVES: The authors sought to compare rates of AE in patients randomized to GDMT medication vs placebo in a meta-analysis of landmark cardiovascular outcomes trials.

METHODS: The authors assessed rates of reported AE in 17 landmark HFrEF clinical trials across each class of GDMT in the placebo and intervention arms. The overall rates of AE for each drug class, the absolute difference in frequency in AEs between the placebo and intervention arms, and the odds of each AE according based on randomization strata were calculated.

RESULTS: AE were reported commonly in trials across each class of GDMT, with 75% to 85% of participants reporting at least 1 AE. There was no significant difference in the frequency of AE between the intervention and placebo arms, except for angiotensin-converting enzyme inhibitors (87.0% [95% CI: 85.0%-88.8%] vs 82.0% [95% CI: 79.8%-84.0%], absolute difference: +5% with intervention; P < 0.001). There was no significant difference in drug discontinuation because of AE between placebo and intervention arms in angiotensin-converting enzyme inhibitors, mineralocorticoid receptor antagonists, sodium glucose cotransporter 2 inhibitors, or angiotensin receptor neprilysin inhibitor/angiotensin II receptor blocker trials. Patients randomized to beta-blocker were significantly less likely to stop study drug because of AE than placebo (11.3% [95% CI: 10.3%-12.3%] vs 13.7% [95% CI: 12.5%-14.9%], absolute difference: -1.1%; P = 0.015). When individual types of AE were assessed, the initiation of an intervention vs placebo resulted in small differences in absolute frequency of AE that were largely not statistically significant.

CONCLUSIONS: In clinical trials of GDMT for HFrEF, AEs are observed frequently. However, rates of AE are similar between active medication and control, suggesting these may reflect the high risk nature of the heart failure disease state rather than be attributive to a specific therapy.

PMID:36881395 | DOI:10.1016/j.jchf.2022.11.026

Mol Biol Rep. 2023 Mar 7. doi: 10.1007/s11033-023-08324-5. Online ahead of print.

ABSTRACT

BACKGROUND: Rice is a key food grain contributor to the global food grain basket and is considered the main food crop in India with a large number of varieties released every year. SSR markers have proven to be an excellent tool for studying genetic diversity. As a result, the present study was done to characterize and assess genetic diversity as well as population structural aspects.

METHODS AND RESULTS: Fifty genotypes of rice were characterized using 40 SSR markers to assess the genetic diversity and genetic relationship. A total of 114 alleles were amplified with an average of 2.85 alleles per locus. The Polymorphism Information Content (PIC) values varied from 0.30 (RM162) to 0.58 (RM413) with an average of 0.44. Gene diversity was in the range of 0.35 (RM162) to 0.66 (RM413), with an average value of 0.52, while heterozygosity ranged from 0.18 (RM27) to 0.74 (RM55), with an average of 0.39. The population structure revealed a narrow genetic base with only three major subpopulations. Analysis of molecular variance revealed that 74% of the variation was attributed within individuals, 23% was among individuals, and 3% was among populations. Pairwise Fst value of population A & B is 0.024, population B & C is 0.120 and population A & C is 0.115. Dendrogram grouped the genotypes into three clusters with wide variation among the accessions.

CONCLUSION: Genotyping combined with phylogeny and population structure analysis proved to be a powerful method for characterizing germplasm in this study. There is significant gene flow within populations, as well as the presence of different combinations of alleles, and that allelic exchange rates within the populations are higher than among the populations. Assessing the genetic diversity among individual genotypes within populations is quite useful in selecting candidate parents for future breeding programs to improve the target traits in rice for the Himalayan region.

PMID:36881341 | DOI:10.1007/s11033-023-08324-5

Sci China Life Sci. 2023 Mar 3. doi: 10.1007/s11427-022-2280-3. Online ahead of print.

ABSTRACT

The utility of the polygenic risk score (PRS) to identify individuals at higher risk of stroke beyond clinical risk remains unclear, and we clarified this using Chinese population-based prospective cohorts. Cox proportional hazards models were used to estimate the 10-year risk, and Fine and Gray’s models were used for hazard ratios (HRs), their 95% confidence intervals (CIs), and the lifetime risk according to PRS and clinical risk categories. A total of 41,006 individuals aged 30-75 years with a mean follow-up of 9.0 years were included. Comparing the top versus bottom 5% of the PRS, the HR was 3.01 (95%CI 2.03-4.45) in the total population, and similar findings were observed within clinical risk strata. Marked gradients in the 10-year and lifetime risk across PRS categories were also found within clinical risk categories. Notably, among individuals with intermediate clinical risk, the 10-year risk for those in the top 5% of the PRS (7.3%, 95%CI 7.1%-7.5%) reached the threshold of high clinical risk (⩾7.0%) for initiating preventive treatment, and this effect of the PRS on refining risk stratification was evident for ischemic stroke. Even among those in the top 10% and 20% of the PRS, the 10-year risk would also exceed this level when aged ⩾50 and ⩾60 years, respectively. Overall, the combination of the PRS with the clinical risk score improved the risk stratification within clinical risk strata and distinguished actual high-risk individuals with intermediate clinical risk.

PMID:36881318 | DOI:10.1007/s11427-022-2280-3