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Nevin Manimala Statistics

Adapting spatiotemporal gait symmetry to functional electrical stimulation during treadmill walking

PLoS One. 2024 Oct 18;19(10):e0312285. doi: 10.1371/journal.pone.0312285. eCollection 2024.

ABSTRACT

Individuals with neurological impairments often exhibit asymmetrical gait patterns. This study explored the potential of using functional electrical stimulation (FES) as a perturbation method during treadmill walking to promote gait symmetry adaptation by investigating whether the FES perturbation could induce gait adaptation concerning spatial and temporal gait symmetry in healthy subjects. In the FES perturbation, both legs received electrical pulses at the same period as the subjects’ initial stride duration, and the temporal gap between the two pulses for each leg was manipulated over a 7-min period. Following this, subjects continued to walk for another 5 minutes without FES. Subjects participated in two trials: implicit and explicit. In the implicit trial, they walked comfortably during FES perturbation without consciously adjusting their gait. In the explicit trial, they voluntarily synchronized their toe-off phase to the stimulation timing. To examine the effects of the FES perturbation, we measured step length and stance time and then analyzed changes in step length and stance time symmetries alongside their subsequent aftereffects. During the explicit trial, subjects adapted their gait patterns to the electrical pulses, resulting in a directional change in stance time (temporal) symmetry, with the left stance becoming shorter than the right. The stance time asymmetry induced by FES perturbation showed a slight residual effect. In the implicit trial, the directional change trend was slightly observed but not statistically significant. No consistent trend in step length (spatial) symmetry changes was observed in either condition, indicating that subjects may adapt their spatial gait patterns independently of their temporal patterns. Our findings suggest that the applied FES perturbation strategy under explicit condition can induce adaptations in subjects’ temporal gait asymmetry, particularly in stance. The implicit condition showed a similar slight trend but was not statistically significant. Further experiments would provide deeper understanding into the mechanism behind subjects’ response to FES perturbations, as well as the long-term effects of these perturbations on the spatial and temporal aspects of gait symmetry.

PMID:39423203 | DOI:10.1371/journal.pone.0312285

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Nevin Manimala Statistics

Understanding the interactions that children and young people have with their natural and built environments: A survey to identify targets for active travel behaviour change in Wales

PLoS One. 2024 Oct 18;19(10):e0311498. doi: 10.1371/journal.pone.0311498. eCollection 2024.

ABSTRACT

Active travel offers many societal benefits, including improving people’s mental and physical health and minimising our impacts on the environment. Increasing active travel is particularly important amongst children and young people (CYP), who are building habits which they will carry into adulthood. Studies on active travel amongst CYP are limited, however, with most research focusing on adult participants or on adult perceptions of children. This study sought to understand CYP’s interactions with the built and natural environment-and therefore their access to active travel-through the Capability, Opportunity, Motivation, Behaviour (COM-B) model. With a stakeholder group representing local government, youth organisations and active travel organisations, we co-created two bilingual questionnaires-one for young people aged 12-16 years living in Wales and the other for parents of young people aged 12-16 years living in Wales. Both questionnaires collected information on behaviour and perceived capability, opportunity and motivation of CYP to engage with their natural and built environments. The questionnaires included a discrete choice experiment (DCE), which proposed a series of binary choice questions indicating preferences based on landscape, journey time and type of travel. A total of 124 questionnaires (38 young people and 86 parents) were returned for analysis. These data indicate that CYP’s time spent outdoors is not dependent upon geography (rural/urban/suburban), season, or school holidays. There was a significant difference in capability, opportunity and motivation between parents and CYP, with parents over-estimating the psychological capability of CYP to engage outdoors. The preference data indicate that active travel is the favoured mode of transport, with both CYP and parents stating that they would increase travel time in order to travel actively. While this response is not consistent with respondent’s day-to-day travel choices, it suggests that the limitations to active travel may be psychological capability and automatic motivation, rather than a lack of opportunity.

PMID:39423197 | DOI:10.1371/journal.pone.0311498

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Nevin Manimala Statistics

Acculturation and depression increase trouble sleeping in Mexican immigrant adults

PLoS One. 2024 Oct 18;19(10):e0311288. doi: 10.1371/journal.pone.0311288. eCollection 2024.

ABSTRACT

Knowledge of Mexican immigrant sleep health is limited. We investigated the association between acculturation, depression, and having trouble sleeping among a nationally representative sample of Mexican immigrant adults. We used a logistic regression model on cross-sectional data from the 2005-2018 National Health and Nutrition Examination Survey on 2,670 non-U.S.-born Mexican adults aged ≥18 years old. Living in the U.S. for ≥10 years (Adjusted Odds Ratio (AOR) = 2.18; 95% Confidence Interval (CI) = 1.39-3.41), speaking majority English (AOR = 1.62; 95% CI = 1.00-2.64), and mild (AOR = 2.70; 95% CI = 1.82-4.02), moderate (AOR = 3.96; 95% CI = 2.53-6.19), and moderately severe/severe (AOR = 5.75; 95% CI = 3.08-10.75) depression levels were associated with having trouble sleeping. Non-U.S. citizenship status was associated with lower odds of having trouble sleeping (AOR = 0.62; 95% CI = 0.43-0.88). Greater acculturation and depression are associated with higher odds of having trouble sleeping. We provide new knowledge on how citizenship status may be linked to the sleep health of Mexican immigrant communities.

PMID:39423189 | DOI:10.1371/journal.pone.0311288

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Nevin Manimala Statistics

Correction: “Selective ensemble methods for deep learning segmentation of major vessels in invasive coronary angiography” DOI: https://doi.org/10.1002/mp.16554

Med Phys. 2024 Sep;51(9):6534. doi: 10.1002/mp.17332. Epub 2024 Jul 30.

NO ABSTRACT

PMID:39423010 | DOI:10.1002/mp.17332

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Nevin Manimala Statistics

Statistical Analysis of Telehealth Use and Pre- and Postpandemic Insurance Coverage in Selected Health Care Specialties in a Large Health Care System in Arkansas: Comparative Cross-Sectional Study

J Med Internet Res. 2024 Oct 18;26:e49190. doi: 10.2196/49190.

ABSTRACT

BACKGROUND: The COVID-19 pandemic triggered policy changes in 2020 that allowed insurance companies to reimburse telehealth services, leading to increased telehealth use, especially in rural and underserved areas. However, with many emergency rules ending in 2022, patients and health care providers face potential challenges in accessing these services.

OBJECTIVE: This study analyzed telehealth use across specialties in Arkansas before and after the pandemic (2017-2022) using data from electronic medical records from the University of Arkansas for Medical Sciences Medical Center. We explored trends in insurance coverage for telehealth visits and developed metrics to compare the performance of telehealth versus in-person visits across various specialties. The results inform insurance coverage decisions for telehealth services.

METHODS: We used pre- and postpandemic data to determine the impacts of the COVID-19 pandemic and changes in reimbursement policies on telehealth visits. We proposed a framework to calculate 3 appointment metrics: indirect waiting time, direct waiting time, and appointment length. Statistical analysis tools were used to compare the performance of telehealth and in-person visits across the following specialties: obstetrics and gynecology, psychiatry, family medicine, gerontology, internal medicine, neurology, and neurosurgery. We used data from approximately 4 million in-person visits and 300,000 telehealth visits collected from 2017 to 2022.

RESULTS: Our analysis revealed a statistically significant increase in telehealth visits across all specialties (P<.001), showing an 89% increase from 51,589 visits in 2019 to 97,461 visits in 2020, followed by a 21% increase to 117,730 visits in 2021. Around 92.57% (134,221/145,001) of telehealth patients from 2020 to 2022 were covered by Medicare, Blue Cross and Blue Shield, commercial and managed care, Medicaid, and Medicare Managed Care. In-person visits covered by Medicare and Medicaid decreased by 15%, from 313,196 in 2019 to 264,696 in 2022. During 2020 to 2022, about 22.84% (33,123/145,001) of total telehealth visits during this period were covered by Medicare and 53.58% (86,317/161,092) were in psychiatry, obstetrics and gynecology, and family medicine. We noticed a statistically significant decrease (P<.001) in the average indirect waiting time for telehealth visits, from 48.4 to 27.7 days, and a statistically significant reduction in appointment length, from 93.2 minutes in 2020 to 39.59 minutes in 2022. The indirect waiting time for psychiatry telehealth visits was almost 50% shorter than that for in-person visits. These findings highlight the potential benefits of telehealth in providing access to health care, particularly for patients needing psychiatric care.

CONCLUSIONS: Reverting to prepandemic regulations could negatively affect Arkansas, where many live in underserved areas. Our analysis shows that telehealth use remained stable beyond 2020, with psychiatry visits continuing to grow. These findings may guide insurance and policy decisions in Arkansas and other regions facing similar access challenges.

PMID:39423000 | DOI:10.2196/49190

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Nevin Manimala Statistics

Different Catch-Up Growth Patterns in Very Preterm and Small for Gestational Age Infants

Clin Pediatr (Phila). 2024 Oct 18:99228241289739. doi: 10.1177/00099228241289739. Online ahead of print.

ABSTRACT

This study aimed to describe the growth pattern in preterm infants and identify factors influencing catch-up growth. A total of 288 preterm infants were divided into groups based on the degree of prematurity, sex, and size for gestational age. Growth in head circumference, length, weight-for-length, and weight was compared between groups at corrected age of 0, 3, 6, 9, 12, 18, and 24 months. Logistic regression analysis was conducted to determine risk factors for catch-up growth. At a corrected age of 24 months, the proportions of preterm infants with z-scores less than -2 for head circumference, length, weight-for-length, and weight were less than the expected 2.3% at 0.9%, 1.7%, 2.1%, and 1.7%, respectively. The head circumference, length, weight-for-length, and weight z-scores at corrected ages of 24 months were lower in the small for gestational age (SGA) group than in the non-SGA group (P < .05). The weight-for-length z-scores were higher in the late preterm birth infants than in the very preterm birth infants at a corrected age of 24 months (P < .05). At a corrected age 24 months, the proportion of male with weight z-scores <-2 was lower than that of female (P < .05). The differences in proportion of the z-scores (head circumference, length, weight-for-length, and weight) <-2 at a corrected age of 24 months among different gestational age groups and intrauterine growth status groups were not statistically significant (P > .05). We found that the factors influencing catch-up growth in preterm infants varied at different corrected age stages, and the impact of factors during hospitalization gradually diminished as the infants grew.

PMID:39422987 | DOI:10.1177/00099228241289739

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Nevin Manimala Statistics

Can AI generate diagnostic reports for radiologist approval on CXR images? A multi-reader and multi-case observer performance study

J Xray Sci Technol. 2024 Oct 16. doi: 10.3233/XST-240051. Online ahead of print.

ABSTRACT

BACKGROUND: Accurately detecting a variety of lung abnormalities from heterogenous chest X-ray (CXR) images and writing radiology reports is often difficult and time-consuming.

OBJECTIVE: To access the utility of a novel artificial intelligence (AI) system (MOM-ClaSeg) in enhancing the accuracy and efficiency of radiologists in detecting heterogenous lung abnormalities through a multi-reader and multi-case (MRMC) observer performance study.

METHODS: Over 36,000 CXR images were retrospectively collected from 12 hospitals over 4 months and used as the experiment group and the control group. In the control group, a double reading method is used in which two radiologists interpret CXR to generate a final report, while in the experiment group, one radiologist generates the final reports based on AI-generated reports.

RESULTS: Compared with double reading, the diagnostic accuracy and sensitivity of single reading with AI increases significantly by 1.49% and 10.95%, respectively (P < 0.001), while the difference in specificity is small (0.22%) and without statistical significance (P = 0.255). Additionally, the average image reading and diagnostic time in the experimental group is reduced by 54.70% (P < 0.001).

CONCLUSION: This MRMC study demonstrates that MOM-ClaSeg can potentially serve as the first reader to generate the initial diagnostic reports, with a radiologist only reviewing and making minor modifications (if needed) to arrive at the final decision. It also shows that single reading with AI can achieve a higher diagnostic accuracy and efficiency than double reading.

PMID:39422982 | DOI:10.3233/XST-240051

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Nevin Manimala Statistics

Exploring Trends and Gaps in Osteoarthritis Biomarker Research (1999-2024): A Citation Analysis of Top 50 Cited Articles

Cartilage. 2024 Oct 18:19476035241288660. doi: 10.1177/19476035241288660. Online ahead of print.

ABSTRACT

PURPOSE: This study aimed to comprehensively analyze the landscape of osteoarthritis (OA) biomarker research through the citation analysis of top-cited articles, identifying trends and gaps in this field.

METHODS: The Web of Science Core Collection was utilized to retrieve the top 50 cited articles on OA biomarkers. Data extraction included publication characteristics, citation metrics, and biomarker categorization. Statistical analyses were conducted to discern correlations and assess significance.

RESULTS: The top 50 cited articles spanned the years 1999 to 2020, and collectively cited 4849 articles, accumulating a total of 6177 citations, resulting in an average of 123.5 citations per document. Citations per article varied between 78 and 359, with a citation density ranging from 3.9 to 23.93. Analysis of the top 50 cited articles revealed comparable impact between recent and older publications. Predominant trends included cartilage-related and blood-based biomarkers, while inflammation-related, radiomics, and multi-omics emerged as potential future research directions. In BIPEDS classification, gaps were identified in biomarkers evaluating intervention efficacy and safety.

CONCLUSION: Despite significant advancements, there is no universally acknowledged biomarker for OA. Addressing gaps in biomarker exploration is crucial for enhancing OA management strategies. This study provides insights into prevailing trends and future research directions in OA biomarkers, guiding future investigations and therapeutic development.

PMID:39422972 | DOI:10.1177/19476035241288660

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Varoglutamstat: Inhibiting Glutaminyl Cyclase as a Novel Target of Therapy in Early Alzheimer’s Disease

J Alzheimers Dis. 2024;101(s1):S79-S93. doi: 10.3233/JAD-231126.

ABSTRACT

BACKGROUND: Varoglutamstat is a first-in-class, small molecule being investigated as a treatment for early Alzheimer’s disease (AD). It is an inhibitor of glutaminyl cyclase (QC), the enzyme that post-translationally modifies amyloid-β (Aβ) peptides into a toxic form of pyroglutamate Aβ (pGlu-Aβ) and iso-QC which post-translationally modifies cytokine monocyte chemoattractant protein-1 (CCL2) into neuroinflammatory pGlu-CCL2. Early phase clinical trials identified dose margins for safety and tolerability of varoglutamstat and biomarker data supporting its potential for clinical efficacy in early AD.

OBJECTIVE: Present the scientific rationale of varoglutamstat in the treatment of early AD and the methodology of the VIVA-MIND (NCT03919162) trial, which uses a seamless phase 2A-2B design. Our review also includes other pharmacologic approaches to pGlu-Aβ.

METHODS: Phase 2A of the VIVA-MIND trial will determine the highest dose of varoglutamstat that is safe and well tolerated with sufficient plasma exposure and a calculated target occupancy. Continuous safety evaluation using a pre-defined safety stopping boundary will help determine the highest tolerated dose that will carry forward into phase 2B. An interim futility analysis of cognitive function and electroencephalogram changes will be conducted to inform the decision of whether to proceed with phase 2B. Phase 2B will assess the efficacy and longer-term safety of the optimal selected phase 2A dose through 72 weeks of treatment.

CONCLUSIONS: Varoglutamstat provides a unique dual mechanism of action addressing multiple pathogenic contributors to the disease cascade. VIVA-MIND provides a novel and efficient trial design to establish its optimal dosing, safety, tolerability, and efficacy in early AD.

PMID:39422941 | DOI:10.3233/JAD-231126

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Time to Sustained Recovery Among Outpatients With COVID-19 Receiving Montelukast vs Placebo: The ACTIV-6 Randomized Clinical Trial

JAMA Netw Open. 2024 Oct 1;7(10):e2439332. doi: 10.1001/jamanetworkopen.2024.39332.

ABSTRACT

IMPORTANCE: The effect of montelukast in reducing symptom duration among outpatients with mild to moderate COVID-19 is uncertain.

OBJECTIVE: To assess the effectiveness of montelukast compared with placebo in treating outpatients with mild to moderate COVID-19.

DESIGN, SETTING, AND PARTICIPANTS: This randomized clinical trial (Accelerating COVID-19 Therapeutic Interventions and Vaccines [ACTIV]-6) was conducted from January 27 through June 23, 2023, during the circulation of Omicron subvariants. Participants aged 30 years or older with confirmed SARS-CoV-2 infection and 2 or more acute COVID-19 symptoms for less than 7 days were included across 104 US sites.

INTERVENTIONS: Participants were randomized 1:1 to receive montelukast, 10 mg once daily, or matched placebo for 14 days.

MAIN OUTCOMES AND MEASURES: The primary outcome was time to sustained recovery (defined as ≥3 consecutive days without symptoms). Secondary outcomes included time to death; time to hospitalization or death; a composite of health care utilization events (hospitalization, urgent care clinic visit, emergency department visit, or death); COVID-19 clinical progression scale score; and difference in mean time unwell. A modified intention-to-treat approach was used for the analysis.

RESULTS: Among 1250 participants who were randomized and received the study drug or placebo, the median age was 53 years (IQR, 42-62 years), 753 (60.2%) were female, and 704 (56.3%) reported receiving 2 or more doses of a SARS-CoV-2 vaccine. Among 628 participants who received montelukast and 622 who received placebo, differences in time to sustained recovery were not observed (adjusted hazard ratio [AHR], 1.02; 95% credible interval [CrI], 0.92-1.12; P = .63 for efficacy). Unadjusted median time to sustained recovery was 10 days (95% CI, 10-11 days) in both groups. No deaths occurred, and hospitalizations were reported for 2 participants (0.3%) in each group; the composite of health care utilization events was reported for 18 participants (2.9%) in the montelukast group and 18 (2.9%) in the placebo group (AHR, 1.01; 95% CrI, 0.45-1.84; P = .48 for efficacy). Five participants (0.4%) experienced serious adverse events (3 [0.5%] in the montelukast group and 2 [0.3%] in the placebo group).

CONCLUSIONS AND RELEVANCE: In this randomized clinical trial of outpatients with mild to moderate COVID-19, treatment with montelukast did not reduce duration of COVID-19 symptoms. These findings do not support the use of montelukast for the treatment of mild to moderate COVID-19.

TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT04885530.

PMID:39422912 | DOI:10.1001/jamanetworkopen.2024.39332