Category: Nevin Manimala

PLoS One. 2023 Jan 23;18(1):e0280887. doi: 10.1371/journal.pone.0280887. eCollection 2023.

ABSTRACT

BACKGROUND: Despite the progress in achieving gender equality to a certain extent, women are found to be more susceptible to health disadvantages compared to men in the older ages. However, research in the Indian context has mainly remained restricted to subjective health that heavily depends on the individual’s perception, which may affect the validity of results. This study addresses this gap by complementing the investigation of the gender differentials in self-reported health outcomes (mobility and functional limitations) with that of objectively measured health status (hand-grip strength and static balance) among the older population of India. Besides, there is a dearth of literature that considers financial empowerment in explaining the gender differentials in health. Women’s ability to participate in household decision-making, especially for important matters like major purchases, including property, indicates their empowerment status. Furthermore, the ability to extend financial support can be considered an important ‘non-altruistic’ driver for kins to care for older adults, indirectly affecting their health and well-being. Thus, the present paper explores the influence of financial empowerment on gender differentials in poor health outcomes.

METHODS: Using the Longitudinal Aging Study in India, Wave-1 (2017-18), six logistic regression models have been specified to capture the adjusted association between gender and poor health outcomes. The first three models successively control for the demographic and social support factors; socioeconomic factors and pre-existing health conditions; and financial empowerment indicators. The last three models investigate the interactions between gender and marital status, living arrangement and involvement in financial decisions, respectively.

RESULTS: The findings reveal that women tend to be more perceptive about their physical discomfort than men and reported a higher prevalence of poor subjective health. In terms of objectively measured health status, older men had a higher prevalence of low hand-grip strength but a lower prevalence of poor balance. Gender demonstrated a strong, adjusted association with poor health outcomes among older adults. However, the magnitude of gender difference either shrunk considerably or became statistically insignificant for all the poor health outcomes after controlling the effect of indicators of financial empowerment. Further, the interaction between gender and involvement in financial matters demonstrated a stronger effect for men in reversing poor subjective health.

CONCLUSION: The study reinforced the positive effect of financial empowerment in mitigating gender disparity in health among older adults.

PMID:36689542 | DOI:10.1371/journal.pone.0280887

PLoS One. 2023 Jan 23;18(1):e0280761. doi: 10.1371/journal.pone.0280761. eCollection 2023.

ABSTRACT

Using solid waste in building materials is an efficient approach to achieving sustainability goals. Also, the application of modern methods like artificial intelligence is gaining attention. In this regard, the flexural strength (FS) of cementitious composites (CCs) incorporating waste glass powder (WGP) was evaluated via both experimental and machine learning (ML) methods. WGP was utilized to partially substitute cement and fine aggregate separately at replacement levels of 0%, 2.5%, 5%, 7.5%, 10%, 12.5%, and 15%. At first, the FS of WGP-based CCs was determined experimentally. The generated data, which included six inputs, was then used to run ML techniques to forecast the FS. For FS estimation, two ML approaches were used, including a support vector machine and a bagging regressor. The effectiveness of ML models was assessed by the coefficient of determination (R2), k-fold techniques, statistical tests, and examining the variation amongst experimental and forecasted FS. The use of WGP improved the FS of CCs, as determined by the experimental results. The highest FS was obtained when 10% and 15% WGP was utilized as a cement and fine aggregate replacement, respectively. The modeling approaches’ results revealed that the support vector machine method had a fair level of accuracy, but the bagging regressor method had a greater level of accuracy in estimating the FS. Using ML strategies will benefit the building industry by expediting cost-effective and rapid solutions for analyzing material characteristics.

PMID:36689541 | DOI:10.1371/journal.pone.0280761

PLoS One. 2023 Jan 23;18(1):e0280633. doi: 10.1371/journal.pone.0280633. eCollection 2023.

ABSTRACT

INTRODUCTION: Many countries around the world are still affected by the global pandemic of coronavirus disease. The vaccine is the most effective method of controlling Coronavirus Disease 2019 (COVID-19). However, attitudes toward vaccination are heavily affected by different factors besides vaccine availability.

OBJECTIVES: This study aimed to determine community attitudes toward the COVID-19 vaccine in Gurage Zone, Ethiopia.

METHODS: A community-based cross-sectional study was conducted from November 15th to December 15th, 2021. A simple random sampling technique was used to select 364 participants in the study area. An interview-administered structured questionnaire was used to collect the data; the data was entered into Epidata 3.1 version, and then exported to SPSS version 23 for further analysis. Descriptive statistics were used to determine the characteristics of study participants. Binary and multivariable logistic regression analyses with a p-value of less than 0.05 were used as a measure of significance.

RESULTS: In this study, 44.7% of study participants had a favorable attitude toward the COVID-19 vaccine. Perceived potential vaccine harm [AOR: 1.85; 95% CI (1.15-2.96)], Having ever had a chronic disease [AOR: 3.22; 95% CI (2.02-5.14)], community belief on the effectiveness of the vaccine [AOR: 2.02; 95% CI (1.27-3.22)], and average monthly income 3001-5000 ETB [AOR: 0.54; 95% CI (0.30-0.97)], average monthly income 5001-10000 ETB [AOR: 0.48; 95% CI(0.27-0.86)] were statistically significantly towards COVID-19 vaccination.

CONCLUSIONS: Overall, less than half of the participants had a favorable attitude toward the COVID-19 vaccine. Perceived potential vaccine harm, having ever had a chronic disease, community belief in the effectiveness of the vaccine, and average monthly income were determinant factors of the community’s attitude toward COVID-19 vaccination. As a result, information conversation with the community’s awareness of the COVID-19 vaccination in reducing vaccine-related suspicion.

PMID:36689539 | DOI:10.1371/journal.pone.0280633

PLoS Comput Biol. 2023 Jan 23;19(1):e1010855. doi: 10.1371/journal.pcbi.1010855. Online ahead of print.

ABSTRACT

How the connectivity of cortical networks determines the neural dynamics and the resulting computations is one of the key questions in neuroscience. Previous works have pursued two complementary approaches to quantify the structure in connectivity. One approach starts from the perspective of biological experiments where only the local statistics of connectivity motifs between small groups of neurons are accessible. Another approach is based instead on the perspective of artificial neural networks where the global connectivity matrix is known, and in particular its low-rank structure can be used to determine the resulting low-dimensional dynamics. A direct relationship between these two approaches is however currently missing, and in particular it remains to be clarified how local connectivity statistics and the global low-rank connectivity structure are inter-related and shape the low-dimensional activity. To bridge this gap, here we develop a method for mapping local connectivity statistics onto an approximate global low-rank structure. Our method rests on approximating the global connectivity matrix using dominant eigenvectors, which we compute using perturbation theory for random matrices. We demonstrate that multi-population networks defined from local connectivity statistics for which the central limit theorem holds can be approximated by low-rank connectivity with Gaussian-mixture statistics. We specifically apply this method to excitatory-inhibitory networks with reciprocal motifs, and show that it yields reliable predictions for both the low-dimensional dynamics, and statistics of population activity. Importantly, it analytically accounts for the activity heterogeneity of individual neurons in specific realizations of local connectivity. Altogether, our approach allows us to disentangle the effects of mean connectivity and reciprocal motifs on the global recurrent feedback, and provides an intuitive picture of how local connectivity shapes global network dynamics.

PMID:36689488 | DOI:10.1371/journal.pcbi.1010855

JMIR Mhealth Uhealth. 2023 Jan 23;11:e42799. doi: 10.2196/42799.

ABSTRACT

BACKGROUND: The World Health Organization recommends that all adults with HIV adhere to antiretroviral therapy (ART). Good adherence to ART is beneficial to patients and the public. Furthermore, mHealth has shown promise in improving HIV medication adherence globally.

OBJECTIVE: The aim of this meta-analysis is to analyze the effectiveness of mHealth on adherence to antiretroviral therapy in patients living with HIV.

METHODS: Randomized controlled trials (RCTs) of the association between mHealth and adherence to ART published until December 2021 were searched in electronic databases. Odds ratios (ORs), weighted mean differences, and 95% CIs were calculated. This meta-analysis was performed using the Mantel-Haenszel method or the inverse variance test. We evaluated heterogeneity with the I² statistic. If I² was ≤50%, heterogeneity was absent, and a fixed effect model was used. If I² was >50%, heterogeneity was present, and a random effects model was used.

RESULTS: A total of 2163 participants in 8 studies were included in this meta-analysis. All included studies were RCTs. The random effects model was used for a meta-analysis of the effects of various intervention measures compared to routine nursing; the outcome was not statistically significant (OR 1.54, 95% CI 0.99-2.38; P=.05). In the subgroups, only short messaging service (SMS)-based interventions significantly increased adherence to ART (OR 1.76, 95% CI 1.07-2.89; P=.03). Further analysis showed that only interactive or bidirectional SMS could significantly increase ART adherence (OR 1.69, 95% CI 1.22-2.34; P=.001). After combining the difference in CD4 cell count before and after the interventions, we concluded that there was no statistical heterogeneity among the studies (I²=0%; tau²=0.37; P=.95).

CONCLUSIONS: Interactive or bidirectional SMS can enhance intervention effects. However, whether mHealth can improve adherence to ART in patients with HIV needs further study. Owing to a lack of the required significant staff time, training, and ongoing supervision, there is still much more to do to apply mHealth to the clinical use of ART for patients living with HIV.

TRIAL REGISTRATION: PROSPERO CRD42022358774; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=358774.

PMID:36689267 | DOI:10.2196/42799

JMIR Ment Health. 2023 Jan 23;10:e37225. doi: 10.2196/37225.

ABSTRACT

BACKGROUND: Major depressive episode (MDE) is a common clinical syndrome. It can be found in different pathologies such as major depressive disorder (MDD), bipolar disorder (BD), posttraumatic stress disorder (PTSD), or even occur in the context of psychological trauma. However, only 1 syndrome is described in international classifications (Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition [DSM-5]/International Classification of Diseases 11th Revision [ICD-11]), which do not take into account the underlying pathology at the origin of the MDE. Clinical interviews are currently the best source of information to obtain the etiological diagnosis of MDE. Nevertheless, it does not allow an early diagnosis and there are no objective measures of extracted clinical information. To remedy this, the use of digital tools and their correlation with clinical symptomatology could be useful.

OBJECTIVE: We aimed to review the current application of digital tools for MDE diagnosis while highlighting shortcomings for further research. In addition, our work was focused on digital devices easy to use during clinical interview and mental health issues where depression is common.

METHODS: We conducted a narrative review of the use of digital tools during clinical interviews for MDE by searching papers published in PubMed/MEDLINE, Web of Science, and Google Scholar databases since February 2010. The search was conducted from June to September 2021. Potentially relevant papers were then compared against a checklist for relevance and reviewed independently for inclusion, with focus on 4 allocated topics of (1) automated voice analysis, behavior analysis by (2) video and physiological measures, (3) heart rate variability (HRV), and (4) electrodermal activity (EDA). For this purpose, we were interested in 4 frequently found clinical conditions in which MDE can occur: (1) MDD, (2) BD, (3) PTSD, and (4) psychological trauma.

RESULTS: A total of 74 relevant papers on the subject were qualitatively analyzed and the information was synthesized. Thus, a digital phenotype of MDE seems to emerge consisting of modifications in speech features (namely, temporal, prosodic, spectral, source, and formants) and in speech content, modifications in nonverbal behavior (head, hand, body and eyes movement, facial expressivity, and gaze), and a decrease in physiological measurements (HRV and EDA). We not only found similarities but also differences when MDE occurs in MDD, BD, PTSD, or psychological trauma. However, comparative studies were rare in BD or PTSD conditions, which does not allow us to identify clear and distinct digital phenotypes.

CONCLUSIONS: Our search identified markers from several modalities that hold promise for helping with a more objective diagnosis of MDE. To validate their potential, further longitudinal and prospective studies are needed.

PMID:36689265 | DOI:10.2196/37225

J Chin Med Assoc. 2023 Jan 23. doi: 10.1097/JCMA.0000000000000883. Online ahead of print.

ABSTRACT

BACKGROUND: Neoadjuvant systemic therapy (NST) is conducted in increased patients with breast cancer overexpressing human epidermal growth factor receptor 2 (HER2). Whether the intensity of HER2 protein expression determines response to treatment is challenged. This study aims to analyse the impact of HER2 immunohistochemical (IHC) scores on NST response and survival outcome.

METHODS: We analysed a total of 197 patients with HER2-positive breast cancer receiving NST and definite surgery from a prospectively collected database. The analysed end points included pathological complete response (pCR), disease-free survival (DFS) and overall survival (OS). More patients with IHC 2+/in situ hybridization (ISH)-positive tumours presented positive for hormonal receptors, compared to those with IHC 3+ tumours. No clinicopathological features except tumour necrosis were significantly associated with pCR.

RESULTS: Both positive hormone receptors and IHC scores stood on the borderline in statistical analysis. IHC 3+ group tends to present a higher pCR rate than IHC 2+/ISH+ groups (52.5% vs. 34.3%). Patients who achieved pCR had better survival outcome than that of non-pCR group. The impact of pCR on survival reached the statistical significance in the IHC 3+ group both in DFS (90.9% vs. 76.5%, p=0.004) and OS (97.4% vs. 83.2%, p=0.002). Multivariate analysis demonstrated IHC scores as an independent predictor of survival outcome with the adjustment of tumour staging and pCR.

CONCLUSION: HER2 IHC score is an independent predictor for outcome. IHC 3+ tumours presented a trend of higher pCR rate and better outcome in HER2-positive breast cancer patients who receive NST.

PMID:36689250 | DOI:10.1097/JCMA.0000000000000883

JAMA. 2023 Jan 23. doi: 10.1001/jama.2022.25080. Online ahead of print.

NO ABSTRACT

PMID:36689237 | DOI:10.1001/jama.2022.25080

JAMA Netw Open. 2023 Jan 3;6(1):e2251182. doi: 10.1001/jamanetworkopen.2022.51182.

ABSTRACT

IMPORTANCE: While research has identified racial and ethnic disparities in access to autism services, the size, extent, and specific locations of these access gaps have not yet been characterized on a national scale. Mapping comprehensive national listings of autism health care services together with the prevalence of autistic children of various races and ethnicities and evaluating geographic regions defined by localized commuting patterns may help to identify areas within the US where families who belong to minoritized racial and ethnic groups have disproportionally lower access to services.

OBJECTIVE: To evaluate differences in access to autism health care services among autistic children of various races and ethnicities within precisely defined geographic regions encompassing all serviceable areas within the US.

DESIGN, SETTING, AND PARTICIPANTS: This population-based cross-sectional study was conducted from October 5, 2021, to June 3, 2022, and involved 530 965 autistic children in kindergarten through grade 12. Core-based statistical areas (CBSAs; defined as areas containing a city and its surrounding commuter region), the Civil Rights Data Collection (CRDC) data set, and 51 071 autism resources (collected from October 1, 2015, to December 18, 2022) geographically distributed into 912 CBSAs were combined and analyzed to understand variation in access to autism health care services among autistic children of different races and ethnicities. Six racial and ethnic categories (American Indian or Alaska Native, Asian, Black or African American, Hispanic or Latino, Native Hawaiian or other Pacific Islander, and White) assigned by the US Department of Education were included in the analysis.

MAIN OUTCOMES AND MEASURES: A regularized least-squares regression analysis was used to measure differences in nationwide resource allocation between racial and ethnic groups. The number of autism resources allocated per autistic child was estimated based on the child’s racial and ethnic group. To evaluate how the CBSA population size may have altered the results, the least-squares regression analysis was run on CBSAs divided into metropolitan (>50 000 inhabitants) and micropolitan (10 000-50 000 inhabitants) groups. A Mann-Whitney U test was used to compare the model estimated ratio of autism resources to autistic children among specific racial and ethnic groups comprising the proportions of autistic children in each CBSA.

RESULTS: Among 530 965 autistic children aged 5 to 18 years, 83.9% were male and 16.1% were female; 0.7% of children were American Indian or Alaska Native, 5.9% were Asian, 14.3% were Black or African American, 22.9% were Hispanic or Latino, 0.2% were Native Hawaiian or other Pacific Islander, 51.7% were White, and 4.2% were of 2 or more races and/or ethnicities. At a national scale, American Indian or Alaska Native autistic children (β = 0; 95% CI, 0-0; P = .01) and Hispanic autistic children (β = 0.02; 95% CI, 0-0.06; P = .02) had significant disparities in access to autism resources in comparison with White autistic children. When evaluating the proportion of autistic children in each racial and ethnic group, areas in which Black autistic children (>50% of the population: β = 0.05; <50% of the population: β = 0.07; P = .002) or Hispanic autistic children (>50% of the population: β = 0.04; <50% of the population: β = 0.07; P < .001) comprised greater than 50% of the total population of autistic children had significantly fewer resources than areas in which Black or Hispanic autistic children comprised less than 50% of the total population. Comparing metropolitan vs micropolitan CBSAs revealed that in micropolitan CBSAs, Black autistic children (β = 0; 95% CI, 0-0; P < .001) and Hispanic autistic children (β = 0; 95% CI, 0-0.02; P < .001) had the greatest disparities in access to autism resources compared with White autistic children. In metropolitan CBSAs, American Indian or Alaska Native autistic children (β = 0; 95% CI, 0-0; P = .005) and Hispanic autistic children (β = 0.01; 95% CI, 0-0.06; P = .02) had the greatest disparities compared with White autistic children.

CONCLUSIONS AND RELEVANCE: In this study, autistic children from several minoritized racial and ethnic groups, including Black and Hispanic autistic children, had access to significantly fewer autism resources than White autistic children in the US. This study pinpointed the specific geographic regions with the greatest disparities, where increases in the number and types of treatment options are warranted. These findings suggest that a prioritized response strategy to address these racial and ethnic disparities is needed.

PMID:36689227 | DOI:10.1001/jamanetworkopen.2022.51182

JAMA Netw Open. 2023 Jan 3;6(1):e2251974. doi: 10.1001/jamanetworkopen.2022.51974.

ABSTRACT

IMPORTANCE: The COVID-19 pandemic has caused millions of infections and deaths and resulted in unprecedented international public health social and economic crises. As SARS-CoV-2 spread across the globe and its impact became evident, the development of safe and effective vaccines became a priority. Outlining the processes used to establish and support the conduct of the phase 3 randomized clinical trials that led to the rapid emergency use authorization and approval of several COVID-19 vaccines is of major significance for current and future pandemic response efforts.

OBSERVATIONS: To support the rapid development of vaccines for the US population and the rest of the world, the National Institute of Allergy and Infectious Diseases established the COVID-19 Prevention Network (CoVPN) to assist in the coordination and implementation of phase 3 efficacy trials for COVID-19 vaccine candidates and monoclonal antibodies. By bringing together multiple networks, CoVPN was able to draw on existing clinical and laboratory infrastructure, community partnerships, and research expertise to quickly pivot clinical trial sites to conduct COVID-19 vaccine trials as soon as the investigational products were ready for phase 3 testing. The mission of CoVPN was to operationalize phase 3 vaccine trials using harmonized protocols, laboratory assays, and a single data and safety monitoring board to oversee the various studies. These trials, while staggered in time of initiation, overlapped in time and course of conduct and ultimately led to the successful completion of multiple studies and US Food and Drug Administration-licensed or -authorized vaccines, the first of which was available to the public less than 1 year from the discovery of the virus.

CONCLUSIONS AND RELEVANCE: This Special Communication describes the design, geographic distribution, and underlying principles of conduct of these efficacy trials and summarizes data from 136 382 prospectively followed-up participants, including more than 2500 with documented COVID-19. These successful efforts can be replicated for other important research initiatives and point to the importance of investments in clinical trial infrastructure integral to pandemic preparedness.

PMID:36689221 | DOI:10.1001/jamanetworkopen.2022.51974