Category: Nevin Manimala

Oncologist. 2023 Mar 14:oyad028. doi: 10.1093/oncolo/oyad028. Online ahead of print.

ABSTRACT

BACKGROUND: There is a lack of consensus regarding the optimal method of assessing health-related quality of life (HR-QOL) among patients with metastatic renal cell carcinoma (mRCC). This study explored the perceived relevance of items that make up the Functional Assessment of Cancer Therapy Kidney Symptom Index-19 (FKSI-19), as judged by patients with mRCC.

METHODS: This was a multinational cross-sectional survey. Eligible patients responded to a questionnaire composed of 18 items that assessed the perceived relevance of each item in the FKSI-19 questionnaire. Open-ended questions assessed additional issues deemed relevant by patients. Responses were grouped as relevant (scores 2-5) or nonrelevant (score 1). Descriptive statistics were collated, and open-ended questions were analyzed and categorized into descriptive categories. Spearman correlation statistics were used to test the association between relevance and clinical characteristics.

RESULTS: A total of 151 patients were included (gender: 78.1 M, 21.9F; median age: 64; treatment: 38.4 immunotherapy, 29.8 targeted therapy, 13.9 immuno-TKI combination therapy) in the study. The most relevant questions evaluated fatigue (77.5), lack of energy (72.2), and worry that their condition will get worse (71.5). Most patients rated blood in urine (15.2), fevers (16.6), and lack of appetite (23.2) as least relevant. Qualitative analysis of open-ended questions revealed several themes, including emotional and physical symptoms, ability to live independently, effectiveness of treatment, family, spirituality, and financial toxicity.

CONCLUSION: There is a need to refine widely used HR-QOL measures that are employed among patients diagnosed with mRCC treated with contemporary therapies. Guidance was provided for the inclusion of more relevant items to patients’ cancer journey.

PMID:36917626 | DOI:10.1093/oncolo/oyad028

Elife. 2023 Mar 14;12:e81446. doi: 10.7554/eLife.81446. Online ahead of print.

ABSTRACT

The beta rhythm (13-30 Hz) is a prominent brain rhythm. Recordings in primates during instructed-delay reaching tasks have shown that different types of traveling waves of oscillatory activity are associated with episodes of beta oscillations in motor cortex during movement preparation. We propose here a simple model of motor cortex based on local excitatory-inhibitory neuronal populations coupled by long-range excitation, where additionally inputs to the motor cortex from other neural structures are represented by stochastic inputs on the different model populations. We show that the model accurately reproduces the statistics of recording data when these external inputs are correlated on a short time scale (25 ms) and have two different components, one that targets the motor cortex locally and another one that targets it in a global and synchronized way. The model reproduces the distribution of beta burst durations, the proportion of the different observed wave types, and wave speeds, which we show not to be linked to axonal propagation speed. When the long-range connectivity or the local input targets are anisotropic, traveling waves are found to preferentially propagate along the axis where connectivity decays the fastest. Different from previously proposed mechanistic explanations, the model suggests that traveling waves in motor cortex are the reflection of the dephasing by external inputs, putatively of thalamic origin, of an oscillatory activity that would otherwise be spatially synchronized by recurrent connectivity.

PMID:36917621 | DOI:10.7554/eLife.81446

PLoS One. 2023 Mar 14;18(3):e0280620. doi: 10.1371/journal.pone.0280620. eCollection 2023.

ABSTRACT

Food insecurity is prevalent and associated with poor health outcomes, but little is known about its geographical nature. The aim of this study is to utilize geospatial modeling of individual-level food insecurity screening data ascertained in health care settings to test for neighborhood hot and cold spots of food insecurity in a large metropolitan area, and then compare these hot spot neighborhoods to cold spot neighborhoods in terms of the CDC’s Social Vulnerability Index. In this cross-sectional secondary data analysis, we geocoded the home addresses of 6,749 unique participants screened for food insecurity at health care locations participating in CMS’s Accountable Health Communities (AHC) Model, as implemented in Houston, TX. Next, we created census-tract level incidence profiles of positive food insecurity screens per 1,000 people. We used Anselin’s Local Moran’s I statistic to test for statistically significant census tract-level hot/cold spots of food insecurity. Finally, we utilized a Mann-Whitney-U test to compare hot spot tracts to cold spot tracts in relation to the CDC’s Social Vulnerability Index. We found that hot spot tracts had higher overall social vulnerability index scores (P <0.001), higher subdomain scores, and higher percentages of individual variables like poverty (P <0.001), unemployment (P <0.001), limited English proficiency (P <0.001), and more. The combination of robust food insecurity screening data, geospatial modeling, and the CDC’s Social Vulnerability Index offers a solid method to understand neighborhood food insecurity.

PMID:36917592 | DOI:10.1371/journal.pone.0280620

PLoS One. 2023 Mar 14;18(3):e0282913. doi: 10.1371/journal.pone.0282913. eCollection 2023.

ABSTRACT

The aging population is a common problem faced by most countries in the world. This study uses 18 years (from 2002 to 2019) of panel data from 31 regions in China (excluding Hong Kong, Macao, and Taiwan Province), and establishes a panel threshold regression model to study the non-linear impact of the aging population on economic development. It is different from traditional research in that this paper divides 31 regions in China into three regions: Eastern, Central, and Western according to the classification standard of the National Bureau of Statistics of China and compares the different impacts of the aging population on economic development in the three regions. Although this study finds that the aging population promotes the economy of China’s eastern, central, and western regions, different threshold variables have dramatically different influences. When the sum of export and import is the threshold variable, the impact of the aging population on the eastern and the central region of China is significantly larger than that of the western region of China. However, when the unemployment rate is the threshold variable, the impact of the aging population on the western region of China is dramatically higher than the other regions’ impact. Thus, one of the contributions of this study is that if the local government wants to increase the positive impact of the aging population on the per capita GDP of China, the local governments of different regions should advocate more policies that align with their economic situation rather than always emulating policies from other regions.

PMID:36917591 | DOI:10.1371/journal.pone.0282913

PLoS One. 2023 Mar 14;18(3):e0280921. doi: 10.1371/journal.pone.0280921. eCollection 2023.

ABSTRACT

INTRODUCTION: Medical students should act as a model for the community in terms of compliance with preventive practices toward COVID-19. The aim of this study was to assess adherence to preventive behaviors related to COVID-19 among medical students and to identify its associated factors.

POPULATION AND METHODS: We conducted a cross-sectional survey in October 2020 in the faculty of medicine of Monastir. We included a representative sample of medical students during registration days for the 2020-2021 academic year. The data were collected through a self-administered anonymous questionnaire. Eleven items related to preventive practices against COVID-19 were assessed (respiratory hygiene practices (Six Item), hand hygiene practices (Three Items) and social distancing (two items)). Items were evaluated using a Likert scale of five points (from 0: (Never) to 4: (Always)). The score obtained from the sum of these items allowed to classify students into two categories: “Good compliance” if the score was ≥ 80% and “Poor compliance” if the score was less than 80%. Scores were compared according to the study population characteristics. Multivariate analysis was used to identify associated factors with good practices. The threshold of statistical significance was set at p < 0.05.

RESULTS: We included 678 medical students. The average age was 21.76 (SD = 1.89 years) with a sex ratio of 0.40. The protection measures most respected by the participants were related to the respiratory hygiene: correct coverage of the nose and mouth with the mask (80%), wearing masks regardless of the presence of symptoms (73.3%) and coverage of the mouth during coughing or sneezing (76.6%). Adherence to hand hygiene measures ranged from 51.4% to 66.3%. The least respected measures were related to social distancing: distancing of at least one meter from others (31.2%) and avoiding crowded places (42.5%). An overall score ≥ 80% was obtained among 61.5% of students. Referring to multivariate analysis, variables that positively affected the overall score of preventive measures related to COVID-19 were the female sex and living alone, with Beta coefficients of 3.82 and 1.37 respectively. The perceived level of stress, E-cigarette and Chicha consumption negatively affected the score with Beta coefficients of (-0.13), (-5.11) and (-2.33) respectively.

CONCLUSION: The level of adherence to good practice among medical students was overall moderate. Awareness programs would be needed in this population, especially for men and those who smoke and vape.

PMID:36917588 | DOI:10.1371/journal.pone.0280921

PLoS One. 2023 Mar 14;18(3):e0281663. doi: 10.1371/journal.pone.0281663. eCollection 2023.

ABSTRACT

This study aims to assess the influence of internal and external factors on the Efficiency of banks in Pakistan using the Data Envelopment Analysis Approach (DEA). Bank’s Efficiency is measured through DEA Model using input and output variables. The input variable includes the number of employees, number of branches, administration expenses, non-interest expenses, and loan loss provisions. In contrast, the output variable consists of net interest income, net commissions, and total other income. This study considers the internal determinants of the bank’s Efficiency as corporate governance, enterprise risk management, ownership structure (state, foreign, and domestic ultimate owned banks), return on equity, financial leverage, and the size of the bank. The external determinants of the bank’s Efficiency include banking structure and macroeconomic conditions. The study has used data from seventeen commercial banks over the period of 2011 to 2020. The study used the Data Envelopment Analysis Approach (DEA) and Logit and Probit Regression Model to evaluate research hypotheses. The Logit model results show that corporate governance, ultimate global ownership, and return on equity have a statistically significant and positive impact on the bank’s Efficiency. Enterprise risk management and financial leverage adversely affect the bank’s Efficiency. Better corporate governance can help banks to control the risk and cost of capital and enhancement the effectiveness of capital. Similarly, better risk management of banks can lead to better operational and strategic decisions in the competitive banking environment.

PMID:36917587 | DOI:10.1371/journal.pone.0281663

PLoS One. 2023 Mar 14;18(3):e0279624. doi: 10.1371/journal.pone.0279624. eCollection 2023.

ABSTRACT

BACKGROUND: Insomnia is a prevalent sleep disorder that affects people all over the world. Creating suitable interventions will require a better understanding of the magnitude and determinants of insomnia. This study aimed to assess the prevalence and associated factors of insomnia symptoms among residents of Mettu town during the pandemic lockdown.

METHODOLOGY: A community-based cross-sectional study was conducted among residents of Mettu town from October 1st to October 15th, 2020. Residents who lived in Mettu town at least for six months were included. To determine the prevalence and determinants of insomnia symptoms, both descriptive and inferential analyses were used. The chi-squared test of association and logistic regression was used to identify predictors of insomnia symptoms among residents of Mettu town. We used SPSS version 25 for all statistical analyses.

PRINCIPAL FINDINGS: The prevalence of depressive symptoms among residents of Mettu town was 52.6%. According to results of multivariable binary logistic regression, being female [AOR = 3.677, 95%CI: 2.124-6.365], being aged between 19 and 40 [AOR = 13.261, 95%CI: 6.953-25.291], being aged above 41 [AOR = 2.627, 95%CI: 1.120-6.159], smoking [AOR = 15.539, 95%CI: 7.961-30.329], satisfaction with information available [AOR = 0.310, 95%CI: 0.168-0.570], fear Corona Virus Disease 2019 (COVID-19), [AOR = 2.171, 95%CI: 1.262-3.733], feeling alienated from others [AOR = 3.288, 95%CI: 1.897-5.699], having somatic symptoms [AOR = 2.298, 95% CI: 1.360-3.884], having depressive symptoms [AOR = 1.841, 95% CI: 1.073-3.160], and experiencing psychological distress [AOR = 1.962, 95% CI: 1.173-3.281] were significantly associated with insomnia symptoms.

CONCLUSION: In this study, the prevalence of insomnia symptoms was found to be high among residents of Mettu town. Being female, being aged between 19 and 40, being aged above 41 years, smoking, fear of Corona Virus Disease 2019, feeling alienated from others, having somatic symptoms, having depressive symptoms, and experiencing psychological distress were all associated with an increased risk of developing insomnia symptoms while being satisfied with the information available decreased the risk of insomnia symptoms among residents of Mettu town. Interventions should be put in place to promote healthy sleep among residents of Mettu town.

PMID:36917577 | DOI:10.1371/journal.pone.0279624

Equine Vet J. 2023 Mar 14. doi: 10.1111/evj.13934. Online ahead of print.

ABSTRACT

BACKGROUND: Equestrian eventing is a dangerous Olympic sport, with 16 rider and 69 horse fatalities at competition in the last 10 years. Despite this, there is limited research that aims to improve safety within the sport.

OBJECTIVES: The purpose of this study was to identify risk factors for horse falls, which are the leading cause of rider fatality within the sport.

STUDY DESIGN: Retrospective cohort study.

METHODS: Competition data between January 2005 and December 2015 were analysed. Descriptive statistics followed by univariable logistic regression to identify risk factors for inclusion in a multivariable logistic regression model were conducted. Models were constructed stepwise using a bi-directional process and assessed using the Akaike Information Criterion. A total of 749 534 cross-country starts were analysed for association with the risk of horse falls.

RESULTS: Sixteen risk factors were identified including: higher event levels, higher dressage penalties and higher number of days since horses’ last start. For example, horse and rider combinations competing at BE100 (OR 1.64, CI 1.37-1.96, p < 0.001), Novice (OR 3.58, CI 3.03-4.24, p < 0.001), Intermediate (OR 8.00, CI 6.54-9.78, p < 0.001), Advanced (OR 12.49, CI 9.42-16.57, p < 0.001) and International (OR 4.63, CI 3.50-6.12, p < 0.001) all had a higher risk of having a horse fall in comparison to combinations competing at BE90 level. Furthermore, for every additional 10 dressage penalties awarded to a horse and rider combination, there was a higher risk of a horse fall (OR 1.20, CI 1.12-1.28, p < 0.001).

MAIN LIMITATIONS: The study is not geographically comprehensive (UK only) and does not include any information on training activity of horses and riders.

CONCLUSIONS: This is the largest-scale study ever conducted on horse falls during eventing competition. Study results can be utilised by sport governing bodies to inform policy which has the potential to reduce the risk of injury and fatality to sport participants. This article is protected by copyright. All rights reserved.

PMID:36917550 | DOI:10.1111/evj.13934

JMIR Res Protoc. 2023 Mar 14;12:e41040. doi: 10.2196/41040.

ABSTRACT

BACKGROUND: Digital transformation is impacting health care delivery. Great market dynamism is bringing opportunities and concerns alike into public discussion. Digital health apps are a vibrant segment where regulation is emerging, with Germany paving the way with its DiGA (Digitale Gesundheitsanwendungen, in German, meaning digital health apps) program. Simultaneously, mental ill-health constitutes a global health concern, and prevalence is expected to worsen due to the COVID-19 pandemic and its containment measures. Portugal and its National Health System may be a useful testbed for digital health interventions.

OBJECTIVE: The paper outlines the protocol for a research project on the attitudes of physicians and potential users toward digital mental health apps to improve access to care, patient outcomes, and reduce the burden of disease of mental ill-health.

METHODS: Web surveys will be conducted to acquire data from the main stakeholders (physicians and the academic community). Data analysis will replicate the statistical analysis performed in the studies from Dahlhausen and Borghouts to derive conclusions regarding the relative acceptance and likelihood of successful implementation of digital mental health apps in Portugal.

RESULTS: The findings of the proposed studies will elicit important information on how physicians and individuals perceive digital mental health app interventions to improve access to care, patient outcomes, and reduce the burden of disease of mental ill-health. Data collection ran between September 26 and November 6, 2022, for the first study and September 20 and October 20, 2022, for the second study. We obtained 160 responses to the first study’s survey and 539 answers to the second study’s survey. Data analysis is concluded, and both studies’ results are expected to be published in 2023.

CONCLUSIONS: The results of the studies projected in this research protocol will have implications for researchers and academia, industry, and policy makers concerning the adoption and implementation of digital health mental apps and associated interventions.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/41040.

PMID:36917172 | DOI:10.2196/41040

Brief Bioinform. 2023 Mar 14:bbad092. doi: 10.1093/bib/bbad092. Online ahead of print.

ABSTRACT

Metagenomic sequencing (mNGS) is a powerful diagnostic tool to detect causative pathogens in clinical microbiological testing owing to its unbiasedness and substantially reduced costs. Rapid and accurate classification of metagenomic sequences is a critical procedure for pathogen identification in dry-lab step of mNGS test. However, clinical practices of the testing technology are hampered by the challenge of classifying sequences within a clinically relevant timeframe. Here, we present GPMeta, a novel GPU-accelerated approach to ultrarapid pathogen identification from complex mNGS data, allowing users to bypass this limitation. Using mock microbial community datasets and public real metagenomic sequencing datasets from clinical samples, we show that GPMeta has not only higher accuracy but also significantly higher speed than existing state-of-the-art tools such as Bowtie2, Bwa, Kraken2 and Centrifuge. Furthermore, GPMeta offers GPMetaC clustering algorithm, a statistical model for clustering and rescoring ambiguous alignments to improve the discrimination of highly homologous sequences from microbial genomes with average nucleotide identity >95%. GPMetaC exhibits higher precision and recall rate than others. GPMeta underlines its key role in the development of the mNGS test in infectious diseases that require rapid turnaround times. Further study will discern how to best and easily integrate GPMeta into routine clinical practices. GPMeta is freely accessible to non-commercial users at https://github.com/Bgi-LUSH/GPMeta.

PMID:36917170 | DOI:10.1093/bib/bbad092