Tag: nevin manimala

PLoS One. 2021 Aug 23;16(8):e0256521. doi: 10.1371/journal.pone.0256521. eCollection 2021.

ABSTRACT

OBJECTIVE: To examine subgroup-specific treatment preferences and characteristics of patients with hemophilia A.

METHODS: Best-Worst Scaling (BWS) Case 3 (four attributes: application type; bleeding frequencies/year; inhibitor development risk; thromboembolic events of hemophilia A treatment risk) conducted via online survey. Respondents chose the best and the worst option of three treatment alternatives. Data were analyzed via latent class model (LCM), allowing capture of heterogeneity in the sample. Respondents were grouped into a predefined number of classes with distinct preferences.

RESULTS: The final dataset contained 57 respondents. LCM analysis segmented the sample into two classes with heterogeneous preferences. Preferences within each were homogeneous. For class 1, the most decisive factor was bleeding frequency/year. Respondents seemed to focus mainly on this in their choice decisions. With some distance, inhibitor development was the second most important. The remaining attributes were of far less importance for respondents in this class. Respondents in class 2 based their choice decisions primarily on inhibitor development, also followed, by some distance, the second most important attribute bleeding frequency/year. There was statistical significance (P < 0.05) between the number of annual bleedings and the probability of class membership.

CONCLUSIONS: The LCM analysis addresses heterogeneity in respondents’ choice decisions, which helps to tailor treatment alternatives to individual needs. Study results support clinical and allocative decision-making and improve the quality of interpretation of clinical data.

PMID:34424920 | DOI:10.1371/journal.pone.0256521

PLoS One. 2021 Aug 23;16(8):e0256235. doi: 10.1371/journal.pone.0256235. eCollection 2021.

ABSTRACT

BACKGROUND: Malnutrition contributes to children’s morbidity and mortality, and the situation undermines the economic growth and development of Bangladesh. Malnutrition is associated with lower levels of education that decrease economic productivity and leads to poverty. The global burden of malnutrition continues to be unacceptably high amid social and economic growth, including in Bangladesh. Therefore, identifying the factors associated with childhood malnutrition and poverty is necessary to stop the vicious cycle of malnutrition leaded poverty.

METHODS: The study utilized the 2017-18 Bangladesh Demographic and Health Survey (BDHS), accumulating 7,738 mother-child pairs. Associations between potential risk factors and nutritional status were determined using chi-square tests, and multivariate logistic regression models were utilized on significant risk factors to measure their odds ratio (OR) with their 95% confidence intervals (CI).

RESULTS: The prevalence of moderate and severe wasting was 7.0% and 1.8%, respectively, whereas the prevalence of moderate and severe stunting was 19.2% and 8.0%, while 16.4% and 3.6% of children were moderately and severely underweight. Children from the poorest and poor households were suffering from at least one form of malnutrition. Adjusted ORs were estimated by controlling socio-economic and demographic risk factors, such as poor maternal body mass index, parents’ lower education level, use of unhygienic toilet, child age in months, and recent experience of diarrhea and fever. The pattern was almost similar for each malnutrition status (i.e., stunting, underweight, and wasting) in the poorest and poor households.

CONCLUSION: Bangladesh achieved the Millennium Development Goals, focusing primarily on health-related indicators and working to achieve the Sustainable Development Goals. Even considering this success, the prevalence of malnutrition and poverty in same household remains relatively high compared to other developing countries. Therefore, the study recommends the implementation of nationwide systematic measures to prevent poverty and malnutrition.

PMID:34424928 | DOI:10.1371/journal.pone.0256235

PLoS One. 2021 Aug 23;16(8):e0243595. doi: 10.1371/journal.pone.0243595. eCollection 2021.

ABSTRACT

Currently, the population dynamics of preclonal cancer cells before clonal expansion of tumors has not been sufficiently addressed thus far. By focusing on preclonal cancer cell population as a Darwinian evolutionary system, we formulated and analyzed the observed mutation frequency among tumors (MFaT) as a proxy for the hypothesized sequence read frequency and beneficial fitness effect of a cancer driver mutation. Analogous to intestinal crypts, we assumed that sample donor patients are separate culture tanks where proliferating cells follow certain population dynamics described by extreme value theory (EVT). To validate this, we analyzed three large-scale cancer genome datasets, each harboring > 10000 tumor samples and in total involving > 177898 observed mutation sites. We clarified the necessary premises for the application of EVT in the strong selection and weak mutation (SSWM) regime in relation to cancer genome sequences at scale. We also confirmed that the stochastic distribution of MFaT is likely of the Fréchet type, which challenges the well-known Gumbel hypothesis of beneficial fitness effects. Based on statistical data analysis, we demonstrated the potential of EVT as a population genetics framework to understand and explain the stochastic behavior of driver-mutation frequency in cancer genomes as well as its applicability in real cancer genome sequence data.

PMID:34424899 | DOI:10.1371/journal.pone.0243595

PLoS One. 2021 Aug 23;16(8):e0256496. doi: 10.1371/journal.pone.0256496. eCollection 2021.

ABSTRACT

BACKGROUND: While vaccines ensure individual protection against COVID-19 infection, delay in receipt or refusal of vaccines will have both individual and community impacts. The behavioral factors of vaccine hesitancy or refusal are a crucial dimension that need to be understood in order to design appropriate interventions. The aim of this study was to explore the behavioral determinants of COVID-19 vaccine acceptance and to provide recommendations to increase the acceptance and uptake of COVID-19 vaccines in Bangladesh.

METHODS: We employed a Barrier Analysis (BA) approach to examine twelve potential behavioral determinants (drawn from the Health Belief Model [HBM] and Theory of Reasoned Action [TRA]) of intended vaccine acceptance. We conducted 45 interviews with those who intended to take the vaccine (Acceptors) and another 45 interviews with those who did not have that intention (Non-acceptors). We performed data analysis to find statistically significant differences and to identify which beliefs were most highly associated with acceptance and non-acceptance with COVID-19 vaccines.

RESULTS: The behavioral determinants associated with COVID-19 vaccine acceptance in Dhaka included perceived social norms, perceived safety of COVID-19 vaccines and trust in them, perceived risk/susceptibility, perceived self-efficacy, perceived positive and negative consequences, perceived action efficacy, perceived severity of COVID-19, access, and perceived divine will. In line with the HBM, beliefs about the disease itself were highly predictive of vaccine acceptance, and some of the strongest statistically-significant (p<0.001) predictors of vaccine acceptance in this population are beliefs around both injunctive and descriptive social norms. Specifically, Acceptors were 3.2 times more likely to say they would be very likely to get a COVID-19 vaccine if a doctor or nurse recommended it, twice as likely to say that most people they know will get a vaccine, and 1.3 times more likely to say that most close family and friends will get a vaccine. The perceived safety of vaccines was found to be important since Non-acceptors were 1.8 times more likely to say that COVID-19 vaccines are “not safe at all”. Beliefs about one’s risk of getting COVID-19 disease and the severity of it were predictive of being a vaccine acceptor: Acceptors were 1.4 times more likely to say that it was very likely that someone in their household would get COVID-19, 1.3 times more likely to say that they were very concerned about getting COVID-19, and 1.3 times more likely to say that it would be very serious if someone in their household contracted COVID-19. Other responses of Acceptors on what makes immunization easier may be helpful in programming to boost acceptance, such as providing vaccination through government health facilities, schools, and kiosks, and having vaccinators maintain proper COVID-19 health and safety protocols.

CONCLUSION: An effective behavior change strategy for COVID-19 vaccines uptake will need to address multiple beliefs and behavioral determinants, reducing barriers and leveraging enablers identified in this study. National plans for promoting COVID-19 vaccination should address the barriers, enablers, and behavioral determinants found in this study in order to maximize the impact on COVID-19 vaccination acceptance.

PMID:34424913 | DOI:10.1371/journal.pone.0256496

PLoS Comput Biol. 2021 Aug 23;17(8):e1009303. doi: 10.1371/journal.pcbi.1009303. Online ahead of print.

ABSTRACT

The development of mobile-health technology has the potential to revolutionize personalized medicine. Biomedical sensors (e.g. wearables) can assist with determining treatment plans for individuals, provide quantitative information to healthcare providers, and give objective measurements of health, leading to the goal of precise phenotypic correlates for genotypes. Even though treatments and interventions are becoming more specific and datasets more abundant, measuring the causal impact of health interventions requires careful considerations of complex covariate structures, as well as knowledge of the temporal and spatial properties of the data. Thus, interpreting biomedical sensor data needs to make use of specialized statistical models. Here, we show how the Bayesian structural time series framework, widely used in economics, can be applied to these data. This framework corrects for covariates to provide accurate assessments of the significance of interventions. Furthermore, it allows for a time-dependent confidence interval of impact, which is useful for considering individualized assessments of intervention efficacy. We provide a customized biomedical adaptor tool, MhealthCI, around a specific implementation of the Bayesian structural time series framework that uniformly processes, prepares, and registers diverse biomedical data. We apply the software implementation of MhealthCI to a structured set of examples in biomedicine to showcase the ability of the framework to evaluate interventions with varying levels of data richness and covariate complexity and also compare the performance to other models. Specifically, we show how the framework is able to evaluate an exercise intervention’s effect on stabilizing blood glucose in a diabetes dataset. We also provide a future-anticipating illustration from a behavioral dataset showcasing how the framework integrates complex spatial covariates. Overall, we show the robustness of the Bayesian structural time series framework when applied to biomedical sensor data, highlighting its increasing value for current and future datasets.

PMID:34424894 | DOI:10.1371/journal.pcbi.1009303

Acta Otolaryngol. 2021 Aug 23:1-4. doi: 10.1080/00016489.2021.1963473. Online ahead of print.

ABSTRACT

BACKGROUND: Mastoid portion of the facial nerve plays an important role in the round window approach of cochlear implantation.

OBJECTIVES: This study aimed to predict the anterior displacement of the mastoid portion of the facial nerve in the preoperative HRCT coronal cuts. We also aimed to detect the implication of anterior displacement of MPFN on the R.W. accessibility through the posterior tympanotomy during cochlear implantation.

MATERIALS AND METHODS: It was a retrospective observational cohort study in tertiary referral hospitals. We included 246 pediatric patients who underwent cochlear implantation due to bilateral severe to profound SNHL through a posterior tympanotomy approach.

RESULTS: Type I MPFN was present in 84 cases, type II MPFN was present in 149 patients, and type III MPFN was present in 13 cases. R.W. was inaccessible in 3 cases with MPFN type II and in 11 subjects with MPFN type III. There was a statistically significant difference regarding the R.W. accessibility between the three types of MPFN (p-value <.05). There was a strong statistically significant correlation between R.W. accessibility and the radiological type of the MPFN.

CONCLUSION: Mandour radiological classification of the mastoid portion of the facial nerve in the preoperative HRCT coronal offers an easily applicable method to detect the anterior displacement of the facial nerve by using easy and well-known landmarks. This classification can also predict R.W. accessibility through posterior tympanotomy during cochlear implantation with 97.97% accuracy.

PMID:34424819 | DOI:10.1080/00016489.2021.1963473

IEEE Trans Neural Netw Learn Syst. 2021 Aug 23;PP. doi: 10.1109/TNNLS.2021.3104896. Online ahead of print.

ABSTRACT

This article proposes a simple yet powerful ensemble classifier, called Random Hyperboxes, constructed from individual hyperbox-based classifiers trained on the random subsets of sample and feature spaces of the training set. We also show a generalization error bound of the proposed classifier based on the strength of the individual hyperbox-based classifiers as well as the correlation among them. The effectiveness of the proposed classifier is analyzed using a carefully selected illustrative example and compared empirically with other popular single and ensemble classifiers via 20 datasets using statistical testing methods. The experimental results confirmed that our proposed method outperformed other fuzzy min-max neural networks (FMNNs), popular learning algorithms, and is competitive with other ensemble methods. Finally, we identify the existing issues related to the generalization error bounds of the real datasets and inform the potential research directions.

PMID:34424848 | DOI:10.1109/TNNLS.2021.3104896

Am J Trop Med Hyg. 2021 Aug 23:tpmd201505. doi: 10.4269/ajtmh.20-1505. Online ahead of print.

ABSTRACT

Hydatidosis is a zoonosis of worldwide distribution with endemic areas in Argentina. The present epidemiological study was conducted to explore the presence of cystic echinococcosis in the rural community of Los Bordos (population 99), in the northern province of La Rioja, Argentina, during March 2018. The study included the search for cysts by abdominal ultrasound and a survey on family risk. Sixty-seven people agreed to undergo ultrasound examination, and five adults showed images compatible with hydatic cysts (7.5% prevalence). A family survey was applied to 29 households (78%), stratifying 24 families (83%) as high risk (95% confidence interval = 64.2-94.1) and 5 (17%) as low risk (95% confidence interval = 5.8-55.7) of transmission of the disease, respectively. The values were statistically different by the McNemar test. The goal of the present study, the first study of its kind in La Rioja, was to assess the family risk of echinococcosis among subjects with ultrasound images compatible with cystic echinococcosis.

PMID:34424861 | DOI:10.4269/ajtmh.20-1505

Can J Psychiatry. 2021 Aug 23:7067437211037125. doi: 10.1177/07067437211037125. Online ahead of print.

ABSTRACT

OBJECTIVE: Child and youth mental health problems are often assessed by parent self-completed checklists that produce dimensional scale scores. When converted to binary ratings of disorder, little is known about their psychometric properties in relation to classifications based on lay-administered structured diagnostic interviews. In addition to estimating agreement, our objective is to test for statistical equivalence in the test-retest reliability and construct validity of two instruments used to classify child emotional, behavioural, and attentional disorders: the 25-item, parent completed Ontario Child Health Study Emotional Behavioural Scales-Brief Version (OCHS-EBS-B) and the Mini International Neuropsychiatric Interview for Children and Adolescents-parent version (MINI-KID-P).

METHODS: This study draws on independent samples (n = 452) and uses the confidence interval approach to test for statistical equivalence. Reliability is based on kappa (κ). Construct validity is based on standardized beta coefficients (β) estimated in structural equation models.

RESULTS: The average differences between the MINI-KID-P and OCHS-EBS-B in κ and β were -0.022 and -0.020, respectively. However, in both instances, criteria for statistical equivalence were met in only 5 of 12 comparisons. Based on κ, between-instrument agreement on the classifications of disorder went from 0.481 (attentional disorder) to 0.721 (emotional disorder) but were substantially higher (0.731 to 0.895, respectively) when corrected for attenuation due to measurement error.

CONCLUSIONS: Although falling short of equivalence, the results suggest on balance that the reliability and validity of the two instruments for classifying child psychiatric disorder assessed by parents are highly comparable. This conclusion is supported by the high levels of agreement between the instruments after correcting for attenuation due to measurement error.

PMID:34424799 | DOI:10.1177/07067437211037125

Sci Prog. 2021 Jul-Sep;104(3):368504211029793. doi: 10.1177/00368504211029793.

ABSTRACT

Strong lockdowns to control COVID-19 pandemic have been enforced globally and strongly restricted social activities with consequent negative effects on mental health. Japan has effectively implemented a unique voluntary policy to control COVID-19, but the mental health impact of the policy has not been examined on a large scale. In this study, we examined the effect of the first declaration on the mental health of affected residents. We used population-level questionnaire data of 17,400 people living under the state of emergency and 9208 who were not through a social-networking-service app and applied a difference-in-differences regression model to estimate the causal effect of the declaration of the state of emergency on psychological wellbeing, stratified by job category. No statistically significant effect of the declaration was observed among all job categories. This suggests that residents’ psychological situation has gradually changed, possibly influenced by other factors such as the surrounding environment, rather than the declaration itself. Given that Japan has a unique policy to control COVID-19 instead of a strict lockdown, our results showed the Japanese-style policy may serve as a form of harm reduction strategy, to control the epidemic with minimal psychological harm, and enable a policy that balances disease control and mental health. Caution is necessary that this study used self-reported data from a limited time period before and after the first declaration in April 2020.

PMID:34424792 | DOI:10.1177/00368504211029793