Category: Nevin Manimala

PLoS One. 2022 Apr 21;17(4):e0266330. doi: 10.1371/journal.pone.0266330. eCollection 2022.

ABSTRACT

More than a year since the appearance of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), many questions about the disease COVID-19 have been answered; however, many more remain poorly understood. Although the situation continues to evolve, it is crucial to understand what factors may be driving transmission through different populations, both for potential future waves, as well as the implications for future pandemics. In this report, we compiled a database of more than 28 potentially explanatory variables for each of the 50 U.S. states through early May 2020. Using a combination of traditional statistical and modern machine learning approaches, we identified those variables that were the most statistically significant, and, those that were the most important. These variables were chosen to be fiduciaries of a range of possible drivers for COVID-19 deaths in the USA. We found that population-weighted population density (PWPD), some “stay at home” metrics, monthly temperature and precipitation, race/ethnicity, and chronic low-respiratory death rate, were all statistically significant. Of these, PWPD and mobility metrics dominated. This suggests that the biggest impact on COVID-19 deaths was, at least initially, a function of where you lived, and not what you did. However, clearly, increasing social distancing has the net effect of (at least temporarily) reducing the effective PWPD. Our results strongly support the idea that the loosening of “lock-down” orders should be tailored to the local PWPD. In contrast to these variables, while still statistically significant, race/ethnicity, health, and climate effects could only account for a few percent of the variability in deaths. Where associations were anticipated but were not found, we discuss how limitations in the parameters chosen may mask a contribution that might otherwise be present.

PMID:35446873 | DOI:10.1371/journal.pone.0266330

PLoS One. 2022 Apr 21;17(4):e0266897. doi: 10.1371/journal.pone.0266897. eCollection 2022.

ABSTRACT

BACKGROUND: For many drugs, mechanisms of action with regard to desired effects and/or unwanted side effects are only incompletely understood. To investigate possible pleiotropic effects and respective molecular mechanisms, we describe here a catalogue of commonly used drugs and their impact on the blood transcriptome.

METHODS AND RESULTS: From a population-based cohort in Germany (LIFE-Adult), we collected genome-wide gene-expression data in whole blood using in Illumina HT12v4 micro-arrays (n = 3,378; 19,974 gene expression probes per individual). Expression profiles were correlated with the intake of active substances as assessed by participants’ medication. This resulted in a catalogue of fourteen substances that were identified as associated with differential gene expression for a total of 534 genes. As an independent replication cohort, an observational study of patients with suspected or confirmed stable coronary artery disease (CAD) or myocardial infarction (LIFE-Heart, n = 3,008, 19,966 gene expression probes per individual) was employed. Notably, we were able to replicate differential gene expression for three active substances affecting 80 genes in peripheral blood mononuclear cells (carvedilol: 25; prednisolone: 17; timolol: 38). Additionally, using gene ontology enrichment analysis, we demonstrated for timolol a significant enrichment in 23 pathways, 19 of them including either GPER1 or PDE4B. In the case of carvedilol, we showed that, beside genes with well-established association with hypertension (GPER1, PDE4B and TNFAIP3), the drug also affects genes that are only indirectly linked to hypertension due to their effects on artery walls or their role in lipid biosynthesis.

CONCLUSIONS: Our developed catalogue of blood gene expressions profiles affected by medication can be used to support both, drug repurposing and the identification of possible off-target effects.

PMID:35446883 | DOI:10.1371/journal.pone.0266897

PLoS One. 2022 Apr 21;17(4):e0267388. doi: 10.1371/journal.pone.0267388. eCollection 2022.

ABSTRACT

IMPORTANCE: Screening and vaccination are essential in the fight against infectious diseases, but need to be integrated and customized based on community and disease characteristics.

OBJECTIVE: To develop effective screening and vaccination strategies, customized for a college campus, to reduce COVID-19 infections, hospitalizations, deaths, and peak hospitalizations.

DESIGN, SETTING, AND PARTICIPANTS: We construct a compartmental model of disease spread under vaccination and routine screening, and study the efficacy of four mitigation strategies (routine screening only, vaccination only, vaccination with partial or full routine screening), and a no-intervention strategy. The study setting is a hypothetical college campus of 5,000 students and 455 faculty members during the Fall 2021 academic semester, when the Delta variant was the predominant strain. For sensitivity analysis, we vary the screening frequency, daily vaccination rate, initial vaccine coverage, and screening and vaccination compliance; and consider scenarios that represent low/medium/high transmission and test efficacy. Model parameters come from publicly available or published sources.

RESULTS: With low initial vaccine coverage (30% in our study), even aggressive vaccination and screening result in a high number of infections: 1,020 to 2,040 (1,530 to 2,480) with routine daily (every other day) screening of the unvaccinated; 280 to 900 with daily screening extended to the newly vaccinated in base- and worst-case scenarios, which respectively consider reproduction numbers of 4.75 and 6.75 for the Delta variant.

CONCLUSION: Integrated vaccination and routine screening can allow for a safe opening of a college when both the vaccine effectiveness and the initial vaccine coverage are sufficiently high. The interventions need to be customized considering the initial vaccine coverage, estimated compliance, screening and vaccination capacity, disease transmission and adverse outcome rates, and the number of infections/peak hospitalizations the college is willing to tolerate.

PMID:35446872 | DOI:10.1371/journal.pone.0267388

PLoS One. 2022 Apr 21;17(4):e0266322. doi: 10.1371/journal.pone.0266322. eCollection 2022.

ABSTRACT

BACKGROUND: Labor pain management is crucial to ensure the quality of obstetric care but it is one of the neglected areas in obstetrics. This study aimed to assess the practice of labor pain management and associated factors among skilled attendants working in public health facilities in Southern, Ethiopia from November 1-January 26, 2019.

METHODS: An Institution-based cross-sectional study design was conducted from November 1-January 26, 2019. A simple random sampling technique was used to select a total of 272 obstetric care providers. Data were collected using pretested, and structured questionnaires. Data were entered to Epi data version 3.1 statistical software and exported to SPSS 22 for analysis. Bivariate and multivariate logistic regression analyses were performed to identify associated factors. P-value <0.05 with 95% confidence level were used to declare statistical significance.

RESULT: Overall, 37.5% (95%CI: 32%, 43%) of health care providers had a good practice on non-pharmacological labor pain management. Clinical experience of 5 years and above (AOR = 2.91, 95%CI: 1.60, 5.42), favorable attitude (AOR = 2.82, 95%CI: 1.56, 5.07), midwife profession (AOR = 1.45, 95%CI: 1.98, 4.27), and working in satisfactory delivery rooms (AOR = 3.45, 95%CI: 2.09, 7.43), were significantly associated with a health professional good practice of labor pain management.

CONCLUSION: This study showed that the practice of non-pharmacological labor pain management was poor in public health facilities in Gamo and Gofa zone. It was observed that having a favorable attitude, having ≥5 years of work experience, being a midwife by professional, and having a satisfactory delivery room were found to be significant predictors of the practice of non -pharmacological labor pain management. Therefore, all health facilities and concerned bodies need efforts to focus on providing training to midwives on non-pharmacological labor pain management practice.

PMID:35446867 | DOI:10.1371/journal.pone.0266322

PLoS One. 2022 Apr 21;17(4):e0265406. doi: 10.1371/journal.pone.0265406. eCollection 2022.

ABSTRACT

OBJECTIVE: We aimed to explore factors affecting family health management during home quarantine as well as the effects of variations in family health management (FHM) on individuals’ health status.

METHODS: Using stratified random sampling, 618 families in Wuhan as well as cities within its surrounding provinces were recruited and surveyed online. Latent class variables were extracted from four modules: disinfection, space layout, physical exercise, and food reserves. The analysis was conducted using the poLCA package in R software (v.4.1.0). Chi-squared tests, Fisher’s exact tests, and non-parametric Kruskal-Wallis tests were used to compare groups as appropriate.

RESULTS: We found an overall questionnaire reliability of 0.77 and a total omega of 0.92, indicating that the survey results were credible. The Bayesian information criterion and Akaike information criterion were used to identified four latent class variables, namely latent non-family health management (18.9%) and latent low, medium, and advanced FHM (30.93%, 29.49%, and 20.59%, respectively). Gender, household income level, body mass index, the presence of a nearby community hospital, and self-rated health status showed statistically significant differences with respect to latent FHM. Moreover, we found a statistically significant difference in emotional reactions when comparing latent advanced and low to mid-level latent FHM. Compared with latent non-family health managers, we detected statistically significant differences in individual energy levels between potential family health managers at latent low and medium levels. Additionally, we found statistically significant differences in individual energy levels between latent advanced and low level family health managers.

CONCLUSIONS: We found that multiple factors, including gender, household income, and body mass index, were correlated with latent FHM during home quarantine. We conclude that FHM can meaningfully improve individuals’ health. Thus, increasing social support for individuals can improve FHM as well as individuals’ health during home quarantine.

PMID:35446866 | DOI:10.1371/journal.pone.0265406

PLoS One. 2022 Apr 21;17(4):e0266780. doi: 10.1371/journal.pone.0266780. eCollection 2022.

ABSTRACT

BACKGROUND: Colonoscopy is widely used for the screening, diagnosis and treatment of intestinal diseases. Adequate bowel preparation is a prerequisite for high-quality colonoscopy. However, the rate of adequate bowel preparation in outpatients is low. Several studies on supplementary education methods have been conducted to improve the rate of adequate bowel preparation in outpatients. However, the controversial results presented encourage us to perform this meta-analysis.

METHOD: According to the PRISMA statement (2020), the meta-analysis was registered on PROSPERO. We searched all studies up to August 28, 2021, in the three major electronic databases of PubMed, Web of Science and Cochrane Library. The primary outcome was adequate bowel preparation rate, and the secondary outcomes included bowel preparation quality score, polyp detection rate, adenoma detection rate, cecal intubation time, withdrawal time, nonattendance rate and willingness to repeat rate. If there was obvious heterogeneity, the funnel plot combined with Egger’s test, meta-regression analysis, sensitivity analysis and subgroup analysis were used to detect the source of heterogeneity. RevMan 5.3 and Stata 17.0 software were used for statistical analysis.

RESULTS: A total of 2061 records were retrieved, and 21 full texts were ultimately included in the analysis. Our meta-analysis shows that supplementary education can increase the rate of adequate bowel preparation for outpatients (79.9% vs 72.9%, RR = 1.14, 95% CI: 1.08-1.20, I2 = 87%, p<0.00001). Supplementary education shortened the withdrawal time (MD: -0.80, 95% CI: -1.54 to -0.05, p = 0.04) of outpatients, increased the Boston Bowel Preparation Scale (MD: 0.40, 95% CI: 0.36 to 0.44, p<0.00001), reduced the Ottawa Bowel Preparation Scale (MD: -1.26, 95% CI: -1.66 to -0.86, p<0.00001) and increased the willingness to repeat (91.9% vs 81.4%, RR:1.14, 95% CI: 1.04 to 1.25, p = 0.004).

CONCLUSION: Supplementary education for outpatients based on the standard of care can significantly improve the quality of bowel preparation.

PMID:35446863 | DOI:10.1371/journal.pone.0266780

PLoS Comput Biol. 2022 Apr 21;18(4):e1010033. doi: 10.1371/journal.pcbi.1010033. eCollection 2022 Apr.

NO ABSTRACT

PMID:35446846 | DOI:10.1371/journal.pcbi.1010033

PLoS One. 2022 Apr 21;17(4):e0263977. doi: 10.1371/journal.pone.0263977. eCollection 2022.

ABSTRACT

The results of a simulation-based evaluation of several policies for vaccine rollout are reported, particularly focusing on the effects of delaying the second dose of two-dose vaccines. In the presence of limited vaccine supply, the specific policy choice is a pressing issue for several countries worldwide, and the adopted course of action will affect the extension or easing of non-pharmaceutical interventions in the next months. We employ a suitably generalised, age-structure, stochastic SEIR (Susceptible → Exposed → Infectious → Removed) epidemic model that can accommodate quantitative descriptions of the major effects resulting from distinct vaccination strategies. The different rates of social contacts among distinct age-groups (as well as some other model parameters) are informed by a recent survey conducted in Greece, but the conclusions are much more widely applicable. The results are summarised and evaluated in terms of the total number of deaths and infections as well as life years lost. The optimal strategy is found to be one based on fully vaccinating the elderly/at risk as quickly as possible, while extending the time-interval between the two vaccine doses to 12 weeks for all individuals below 75 years old, in agreement with epidemic theory which suggests targeting a combination of susceptibility and infectivity. This policy, which is similar to the approaches adopted in the UK and in Canada, is found to be effective in reducing deaths and life years lost in the period while vaccination is still being carried out.

PMID:35446847 | DOI:10.1371/journal.pone.0263977

PLoS Comput Biol. 2022 Apr 21;18(4):e1010066. doi: 10.1371/journal.pcbi.1010066. Online ahead of print.

ABSTRACT

Machine learning-based classification approaches are widely used to predict host phenotypes from microbiome data. Classifiers are typically employed by considering operational taxonomic units or relative abundance profiles as input features. Such types of data are intrinsically sparse, which opens the opportunity to make predictions from the presence/absence rather than the relative abundance of microbial taxa. This also poses the question whether it is the presence rather than the abundance of particular taxa to be relevant for discrimination purposes, an aspect that has been so far overlooked in the literature. In this paper, we aim at filling this gap by performing a meta-analysis on 4,128 publicly available metagenomes associated with multiple case-control studies. At species-level taxonomic resolution, we show that it is the presence rather than the relative abundance of specific microbial taxa to be important when building classification models. Such findings are robust to the choice of the classifier and confirmed by statistical tests applied to identifying differentially abundant/present taxa. Results are further confirmed at coarser taxonomic resolutions and validated on 4,026 additional 16S rRNA samples coming from 30 public case-control studies.

PMID:35446845 | DOI:10.1371/journal.pcbi.1010066

PLoS One. 2022 Apr 21;17(4):e0252736. doi: 10.1371/journal.pone.0252736. eCollection 2022.

ABSTRACT

BACKGROUND: The correct estimation of fibre orientations is a crucial step for reconstructing human brain tracts. Bayesian Estimation of Diffusion Parameters Obtained using Sampling Techniques (bedpostx) is able to estimate several fibre orientations and their diffusion parameters per voxel using Markov Chain Monte Carlo (MCMC) in a whole brain diffusion MRI data, and it is capable of running on GPUs, achieving speed-up of over 100 times compared to CPUs. However, few studies have looked at whether the results from the CPU and GPU algorithms differ. In this study, we compared CPU and GPU bedpostx outputs by running multiple trials of both algorithms on the same whole brain diffusion data and compared each distribution of output using Kolmogorov-Smirnov tests.

RESULTS: We show that distributions of fibre fraction parameters and principal diffusion direction angles from bedpostx and bedpostx_gpu display few statistically significant differences in shape and are localized sparsely throughout the whole brain. Average output differences are small in magnitude compared to underlying uncertainty.

CONCLUSIONS: Despite small amount of differences in output between CPU and GPU bedpostx algorithms, results are comparable given the difference in operation order and library usage between CPU and GPU bedpostx.

PMID:35446840 | DOI:10.1371/journal.pone.0252736