Tag: pubmed

PLoS One. 2021 Dec 23;16(12):e0261120. doi: 10.1371/journal.pone.0261120. eCollection 2021.

ABSTRACT

Data-based instruction (DBI) is an ongoing process to utilize students’ data for determining when and how to intensify intervention. It is an educational approach that is suggested as effective to enhance achievements of struggling learners, particularly for those who did not respond to intensive intervention in usual ways. In Korea, DBI was introduced and applied for students with learning difficulties especially since 2000 when the first Korea curriculum-based measurement (CBM) was developed as the name of Basic Academic Skills Assessment. Despite a number of studies accumulated since then, there has been a lack of research that examined the level of evidence-based practice (EBP) of DBI research. Thus, the present study sought to synthesize the DBI research so far in Korea by analyzing the effectiveness of DBI for school-aged students with learning difficulties via meta-analysis and evaluating the quality of the research. In this study, a total of 32 single-subject design studies were used. Multilevel meta-analysis revealed that the mean effect size of DBI was statistically significant (B = 1.34) and there was significant variance across participants in effect sizes. The results from the conditional model showed that exceptionality type, the number of sessions, and the length of each session were significantly accountable for the variability of effect sizes. In addition, the results of the qualitative analysis revealed the acceptable quality of the overall DBI research with some limitations. Based on these findings, implications and study limitations were discussed.

PMID:34941909 | DOI:10.1371/journal.pone.0261120

PLoS One. 2021 Dec 23;16(12):e0261746. doi: 10.1371/journal.pone.0261746. eCollection 2021.

ABSTRACT

OBJECTIVE: Women living with HIV (WLWH) experience psychosocial stress related to social-structural vulnerabilities. To investigate neuroendocrine pathways linking stress and increased cardiovascular disease risk among WLWH, we evaluated associations between psychosocial stress (i.e., perceived stress, posttraumatic stress, and experiences of race- and gender-based harassment) and a composite neuroendocrine biomarker index among WLWH and women without HIV.

METHODS: In 2019-2020, Women’s Interagency HIV Study participants in Washington, DC completed a questionnaire and provided blood and 12-hour overnight urine samples for testing of serum dehydroepiandrosterone sulfate (DHEA-S) and urinary free cortisol, epinephrine, and norepinephrine. Psychosocial stress was measured using the Perceived Stress Scale, PTSD Checklist-Civilian Version, and Racialized Sexual Harassment Scale. Latent profile analysis was used to classify participants into low (38%), moderate (44%), and high (18%) stress groups. Composite biomarker index scores between 0-4 were assigned based on participants’ number of neuroendocrine biomarkers in high-risk quartiles (≥75th percentile for cortisol, epinephrine, and norepinephrine and ≤25th percentile for DHEA-S). We evaluated associations between latent profile and composite biomarker index values using multivariable linear regression, adjusting for socio-demographic, behavioral, metabolic, and HIV-related factors.

RESULTS: Among 90 women, 62% were WLWH, 53% were non-Hispanic Black, and median age was 55 years. In full multivariable models, there was no statistically significant association between psychosocial stress and composite biomarker index values among all women independent of HIV status. High (vs. low) psychosocial stress was positively associated with higher mean composite biomarker index values among all monoracial Black women (adjusted β = 1.32; 95% CI: 0.20-2.43), Black WLWH (adjusted β = 1.93; 95% CI: 0.02-3.83) and Black HIV-negative women (adjusted β = 2.54; 95% CI: 0.41-4.67).

CONCLUSIONS: Despite a null association in the overall sample, greater psychosocial stress was positively associated with higher neuroendocrine biomarker concentrations among Black women, highlighting a plausible mechanism by which psychosocial stress could contribute to cardiovascular disease risk.

PMID:34941922 | DOI:10.1371/journal.pone.0261746

PLoS One. 2021 Dec 23;16(12):e0260937. doi: 10.1371/journal.pone.0260937. eCollection 2021.

ABSTRACT

Data from the 2016-17 Multiple Indicator Cluster Survey from Nigeria are used to study the relationship between child stature, mother’s years of education, and indicators of early childhood development (ECD). The relationships are contrasted between two empirical approaches: the conventional approach whereby control variables are selected in an ad-hoc manner, and the double machine-learning (DML) approach that employs data-driven methods to select controls from a much wider set of variables and thus reducing potential omitted variable bias. Overall, the analysis confirms that maternal education and the incidence of chronic malnutrition have a significant direct effect on measures of early childhood development. The point estimates based on the ad-hoc specification tend to be larger in absolute value than those based on the DML specification. Frequently, the point estimates based on the ad-hoc specification fall inside the confidence interval of the DML point estimates, suggesting that in these cases the omitted variable bias is not serious enough to prevent making causal inferences based on the ad-hoc specification. However, there are instances where the omitted variable bias is sufficiently large for the ad hoc specification to yield a statistically significant relationship when in fact the more robust DML specification suggests there is none. The DML approach also reveals a more complex picture that highlights the role of context. In rural areas, mother’s education affects early childhood development both directly and indirectly through its impact on the nutritional status of both older and younger children. In contrast, in urban areas, where the average level of maternal education is much higher, increases in a mother’s education have only a direct effect on child ECD measures but no indirect effect through child nutrition. Thus, DML provides a practical and feasible approach to reducing threats to internal validity for robust inferences and policy design based on observational data.

PMID:34941902 | DOI:10.1371/journal.pone.0260937

PLoS One. 2021 Dec 23;16(12):e0260730. doi: 10.1371/journal.pone.0260730. eCollection 2021.

ABSTRACT

This study aimed to clarify the etiologic factors predicting acute ocular progression in SJS/TEN, and identify patients who require immediate and intensive ophthalmological treatment. We previously conducted two Japanese Surveys of SJS/TEN (i.e., cases arising between 2005-2007 and between 2008-2010), and obtained the medical records, including detailed dermatological and ophthalmological findings, of 230 patients. Acute ocular severity was evaluated as none, mild, severe, and very severe. A multi-state model assuming the Markov process based on the Cox proportional hazards model was used to elucidate the specific factors affecting the acute ocular progression. Our findings revealed that of the total 230 patients, 23 (24%) of 97 cases that were mild at initial presentation worsened to severe/very severe. Acute ocular progression developed within 3 weeks from disease onset. Exposure to nonsteroidal anti-inflammatory drugs (NSAIDs) and younger patient age were found to be statistically significant for the progression of ocular severity from mild to severe/very severe [hazard ratio (HR) 3.83; 95% confidence interval (CI) 1.48 to 9.91] and none to severe/very severe [HR 0.98; 95% CI 0.97 to 0.99], respectively. The acute ocular severity score at worst-condition was found to be significantly correlated with ocular sequelae. Thus, our detailed findings on acute ocular progression revealed that in 24% of SJS/TEN cases with ocular involvement, ocular severity progresses even after initiating intensive treatment, and that in younger-age patients with a history of exposure to NSAIDs, very strict attention must be given to their ophthalmological appearances.

PMID:34941887 | DOI:10.1371/journal.pone.0260730

PLoS One. 2021 Dec 23;16(12):e0259877. doi: 10.1371/journal.pone.0259877. eCollection 2021.

ABSTRACT

The shape of phylogenetic trees can be used to gain evolutionary insights. A tree’s shape specifies the connectivity of a tree, while its branch lengths reflect either the time or genetic distance between branching events; well-known measures of tree shape include the Colless and Sackin imbalance, which describe the asymmetry of a tree. In other contexts, network science has become an important paradigm for describing structural features of networks and using them to understand complex systems, ranging from protein interactions to social systems. Network science is thus a potential source of many novel ways to characterize tree shape, as trees are also networks. Here, we tailor tools from network science, including diameter, average path length, and betweenness, closeness, and eigenvector centrality, to summarize phylogenetic tree shapes. We thereby propose tree shape summaries that are complementary to both asymmetry and the frequencies of small configurations. These new statistics can be computed in linear time and scale well to describe the shapes of large trees. We apply these statistics, alongside some conventional tree statistics, to phylogenetic trees from three very different viruses (HIV, dengue fever and measles), from the same virus in different epidemiological scenarios (influenza A and HIV) and from simulation models known to produce trees with different shapes. Using mutual information and supervised learning algorithms, we find that the statistics adapted from network science perform as well as or better than conventional statistics. We describe their distributions and prove some basic results about their extreme values in a tree. We conclude that network science-based tree shape summaries are a promising addition to the toolkit of tree shape features. All our shape summaries, as well as functions to select the most discriminating ones for two sets of trees, are freely available as an R package at http://github.com/Leonardini/treeCentrality.

PMID:34941890 | DOI:10.1371/journal.pone.0259877

PLoS One. 2021 Dec 23;16(12):e0259996. doi: 10.1371/journal.pone.0259996. eCollection 2021.

ABSTRACT

OBJECTIVES: To evaluate (1) the relationship between heating, ventilation, and air conditioning (HVAC) systems and bioaerosol concentrations in hospital rooms, and (2) the effectiveness of laminar air flow (LAF) and high efficiency particulate air (HEPA) according to the indoor bioaerosol concentrations.

METHODS: Databases of Embase, PubMed, Cochrane Library, MEDLINE, and Web of Science were searched from 1st January 2000 to 31st December 2020. Two reviewers independently extracted data and assessed the quality of the studies. The samples obtained from different areas of hospitals were grouped and described statistically. Furthermore, the meta-analysis of LAF and HEPA were performed using random-effects models. The methodological quality of the studies included in the meta-analysis was assessed using the checklist recommended by the Agency for Healthcare Research and Quality.

RESULTS: The mean CFU/m3 of the conventional HVAC rooms and enhanced HVAC rooms was lower than that of rooms without HVAC systems. Furthermore, the use of the HEPA filter reduced bacteria by 113.13 (95% CI: -197.89, -28.38) CFU/m3 and fungi by 6.53 (95% CI: -10.50, -2.55) CFU/m3. Meanwhile, the indoor bacterial concentration of LAF systems decreased by 40.05 (95% CI: -55.52, -24.58) CFU/m3 compared to that of conventional HVAC systems.

CONCLUSIONS: The HVAC systems in hospitals can effectively remove bioaerosols. Further, the use of HEPA filters is an effective option for areas that are under-ventilated and require additional protection. However, other components of the LAF system other than the HEPA filter are not conducive to removing airborne bacteria and fungi.

LIMITATION OF STUDY: Although our study analysed the overall trend of indoor bioaerosols, the conclusions cannot be extrapolated to rare, hard-to-culture, and highly pathogenic species, as well as species complexes. These species require specific culture conditions or different sampling requirements. Investigating the effects of HVAC systems on these species via conventional culture counting methods is challenging and further analysis that includes combining molecular identification methods is necessary.

STRENGTH OF THE STUDY: Our study was the first meta-analysis to evaluate the effect of HVAC systems on indoor bioaerosols through microbial incubation count. Our study demonstrated that HVAC systems could effectively reduce overall bioaerosol concentrations to maintain better indoor air quality. Moreover, our study provided further evidence that other components of the LAF system other than the HEPA filter are not conducive to removing airborne bacteria and fungi.

PRACTICAL IMPLICATION: Our research showed that HEPA filters are more effective at removing bioaerosols in HVAC systems than the current LAF system. Therefore, instead of opting for the more costly LAF system, a filter with a higher filtration rate would be a better choice for indoor environments that require higher air quality; this is valuable for operating room construction and maintenance budget allocation.

PMID:34941879 | DOI:10.1371/journal.pone.0259996

PLoS One. 2021 Dec 23;16(12):e0261152. doi: 10.1371/journal.pone.0261152. eCollection 2021.

ABSTRACT

BACKGROUND: Loss to follow-up (LTFU) among pulmonary tuberculosis (PTB) patients is a significant challenge for TB control. However, there is a dearth of information about the factors leading to LTFU among marginalized communities. This study highlights the factors associated with LTFU in Saharia, a tribe of Madhya Pradesh having high tuberculosis (TB) prevalence.

METHODS: A qualitative study was carried out during January-April 2020 among twenty-two pulmonary TB patients, recorded as LTFU in NIKSHAY, with ten treatment supporters and ten patient’s family members. Semi-structured personal interview tools were used to collect the information on the history of anti-tuberculosis treatment, adverse drug events (ADE), social cognitive, behaviors, myths, and misbeliefs. The interviews were transcribed and thematically analysed to examine underlying themes.

RESULTS: The study explored various social, behavioral factors leading to loss to follow-up among PTB patients. Drug side effects, alcoholism, social stigma, lack of awareness of the seriousness of the diseases and poor counseling are the main barriers to treatment adherence in this community.

CONCLUSIONS: The study highlights the need to address the issues related to LTFU during TB treatment. The enhanced efforts of treatment supporters, health staff, and family & community persons must motivate and support the patients.

PMID:34941885 | DOI:10.1371/journal.pone.0261152

PLoS Comput Biol. 2021 Dec 23;17(12):e1009295. doi: 10.1371/journal.pcbi.1009295. Online ahead of print.

ABSTRACT

Pre-exposure prophylaxis (PrEP) is an important pillar to prevent HIV transmission. Because of experimental and clinical shortcomings, mathematical models that integrate pharmacological, viral- and host factors are frequently used to quantify clinical efficacy of PrEP. Stochastic simulations of these models provides sample statistics from which the clinical efficacy is approximated. However, many stochastic simulations are needed to reduce the associated sampling error. To remedy the shortcomings of stochastic simulation, we developed a numerical method that allows predicting the efficacy of arbitrary prophylactic regimen directly from a viral dynamics model, without sampling. We apply the method to various hypothetical dolutegravir (DTG) prophylaxis scenarios. The approach is verified against state-of-the-art stochastic simulation. While the method is more accurate than stochastic simulation, it is superior in terms of computational performance. For example, a continuous 6-month prophylactic profile is computed within a few seconds on a laptop computer. The method’s computational performance, therefore, substantially expands the horizon of feasible analysis in the context of PrEP, and possibly other applications.

PMID:34941864 | DOI:10.1371/journal.pcbi.1009295

Vet Sci. 2021 Dec 13;8(12):328. doi: 10.3390/vetsci8120328.

ABSTRACT

Feline infectious peritonitis (FIP) is a fatal disease caused by feline coronavirus or its variant, referred to as the FIP virus. Recently, favorable treatment outcomes of the anti-viral drug Mutian^® Xraphconn (Mutian X) were noted in cats with FIP. Thus, the therapeutic efficacy of Mutian X in cats with FIP must be explored, although the predictors of therapeutic success remain unknown. In the present study, we administered Mutian X to 141 pet cats with effusive FIP following initial veterinarian examinations. Of these, 116 cats survived but the remaining 25 died during treatment. Pre-treatment signalment, viral gene expression, and representative laboratory parameters for routine FIP diagnosis (i.e., hematocrit, albumin-to-globulin ratio, total bilirubin, serum amyloid-A, and α1-acid glycoprotein) were statistically compared between the survivor and non-survivor groups. The majority of these parameters, including hematocrit, albumin-to-globulin ratio, serum amyloid-A, α1-acid glycoprotein, and viral gene expression, were comparable between the two groups. Interestingly, however, total bilirubin levels in the survivor group were significantly lower than those in the non-survivor group (p < 0.0001). Furthermore, in almost all surviving cats with effusive FIP (96.6%, 28/29), the pre-treatment total bilirubin levels were below 0.5 mg/dL; however, the survival rate decreased drastically (14.3%, 1/7) when the pre-treatment total bilirubin levels exceeded 4.0 mg/dL. Thus, circulating total bilirubin levels may act as a prognostic risk factor for severe FIP and may serve as the predictor of the therapeutic efficacy of Mutian X against this fatal disease.

PMID:34941855 | DOI:10.3390/vetsci8120328

J Cardiovasc Med (Hagerstown). 2021 Dec 16. doi: 10.2459/JCM.0000000000001267. Online ahead of print.

ABSTRACT

BACKGROUND: Data of the EMPA-REG OUTCOME study have demonstrated a beneficial effect of the sodium-glucose cotransporter 2 inhibitor empagliflozin on cardiovascular outcome in patients with type 2 diabetes. The reduction in cardiovascular mortality and hospitalization due to heart failure might be in part explained by the direct effects of empagliflozin on cardiac diastolic function. The EmDia trial investigates the short-term effects of empagliflozin compared to placebo on the left ventricular E/E’ ratio as a surrogate of left ventricular diastolic function.

METHODS AND RESULTS: EmDia is a single-center, randomized, double-blind, two-arm, placebo-controlled, parallel group study of phase IV. Individuals with diabetes mellitus type 2 (T2DM) are randomized 1:1 to receive empagliflozin 10 mg per day or a placebo for 12 weeks. The main inclusion criteria are diagnosed as T2DM with stable glucose-lowering and/or dietary treatment, elevated HbA1c level (6.5-10.0% if receiving glucose-lowering therapy, or 6.5-9.0% if drug-naive), and diastolic cardiac dysfunction with left ventricular E/E’>=8. The primary end point is the difference of the change in the E/E’ ratio by treatment groups after 12 weeks. Secondary end points include assessment of the effect of empagliflozin on left ventricular systolic function, measures of vascular structure and function, as well as humoral cardiovascular biomarkers (i.e. brain natriuretic peptide, troponin, C-reactive protein). In addition, the multidimensional biodatabase enables explorative analyses of molecular biomarkers to gain insights into possible mechanisms of the effects of empagliflozin on human health in a systems medicine-oriented, multiomics approach.

CONCLUSION: By evaluating the short-term effect of empagliflozin with a comprehensive biobanking program, the EmDia Study offers an opportunity to primarily assess the effects on diastolic function but also to examine effects on clinical and molecular cardiovascular traits.

TRIAL REGISTRATION: ClinicalTrials.gov; NCT02932436. Registration date, 2016/10/13.

PMID:34939776 | DOI:10.2459/JCM.0000000000001267