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Nevin Manimala Statistics

Clinical and epidemiological characteristics of patients seeking COVID-19 testing in a private centre in Malaysia: Is there a role for private healthcare in battling the outbreak?

PLoS One. 2021 Oct 14;16(10):e0258671. doi: 10.1371/journal.pone.0258671. eCollection 2021.

ABSTRACT

OBJECTIVE: This cross-sectional observational study summarized the baseline characteristics of subjects who underwent COVID-19 molecular testing in a private medical centre located in the state of Selangor in Malaysia between 1 Oct 2020 and 31 Jan 2021. We compared the baseline characteristics between subjects who were tested positive and negative of SARS-CoV-2 infection, and identified risk factors which may be predictive of SARS-CoV-2 positivity.

METHODS AND FINDINGS: A total of 36603 subjects who were tested for COVID-19 infection via molecular assays at Sunway Medical Centre between Oct 1, 2020 and Jan 31, 2021, and consented to participate in this observation study were included for analysis. Descriptive statistics was used to summarize the study cohort, whereas logistic regression analysis was used to identify risk factors associated with SARS-CoV-2 positivity. Among the reasons listed for COVID-19 screening were those who needed clearance for travelling, clearance to return to work, or clearance prior to hospital admission. They accounted for 67.7% of tested subjects, followed by the self-referred group (27.3%). Most of the confirmed cases were asymptomatic (62.6%), had no travel history (99.6%), and had neither exposure to SARS-CoV-2 confirmed cases (61.9%) nor exposure to patients under investigation (82.7%) and disease clusters (89.2%). Those who presented with loss of smell or taste (OR: 26.91; 95% CI: 14.81-48.92, p<0.001), fever (OR:3.97; 95% CI: 2.54-6.20, p<0.001), running nose (OR: 1.75; 95% CI:1.10-2.79, p = 0.019) or other symptoms (OR: 5.63; 95% CI:1.68-18.91, p = 0.005) were significantly associated with SARS-CoV-2 positivity in the multivariate logistic regression analysis.

CONCLUSION: Our study showed that majority of patients seeking COVID-19 testing in a private healthcare setting were mainly asymptomatic with low epidemiological risk. Consequently, the average positivity rate was 1.2% compared to the national cumulative positivity rate of 4.65%. Consistent with other studies, we found that loss of smell or taste, fever and running nose were associated with SARS-CoV-2 positivity. We believe that strengthening the capacity of private health institutions is important in the national battle against the COVID-19 pandemic, emphasizing the importance of public-private partnership to improve the quality of clinical care.

PMID:34648575 | DOI:10.1371/journal.pone.0258671

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Nevin Manimala Statistics

Estimated glomerular filtration rate may be an independent predictor for clinical outcomes regardless of acute kidney injury complication in the emergency department

PLoS One. 2021 Oct 14;16(10):e0258665. doi: 10.1371/journal.pone.0258665. eCollection 2021.

ABSTRACT

STUDY OBJECTIVE: Acute kidney injury (AKI), chronic kidney disease (CKD), and decreased estimated glomerular filtration rate (eGFR) are all associated with poor clinical outcomes among emergency department (ED) patients. This study aimed to evaluate the effect of different types of renal dysfunction and the degree of eGFR reduction on the clinical outcomes in a real-world ED setting.

METHODS: Adult patients with an eGFR lower than 60 mL/min/1.73m2 in our ED, from October 1, 2016, to December 31, 2016, were enrolled in this retrospective observational study. Besides AKI and CKD, patients with unknown baseline renal function before an ED visit were categorized in the undetermined renal dysfunction (URD) category.

RESULTS: Among 1495 patients who had eGFR evaluation at ED, this study finally enrolled 441 patients; 22 patients (5.0%) had AKI only, 32 (7.3%) had AKI on CKD, 196 (44.4%) had CKD only, 27 (6.1%) had subclinical kidney injury (those who met neither criteria for AKI nor CKD), and 164 (37.2%) had URD. There was a significant association between eGFR and critical illness defined as the composite outcome of death or intensive care unit (ICU) need, hospitalization, ICU need, death, and renal replacement therapy need (odds ratio [95% confidence interval]: 1.72 [1.45-2.05], 1.36 [1.16-1.59], 1.66 [1.39-2.00], 1.73 [1.32-2.28], and 2.71 [1.73-4.24] for every 10 mL/min/1.73m2 of reduction, respectively). Multivariate logistic regression analysis showed eGFR was an independent predictor of critical illness composite outcome (death or ICU need), hospitalization, and ICU need even after adjustment with AKI or URD.

CONCLUSIONS: Estimated GFR may be a sufficient predictor of clinical outcomes of ED patients regardless of AKI complication. Considerable ED patients were determined as URD, which might have a significant impact on the ED statistics regarding renal dysfunction.

PMID:34648576 | DOI:10.1371/journal.pone.0258665

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Nevin Manimala Statistics

Factors associated with nutritional status, knowledge and attitudes among tuberculosis patients receiving treatment in Ghana: A cross-sectional study in the Tema Metropolis

PLoS One. 2021 Oct 14;16(10):e0258033. doi: 10.1371/journal.pone.0258033. eCollection 2021.

ABSTRACT

BACKGROUND: Nutritional deficiencies are generally associated with increased risk and severity of tuberculosis. This study investigated the nutritional status, knowledge, and attitudes of tuberculosis (TB) patients receiving treatment in the Tema Metropolis.

METHOD: A cross-sectional design was used to collect data on the nutritional knowledge, attitude, and status of TB patients. Nutritional status was analysed using World Health Organization’s formula for body mass index. Pearson’s chi-square and logistic regression models were used to assess associations between predictor and outcome variables. All statistical analyses were considered significant at p-values < 0.05.

RESULT: The prevalence of malnutrition among TB patients was 39.7%, 14.4%, and 4.8% for underweight, overweight, and obesity respectively. There was a high (61.0%) knowledge of nutrition among the patients. Also, 65.8% had good attitude towards nutrition. There were significant associations between normal nutritional status and age of the TB patients (p = 0.041), highest educational level attained (p = 0.036), employment status (p = 0.019), status of alcohol intake (p = 0.031), number of months on TB treatment (p = 0.021), and attitude towards nutrition (p = 0.028).

CONCLUSION: There was a reasonable nutrition-related knowledge and attitude towards nutrition among the TB patients. However, that did not reflect on their nutritional status. We recommend continuing education on smoking cessation, avoidance of harmful use of alcohol, and the establishment of food aid and other livelihood intervention programs for TB patients.

PMID:34648547 | DOI:10.1371/journal.pone.0258033

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Nevin Manimala Statistics

Differences in the gray-to-white matter ratio according to different computed tomography scanners for outcome prediction in post-cardiac arrest patients receiving target temperature management

PLoS One. 2021 Oct 14;16(10):e0258480. doi: 10.1371/journal.pone.0258480. eCollection 2021.

ABSTRACT

The gray-to-white matter ratio (GWR) has been used to identify brain damage in comatose patients after cardiac arrest. However, Hounsfield units (HUs), the measurement of brain density on computed tomography (CT) images, may vary depending on the machine type or parameter. Therefore, differences in CT scanners may affect the GWR in post-cardiac arrest patients. We performed a retrospective study on comatose post-cardiac arrest patients who visited the hospital from 2007 to 2017. Two CT, Lightspeed and SOMATOM, scanners were used. Two observers independently measured the HUs of the caudate nucleus, putamen, posterior internal capsule, and corpus callosum using regions of interest. We compared the GWR calculated from the HUs measured at different CT scanners. The analysis of different scanners showed statistically significant differences in the measured HUs and GWR. The HUs and GWR of Lightspeed were measured lower than SOMATOM. The difference between the two CT scanners was also evident in groups divided by neurological prognosis. The area under the curve of the receiver operating characteristic curve to predict poor outcomes of Lightspeed was 0.798, and the cut-off value for 100% specificity was 1.172. The SOMATOM was 0.855, and the cut-off value was 1.269. The difference in scanners affects measurements and performance characteristics of the GWR in post-cardiac arrest patients. Therefore, when applying the results of the GWR study to clinical practice, reference values for each device should be presented, and an integrated plan should be prepared.

PMID:34648574 | DOI:10.1371/journal.pone.0258480

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Nevin Manimala Statistics

Bayesian analysis of static light scattering data for globular proteins

PLoS One. 2021 Oct 14;16(10):e0258429. doi: 10.1371/journal.pone.0258429. eCollection 2021.

ABSTRACT

Static light scattering is a popular physical chemistry technique that enables calculation of physical attributes such as the radius of gyration and the second virial coefficient for a macromolecule (e.g., a polymer or a protein) in solution. The second virial coefficient is a physical quantity that characterizes the magnitude and sign of pairwise interactions between particles, and hence is related to aggregation propensity, a property of considerable scientific and practical interest. Estimating the second virial coefficient from experimental data is challenging due both to the degree of precision required and the complexity of the error structure involved. In contrast to conventional approaches based on heuristic ordinary least squares estimates, Bayesian inference for the second virial coefficient allows explicit modeling of error processes, incorporation of prior information, and the ability to directly test competing physical models. Here, we introduce a fully Bayesian model for static light scattering experiments on small-particle systems, with joint inference for concentration, index of refraction, oligomer size, and the second virial coefficient. We apply our proposed model to study the aggregation behavior of hen egg-white lysozyme and human γS-crystallin using in-house experimental data. Based on these observations, we also perform a simulation study on the primary drivers of uncertainty in this family of experiments, showing in particular the potential for improved monitoring and control of concentration to aid inference.

PMID:34648536 | DOI:10.1371/journal.pone.0258429

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Nevin Manimala Statistics

Meta-Analysis illustrates possible role of lipopolysaccharide (LPS)-induced tissue injury in nasopharyngeal carcinoma (NPC) pathogenesis

PLoS One. 2021 Oct 14;16(10):e0258187. doi: 10.1371/journal.pone.0258187. eCollection 2021.

ABSTRACT

BACKGROUND: Nasopharyngeal carcinoma (NPC) is a cancer of epithelial origin with a high incidence in certain populations. While NPC has a high remission rate with concomitant chemoradiation, recurrences are frequent, and the downstream morbidity of treatment is significant. Thus, it is imperative to find alternative therapies.

METHODS: We employed a Search Tag Analyze Resource (STARGEO) platform to conduct a meta-analysis using the National Center for Biotechnology’s (NCBI) Gene Expression Omnibus (GEO) to define NPC pathogenesis. We identified 111 tumor samples and 43 healthy nasopharyngeal epithelium samples from NPC public patient data. We analyzed associated signatures in Ingenuity Pathway Analysis (IPA), restricting genes that showed statistical significance (p<0.05) and an absolute experimental log ratio greater than 0.15 between disease and control samples.

RESULTS: Our meta-analysis identified activation of lipopolysaccharide (LPS)-induced tissue injury in NPC tissue. Additionally, interleukin-1 (IL-1) and SB203580 were the top upstream regulators. Tumorigenesis-related genes such as homeobox A10 (HOXA10) and prostaglandin-endoperoxide synthase 2 (PTGS2 or COX-2) as well as those associated with extracellular matrix degradation, such as matrix metalloproteinases 1 and 3 (MMP-1, MMP-3) were also upregulated. Decreased expression of genes that encode proteins associated with maintaining healthy nasal respiratory epithelium structural integrity, including sentan-cilia apical structure protein (SNTN) and lactotransferrin (LTF) was documented. Importantly, we found that etanercept inhibits targets upregulated in NPC and LPS induction, such as MMP-1, PTGS2, and possibly MMP-3.

CONCLUSIONS: Our analysis illustrates that nasal epithelial barrier dysregulation and maladaptive immune responses are key components of NPC pathogenesis along with LPS-induced tissue damage.

PMID:34648530 | DOI:10.1371/journal.pone.0258187

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Nevin Manimala Statistics

Systematic review of the scrub typhus treatment landscape: Assessing the feasibility of an individual participant-level data (IPD) platform

PLoS Negl Trop Dis. 2021 Oct 14;15(10):e0009858. doi: 10.1371/journal.pntd.0009858. Online ahead of print.

ABSTRACT

BACKGROUND: Scrub typhus is an acute febrile illness caused by intracellular bacteria from the genus Orientia. It is estimated that one billion people are at risk, with one million cases annually mainly affecting rural areas in Asia-Oceania. Relative to its burden, scrub typhus is understudied, and treatment recommendations vary with poor evidence base. These knowledge gaps could be addressed by establishing an individual participant-level data (IPD) platform, which would enable pooled, more detailed and statistically powered analyses to be conducted. This study aims to assess the characteristics of scrub typhus treatment studies and explore the feasibility and potential value of developing a scrub typhus IPD platform to address unanswered research questions.

METHODOLOGY/PRINCIPAL FINDINGS: We conducted a systematic literature review looking for prospective scrub typhus clinical treatment studies published from 1998 to 2020. Six electronic databases (Ovid Embase, Ovid Medline, Ovid Global Health, Cochrane Library, Scopus, Global Index Medicus), ClinicalTrials.gov, and WHO ICTRP were searched. We extracted data on study design, treatment tested, patient characteristics, diagnostic methods, geographical location, outcome measures, and statistical methodology. Among 3,100 articles screened, 127 were included in the analysis. 12,079 participants from 12 countries were enrolled in the identified studies. ELISA, PCR, and eschar presence were the most commonly used diagnostic methods. Doxycycline, azithromycin, and chloramphenicol were the most commonly administered antibiotics. Mortality, complications, adverse events, and clinical response were assessed in most studies. There was substantial heterogeneity in the diagnostic methods used, treatment administered (including dosing and duration), and outcome assessed across studies. There were few interventional studies and limited data collected on specific groups such as children and pregnant women.

CONCLUSIONS/SIGNIFICANCE: There were a limited number of interventional trials, highlighting that scrub typhus remains a neglected disease. The heterogeneous nature of the available data reflects the absence of consensus in treatment and research methodologies and poses a significant barrier to aggregating information across available published data without access to the underlying IPD. There is likely to be a substantial amount of data available to address knowledge gaps. Therefore, there is value for an IPD platform that will facilitate pooling and harmonisation of currently scattered data and enable in-depth investigation of priority research questions that can, ultimately, inform clinical practice and improve health outcomes for scrub typhus patients.

PMID:34648517 | DOI:10.1371/journal.pntd.0009858

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Nevin Manimala Statistics

Knowledge and practice of cattle handlers on antibiotic residues in meat and milk in Kwara State, Northcentral Nigeria

PLoS One. 2021 Oct 14;16(10):e0257249. doi: 10.1371/journal.pone.0257249. eCollection 2021.

ABSTRACT

OBJECTIVES: Antibiotics are important for improving animal health and production. However, the deposition of its residues in food of animal origin intended for human consumption at non-permissible levels has generated global health concern and the need to tackle this using the “One Health Approach”. This study assessed the knowledge and practice of 286 cattle handlers in Kwara State, Nigeria.

METHODS: A web-based cross sectional online survey using a semi-structured questionnaire was conducted from November to December, 2019. Univariate, bivariate and multivariate analyses were performed at 95% confidence interval to determine predictors of good knowledge and practices towards Antibiotic Residues in Meat and Milk among cattle handlers.

RESULTS: This study revealed that majority (52.7% n = 165/286) of the cattle handlers were not aware of antibiotic residues. Knowledge and practices regarding antibiotic residues were generally poor among the study population; 36.7% and 35.5% had satisfactory knowledge and practice respectively. The age (p = 0.026), gender (p = 0.006) and business duration (p = 0.001) of participants were significantly associated with their knowledge of antimicrobial residues. The effect of education on knowledge was modified by age. The odds of having poor knowledge on antibiotic residues increased 4 times among participants who were ≤40 years old than those above 40 years (Stratum Specific OR = 3.65; CI = 1.2, 11.1; p = 0.026). Knowledge levels of participants were statistically associated with their practice levels p<0.05 (OR = 2.43; CI = 1.45. 4.06; p = 0.0006).

CONCLUSION: This implies that poor knowledge is a risk factor to having poor practice among cattle handlers. Deliberate efforts towards educating cattle farmers on best farm practices in antibiotic use would prevent antibiotic residues in meat and milk. Also, an effective surveillance system for monitoring the use of veterinary drugs in Kwara State, Nigeria is crucial.

PMID:34648524 | DOI:10.1371/journal.pone.0257249

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Nevin Manimala Statistics

Prevalence and health correlates of Onine Fatigue: A cross-sectional study on the Italian academic community during the COVID-19 pandemic

PLoS One. 2021 Oct 14;16(10):e0255181. doi: 10.1371/journal.pone.0255181. eCollection 2021.

ABSTRACT

BACKGROUND: During the COVID-19 pandemic, many people had to shift their social and work life online. A few researchers and journalists described a new form of fatigue associated with a massive use of technology, including videoconferencing platforms. In this study, this type of fatigue was referred to as Online Fatigue. A new tool (the Online Fatigue Scale) was developed, and its psychometric properties were evaluated. This tool was used to assess Online Fatigue among Italian academics and to examine its associations with psychological and physical health.

METHODS: An online survey was conducted in December 2020 on a sample of Italian academics. Besides the Online Fatigue Scale (11 items) used to assess Online Fatigue, the survey was composed of questionnaires (including validated measures) focused on sociodemographic and job-related information, technostress creators, health status, psychological well-being, and COVID-related perceived distress. The psychometric properties of the Online Fatigue Scale were evaluated, and statistical analyses were conducted to examine the associations between Online Fatigue and all the other variables.

RESULTS: Participants were 307 academics aged 24-70 years old (mean age = 40.7; SD = 10.1). The Online Fatigue Scale showed good psychometric properties. Two subscales were identified: Off-Balance Fatigue and Virtual Relations Fatigue. High levels of Off-Balance Fatigue were associated with a greater use of technology, female gender, and presence of minor children. Participants with high scores on both subscales reported a greater frequency of psychosomatic symptoms, unhealthy habits, poorer psychological well-being, and greater Covid-related perceived distress.

CONCLUSIONS: The Online Fatigue Scale can be considered a reliable tool to assess Online Fatigue, which was significantly detected in our sample of Italian academics, along with its negative effects on physical and psychological health. Being a woman and having young children represent important risk factors. Universities should promote the separation between work and private life by encouraging self-care activities.

PMID:34648507 | DOI:10.1371/journal.pone.0255181

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Nevin Manimala Statistics

Investigating the association of CD36 gene polymorphisms (rs1761667 and rs1527483) with T2DM and dyslipidemia: Statistical analysis, machine learning based prediction, and meta-analysis

PLoS One. 2021 Oct 14;16(10):e0257857. doi: 10.1371/journal.pone.0257857. eCollection 2021.

ABSTRACT

CD36 (cluster of differentiation 36) is a membrane protein involved in lipid metabolism and has been linked to pathological conditions associated with metabolic disorders, such as diabetes and dyslipidemia. A case-control study was conducted and included 177 patients with type-2 diabetes mellitus (T2DM) and 173 control subjects to study the involvement of CD36 gene rs1761667 (G>A) and rs1527483 (C>T) polymorphisms in the pathogenesis of T2DM and dyslipidemia among Jordanian population. Lipid profile, blood sugar, gender and age were measured and recorded. Also, genotyping analysis for both polymorphisms was performed. Following statistical analysis, 10 different neural networks and machine learning (ML) tools were used to predict subjects with diabetes or dyslipidemia. Towards further understanding of the role of CD36 protein and gene in T2DM and dyslipidemia, a protein-protein interaction network and meta-analysis were carried out. For both polymorphisms, the genotypic frequencies were not significantly different between the two groups (p > 0.05). On the other hand, some ML tools like multilayer perceptron gave high prediction accuracy (≥ 0.75) and Cohen’s kappa (κ) (≥ 0.5). Interestingly, in K-star tool, the accuracy and Cohen’s κ values were enhanced by including the genotyping results as inputs (0.73 and 0.46, respectively, compared to 0.67 and 0.34 without including them). This study confirmed, for the first time, that there is no association between CD36 polymorphisms and T2DM or dyslipidemia among Jordanian population. Prediction of T2DM and dyslipidemia, using these extensive ML tools and based on such input data, is a promising approach for developing diagnostic and prognostic prediction models for a wide spectrum of diseases, especially based on large medical databases.

PMID:34648514 | DOI:10.1371/journal.pone.0257857