Category: Nevin Manimala

Psychooncology. 2021 Apr 2. doi: 10.1002/pon.5691. Online ahead of print.

ABSTRACT

OBJECTIVE: Black Americans are disproportionately affected by cancer and chronic diseases. Black patients with cancer and their family caregivers may concurrently experience symptoms that influence their wellbeing. This study investigates the influence of mental and physical symptom distress on quality of life (QOL) among Black Americans with cancer and their family caregivers from a dyadic perspective.

METHODS: One hundred and fifty-one dyads comprised of a Black American with breast, colorectal, lung or prostate cancer and a Black family caregiver were included in this secondary analysis of pooled baseline data from three studies. Self-reports of problems managing 13 symptoms were used to measure mental and physical symptom distress. Descriptive statistics and the actor-partner interdependence model were used to examine symptom prevalence and the influence of each person’s symptom distress on their own and each other’s QOL.

RESULTS: Fatigue, sleep problems, pain and mental distress were prevalent. Patients and caregivers reported similar levels of mental distress; however, patients reported higher physical distress. Increased patient mental distress was associated with decreased patient QOL (overall, emotional, social, functional). Increased patient physical distress was associated with decreased patient QOL (overall, physical, emotional, functional) and decreased caregiver emotional wellbeing. Increased caregiver mental distress was associated with decreased caregiver QOL (overall, emotional, social, functional) and decreased patient overall QOL. Increased caregiver physical distress was associated with decreased caregiver QOL (overall, physical, functional), decreased patient emotional wellbeing, and better patient social wellbeing.

CONCLUSIONS: Supporting symptom management in Black patient/caregiver dyads may improve their QOL.

PMID:33861891 | DOI:10.1002/pon.5691

IET Syst Biol. 2021 Apr 16. doi: 10.1049/syb2.12018. Online ahead of print.

ABSTRACT

The dynamics of cortical neuronal activity plays important roles in controlling body movement and is regulated by connection weights between neurons in a cortex-basal ganglia-thalamus (BGCT) loop. Beta-band oscillation of cortical activity is closely associated with the movement disorder of Parkinson’s disease, which is caused by an imbalance in the connection weights of direct and indirect pathways in the BGCT loop. In this study, the authors investigate how the dynamics of cortical activity are modulated by connection weights of direct and indirect pathways in the BGCT loop under low dopamine levels through bifurcation analyses and potential landscapes. The results reveal that cortical activity displays rich dynamics under different connection weights, including one, two, or three stable steady states, one or two stable limit cycles, and the coexistence of one stable limit cycle with one stable steady state or two stable ones. For a low dopamine level, cortical activity exhibits oscillation for larger connection weights of direct and indirect pathways. The stability of these stable dynamics is explored by the potential landscapes.

PMID:33861900 | DOI:10.1049/syb2.12018

PLoS One. 2021 Apr 16;16(4):e0250370. doi: 10.1371/journal.pone.0250370. eCollection 2021.

ABSTRACT

BACKGROUND: Accurately predicting the survival rate of breast cancer patients is a major issue for cancer researchers. Machine learning (ML) has attracted much attention with the hope that it could provide accurate results, but its modeling methods and prediction performance remain controversial. The aim of this systematic review is to identify and critically appraise current studies regarding the application of ML in predicting the 5-year survival rate of breast cancer.

METHODS: In accordance with the PRISMA guidelines, two researchers independently searched the PubMed (including MEDLINE), Embase, and Web of Science Core databases from inception to November 30, 2020. The search terms included breast neoplasms, survival, machine learning, and specific algorithm names. The included studies related to the use of ML to build a breast cancer survival prediction model and model performance that can be measured with the value of said verification results. The excluded studies in which the modeling process were not explained clearly and had incomplete information. The extracted information included literature information, database information, data preparation and modeling process information, model construction and performance evaluation information, and candidate predictor information.

RESULTS: Thirty-one studies that met the inclusion criteria were included, most of which were published after 2013. The most frequently used ML methods were decision trees (19 studies, 61.3%), artificial neural networks (18 studies, 58.1%), support vector machines (16 studies, 51.6%), and ensemble learning (10 studies, 32.3%). The median sample size was 37256 (range 200 to 659820) patients, and the median predictor was 16 (range 3 to 625). The accuracy of 29 studies ranged from 0.510 to 0.971. The sensitivity of 25 studies ranged from 0.037 to 1. The specificity of 24 studies ranged from 0.008 to 0.993. The AUC of 20 studies ranged from 0.500 to 0.972. The precision of 6 studies ranged from 0.549 to 1. All of the models were internally validated, and only one was externally validated.

CONCLUSIONS: Overall, compared with traditional statistical methods, the performance of ML models does not necessarily show any improvement, and this area of research still faces limitations related to a lack of data preprocessing steps, the excessive differences of sample feature selection, and issues related to validation. Further optimization of the performance of the proposed model is also needed in the future, which requires more standardization and subsequent validation.

PMID:33861809 | DOI:10.1371/journal.pone.0250370

PLoS One. 2021 Apr 16;16(4):e0250269. doi: 10.1371/journal.pone.0250269. eCollection 2021.

ABSTRACT

BACKGROUND: Given the economic and social divide that exists in South Africa, it is critical to manage the health response of its residents to the Covid-19 pandemic within the different socio-economic contexts that define the lived realities of individuals.

OBJECTIVE: The objective of this study is to analyse the Covid-19 preventive behaviour and the socio-economic drivers behind the health-response behaviour.

DATA: The study employs data from waves 1 and 2 of South Africa’s nationally representative National Income Dynamics Study (NIDS)-Coronavirus Rapid Mobile Survey (CRAM). The nationally representative panel data has a sample of 7073 individuals in Wave 1 and 5676 individuals in Wave 2.

METHODS: The study uses bivariate statistics, concentration indices and multivariate estimation techniques, ranging from a probit, control-function approach, special-regressor method and seemingly unrelated regression to account for endogeneity while identifying the drivers of the response behaviour.

FINDINGS: The findings indicate enhanced behavioural responsiveness to Covid-19. Preventive behaviour is evolving over time; the use of face mask has overtaken handwashing as the most utilised preventive measure. Other measures, like social distancing, avoiding close contact, avoiding big groups and staying at home, have declined between the two periods of the study. There is increased risk perception with significant concentration among the higher income groups, the educated and older respondents. Our findings validate the health-belief model, with perceived risk, self-efficacy, perceived awareness and barriers to preventive strategy adoption identified as significant drivers of health-response behaviour. Measures such as social distancing, avoiding close contact, and the use of sanitisers are practised more by the rich and educated, but not by the low-income respondents.

CONCLUSION: The respondents from lower socio-economic backgrounds are associated with optimism bias and face barriers to the adoption of preventive strategies. This requires targeted policy attention in order to make response behaviour effective.

PMID:33861811 | DOI:10.1371/journal.pone.0250269

PLoS One. 2021 Apr 16;16(4):e0250359. doi: 10.1371/journal.pone.0250359. eCollection 2021.

ABSTRACT

Tobacco smoking is associated with an increased risk of oral leukoplakia and head and neck cancer. Although it has recently been reported that the establishment of an immunosuppressive microenvironment in oral potentially malignant disorders may lead to malignant transformation, it is unclear whether the microenvironments of oral potentially malignant disorders differ according to smoking status. We examined differences in programmed death-ligand 1 (PD-L1) expression and subepithelial CD163+ TAM and CD8+ cell/lymphocyte counts in the microenvironment of oral leukoplakia of smoking and non-smoking patients and investigated their associations with malignant transformation. Pathology reports and original biopsy request forms from 1995-2015 were retrospectively reviewed. Lesions clinically characterized as white plaques/lesions of the oral mucosa and pathologically diagnosed as oral epithelial dysplasia were included. Immunohistochemistry was performed to evaluate PD-L1 expression and subepithelial CD163+/CD8+ cell counts. The significance of prognostic factors in predicting malignant transformation was determined using Cox regression analysis. Statistical significance was defined as P<0.05. In total, 200 patients with oral leukoplakia were selected. The mean age at diagnosis was higher in non-smoking patients (n = 141; 66.9 years) than in smoking patients (n = 59; 60.5 years). The 5-year cumulative malignant transformation rate was higher in non-smoking patients than in smoking patients (9.3% vs. 3.0%, respectively). Oral leukoplakia was associated with significantly higher PD-L1 expression and increased numbers of subepithelial CD163+ cells in the non-smoking group compared with the smoking group. Non-smoking-related oral leukoplakia with positive PD-L1 expression was associated with a 6.97-fold (95% confidence interval: 2.14-22.7) increased risk of malignant transformation. The microenvironment of oral leukoplakia differed according to smoking status. A combination of smoking status and PD-L1 expression may predict malignant transformation in oral leukoplakia patients. This study highlights the importance of understanding the interaction between smoking and the microenvironment in oral leukoplakia.

PMID:33861793 | DOI:10.1371/journal.pone.0250359

PLoS One. 2021 Apr 16;16(4):e0250323. doi: 10.1371/journal.pone.0250323. eCollection 2021.

ABSTRACT

With current trends in cannabis legalization, large efforts are being made to understand the effects of less restricted legislation on human consumption, health, and abuse of these products. Little is known about the effects of cannabis legalization and increased cannabis use on vulnerable populations, such as dogs. The objective of this study was to examine the effects of different state-level cannabis legislation, county-level socioeconomic factors, and dog-level characteristics on dog cannabis poisoning reports to an animal poison control center (APCC). Data were obtained concerning reports of dog poisoning events, county characteristics, and state cannabis legislation from the American Society for the Prevention of Cruelty to Animals’ (ASPCA) APCC, the US Census Bureau, and various public policy-oriented and government websites, respectively. A multilevel logistic regression model with random intercepts for county and state was fitted to investigate the associations between the odds of a call to the APCC being related to a dog being poisoned by a cannabis product and the following types of variables: dog characteristics, county-level socioeconomic characteristics, and the type of state-level cannabis legislation. There were significantly higher odds of a call being related to cannabis in states with lower penalties for cannabis use and possession. The odds of these calls were higher in counties with higher income variability, higher percentage of urban population, and among smaller, male, and intact dogs. These calls increased throughout the study period (2009-2014). Reporting of cannabis poisonings were more likely to come from veterinarians than dog owners. Reported dog poisonings due to cannabis appear to be influenced by dog-level and community-level factors. This study may increase awareness to the public, public health, and veterinary communities of the effects of recreational drug use on dog populations. This study highlights the need to educate dog owners about safeguarding cannabis products from vulnerable populations.

PMID:33861797 | DOI:10.1371/journal.pone.0250323

PLoS One. 2021 Apr 16;16(4):e0250321. doi: 10.1371/journal.pone.0250321. eCollection 2021.

ABSTRACT

OBJECTIVE: Obesity is a negative prognostic factor for various clinical conditions. In this observational cohort study, we evaluated a CT-based assessment of the adipose tissue distribution as a potential non-invasive prognostic parameter in critical illness.

METHODS: Routine CT-scans upon admission to the intensive care unit (ICU) were used to analyze the visceral and subcutaneous adipose tissue areas at the 3rd lumbar vertebra in 155 patients. Results were correlated with various prognostic markers and both short-term- and overall survival. Multiple statistical tools were used for data analysis.

RESULTS: We observed a significantly larger visceral adipose tissue area in septic patients compared to non-sepsis patients. Interestingly, patients requiring mechanical ventilation had a significantly higher amount of visceral adipose tissue correlating with the duration of mechanical ventilation. Moreover, both visceral and subcutaneous adipose tissue area significantly correlated with several laboratory markers. While neither the visceral nor the subcutaneous adipose tissue area was predictive for short-term ICU survival, patients with a visceral adipose tissue area above the optimal cut-off (241.4 cm2) had a significantly impaired overall survival compared to patients with a lower visceral adipose tissue area.

CONCLUSIONS: Our study supports a prognostic role of the individual adipose tissue distribution in critically ill patients. However, additional investigations need to confirm our suggestion that routine CT-based assessment of adipose tissue distribution can be used to yield further information on the patients’ clinical course. Moreover, future studies should address functional and metabolic analysis of different adipose tissue compartments in critical illness.

PMID:33861804 | DOI:10.1371/journal.pone.0250321

PLoS One. 2021 Apr 16;16(4):e0249305. doi: 10.1371/journal.pone.0249305. eCollection 2021.

ABSTRACT

Genetic studies have shifted to sequencing-based rare variants discovery after decades of success in identifying common disease variants by Genome-Wide Association Studies using Single Nucleotide Polymorphism chips. Sequencing-based studies require large sample sizes for statistical power and therefore often inadvertently introduce batch effects because samples are typically collected, processed, and sequenced at multiple centers. Conventionally, batch effects are first detected and visualized using Principal Components Analysis and then controlled by including batch covariates in the disease association models. For sequencing-based genetic studies, because all variants included in the association analyses have passed sequencing-related quality control measures, this conventional approach treats every variant as equal and ignores the substantial differences still remaining in variant qualities and characteristics such as genotype quality scores, alternative allele fractions (fraction of reads supporting alternative allele at a variant position) and sequencing depths. In the Alzheimer’s Disease Sequencing Project (ADSP) exome dataset of 9,904 cases and controls, we discovered hidden variant-level differences between sample batches of three sequencing centers and two exome capture kits. Although sequencing centers were included as a covariate in our association models, we observed differences at the variant level in genotype quality and alternative allele fraction between samples processed by different exome capture kits that significantly impacted both the confidence of variant detection and the identification of disease-associated variants. Furthermore, we found that a subset of top disease-risk variants came exclusively from samples processed by one exome capture kit that was more effective at capturing the alternative alleles compared to the other kit. Our findings highlight the importance of additional variant-level quality control for large sequencing-based genetic studies. More importantly, we demonstrate that automatically filtering out variants with batch differences may lead to false negatives if the batch discordances come largely from quality differences and if the batch-specific variants have better quality.

PMID:33861770 | DOI:10.1371/journal.pone.0249305

PLoS One. 2021 Apr 16;16(4):e0250169. doi: 10.1371/journal.pone.0250169. eCollection 2021.

ABSTRACT

OBJECTIVES: To measure the effects of peer influence and peer selection on drinking behavior in adolescence through a rigorous statistical approach designed to unravel these interrelated processes.

METHODS: We conducted systematic searches of electronic databases, thesis collections and conference proceedings to identify studies that used longitudinal network design and stochastic actor-oriented modeling to analyze drinking behavior in adolescents. Parameter estimates collected from individual studies were analyzed using multilevel random-effects models.

RESULTS: We identified 26 articles eligible for meta-analysis. Meta-analyses for different specifications of the peer influence effect were conducted separately. The peer influence effect was positive for every specification: for average similarity (avSim) mean log odds ratio was 1.27 with 95% confidence interval [0.04; 2.49]; for total similarity (totSim) 0.46 (95% CI = [0.44; 0.48]), and for average alter (avAlt) 0.70 (95% CI = [-0.01; 1.41]). The peer selection effect (simX) was also positive: 0.46 (95% CI = [0.28; 0.63]). Conversion log odds ratio values to Cohen’s d gives estimates from 0.25 to 0.70, which is considered as medium to large effect.

CONCLUSIONS: Advances in methodology for social network analysis have made it possible to accurately estimate peer influence effects free from peer selection effects. More research is necessary to clarify the roles of age, gender, and individual susceptibility on the changing behavior of adolescents under the influence of their peers. Understanding the effects of peer influence should inform practitioners and policy makers to design and deliver more effective prevention programs.

PMID:33861781 | DOI:10.1371/journal.pone.0250169

PLoS One. 2021 Apr 16;16(4):e0250174. doi: 10.1371/journal.pone.0250174. eCollection 2021.

ABSTRACT

INTRODUCTION: Post cesarean section surgical site infection increases both the duration of a patient’s hospital stay and unplanned hospital costs. It can delays recovery, prolongs hospitalization, necessitates readmission, and adds to hospital bills and other morbidities as well as mortalities.

METHOD: Facility-based case-control study was conducted from 1st March to 20th April, 2019 among all the mother records enrolled from 1st January to 31st December, 2018 at Public hospitals in Dire Dawa administration. The records of the mothers’ who had post-cesarean section surgical site infection (119) was extracted by a census and every three consecutive controls (357) for each case were collected by trained data collectors using a structured data extraction tool. Variables which had p-value <0.25 in bivariate analysis were considered as candidates for multivariable analysis. Statistical significance was declared at P-value ≤0.05 with adjusted odd ratio and 95% confidence interval in the multivariable logistic regression model.

RESULT: Age 20-34 years (AOR:5.4; 95%CI:2.35,12.7), age >35 years (AOR:8.9; 95%CI:1.8,43.9), ≥4 per vaginal examinations (AOR: 4.2; 95%CI:2.16,8.22), current history of Chorioamnionitis (AOR:5; 95%CI:1.05,23.9), previous history of cesarean section (AOR:6.2; 95%CI: 2.72,14.36), provision of antibiotics prophylaxis (AOR:3.2; 95%CI:1.81,5.62), perioperative HCT level <30% (AOR:6.9; 95%CI:3.45,14.1) and duration of rupture of membrane >12 hours (AOR:5.4; 95%CI:1.84,15.87) were the independent determinants of post-cesarean section surgical site infection.

CONCLUSION: Increased in age of the mother, higher number of per vaginal examination, having a history of chorioamnionitis, having previous history of cesarean section, not receiving antibiotics prophylaxis, lower perioperative hematocrit level and longer duration of rupture of membrane were statistically significant in multivariable analysis. Therefore; emphasis should be given for mothers who have higher age category, previous cesarean scar and history of choriamnionitis. In addition; provision of antibiotics should be comprehensive for all mothers undergoing cesarean section.

PMID:33861783 | DOI:10.1371/journal.pone.0250174