Category: Nevin Manimala

Vector Borne Zoonotic Dis. 2022 Jun 30. doi: 10.1089/vbz.2021.0091. Online ahead of print.

ABSTRACT

Crimean-Congo hemorrhagic fever (CCHF) is a tick-borne disease that can be contracted by direct contact with viremic animals or humans. Domestic animals are accidental hosts and contribute to the spread and amplification of the virus. The main objective of this study was to provide updated information related to CCHF virus (CCHFV) infection in Southern Romania by assessing the seroprevalence of CCHF in small ruminants (sheep and goats) using a double-antigen sandwich enzyme-linked immunosorbent assay and by detection of CCHFV in engorged ticks and serum samples using real-time RT-PCR. The overall seroprevalence of CCHF in small ruminants was 37.7% (95% CI 31.7 to 43.7). No statistical seroprevalence difference was observed between the two species of ruminants (p = 0.76), but a significant difference was established between the locations (p < 0.01). No CCHFV RNA was detected in tick pools and small ruminant’s sera tested by real-time RT-PCR, although the high seroprevalence to CCHFV among ruminants indicates that CCHV or a closely related virus circulates in Southern Romania.

PMID:35772004 | DOI:10.1089/vbz.2021.0091

Blood. 2022 Jun 30:blood.2022015727. doi: 10.1182/blood.2022015727. Online ahead of print.

ABSTRACT

While venous thromboembolism (VTE) is an important treatment and disease-related complication in myeloma, a validated risk-prediction model including disease-specific variables such as cytogenetics or tumor burden is lacking. The aim of our study was to develop a new risk-prediction model for VTE in the context of modern anti-myeloma therapy. All consecutive patients diagnosed at Cleveland Clinic during 2008-2018 and with available data on baseline candidate risk-factors constituted the derivation cohort. The primary outcome was VTE (deep venous thrombosis/pulmonary embolism) within one year of treatment initiation. A multivariable model was utilized and weights were derived from subdistribution hazard ratios (sHR) to construct a risk-score. The model was validated both by internal bootstrap validation and in an external validation cohort. The derivation cohort consisted of 783 patients. A 5 component risk-prediction tool, named PRISM score, was developed, including the following variables: prior VTE, prior surgery, immunomodulatory drug (IMiD) use, abnormal metaphase cytogenetics, and Black race. The c-statistic of the model was 0.622 (95% CI, 0.567-0.674). The model stratified patients into low, intermediate, and high-risk, with 12-month cumulative VTE incidence of 2.7%, 10.8%, and 36.5% respectively. Risk of VTE increased significantly with increasing score in both derivation and external validation datasets, with the sHR per 1-point increase being 1.28 (95% CI, 1.19-1.39; p<0.001) and 1.23 (95% CI, 1.07-1.41; p=0.004) respectively. While PRISM score can guide clinicians in identifying patients at a high risk of VTE, additional external validation is necessary for incorporation into routine clinical practice.

PMID:35772005 | DOI:10.1182/blood.2022015727

J Biopharm Stat. 2022 Jun 30:1-24. doi: 10.1080/10543406.2022.2065505. Online ahead of print.

ABSTRACT

Torsades de pointes (TdP) is an irregular heart rhythm characterized by faster beat rates and potentially could lead to sudden cardiac death. Much effort has been invested in understanding the drug-induced TdP in preclinical studies. However, a comprehensive statistical learning framework that can accurately predict the drug-induced TdP risk from preclinical data is still lacking. We proposed ordinal logistic regression and ordinal random forest models to predict low-, intermediate-, and high-risk drugs based on datasets generated from two experimental protocols. Leave-one-drug-out cross-validation, stratified bootstrap, and permutation predictor importance were applied to estimate and interpret the model performance under uncertainty. The potential outlier drugs identified by our models are consistent with their descriptions in the literature. Our method is accurate, interpretable, and thus useable as supplemental evidence in the drug safety assessment.

PMID:35771997 | DOI:10.1080/10543406.2022.2065505

PLoS One. 2022 Jun 30;17(6):e0270848. doi: 10.1371/journal.pone.0270848. eCollection 2022.

ABSTRACT

BACKGROUND: Menstruation is a biological process which is crucial for human reproduction. Menstruation is a source of absenteeism, yet the subject matter has not been well explored. This study aimed to assess the correlates of absenteeism at school, work and social activities during menstruation among Ghanaian women of reproductive age.

METHODS: This study was an analysis of secondary data from the 2017/18 Ghana Multiple Indicator Cluster Survey. Data were analysed using descriptive statistics, Chi-square and Binomial Logistic Regression with the aid of Stata/SE, version 16.

RESULTS: The majority of the participants were aged 25-49 years (63%), married/in union (55%) and resided in urban areas (52%). Nine in ten participants had access to privacy at home and 98% used menstrual materials during their last period. Eight in ten participants used disposable menstrual materials. Exactly 19% of the participants missed school, work or social activities during their last period. Participants who used disposable menstrual materials (AOR = 0.67; 95% CI: 0.52-0.85) were less likely to miss school, work or social activities during menstruation compared to those who used reusable menstrual materials.

CONCLUSION: This study demonstrated that a significant minority of women in Ghana miss academic, economic or social activities during menstruation. Therefore, there is a need for effective interventions to help reduce menstruation-related absenteeism among women and girls in Ghana.

PMID:35771899 | DOI:10.1371/journal.pone.0270848

PLoS One. 2022 Jun 30;17(6):e0270340. doi: 10.1371/journal.pone.0270340. eCollection 2022.

ABSTRACT

BACKGROUND: China established the Tiered-network Healthcare Delivery System (THDS) in 2015 to address the disproportionate number of patients attending tertiary hospitals relative to primary- or secondary-care institutions. Although the reported number of outpatients visiting tertiary hospitals is slowly decreasing, numerous patients choose to visit them regardless of their disease’s severity. To effectively implement the THDS, this article explored the relationship between patients’ sociodemographic and belief characteristics and their healthcare-seeking behavioral decision-making in China.

METHODS: Data obtained through questionnaires were analyzed using decision tree and logistic regression models to explore outpatients’ characteristics and medical decision-making using comprehensive feature data. Moreover, further statistical analyses were conducted on the outpatient data obtained from the regional population health platform in Jiaxing, China.

RESULTS: The decision tree model revealed that whether outpatients have medical insurance is the primary factor guiding their healthcare-seeking behaviors, with those without medical insurance more likely to choose primary or secondary hospitals to treat minor diseases. For those with medical insurance, profession is the main factor, with industrial workers more inclined to choose primary or secondary hospitals for minor diseases. The logistic regression analyses revealed that outpatients without insurance and who were not freelancers or individual owners were more likely to choose primary or secondary hospitals for minor diseases. Further statistical analysis of the data from the Jiaxing population health platform showed that, for minor or general diseases, outpatients without medical insurance and employed as farmers tended to choose primary and secondary hospitals over tertiary hospitals.

CONCLUSION: The three analyses yielded consistent results: in China, medical insurance and patients’ profession are the most important factors guiding outpatients’ healthcare-seeking behaviors. Accordingly, we propose that the government should focus on economic reforms to increase outpatients’ visits to primary and secondary hospitals and diagnosis-related groups’ payment of medical insurance to decrease the admittance of patients with minor diseases in large tertiary hospitals. Meanwhile, the government should correct patients’ belief prejudice about selecting hospitals through corresponding publicity.

PMID:35771896 | DOI:10.1371/journal.pone.0270340

PLoS Med. 2022 Jun 30;19(6):e1004043. doi: 10.1371/journal.pmed.1004043. Online ahead of print.

ABSTRACT

BACKGROUND: The evidence is sparse regarding the associations between serious mental illnesses (SMIs) prevalence and environmental factors in adulthood as well as the geographic distribution and variability of these associations. In this study, we evaluated the association between availability and proximity of green and blue space with SMI prevalence in England as a whole and in its major conurbations (Greater London, Birmingham, Liverpool and Manchester, Leeds, and Newcastle).

METHODS AND FINDINGS: We carried out a retrospective analysis of routinely collected adult population (≥18 years) data at General Practitioner Practice (GPP) level. We used data from the Quality and Outcomes Framework (QOF) on the prevalence of a diagnosis of SMI (schizophrenia, bipolar affective disorder and other psychoses, and other patients on lithium therapy) at the level of GPP over the financial year April 2014 to March 2018. The number of GPPs included ranged between 7,492 (April 2017 to March 2018) to 7,997 (April 2014 to March 2015) and the number of patients ranged from 56,413,719 (April 2014 to March 2015) to 58,270,354 (April 2017 to March 2018). Data at GPP level were converted to the geographic hierarchy unit Lower Layer Super Output Area (LSOA) level for analysis. LSOAs are a geographic unit for reporting small area statistics and have an average population of around 1,500 people. We employed a Bayesian spatial regression model to explore the association of SMI prevalence in England and its major conurbations (greater London, Birmingham, Liverpool and Manchester, Leeds, and Newcastle) with environmental characteristics (green and blue space, flood risk areas, and air and noise pollution) and socioeconomic characteristics (age, ethnicity, and index of multiple deprivation (IMD)). We incorporated spatial random effects in our modelling to account for variation at multiple scales. Across England, the environmental characteristics associated with higher SMI prevalence at LSOA level were distance to public green space with a lake (prevalence ratio [95% credible interval]): 1.002 [1.001 to 1.003]), annual mean concentration of PM2.5 (1.014 [1.01 to 1.019]), and closeness to roads with noise levels above 75 dB (0.993 [0.992 to 0.995]). Higher SMI prevalence was also associated with a higher percentage of people above 24 years old (1.002 [1.002 to 1.003]), a higher percentage of ethnic minorities (1.002 [1.001 to 1.002]), and more deprived areas. Mean SMI prevalence at LSOA level in major conurbations mirrored the national associations with a few exceptions. In Birmingham, higher average SMI prevalence at LSOA level was positively associated with proximity to an urban green space with a lake (0.992 [0.99 to 0.998]). In Liverpool and Manchester, lower SMI prevalence was positively associated with road traffic noise ≥75 dB (1.012 [1.003 to 1.022]). In Birmingham, Liverpool, and Manchester, there was a positive association of SMI prevalence with distance to flood zone 3 (land within flood zone 3 has ≥1% chance of flooding annually from rivers or ≥0.5% chance of flooding annually from the sea, when flood defences are ignored): Birmingham: 1.012 [1.000 to 1.023]; Liverpool and Manchester: 1.016 [1.006 to 1.026]. In contrast, in Leeds, there was a negative association between SMI prevalence and distance to flood zone 3 (0.959 [0.944 to 0.975]). A limitation of this study was because we used a cross-sectional approach, we are unable to make causal inferences about our findings or investigate the temporal relationship between outcome and risk factors. Another limitation was that individuals who are exclusively treated under specialist mental health care and not seen in primary care at all were not included in this analysis.

CONCLUSIONS: Our study provides further evidence on the significance of socioeconomic associations in patterns of SMI but emphasises the additional importance of considering environmental characteristics alongside socioeconomic variables in understanding these patterns. In this study, we did not observe a significant association between green space and SMI prevalence, but we did identify an apparent association between green spaces with a lake and SMI prevalence. Deprivation, higher concentrations of air pollution, and higher proportion of ethnic minorities were associated with higher SMI prevalence, supporting a social-ecological approach to public health prevention. It also provides evidence of the significance of spatial analysis in revealing the importance of place and context in influencing area-based patterns of SMI.

PMID:35771888 | DOI:10.1371/journal.pmed.1004043

PLoS One. 2022 Jun 30;17(6):e0270497. doi: 10.1371/journal.pone.0270497. eCollection 2022.

ABSTRACT

BACKGROUND: Actovegin is a hemodialysate of calf’s blood and has been used for several decades in the countries of Central Asia, East Asia, Russia and some European countries. It has been used to treat patients with various neurological conditions, vascular disorders, and ischemic stroke.

OBJECTIVES: To perform a systematic review to evaluate the effect of Actovegin in patients who have suffered an ischemic stroke.

METHODS: A search of MEDLINE, PubMed, Cochrane and Embase was carried out from inception to October 10, 2021 for clinical trials and observational studies with a control group, published in English or Russian.

RESULTS: Of 220 identified unique records, 84 full-text articles were screened, and 5 studies were selected that met the inclusion criteria. This included 4 observational studies with control groups and one randomized, placebo-controlled clinical trial. These studies enrolled a total of 3879 patients of which 720 patients received Actovegin administered intravenously and/or orally for a duration ranging from 10 to 180 days. Because of study heterogeneity, meta-analysis was not performed. No consistent evidence on improved survival, quality of life, neurologic symptoms, activities of daily living or disability was identified. One study showed statistically significant improvements in the Alzheimer’s Disease Assessment Scale, cognitive subscale, extended version (ADAS-cog+) for Actovegin compared with placebo at 6 months but the clinical relevance of this change is uncertain. One study reported a higher incidence of recurrent ischemic stroke, transient ischemic attack or intracerebral hemorrhage in patients taking Actovegin compared to placebo.

CONCLUSIONS: The benefits of Actovegin are uncertain and that there is potential risk of harm in patients with stroke. More evidence is needed from rigorously designed clinical trials to justify the role of Actovegin in patients with ischemic stroke.

PMID:35771887 | DOI:10.1371/journal.pone.0270497

PLoS One. 2022 Jun 30;17(6):e0270194. doi: 10.1371/journal.pone.0270194. eCollection 2022.

ABSTRACT

Election forecasting has been traditionally dominated by subjective surveys and polls or methods centered upon them. We have developed a novel platform for forecasting elections based on agent-based modeling (ABM), which is entirely independent from surveys and polls. The platform uses statistical results from objective data along with simulation models to capture how voters have voted in past elections and how they are likely to vote in an upcoming election. We screen for models that can reproduce results that are very close to the actual results of historical elections and then deploy these selected models to forecast an upcoming election with simulations by combining extrapolated data from historical demographic record and more updated data on economic growth, employment, shock events, and other factors. Here, we report the results of two recent experiments of real-time election forecasting: the 2020 general election in Taiwan and six states in the 2020 general election in the United States. Our mostly objective method using ABM may transform how elections are forecasted and studied.

PMID:35771877 | DOI:10.1371/journal.pone.0270194

J Natl Cancer Inst. 2022 Jun 30:djac125. doi: 10.1093/jnci/djac125. Online ahead of print.

ABSTRACT

BACKGROUND: Breast cancer (BC) risk is increased among Hodgkin lymphoma (HL) survivors treated with chest radiotherapy. Case-control studies showed a linear radiation dose-response relationship for estimated dose to the breast tumor location. However, these relative risks cannot be used for absolute risk prediction of BC anywhere in the breasts. Furthermore, the independent and joint effects of radiation dose and irradiated volumes are unclear. Therefore, we examined the effects of mean breast dose and various dose-volume parameters on BC risk in HL patients.

METHODS: We conducted a nested case-control study of BC among five-year HL survivors (173 cases, 464 matched controls). Dose-volume histograms (DVHs) were obtained from reconstructed voxel-based three-dimensional dose distributions. Summary parameters of DVH were studied next to mean and median breast dose, Gini index and the new dose metric mean absolute difference (MAD) of dose, using categorical and linear excess odds ratio (EOR) models. Interactions between dose-volume parameters and mean dose were also examined.

RESULTS: Statistically significant linear dose-response relationships were observed for mean breast dose (EOR/Gy: 0.19; 95% confidence interval [CI]: 0.05 to 1.06) and median dose (EOR/Gy: 0.06; 95% CI: 0.02 to 0.19), with no statistically significant curvature. All metrics except Gini and MAD were positively correlated with each other. These metrics all showed similar patterns of dose-response that were no longer statistically significant when adjusting for mean dose. No statistically significant modification of the effect of mean dose was observed.

CONCLUSION: Mean breast dose predicts subsequent BC risk in long-term HL survivors.

PMID:35771630 | DOI:10.1093/jnci/djac125

JMIR Mhealth Uhealth. 2022 Jun 30;10(6):e37086. doi: 10.2196/37086.

ABSTRACT

BACKGROUND: There has been a rapid increase in the use of commercially available activity trackers, such as Fitbit, in physical activity intervention research. However, little is known about the long-term sustained use of trackers and behavior change after short-term interventions.

OBJECTIVE: This study aims to use minute-level data collected from a Fitbit tracker for up to 2 years after the end of a randomized controlled trial to examine patterns of Fitbit use and activity over time.

METHODS: Participants in this secondary data analysis were 75 female breast cancer survivors who had been enrolled in a 12-week physical activity randomized controlled trial. Participants randomized to the exercise intervention (full intervention arm) received a Fitbit One, which was worn daily throughout the 12-week intervention, and then were followed for 2 years after the intervention. Participants randomized to the waitlist arm, after completing the randomized controlled trial, received a Fitbit One and a minimal version of the exercise intervention (light intervention arm), and then were followed for 2 years after the intervention. Average and daily adherence and MVPA were compared between the 2 groups in the interventional and postinterventional periods using both linear and generalized additive mixed effects models.

RESULTS: Adherence to wearing the Fitbit during the 12-week intervention period was significantly higher in the full intervention arm than in the light intervention arm (85% vs 60%; P<.001). Average adherence was significantly lower for both study arms during the follow-up period than in the intervention period; however, there were statistically different patterns of adherence during the follow-up period, with the light intervention arm having steeper declines than the full intervention arm over time (P<.001). Similar to the adherence results, mean minutes of Fitbit-measured MVPA was higher for the full intervention arm than for the light intervention arm during the 12-week intervention period (mean MVPA 27.89 minutes/day, SD 16.38 minutes/day vs 18.35 minutes/day, SD 12.64 minutes/day; P<.001). During the follow-up period, average MVPA was significantly lower than the 12-week intervention period for both the full intervention arm (21.74 minutes/day, SD 24.65 minutes/day; P=.002) and the light intervention arm (15.03 minutes/day, SD 13.27 minutes/day; P=.004). Although the mean MVPA in each arm was similar across the follow-up period (P=.33), the pattern of daily MVPA was significantly different between the 2 groups (P<.001).

CONCLUSIONS: While adherence to wearing activity trackers and maintaining physical activities declined after completion of a 12-week exercise intervention, a more active interventional strategy resulted in greater wear time and activity levels during the intervention and more stable patterns of adherence and activity in the long term. An improved understanding of long-term maintenance patterns may inform improved exercise interventions that result in sustained increases in physical activity.

TRIAL REGISTRATION: ClinicalTrials.gov NCT02332876; https://clinicaltrials.gov/ct2/show/NCT02332876.

PMID:35771607 | DOI:10.2196/37086