Tag: pubmed

PLoS Negl Trop Dis. 2021 Aug 6;15(8):e0009673. doi: 10.1371/journal.pntd.0009673. Online ahead of print.

ABSTRACT

BACKGROUND: Hemorrhagic fever with renal syndrome (HFRS) is a rodent-borne disease caused by hantavirus which was endemic Zhejiang Province, China. In this study, we aim to explore the changing epidemiology of HFRS in Zhejiang, identify high-risk areas and populations, and evaluate relevant policies and interventions to better improve HFRS control and prevention.

METHODS: Surveillance data on HFRS during 1963-2020 in Zhejiang Province were extracted from Zhejiang Provincial Center for Disease Control and Prevention archives and the Chinese Notifiable Disease Reporting System. The changing epidemiological characteristics of HFRS including seasonal distribution, geographical distribution, and demographic features, were analyzed using joinpoint regression, autoregressive integrated moving average model, descriptive statistical methods, and Spatio-temporal cluster analysis.

RESULTS: From 1963 to 2020, 114 071 HFRS cases and 1269 deaths were reported in Zhejiang Province. The incidence increased sharply from 1973 and peaked in 1986, then decreased steadily and maintained a stable incidence from 2004. HFRS cases were reported in all 11 prefecture-level cities of Zhejiang Province from 1963 to 2020. The joint region (Shengzhou, Xinchang, Tiantai, and surrounding areas), and Kaihua County are the most seriously affected regions throughout time. After 1990, the first HFRS incidence peak was in May-June, with another one from November to January. Most HFRS cases occurred in 21- (26.48%) and 30- years group (24.25%) from 1991 to 2004, but 41- (25.75%) and 51-years (23.30%) had the highest proportion from 2005 to 2020. Farmers accounted for most cases (78.10%), and cases are predominantly males with a male-to-female ratio of 2.6:1. It was found that the median time from onset to diagnosis was 6.5 days (IQR 3.75-10.42), and the time from diagnosis to disease report was significantly shortened after 2011.

CONCLUSIONS: We observed dynamic changes in the seasonal distribution, geographical distribution, and demographic features of HFRS, which should be well considered in the development of control and prevention strategies in future. Additional researches are warranted to elucidate the environmental, meteorological, and social factors associated with HFRS incidence in different decades.

PMID:34358248 | DOI:10.1371/journal.pntd.0009673

PLoS Negl Trop Dis. 2021 Aug 6;15(8):e0009593. doi: 10.1371/journal.pntd.0009593. Online ahead of print.

ABSTRACT

BACKGROUND: Brucellosis is widespread in Ethiopia with variable reported prevalence depending on the geographical area, husbandry practices and animal species. However, there is limited information on the disease prevalence amongst pastoral communities, whose life is intricately linked with their livestock.

METHODOLOGY: We conducted an integrated human-animal brucellosis sero-surveillance study in two adjacent pastoral regions, Afar and Somali region (SRS). This cross-sectional study included 13 woredas (districts) and 650 households. Blood samples were collected from people and livestock species (cattle, camel, goats and sheep). Sera were analyzed with C-ELISA for camels and shoats (sheep and goats), with I-ELISA for cattle and IgG ELISA for humans. Descriptive and inferential statistics analyses were performed.

RESULTS: A total of 5469 sera were tested by ELISA. Prevalence of livestock was 9.0% in Afar and 8.6% in SRS (ranging from 0.6 to 20.2% at woreda level). In humans, prevalence was 48.3% in Afar and 34.9% in SRS (ranging from 0.0 to 74.5% at woreda level). 68.4% of all households in Afar and 57.5% of households in SRS had at least one animal reactor. Overall, 4.1% of animals had a history of abortion. The proportion of animals with abortion history was higher in seropositive animals than in seronegative animals. Risk factor analysis showed that female animals were significantly at higher risk of being reactors (p = 0.013). Among the species, cattle had the least risk of being reactors (p = 0.014). In humans, there was a clear regional association of disease prevalence (p = 0.002). The older the people, the highest the odds of being seropositive.

CONCLUSION: Brucellosis is widespread in humans and animals in pastoral communities of Afar and SRS with the existence of geographical hotspots. No clear association was seen between human and particular livestock species prevalence, hence there was no indication as whether B. abortus or B. melitensis are circulating in these areas, which warrants further molecular research prior to embarking on a national control programs. Such programs will need to be tailored to the pastoral context.

PMID:34358232 | DOI:10.1371/journal.pntd.0009593

PLoS One. 2021 Aug 6;16(8):e0255269. doi: 10.1371/journal.pone.0255269. eCollection 2021.

ABSTRACT

The Sine-Cosine algorithm (SCA) is a population-based metaheuristic algorithm utilizing sine and cosine functions to perform search. To enable the search process, SCA incorporates several search parameters. But sometimes, these parameters make the search in SCA vulnerable to local minima/maxima. To overcome this problem, a new Multi Sine-Cosine algorithm (MSCA) is proposed in this paper. MSCA utilizes multiple swarm clusters to diversify & intensify the search in-order to avoid the local minima/maxima problem. Secondly, during update MSCA also checks for better search clusters that offer convergence to global minima effectively. To assess its performance, we tested the MSCA on unimodal, multimodal and composite benchmark functions taken from the literature. Experimental results reveal that the MSCA is statistically superior with regards to convergence as compared to recent state-of-the-art metaheuristic algorithms, including the original SCA.

PMID:34358237 | DOI:10.1371/journal.pone.0255269

PLoS One. 2021 Aug 6;16(8):e0253425. doi: 10.1371/journal.pone.0253425. eCollection 2021.

ABSTRACT

Statistical models for outcome prediction are central to traumatic brain injury research and critical to baseline risk adjustment. Glasgow coma score (GCS) and pupil reactivity are crucial covariates in all such models but may be measured at multiple time points between the time of injury and hospital and are subject to a variable degree of unreliability and/or missingness. Imputation of missing data may be undertaken using full multiple imputation or by simple substitution of measurements from other time points. However, it is unknown which strategy is best or which time points are more predictive. We evaluated the pseudo-R2 of logistic regression models (dichotomous survival) and proportional odds models (Glasgow Outcome Score-extended) using different imputation strategies on the The Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study dataset. Substitution strategies were easy to implement, achieved low levels of missingness (<< 10%) and could outperform multiple imputation without the need for computationally costly calculations and pooling multiple final models. While model performance was sensitive to imputation strategy, this effect was small in absolute terms and clinical relevance. A strategy of using the emergency department discharge assessments and working back in time when these were missing generally performed well. Full multiple imputation had the advantage of preserving time-dependence in the models: the pre-hospital assessments were found to be relatively unreliable predictors of survival or outcome. The predictive performance of later assessments was model-dependent. In conclusion, simple substitution strategies for imputing baseline GCS and pupil response can perform well and may be a simple alternative to full multiple imputation in many cases.

PMID:34358231 | DOI:10.1371/journal.pone.0253425

PLoS Comput Biol. 2021 Aug 6;17(8):e1009275. doi: 10.1371/journal.pcbi.1009275. Online ahead of print.

ABSTRACT

In modern computational biology, there is great interest in building probabilistic models to describe collections of a large number of co-varying binary variables. However, current approaches to build generative models rely on modelers’ identification of constraints and are computationally expensive to infer when the number of variables is large (N~100). Here, we address both these issues with Super-statistical Generative Model for binary Data (SiGMoiD). SiGMoiD is a maximum entropy-based framework where we imagine the data as arising from super-statistical system; individual binary variables in a given sample are coupled to the same ‘bath’ whose intensive variables vary from sample to sample. Importantly, unlike standard maximum entropy approaches where modeler specifies the constraints, the SiGMoiD algorithm infers them directly from the data. Due to this optimal choice of constraints, SiGMoiD allows to model collections of a very large number (N>1000) of binary variables. Finally, SiGMoiD offers a reduced dimensional description of the data, allowing us to identify clusters of similar data points as well as binary variables. We illustrate the versatility of SiGMoiD using several datasets spanning several time- and length-scales.

PMID:34358223 | DOI:10.1371/journal.pcbi.1009275

Echocardiography. 2021 Aug 6. doi: 10.1111/echo.15170. Online ahead of print.

ABSTRACT

AIM: Chest computed tomography (CT) imaging plays a diagnostic and prognostic role in Coronavirus disease 2019 (COVID-19) patients. This study aimed to investigate and compare predictive capacity of main pulmonary artery diameter (MPA), ascending aorta diameter (AAo), and MPA-to-AAo ratio to determine in-hospital mortality in COVID-19 patients.

MATERIALS AND METHODS: This retrospective study included 255 hospitalized severe or critical COVID-19 patients. MPA was measured at the level of pulmonary artery bifurcation perpendicular to the direction of the vessel through transverse axial images and AAo was measured by using the same CT slice at its maximal diameter. MPA-to-AAo ratio was calculated by division of MPA to AAo.

RESULTS: Multivariate logistic regression model yielded MPA ≥29.15 mm (OR: 4.95, 95% CI: 2.01-12.2, p = 0.001), MPA (OR: 1.28, 95% CI: 1.13-1.46, p < 0.001), AAo (OR: .90, 95% CI: .81-.99, p = 0.040), and MPA-to-AAo ratio ≥.82 (OR: 4.67, 95% CI: 1.86-11.7, p = 0.001) as independent predictors of in-hospital mortality. Time-dependent multivariate Cox-proportion regression model demonstrated MPA ≥29.15 mm (HR: 1.96, 95% CI: 1.03-3.90, p = 0.047) and MPA (HR: 1.08, 95% CI: 1.01-1.17, p = 0.048) as independent predictors of in-hospital mortality, whereas AAo and MPA-to-AAo ratio did not reach statistical significance.

CONCLUSION: Pulmonary artery enlargement strongly predicts in-hospital mortality in hospitalized COVID-19 patients. MPA, which can be calculated easily from chest CT imaging, can be beneficial in the prognostication of these patients.

PMID:34355824 | DOI:10.1111/echo.15170

J Magn Reson Imaging. 2021 Aug 6. doi: 10.1002/jmri.27871. Online ahead of print.

ABSTRACT

BACKGROUND: CD8⁺ T cell in pancreatic ductal adenocarcinoma (PDAC) is closely related to the prognosis and treatment response of patients. Accurate preoperative CD8⁺ T-cell expression can better identify the population benefitting from immunotherapy.

PURPOSE: To develop and validate a machine learning classifier based on noncontrast magnetic resonance imaging (MRI) for the preoperative prediction of CD8⁺ T-cell expression in patients with PDAC.

STUDY TYPE: Retrospective cohort study.

POPULATION: Overall, 114 patients with PDAC undergoing MR scan and surgical resection; 97 and 47 patients in the training and validation cohorts. FIELD STRENGTH/SEQUENCE/3 T: Breath-hold single-shot fast-spin echo T2-weighted sequence and noncontrast T1-weighted fat-suppressed sequences.

ASSESSMENT: CD8⁺ T-cell expression was quantified using immunohistochemistry. For each patient, 2232 radiomics features were extracted from noncontrast T1- and T2-weighted images and reduced using the Wilcoxon rank-sum test and least absolute shrinkage and selection operator method. Linear discriminative analysis was used to construct radiomics and mixed models. Model performance was determined by its discriminative ability, calibration, and clinical utility.

STATISTICAL TESTS: Kaplan-Meier estimates, Student’s t-test, the Kruskal-Wallis H test, and the chi-square test, receiver operating characteristic curve, and decision curve analysis.

RESULTS: A log-rank test showed that the survival duration in the CD8-high group (25.51 months) was significantly longer than that in the CD8-low group (22.92 months). The mixed model included all MRI characteristics and 13 selected radiomics features, and the area under the curve (AUC) was 0.89 (95% confidence interval [CI], 0.77-0.92) and 0.69 (95% CI, 0.53-0.82) in the training and validation cohorts. The radiomics model included 13 radiomics features, which showed good discrimination in the training cohort (AUC, 0.85; 95% CI, 0.77-0.92) and the validation cohort (AUC, 0.76; 95% CI, 0.61-0.87).

DATA CONCLUSIONS: This study developed a noncontrast MRI-based radiomics model that can preoperatively determine CD8⁺ T-cell expression in patients with PDAC and potentially immunotherapy planning.

EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: Stage 2.

PMID:34355834 | DOI:10.1002/jmri.27871

Clin Cardiol. 2021 Aug 6. doi: 10.1002/clc.23708. Online ahead of print.

ABSTRACT

BACKGROUND: Recent reports have indicated the beneficial role of strain measurement in COVID-19 patients.

HYPOTHESIS: To determine the association between right and left global longitudinal strain (RVGLS, LVGLS) and COVID-19 patients’ outcomes.

METHODS: Hospitalized COVID-19 patients between June and August 2020 were included. Two-dimensional echocardiography and biventricular global longitudinal strain measurement were performed. The outcome measure was defined as mortality, ICU admission, and need for intubation. Appropriate statistical tests were used to compare different groups.

RESULTS: In this study 207 patients (88 females) were enrolled. During 64 ± 4 days of follow-up, 22 (10.6%) patients died. Mortality, ICU admission, and intubation were significantly associated with LVGLS and RVGLS tertiles. LVGLS tertiles could predict poor outcome with significant odds ratios in the total population (OR = 0.203, 95% CI: 0.088-0.465; OR = 0.350, 95% CI: 0.210-0.585; OR = 0.354, 95% CI: 0.170-0.736 for mortality, ICU admission, and intubation). Although odds ratios of LVGLS for the prediction of outcome were statistically significant among hypertensive patients, these odds ratios did not reach significance among non-hypertensive patients. RVGLS tertiles revealed significant odds ratios for the prediction of mortality (OR = 0.322, 95% CI: 0.162-0.640), ICU admission (OR = 0.287, 95% CI: 0.166-0.495), and need for intubation (OR = 0.360, 95% CI: 0.174-0.744). Odds ratios of RVGLS remained significant even after adjusting for hypertension when considering mortality and ICU admission.

CONCLUSION: RVGLS and LVGLS can be acceptable prognostic factors to predict mortality, ICU admission, and intubation in hospitalized COVID-19 patients. However, RVGLS seems more reliable, as it is not confounded by hypertension.

PMID:34355809 | DOI:10.1002/clc.23708

Echocardiography. 2021 Aug 6. doi: 10.1111/echo.15175. Online ahead of print.

ABSTRACT

BACKGROUND: The evaluation of the tricuspid annular plane systolic excursion (TAPSE) is recommended to assess the right ventricular (RV) systolic function. We performed an updated meta-analysis of the association between TAPSE and short-term mortality in COVID-19 patients.

METHODS: MEDLINE and Scopus databases were searched to locate all the articles published up to May 1, 2021, reporting data on TAPSE among COVID-19 survivors and non-survivors. The difference of TAPSE between the two groups was expressed as mean difference (MD) with the corresponding 95% confidence interval (CI) using the Mantel-Haenszel random effects model. Both Q value and I² statistics were used to assess heterogeneity across studies. Sensitivity analysis, meta-regression, and evaluation of bias were performed.

RESULTS: Twelve studies, enrolling 1272 COVID-19 patients (778 males, mean age 69.3 years), met the inclusion criteria and were included in the final analysis. Non-survivors had a lower TAPSE compared to survivors (MD = -3.089 mm, 95% CI = -4.087 to -2.091, p < 0.0001, I² = 79.0%). Both the visual inspection of the funnel plot and the Egger’s tests (t = 1.195, p = 0.259) revealed no evidence of publication bias. Sensitivity analysis confirmed yielded results. Meta-regression analysis evidenced that the difference in TAPSE between the two groups was only influenced by pre-existing chronic obstructive pulmonary disease (COPD, p = 0.02).

CONCLUSION: COVID-19 non-survivors have a lower TAPSE when compared to survivors, especially in COPD subjects. Current data suggest that the TAPSE assessment may provide useful information regarding the short-term prognosis of COVID-19 patients during the infection.

PMID:34355816 | DOI:10.1111/echo.15175

Cardiol J. 2021 Aug 6. doi: 10.5603/CJ.a2021.0083. Online ahead of print.

ABSTRACT

BACKGROUND: Atrial fibrillation (AF) is the leading cause of stroke. The European Society of Cardiology (ESC) advises opportunistic AF screening among patients aged ≥ 65 years. Considering this, the aim herein, was compare the feasibility of two different systems of smartphone-based electrocardiogram (ECG) recordings to identify AF among those without a previous arrhythmia history.

METHODS: Prospective AF screening was conducted at six pharmacies using Kardia Mobile and Hartmann Veroval 2 in 1. A single-lead ECG was acquired by the placement of fingers on the pads. A cardiologist evaluated findings from both devices.

RESULTS: Atrial fibrillation was identified in 3.60% and previously unknown AF was detected in 1.92% of the study participants. Sensitivity and specificity of the Kardia application in detecting AF were 66.7% (95% confidence interval [CI] 38.4-88.2%) and 98.5% (95% CI 96.7-99.5%), and for Veroval 10.0% (95% CI 0.23-44.5%) and 94.96% (95% CI 92.15-96.98%), accordingly. Inter-rater agreement was k = 0.088 (95% CI 1.59-16.1%).

CONCLUSIONS: Mobile devices can detect AF, but each finding must be verified by a professional. The Kardia application appeared to be more user-friendly than Veroval. Cardiovascular screening using mobile devices is feasible at pharmacies. Hence it might be considered for routine use.

PMID:34355779 | DOI:10.5603/CJ.a2021.0083