Poincaré plots to analyze photoplethysmography signal between non-smokers and smokers

<span>An analysis of blood circulation was used to identify variations of heart rate and to create an early warning system of autonomic dysfunction. The Poincaré plot analyzed blood circulation using photoplethysmography (PPG) signals between non-smokers and smokers in three different indices: SD1, SD2, and SD1 SD2 ratio (SSR). There were twenty subjects separated into non-smoker and smoker groups with sample sizes of 10, respectively. An independent sample t-test to compare the continuous variables. Whereas, the comparison between two groups employed Fisher’s exact test for categorical variables. The result showed that SD1 was found to be considerably lower in the group of smokers (0.03±0.01) than that of the non-smokers (0.06±0.03). Similarly, SSR was recorded at 0.0012±0.0005 and 0.0023±0.0012 for smoking and non-smoking subjects, respectively. As a comparison, SD2 for non-smokers (25.7±0.5) was lower than smokers (27.3±0.4). In conclusion, we revealed that the parameters of Poincaré plots (SD1, SD2, and SSR) exert good performances to significantly differentiate the PPG signals of the group of non-smokers from those of smokers. We also supposed that the method promises to be a suitable method to distinguish the cardiovascular disease group. Therefore, this method can be applied as a part of early detection system of cardiovascular diseases.</span>

SARS-CoV-2 Gastrointestinal Shedding in Hospitalized Children

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a respiratory virus that can cause gastrointestinal (GI) symptoms, with studies demonstrating detection of stool viral RNA weeks after respiratory tract clearance. It is unknown if children who test negative for SARS-CoV-2 on a nasopharyngeal (NP) swab may be shedding the virus in their stool. OBJECTIVE: To measure the prevalence of SARS-CoV-2 stool shedding in children with positive and negative SARS-CoV-2 NP polymerase chain reactions (PCR) tests, and to determine clinical factors associated with GI shedding. METHODS: In this cross-sectional study, we enrolled hospitalized patients 0 to 21 years old with a positive or a negative SARS-CoV-2 NP PCR test who had respiratory and/or GI symptoms. Participants were surveyed, and stool samples were sent for viral PCR testing. Fisher’s exact test was used to evaluate bivariate associations of stool PCR test positivity with categorical variables. RESULTS: Sixty-seven patients were consented; 34 patients did not provide stool samples so 33 patients were included: 17 NP-positive and 16 NP-negative for SARS-CoV-2. Eight of the 17 NP-positive patients had a positive stool PCR test for SARS-CoV-2, while none of the 16 SARS-CoV-2 NP-negative patients had a positive result (P &lt; .01). For the 17 SARS-CoV-2 NP-positive patients, GI symptoms were associated with a positive stool PCR test (P = .05) for SARS-CoV-2, but this association was not found for all 33 patients (P = .11). No associations were found with patients in an immunocompromised state or those with a comorbid condition, fever and/or chills, respiratory symptoms, headache and/or myalgias, or anosmia and/or ageusia. CONCLUSIONS: SARS-CoV-2 GI shedding is common and associated with GI symptoms in NP-positive children, with 47% having positive stool PCRs for SARS-CoV-2. GI shedding was not demonstrated in SARS-CoV-2 NP-negative children.

A Low Advanced Lung Cancer Inflammation Index Predicts a Poor Prognosis in Patients With Metastatic Non–Small Cell Lung Cancer

Introduction: Inflammation plays a crucial role in cancers, and the advanced lung cancer inflammation index (ALI) is considered to be a potential factor reflecting systemic inflammation.Objectives: This work aimed to explore the prognostic value of the ALI in metastatic non–small cell lung cancer (NSCLC) and classify patients according to risk and prognosis.Methods: We screened 318 patients who were diagnosed with stage IV NSCLC in Hubei Cancer Hospital from July 2012 to December 2013. The formula for ALI is body mass index (BMI, kg/m2) × serum albumin (Alb, g/dl)/neutrophil–lymphocyte ratio (NLR). Categorical variables were analyzed by the chi-square test or Fisher’s exact test. The overall survival (OS) rates were analyzed by the Kaplan–Meier method and plotted with the R language. A multivariate Cox proportional hazard model was used to analyze the relationship between ALI and OS.Results: According to the optimal cut-off value determined by X-tile software, patients were divided into two groups (the ALI &lt;32.6 and ALI ≥32.6 groups), and the median OS times were 19.23 and 39.97 months, respectively (p &lt; 0.01). A multivariable Cox regression model confirmed that ALI and chemotherapy were independent prognostic factors for OS in patients with NSCLC. OS in the high ALI group was better than that in the low ALI group (HR: 1.39; 95% CI: 1.03–1.89; p = 0.03).Conclusions: Patients with a low ALI tend to have lower OS among those with metastatic NSCLC, and the ALI can serve as an effective prognostic factor for NSCLC patients.

A framework for inserting visually-supported inferences into geographical analysis workflow: application to road safety research

Road safety research is a data-rich field with large social impacts. Like in medical research, the ambition is to build knowledge around risk factors that can save lives. Unlike medical research, road safety research generates empirical findings from messy observational datasets. Records of road crashes contain numerous intersecting categorical variables, dominating patterns that are complicated by confounding and, when conditioning on data to make inferences net of this, observed effects that are subject to uncertainty due to diminishing sample sizes. We demonstrate how visual data analysis approaches can inject rigour into exploratory analysis of such datasets. A framework is presented whereby graphics are used to expose, model and evaluate spatial patterns in observational data, as well as protect against false discovery. The framework is supported through an applied data analysis of national crash patterns recorded in STATS19, the main source of road crash information in Great Britain. Our framework moves beyond typical depictions of exploratory data analysis and helps navigate complex data analysis decision spaces typical in modern geographical analysis settings, generating data-driven outputs that support effective policy interventions and public debate.

Prevalence and Postpartum Screening Practice for Type 2 Diabetes following GDM in King Abdulaziz Medical City: A 3-Years Retrospective Cohort Study

Aim: GDM patients were associated to develop T2DM but mostly failed to undergo screening after delivery. This study aims to examine the practice of T2DM screening and prevalence of developing T2DM among women who had GDM in King Abdulaziz Medical City (KAMC), Saudi Arabia. Methods: Retrospective study involving 642 pregnant women with GDM. Medical records on screenings conducted, delivery mode, GDM and diabetes family history were collected and investigated. Statistical analysis was conducted. Frequencies and percentages were used for categorical variables while means and SD for continuous. Chi-square and t-test were used to establish relationship of categorical and comparing two group means, respectively. Results: Patients were 98.8% Saudi nationals, mean weight, height, parity and number of pregnancies were 76.96 kg, 2.74 m, 3.37 and 1.35, respectively. Majority were obese (56.9%), SVD (56.4%) mode of delivery and good lifestyle (91.4%) as management practice. OGTT was used for screening T2DM with 0 hr fasting and 2-hrs after consuming 75g of glucose, physician ordered 6 weeks after delivery. Only 20% had screening for T2DM and 3.9% developed postpartum diabetes with high number of women not returning for ordered OGTT screening (65.6%). Significant predictors identified were parity and mode of delivery for development of T2DM, while only mode of delivery for both screening for T2DM and management of GDM.Conclusion: Low prevalence of developing T2DM but high number of women failed to follow the ordered OGTT screening. Effort on the implementation of OGTT screening for T2DM needs improvement.

Optimal experimental designs for estimating genetic and non-genetic effects underlying infectious disease transmission

BACKGROUND: Infectious disease spread in populations is controlled by individuals' susceptibility (propensity to acquire infection), infectivity (propensity to pass on infection to others) and recoverability (propensity to recover/die). Estimating the effects of genetic risk factors on these host epidemiological traits can help reduce disease spread through genetic control strategies. However, the effects of previously identified "disease resistance SNPs" on these epidemiological traits are usually unknown. Recent advances in computational statistics make it now possible to estimate the effects of single nucleotide polymorphisms (SNPs) on these traits from longitudinal epidemic data (e.g. infection and/or recovery times of individuals or diagnostic test results). However, little is known how to optimally design disease transmission experiments or field studies to maximise the precision at which pleiotropic SNP effects estimates for susceptibility, infectivity and recoverability can be estimated. RESULTS: We develop and validate analytical expressions for the precision of SNP effects estimates on the three host traits assuming a disease transmission experiment with one or more non-interacting contact groups. Maximising these leads to three distinct "experimental" designs, each specifying a different set of ideal SNP genotype compositions across groups: a) appropriate for a single contact-group, b) a multi-group design termed "pure", and c) a multi-group design termed "mixed", where "pure" and "mixed" refer to contact groups consisting of individuals with the same or different SNP genotypes, respectively. Precision estimates for susceptibility and recoverability were found to be less sensitive to the experimental design than infectivity. Data from multiple groups were found more informative about infectivity effects than from a single group containing the same number of individuals. Whilst the analytical expressions suggest that the multi-group pure and mixed designs estimate SNP effects with similar precision, the mixed design is preferable because it uses information from naturally occurring infections rather than those artificially induced. The same optimal design principles apply to estimating other categorical fixed effects, such as vaccinations status, helping to more effectively quantify their epidemiological impact. An online software tool SIRE-PC has been developed which calculates the precision of estimated substitution and dominance effects of a single SNP (or vaccine status) associated with all three traits depending on experimental design parameters. CONCLUSIONS: The developed methodology and software tool can be used to aid the design of disease transmission experiments for estimating the effect of individual SNPs and other categorical variables underlying host susceptibility, infectivity and recoverability.

Balloon expandable Stent utility for early Secondary Prevention of new Cerebral Ischemic events Caused by Intracranial Atherosclerotic Stenosis. Technical Nuances

Objective: Recurrent cerebral ischemic events are estimated to appear in between 12-15% of symptomatic intracranial atherosclerotic disease (ICAD), regardless of the use of leading pharmacological therapies. Balloon expandable stent (balloon mounted coronary stent) could represent a feasible alternative in this disease’s treatment. This study pretends to report the balloon-expandable placement experience in our center. Materials and Methods: A unicentric retrospective study dated between September 2009 and March 2018 was conducted. Patients previously diagnosed with ICAD and symptomatic stenosis treated with balloon-expandable stent were included. Clinical features, morbidity, mortality, short and long-term evolution, and pre-and post-treatment angiographic features were analyzed, as well as a mean 8 years-period follow-up. Data are presented as means, frequencies, and percentages for categorical variables, and ranks for continuous variables. Statistical analysis was carried by IBM SPSS Statistics Base V22.0 (IBM Corporation, Mexico). A Wilcoxon Signed-rank test statistical analysis was performed. Statistical significance was considered when a p-value lesser than 0.05 was measured for every result. Results: A total of 6 patients with 7 affected vessels were treated, with an average age of 62.7 years. Affected and treated vessels were located in the Internal Carotid Artery (ICA) segment in 42.9%, Vertebral Artery (VA) V4 segment in 14.3%, Middle Cerebral Artery (MCA) M1 segment in 28.5%, and Posterior Cerebral Artery (PCA) P1 segment in 14.3%. The incidence of peri-operatory thrombotic events was 0%. Intracranial hemorrhage presented in 0% of cases. Recurrent ischemic or thrombotic events were not reported in a 97-months mean follow-up. 71.4% of patients scored ≤2 in the modified Rankin Score (mRS) pre-treatment, in a 90 day and 12-month follow-up. 100% presented a favorable evolution with mRS ≤2. Restenosis cases were not reported in radiologic control and retreatment was not needed in a 97-month mean follow-up. Conclusions: This study suggests that balloon-expandable stent therapy with some technical endovascular variants for its navigation and placement could be a safe and effective alternative in the treatment of ICAD as a means of cerebral ischemic event early secondary prevention. We propose to consider not to limit endovascular treatment exclusively to those symptomatic ICAD patients refractory to medical-exclusive treatment, as a means to reduce the risk of presenting a new neurological deficit. Further expanded clinical trials are needed to confirm these findings and the advantage of this kind of stents against other kinds reported in the literature.

Breast Cancer Classification Based on Tumor Budding and Stem Cell-Related Signatures Facilitate Prognosis Evaluation

BackgroundTumor budding (TB) is emerging as a prognostic factor in multiple cancers. Likewise, the stemness of cancer cells also plays a vital role in cancer progression. However, nearly no research has focused on the interaction of TB and tumor stemness in cancer.MethodsTissue microarrays including 229 cases of invasive breast cancer (BC) were established and subjected to pan-cytokeratin immunohistochemical staining to evaluate molecular expression. Univariate and multivariate analyses were applied to identify prognostic factors of BC, and the Chi-square test was used for comparison of categorical variables.ResultsHigh-grade TB was significantly associated with T stage, lymph node metastasis, tumor node metastasis (TNM) stage, epithelial-mesenchymal transition, and poor disease-free survival (DFS) of BC patients. We also found that the prognostic value of TB varied widely among different subtypes and subgroups. Cox regression analysis then showed that TB grade was an independent prognostic factor. Moreover, cancer stem cell (CSC) markers CD44 and ALDH1A1 were significantly higher in high-grade TB tumors. Consequently, patients were classified into high CSC score subgroup and low CSC score subgroups. Further research found that CSC scores correlated with clinicopathological features and DFS of BC patients. Based on TB grade and CSC scores, we classified BC patients into TBlow-CSCslow (type I), TBlow-CSCshigh (type II), TBhigh-CSCslow (type III), and TBhigh-CSCshigh (type IV) subgroups. Survival analysis showed that patients in the type I subgroup had the best DFS, whereas those in the type IV subgroup had the worst DFS. Finally, a TB-CSC-based nomogram for use in BC was established. The nomogram was well calibrated to predict the probability of 5-year DFS, and the C-index was 0.837. Finally, the area under the curve value for the nomogram (0.892) was higher than that of the TNM staging system (0.713).ConclusionThe combination of TB grade with CSC score improves the prognostic evaluation of BC patients. A novel nomogram containing TB grade and CSC score provides doctors with a candidate tool to guide the individualized treatment of cancer patients.

Perceptions of Cannabis in sub-Saharan Africa: Findings from a general population survey in six African countries with different Cannabis policies.

Background Recently, legislative shifts in cannabis regulation away from exclusively prohibitionist controls have been seen in sub-Saharan African countries. However, the extent to which public perceptions are aligned with policy trends is unclear. Given that views concerning cannabis may be influenced by associated legislation we aimed to compare public opinion towards cannabis amongst countries with legislatively different cannabis policies. Methods We conducted an online survey of the general adult population in six purposively selected countries representative of maximum policy variation across sub-Saharan Africa i.e., Ghana, Nigeria, Sierra Leone, South Africa and Zimbabwe. Survey questions covered perceptions towards users, risks and benefits, regulations and public health impacts as well as sociodemographic characteristics. Chi square tests were used to analyse the association between categorical variables and explore country level differences. Results Totally 1216 responses were received. Large variations were noted in responses towards user stereotypes, risks and preferred legislation. In relation to users being honest (X2=43.316, P<0.0001), most in Sierra Leone(52.9%), Nigeria (45.6%) and Uganda(48.6%) disagreed whereas in Ghana(39.4%), South Africa(43.3%) and Zimbabwe(40.1%) most agreed. Differences in smoking cannabis and smoking tobacco products(X2= 27.712, P=0.002) saw respondents from Ghana(51.4%), Nigeria(58.8%), Uganda(50.9%) and Zimbabwe(46.8%) agreeing that smoking cannabis is more harmful to health, whereas majorities in Sierra Leone(45.7%) and South Africa(49.8%) disagreed. Apart from South Africa were the greater proportion opted to allow cannabis for all purposes(28.8%), majorities in other countries supported only medicinal legalisation(X2= 96.631, P<0.0001). Conclusion Dependent upon the question of focus, at the liberal end of the policy spectrum are Ghana, South Africa and Zimbabwe whilst Nigeria, Sierra Leone and Uganda were more conservative. Responses tended to reflect the policy position of respective countries, however our findings suggest overall increasing medicinal cannabis support. Greater understanding of policy dynamics may help create frameworks for countries contemplating reforms.

Discordance between LDL-C and Apolipoprotein B Levels and Its Association with Renal Dysfunction: Insights from a Population-Based Study

Low-density lipoprotein cholesterol (LDL-C) and apolipoprotein B (ApoB) are established markers of atherosclerotic cardiovascular disease (ASCVD), but when concentrations are discordant ApoB is the superior predictor. Chronic kidney disease (CKD) is associated with ASCVD, yet the independent role of atherogenic lipoproteins is contentious. Four groups were created based upon high and low levels of ApoB and LDL-C. Continuous and categorical variables were compared across groups, as were adjusted markers of CKD. Logistic regression analysis assessed association(s) with CKD based on the groups. Subjects were categorised by LDL-C and ApoB, using cut-off values of >160 mg/dL and >130 mg/dL, respectively. Those with low LDL-C and high ApoB, compared to those with high LDL-C and high ApoB, had significantly higher body mass index (30.7 vs. 30.1 kg/m2) and waist circumference (106.1 vs. 102.7 cm) and the highest fasting blood glucose (117.5 vs. 112.7 mg/dL), insulin (16.6 vs. 13.1 μU/mL) and homeostatic model assessment of insulin resistance (5.3 vs. 3.7) profiles (all p < 0.001). This group, compared to those with high LDL-C and high ApoB, also had the highest levels of urine albumin (2.3 vs. 2.2 mg/L), log albumin-creatinine ratio (2.2 vs. 2.1 mg/g) and serum uric acid (6.1 vs. 5.6 mg/dL) and the lowest estimated glomerular filtration rate (81.3 vs. 88.4 mL/min/1.73 m2) (all p < 0.001). In expanded logistic regression models, using the low LDL-C and low ApoB group as a reference, those with low LDL-C and high ApoB had the strongest association with CKD, odds ratio (95% CI) 1.12 (1.08–1.16). Discordantly high levels of ApoB are independently associated with increased likelihood of CKD. ApoB remains associated with metabolic dysfunction, regardless of LDL-C.