Abstract P36: Lesional Perfusion and Permeability Are Diagnostic and Prognostic Biomarkers of Cavernous Angioma With Symptomatic Hemorrhage

Stroke ◽  
2021 ◽  
Vol 52 (Suppl_1) ◽  
Author(s):  
Je Yeong Sone ◽  
Nicholas Hobson ◽  
Sharbel Romanos ◽  
Abhinav Srinath ◽  
Abdallah Shkoukani ◽  
...  
Keyword(s):  
Regression Models ◽  
Prognostic Biomarker ◽  
Information Criterion ◽  
Cavernous Angioma ◽  
Prognostic Biomarkers ◽  
Diagnostic Efficacy ◽  
Logistic Regression Models ◽  
Conventional Mri ◽  
Contrast Enhanced ◽  
Univariate Analyses

Introduction: Diagnosis of cavernous angioma with symptomatic hemorrhage (CASH) requires MRI evidence of lesional bleeding associated directly with attributable symptoms. However, hemorrhagic signs of CASH may become clinically silent on conventional MRI after 3 months. As CASH is likely to rebleed for several years, accurate diagnosis of CASH that bled more than 3 months prior is needed. Hypothesis: Perfusion and permeability derivations of dynamic contrast-enhanced quantitative perfusion (DCEQP) MRI can diagnose CASH and predict bleeding/growth in CAs. Methods: CAs of 205 consecutively enrolled patients scanned with DCEQP during clinical visits were classified as CASH that bled 3 - 12 months prior (N = 55) versus non-CASH (N = 658) or CA with (N = 23) versus without (N = 721) bleeding/growth within a year after MRI. Demographics and 13 perfusion and 13 permeability derivations of DCEQP were assessed via machine learning and univariate analyses. Logistic regression models ln ( P / 1 - P ) = Σ (β i x i ) + β 0 were selected as the best diagnostic and prognostic biomarkers by minimizing the Bayesian information criterion (BIC). Results: The best diagnostic biomarker of CASH that bled 3 - 12 months prior (BIC = 321.6, Figure A) showed 80% sensitivity and 82% specificity. Permeability derivations did not add diagnostic efficacy when combined with perfusion. The best prognostic biomarker of bleeding/growth (BIC = 201.5, Figure B) showed 77% sensitivity and 72% specificity. Conclusion: Perfusion imaging may diagnose CASH even after hemorrhagic signs disappear on conventional MRI. A combination of permeability and perfusion derivations may help predict bleeding/growth in CAs.

scholarly journals Habitat or matrix: which is more relevant to predict road-kill of vertebrates?

2015 ◽  
Vol 75 (4 suppl 1) ◽  
pp. 228-238 ◽  
Author(s):  
C. Bueno ◽  
C. O. M. Sousa ◽  
S. R. Freitas
Keyword(s):  
Regression Models ◽  
Movement Ecology ◽  
Information Criterion ◽  
Mitigation Measures ◽  
Conservation Strategies ◽  
Southeastern Brazil ◽  
Logistic Regression Models ◽  
Road Kill ◽  
Landscape Characteristics ◽  
Effect Model

Abstract We believe that in tropics we need a community approach to evaluate road impacts on wildlife, and thus, suggest mitigation measures for groups of species instead a focal-species approach. Understanding which landscape characteristics indicate road-kill events may also provide models that can be applied in other regions. We intend to evaluate if habitat or matrix is more relevant to predict road-kill events for a group of species. Our hypothesis is: more permeable matrix is the most relevant factor to explain road-kill events. To test this hypothesis, we chose vertebrates as the studied assemblage and a highway crossing in an Atlantic Forest region in southeastern Brazil as the study site. Logistic regression models were designed using presence/absence of road-kill events as dependent variables and landscape characteristics as independent variables, which were selected by Akaike’s Information Criterion. We considered a set of candidate models containing four types of simple regression models: Habitat effect model; Matrix types effect models; Highway effect model; and, Reference models (intercept and buffer distance). Almost three hundred road-kills and 70 species were recorded. River proximity and herbaceous vegetation cover, both matrix effect models, were associated to most road-killed vertebrate groups. Matrix was more relevant than habitat to predict road-kill of vertebrates. The association between river proximity and road-kill indicates that rivers may be a preferential route for most species. We discuss multi-species mitigation measures and implications to movement ecology and conservation strategies.

scholarly journals HLA-DRB1 Amino Acid Positions and Residues Associated with Antibody-positive Rheumatoid Arthritis in Black South Africans

2018 ◽  
Vol 46 (2) ◽  
pp. 138-144 ◽  
Author(s):  
Nimmisha Govind ◽  
Richard J. Reynolds ◽  
Bridget Hodkinson ◽  
Claudia Ickinger ◽  
Michele Ramsay ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Amino Acid ◽  
Regression Models ◽  
Amino Acid Residues ◽  
Site Specific ◽  
Specific Amino Acid ◽  
Logistic Regression Models ◽  
South Africans ◽  
Black South Africans ◽  
Univariate Analyses

Objective.To investigate the association of specific amino acid positions, residues, and haplotypes of HLA-DRB1 in black South Africans with autoantibody-positive rheumatoid arthritis (RA).Methods.High-resolutionHLA-DRB1genotyping was performed in 266 black South Africans with autoantibody-positive RA and 362 ethnically and geographically matched controls. The alleles were converted to specific amino acid residues at polymorphic sites for downstream analyses. Logistic regression models were used to test whether variability at site, specific amino acid residues, and haplotypes (constructed from positions 11, 71, and 74) were associated with RA.Results.Of the 29 amino acid positions examined, positions 11, 13, and 33 (permutation p = 3.4e-26, 1.2e-27, and 2.1e-28, respectively) showed the strongest association with RA. Univariate analyses of individual amino acid residues showed valine at position 11 (OR 5.1, 95% CI 3.7–7.0) and histidine at position 13 (OR 6.1, 95% CI 4.2–8.6) conferred the highest risk. The valine containing haplotypes of position 11, 71, 74, V_K_A conferred the most risk (OR 4.52, 95% CI 2.68–7.61) and conversely the haplotype with serine at this position, S_K_R, conferred the most protection (OR 0.83, 95% CI 0.61–1.15).Conclusion.Autoantibody-positive RA in black South Africans is associated with histidine at position 13 and valine at position 11 of HLA-DRB1, and haplotypes with valine at position 11 conferred the highest risk; conversely, serine at position 11 conveyed protection.

scholarly journals Spatial–temporal trend for mother-to-child transmission of HIV up to infancy and during pre-Option B+ in western Kenya, 2007–13

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e4427 ◽  
Author(s):  
Anthony Waruru ◽  
Thomas N.O. Achia ◽  
Hellen Muttai ◽  
Lucy Ng’ang’a ◽  
Emily Zielinski-Gutierrez ◽  
...  
Keyword(s):  
Regression Models ◽  
Deviance Information Criterion ◽  
Information Criterion ◽  
Temporal Analysis ◽  
Mother To Child Transmission ◽  
Child Transmission ◽  
Western Kenya ◽  
Logistic Regression Models ◽  
Live Births ◽  
Mother To Child

Introduction Using spatial–temporal analyses to understand coverage and trends in elimination of mother-to-child transmission of HIV (e-MTCT) efforts may be helpful in ensuring timely services are delivered to the right place. We present spatial–temporal analysis of seven years of HIV early infant diagnosis (EID) data collected from 12 districts in western Kenya from January 2007 to November 2013, during pre-Option B+ use. Methods We included in the analysis infants up to one year old. We performed trend analysis using extended Cochran–Mantel–Haenszel stratified test and logistic regression models to examine trends and associations of infant HIV status at first diagnosis with: early diagnosis (<8 weeks after birth), age at specimen collection, infant ever having breastfed, use of single dose nevirapine, and maternal antiretroviral therapy status. We examined these covariates and fitted spatial and spatial–temporal semiparametric Poisson regression models to explain HIV-infection rates using R-integrated nested Laplace approximation package. We calculated new infections per 100,000 live births and used Quantum GIS to map fitted MTCT estimates for each district in Nyanza region. Results Median age was two months, interquartile range 1.5–5.8 months. Unadjusted pooled positive rate was 11.8% in the seven-years period and declined from 19.7% in 2007 to 7.0% in 2013, p < 0.01. Uptake of testing ≤8 weeks after birth was under 50% in 2007 and increased to 64.1% by 2013, p < 0.01. By 2013, the overall standardized MTCT rate was 447 infections per 100,000 live births. Based on Bayesian deviance information criterion comparisons, the spatial–temporal model with maternal and infant covariates was best in explaining geographical variation in MTCT. Discussion Improved EID uptake and reduced MTCT rates are indicators of progress towards e-MTCT. Cojoined analysis of time and covariates in a spatial context provides a robust approach for explaining differences in programmatic impact over time. Conclusion During this pre-Option B+ period, the prevention of mother to child transmission program in this region has not achieved e-MTCT target of ≤50 infections per 100,000 live births. Geographical disparities in program achievements may signify gaps in spatial distribution of e-MTCT efforts and could indicate areas needing further resources and interventions.

scholarly journals LO10: Associations between ED crowding metrics and 72h-hour ED re-visits: Which crowding metrics are most highly associated with patient-oriented adverse outcomes?

CJEM ◽  
2019 ◽  
Vol 21 (S1) ◽  
pp. S10
Author(s):  
A. McRae ◽  
G. Innes ◽  
M. Schull ◽  
E. Lang ◽  
E. Grafstein ◽  
...  
Keyword(s):  
Patient Outcomes ◽  
Regression Models ◽  
Information Criterion ◽  
Patient Characteristics ◽  
Adverse Outcomes ◽  
Logistic Regression Models ◽  
Return Visits ◽  
Offload Delay ◽  
Ed Crowding ◽  
Meaningful Measure

Introduction: Emergency Department (ED) crowding is a pervasive problem and is associated with adverse patient outcomes. Yet, there are no widely accepted, universal ED crowding metrics. The objective of this study is to identify ED crowding metrics with the strongest association to the risk of ED revisits within 72 hours, which is a patient-oriented adverse outcome. Methods: Crowding metrics, patient characteristics and outcomes were obtained from administrative data for all ED encounters from 2011-2014 for three adult EDs in Calgary, AB. The data were randomly divided into three partitions for cross-validation, and further divided by CTAS category 1, 2/3 and 4/5. Twenty unique ED crowding metrics were calculated and assigned to each patient seen on each calendar day or shift, to standardize the exposure. Logistic regression models were fitted with 72h ED revisit as the dependent variable, and an individual crowding metric along with a common list of confounders as independent variables. Adjusted odds ratios (OR) for the 72h return visits were obtained for each crowding metric. The strength of associations between 72h revisits and crowding metrics were compared using Akaike's Information Criterion and Akaike weights. Results: This analysis is based on 1,149,939 ED encounters. Across all CTAS groups, INPUT metrics (ED census, ED occupancy, waiting time, EMS offload delay, LWBS%) were only weakly associated with the risk of 72h re-visit. Among THROUGHPUT metrics, ED Length of Stay and MD Care Time had similar adjusted ORs for 72h ED re-visit (range 0.99-1.15). Akaike weights ranging from 0.3/1.00 to 0.4/1.00 indicate that both THROUGHPUT metrics are reasonable predictors of 72h ED re-visits. All OUTPUT metrics (boarding time, # of boarded patients, % of beds occupied by boarded patients, hospital occupancy) had statistically significant ORs for 72h ED re-visits. The median boarding time had the highest adjusted OR for 72h ED re-visit (adjusted OR 1.40, 95% CI 1.33-1.47) and highest Akaike weight (0.97/1.00) compared to all other OUTPUT metrics, indicating that median boarding time had the strongest association with 72h re-visits. Conclusion: ED THROUGHPUT and OUTPUT metrics had consistent associations with 72h ED re-visits, while INPUT metrics had little to no association with 72h re-visits. Median boarding time is the strongest predictor of 72h re-visits, indicating that this may be the most meaningful measure of ED crowding.

Perfusion and permeability as diagnostic biomarkers of cavernous angioma with symptomatic hemorrhage

2021 ◽  
pp. 0271678X2110205
Author(s):  
Je Yeong Sone ◽  
Yan Li ◽  
Nicholas Hobson ◽  
Sharbel G Romanos ◽  
Abhinav Srinath ◽  
...  
Keyword(s):  
Blood Flow ◽  
Information Criterion ◽  
Cavernous Angioma ◽  
Plasma Biomarker ◽  
Brainstem Lesion ◽  
Enhanced Sensitivity ◽  
Conventional Mri ◽  
Cluster Area ◽  
Mri Sequences ◽  
Similar Accuracy

Cavernous angiomas with symptomatic hemorrhage (CASH) have a high risk of rebleeding, and hence an accurate diagnosis is needed. With blood flow and vascular leak as established mechanisms, we analyzed perfusion and permeability derivations of dynamic contrast-enhanced quantitative perfusion (DCEQP) MRI in 745 lesions of 205 consecutive patients. Thirteen respective derivations of lesional perfusion and permeability were compared between lesions that bled within a year prior to imaging (N = 86), versus non-CASH (N = 659) using machine learning and univariate analyses. Based on logistic regression and minimizing the Bayesian information criterion (BIC), the best diagnostic biomarker of CASH within the prior year included brainstem lesion location, sporadic genotype, perfusion skewness, and high-perfusion cluster area (BIC = 414.9, sensitivity = 74%, specificity = 87%). Adding a diagnostic plasma protein biomarker enhanced sensitivity to 100% and specificity to 85%. A slightly modified derivation achieved similar accuracy (BIC = 321.6, sensitivity = 80%, specificity = 82%) in the cohort where CASH occurred 3–12 months prior to imaging after signs of hemorrhage would have disappeared on conventional MRI sequences. Adding the same plasma biomarker enhanced sensitivity to 100% and specificity to 87%. Lesional blood flow on DCEQP may distinguish CASH after hemorrhagic signs on conventional MRI have disappeared and are enhanced in combination with a plasma biomarker.

The impact of SPY angiography on intraoperative decision making and outcomes for post-mastectomy reconstruction

2019 ◽  
pp. 1-5
Keyword(s):  
Decision Making ◽  
Logistic Regression ◽  
Skin Necrosis ◽  
Regression Models ◽  
Multivariable Analysis ◽  
P Value ◽  
Flap Necrosis ◽  
Single Institution ◽  
Logistic Regression Models ◽  
The Impact

Objective: While the use of intraoperative laser angiography (SPY) is increasing in mastectomy patients, its impact in the operating room to change the type of reconstruction performed has not been well described. The purpose of this study is to investigate whether SPY angiography influences post-mastectomy reconstruction decisions and outcomes. Methods and materials: A retrospective analysis of mastectomy patients with reconstruction at a single institution was performed from 2015-2017.All patients underwent intraoperative SPY after mastectomy but prior to reconstruction. SPY results were defined as ‘good’, ‘questionable’, ‘bad’, or ‘had skin excised’. Complications within 60 days of surgery were compared between those whose SPY results did not change the type of reconstruction done versus those who did. Preoperative and intraoperative variables were entered into multivariable logistic regression models if significant at the univariate level. A p-value <0.05 was considered significant. Results: 267 mastectomies were identified, 42 underwent a change in the type of planned reconstruction due to intraoperative SPY results. Of the 42 breasts that underwent a change in reconstruction, 6 had a ‘good’ SPY result, 10 ‘questionable’, 25 ‘bad’, and 2 ‘had areas excised’ (p<0.01). After multivariable analysis, predictors of skin necrosis included patients with ‘questionable’ SPY results (p<0.01, OR: 8.1, 95%CI: 2.06 – 32.2) and smokers (p<0.01, OR:5.7, 95%CI: 1.5 – 21.2). Predictors of any complication included a change in reconstruction (p<0.05, OR:4.5, 95%CI: 1.4-14.9) and ‘questionable’ SPY result (p<0.01, OR: 4.4, 95%CI: 1.6-14.9). Conclusion: SPY angiography results strongly influence intraoperative surgical decisions regarding the type of reconstruction performed. Patients most at risk for flap necrosis and complication post-mastectomy are those with questionable SPY results.

Demographic factors associated with missed follow-up among solid tumor patients treated at a large multi-site academic institution

2020 ◽  
Vol 16 (32) ◽  
pp. 2635-2643
Author(s):  
Samantha L Freije ◽  
Jordan A Holmes ◽  
Saleh Rachidi ◽  
Susannah G Ellsworth ◽  
Richard C Zellars ◽  
...  
Keyword(s):  
Cancer Patients ◽  
Odds Ratio ◽  
Regression Models ◽  
Tumor Patients ◽  
Logistic Regression Models ◽  
Factors Associated ◽  
Follow Up Care ◽  
Risk Patients ◽  
African American Race

Aim: To identify demographic predictors of patients who miss oncology follow-up, considering that missed follow-up has not been well studies in cancer patients. Methods: Patients with solid tumors diagnosed from 2007 to 2016 were analyzed (n = 16,080). Univariate and multivariable logistic regression models were constructed to examine predictors of missed follow-up. Results: Our study revealed that 21.2% of patients missed ≥1 follow-up appointment. African–American race (odds ratio [OR] 1.33; 95% CI: 1.17–1.51), Medicaid insurance (OR 1.59; 1.36–1.87), no insurance (OR 1.66; 1.32–2.10) and rural residence (OR 1.78; 1.49–2.13) were associated with missed follow-up. Conclusion: Many cancer patients miss follow-up, and inadequate follow-up may influence cancer outcomes. Further research is needed on how to address disparities in follow-up care in high-risk patients.

scholarly journals COVID-19 Preventive Behaviours in Cameroon: A Six-Month Online National Survey

2021 ◽  
Vol 18 (5) ◽  
pp. 2554
Author(s):  
Joseph Nelson Siewe Fodjo ◽  
Leonard Ngarka ◽  
Wepnyu Y. Njamnshi ◽  
Leonard N. Nfor ◽  
Michel K. Mengnjo ◽  
...  
Keyword(s):  
Regression Models ◽  
Health Personnel ◽  
Online Survey ◽  
Preventive Measures ◽  
Face Mask ◽  
Logistic Regression Models ◽  
Adherence Score ◽  
Preventive Behaviour ◽  
Predictors Of Adherence

Since March 2020, the Cameroonian government implemented nationwide measures to stall COVID-19 transmission. However, little is known about how well these unprecedented measures are being observed as the pandemic evolves. We conducted a six-month online survey to assess the preventive behaviour of Cameroonian adults during the COVID-19 outbreak. A five-point adherence score was constructed based on self-reported observance of the following preventive measures: physical distancing, face mask use, hand hygiene, not touching one’s face, and covering the mouth when coughing or sneezing. Predictors of adherence were investigated using ordinal logistic regression models. Of the 7381 responses received from all ten regions, 73.3% were from male respondents and overall mean age was 32.8 ± 10.8 years. Overall mean adherence score was 3.96 ± 1.11 on a scale of 0–5. Mean weekly adherence scores were initially high, but gradually decreased over time accompanied by increasing incidence of COVID-19 during the last study weeks. Predictors for higher adherence included higher age, receiving COVID-19 information from health personnel, and agreeing with the necessity of lockdown measures. Meanwhile, experiencing flu-like symptoms was associated with poor adherence. Continuous observance of preventive measures should be encouraged among Cameroonians in the medium- to long-term to avoid a resurgence in COVID-19 infections.

scholarly journals Behavioral and Attitudinal Correlates of Trusted Sources of COVID-19 Vaccine Information in the US

2021 ◽  
Vol 11 (4) ◽  
pp. 56
Author(s):  
Carl A. Latkin ◽  
Lauren Dayton ◽  
Jacob R. Miller ◽  
Grace Yi ◽  
Afareen Jaleel ◽  
...  
Keyword(s):  
Regression Models ◽  
Logistic Regression Models ◽  
The Public ◽  
Public Health Systems ◽  
Online Study ◽  
News Sources ◽  
The Us ◽  
Vulnerable People ◽  
Two Factors ◽  
Vaccine Information

There is a critical need for the public to have trusted sources of vaccine information. A longitudinal online study assessed trust in COVID-19 vaccine information from 10 sources. A factor analysis for data reduction revealed two factors. The first factor contained politically conservative sources (PCS) of information. The second factor included eight news sources representing mainstream sources (MS). Multivariable logistic regression models were used. Trust in Dr. Fauci was also examined. High trust in MS was associated with intention to encourage family members to get COVID-19 vaccines, altruistic beliefs that more vulnerable people should have vaccine priority, and belief that racial minorities with higher rates of COVID-19 deaths should have priority. High trust in PCS was associated with intention to discourage friends from getting vaccinated. Higher trust in PCS was also associated with participants more likely to disagree that minorities with higher rates of COVID-19 deaths should have priority for a vaccine. High trust in Dr. Fauci as a source of COVID-19 vaccine information was associated with factors similar to high trust in MS. Fair, equitable, and transparent access and distribution are essential to ensure trust in public health systems’ abilities to serve the population.

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