scholarly journals Outcomes of COVID-19: disparities by ethnicity

2020 ◽  
Author(s):  
Hamad Ali ◽  
Abdullah Alshukry ◽  
Sulaiman K Marafie ◽  
Monera AlRukhayes ◽  
Yaseen Ali ◽  
...  
Keyword(s):  
South Asian ◽  
Regression Models ◽  
South Asians ◽  
P Value ◽  
Multivariate Logistic Regression ◽  
Death Rates ◽  
Logistic Regression Models ◽  
Asian Patients ◽  
Worse Prognosis

AbstractObjectivesTo investigate the role of ethnicity in COVID-19 outcome disparities in a cohort in Kuwait.MethodsThis is a retrospective analysis of 405 individuals infected with SARS-CoV-2 in Kuwait. Outcomes such as symptoms severity and mortality were considered. Multivariate logistic regression models were used to report the odds ratios (OR) for ICU admission and dying from COVID-19.ResultsThe cohort included 290 Arabs and 115 South Asians. South Asians recorded significantly higher COVID-19 death rates compared to Arabs (33% vs. 7.6%, P value<0.001). When compared to Arabs, South Asians also had higher odds of being admitted to the ICU (OR = 6.28, 95% CI: 3.34 – 11.80, p < 0.001). South Asian patients showed 7.62 (95% CI: 3.62 – 16.02, p < 0.001) times the odds of dying from COVID-19.ConclusionCOVID-19 patients with South Asians ethnicity are more likely to have worse prognosis and outcome when compared to patients with Arab ethnicity. This suggest a possible role for ethnicity in COVID-19 outcome disparities and this role is likely to be multifactorial.

scholarly journals Earlier onset of proteinuria or hypertension is a predictor of progression from gestational hypertension or gestational proteinuria to preeclampsia

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Mamoru Morikawa ◽  
Michinori Mayama ◽  
Kiwamu Noshiro ◽  
Yoshihiro Saito ◽  
Kinuko Nakagawa-Akabane ◽  
...  
Keyword(s):  
Cohort Study ◽  
Retrospective Cohort ◽  
Regression Models ◽  
Gestational Hypertension ◽  
P Value ◽  
Hypertensive Disorders Of Pregnancy ◽  
Multivariate Logistic Regression ◽  
Logistic Regression Models ◽  
Hypertensive Disorders ◽  
New Onset

AbstractAlthough gestational hypertension (GH) is a well-known disorder, gestational proteinuria (GP) has been far less emphasized. According to international criteria, hypertensive disorders of pregnancy include GH but not GP. Previous studies have not revealed the predictors of progression from GP to preeclampsia or those of progression from GH to preeclampsia. We aimed to determine both sets of predictors. A retrospective cohort study was conducted with singleton pregnant women who delivered at 22 gestational weeks or later. Preeclampsia was divided into three types: new onset of hypertension/proteinuria at 20 gestational weeks or later and additional new onset of other symptoms at < 7 days or at ≥ 7 days later. Of 94 women with preeclampsia, 20 exhibited proteinuria before preeclampsia, 14 experienced hypertension before preeclampsia, and 60 exhibited simultaneous new onset of both hypertension and proteinuria before preeclampsia; the outcomes of all types were similar. Of 34 women with presumptive GP, 58.8% developed preeclampsia; this proportion was significantly higher than that of 89 women with presumptive GH who developed preeclampsia (15.7%). According to multivariate logistic regression models, earlier onset of hypertension/proteinuria (before or at 34.7/33.9 gestational weeks) was a predicator for progression from presumptive GH/GP to preeclampsia (odds ratios: 1.21/1.21, P value: 0.0044/0.0477, respectively).

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.

scholarly journals CANTARE: finding and visualizing network-based multi-omic predictive models

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Janet C. Siebert ◽  
Martine Saint-Cyr ◽  
Sarah J. Borengasser ◽  
Brandie D. Wagner ◽  
Catherine A. Lozupone ◽  
...  
Keyword(s):  
Random Forests ◽  
Predictive Models ◽  
Regression Models ◽  
Dynamic Range ◽  
P Value ◽  
Published Data ◽  
Logistic Regression Models ◽  
Pairwise Models ◽  
Biological Insight ◽  
Analytical Approaches

Abstract Background One goal of multi-omic studies is to identify interpretable predictive models for outcomes of interest, with analytes drawn from multiple omes. Such findings could support refined biological insight and hypothesis generation. However, standard analytical approaches are not designed to be “ome aware.” Thus, some researchers analyze data from one ome at a time, and then combine predictions across omes. Others resort to correlation studies, cataloging pairwise relationships, but lacking an obvious approach for cohesive and interpretable summaries of these catalogs. Methods We present a novel workflow for building predictive regression models from network neighborhoods in multi-omic networks. First, we generate pairwise regression models across all pairs of analytes from all omes, encoding the resulting “top table” of relationships in a network. Then, we build predictive logistic regression models using the analytes in network neighborhoods of interest. We call this method CANTARE (Consolidated Analysis of Network Topology And Regression Elements). Results We applied CANTARE to previously published data from healthy controls and patients with inflammatory bowel disease (IBD) consisting of three omes: gut microbiome, metabolomics, and microbial-derived enzymes. We identified 8 unique predictive models with AUC > 0.90. The number of predictors in these models ranged from 3 to 13. We compare the results of CANTARE to random forests and elastic-net penalized regressions, analyzing AUC, predictions, and predictors. CANTARE AUC values were competitive with those generated by random forests and  penalized regressions. The top 3 CANTARE models had a greater dynamic range of predicted probabilities than did random forests and penalized regressions (p-value = 1.35 × 10–5). CANTARE models were significantly more likely to prioritize predictors from multiple omes than were the alternatives (p-value = 0.005). We also showed that predictive models from a network based on pairwise models with an interaction term for IBD have higher AUC than predictive models built from a correlation network (p-value = 0.016). R scripts and a CANTARE User’s Guide are available at https://sourceforge.net/projects/cytomelodics/files/CANTARE/. Conclusion CANTARE offers a flexible approach for building parsimonious, interpretable multi-omic models. These models yield quantitative and directional effect sizes for predictors and support the generation of hypotheses for follow-up investigation.

scholarly journals Recommendations for Abnormal Behaviour Ethograms in Monkey Research

Animals ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 1461
Author(s):  
Andrea Polanco ◽  
Brenda McCowan ◽  
Lee Niel ◽  
David L. Pearl ◽  
Georgia Mason
Keyword(s):  
Macaca Mulatta ◽  
Regression Models ◽  
Convergent Validity ◽  
P Value ◽  
Morphological Similarity ◽  
Abnormal Behaviour ◽  
Logistic Regression Models ◽  
The Third ◽  
Welfare Implications ◽  
Self Stimulation

Laboratory monkey ethograms currently include subcategories of abnormal behaviours that are based on superficial morphological similarity. Yet, such ethograms may be misclassifying behaviour, with potential welfare implications as different abnormal behaviours are likely to have distinct risk factors and treatments. We therefore investigated the convergent validity of four hypothesized subcategories of abnormal behaviours (‘motor’, e.g., pacing; ‘self-stimulation’, e.g., self-sucking; ‘postural’, e.g., hanging; and ‘self-abuse’, e.g., self-biting). This hypothesis predicts positive relationships between the behaviours within each subcategory. Rhesus macaque (Macaca mulatta) data on 19 abnormal behaviours were obtained from indoor-housed animals (n = 1183). Logistic regression models, controlling for sex, age, and the number of observations, revealed that only 1/6 ‘motor’ behaviours positively predicted pacing, while 2/3 ‘self-abuse’ behaviours positively predicted self-biting (one-tailed p-value < 0.05). Furthermore, ‘self-stimulation’ behaviours did not predict self-sucking, and none of the ‘postural’ behaviours predicted hanging. Thus, none of the subcategories fully met convergent validity. Subsequently, we created four new valid subcategories formed of comorbid behaviours. The first consisted of self-biting, self-hitting, self-injurious behaviour, floating limb, leg-lifting, and self-clasping. The second comprised twirling, bouncing, rocking, swinging, and hanging. The third comprised pacing and head-twisting, while the final subcategory consisted of flipping and eye-poking. Self-sucking, hair-plucking, threat-biting, and withdrawn remained as individual behaviours. We encourage laboratories to replicate the validation of these subcategories first, and for scientists working with other species to validate their ethograms before using them in welfare assessments.

scholarly journals The Differential Effects of Caregiving Intensity on Overnight Hospitalization in the Previous 2 Years

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 76-76
Author(s):  
Kylie Meyer ◽  
Zachary Gassoumis ◽  
Kathleen Wilber
Keyword(s):  
Health Services ◽  
Fixed Effects ◽  
Regression Models ◽  
P Value ◽  
Logistic Regression Models ◽  
Spousal Caregiving ◽  
Health Insurance Status ◽  
Race Ethnicity ◽  
Self Assessed Health ◽  
Retirement Study

Abstract Caregiving for a spouse is considered a major stressor many Americans will encounter during their lifetimes. Although most studies indicate caregiving is associated with experiencing diminished health outcomes, little is known about how this role affects caregivers’ use of acute health services. To understand how spousal caregiving affects the use of acute health services, we use data from the Health and Retirement Study. We apply fixed effects (FE) logistic regression models to examine odds of experiencing an overnight hospitalization in the previous two years according to caregiving status, intensity, and changes in caregiving status and intensity. Models controlled for caregiver gender, age, race, ethnicity, educational attainment, health insurance status, the number of household residents, and self-assessed health. Overall, caregivers were no more likely to experience an overnight hospitalization compared to non-caregivers (OR 0.92; CI 0.84 to 1.00; p-value=0.057). However, effects varied according to the intensity of caregiving and the time spent in this role. Compared to non-caregivers, for example, spouses who provided care to someone with no need for assistance with activities of daily living had lower odds of experiencing a hospitalization (OR 0.77; CI 0.66 to 0.89). In contrast, caregivers who provided care to someone with dementia for 4 to &lt;6 years had 3.29 times the odds of experiencing an overnight hospitalization (CI 1.04 to 10.38; p-value=0.042). Findings indicate that, although caregivers overall appear to use acute health services about as much as non-caregivers, large differences exist between caregivers. Results emphasize the importance of recognizing diversity within caregiving experiences.

Trends in the prevalence of metabolic syndrome and its components in Mexican adults, 2006-2018

2021 ◽  
Vol 63 (6, Nov-Dic) ◽  
pp. 713-724
Author(s):  
Rosalba Rojas-Martínez ◽  
Carlos A Aguilar-Salinas ◽  
Martín Romero-Martínez ◽  
Lilia Castro-Porras ◽  
Donaji Gómez-Velasco ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Metabolic Syndrome ◽  
Regression Models ◽  
Significant Risk ◽  
P Value ◽  
Logistic Regression Models ◽  
Mexican Adults ◽  
Diabetes Risk Score ◽  
Linear Trends

Objective. To examine trends in the prevalence of metabolic syndrome (MS) and its components. Materials and methods. Data from 27 800 Mexican adults who participated in Ensanut 2006, 2012, 2016 and 2018 were analyzed. Linear regression was used across each Ensanut period to assess temporal linear trends in the prevalence of MS. Logistic regression models were obtained to calculate the percentage change, p-value for the trend and the association between the presence of MS and the risk of developing type 2 diabetes mellitus (T2DM) over 10 years using the Finnish Diabetes Risk Score (FINDRISC) and cardiovascular disease (CVD) using Globorisk. Results. The prevalence of MS in Mexican adults according to the harmonized definition was: 40.2, 57.3, 59.99 and 56.31%, in 2006, 2012, 2016 and 2018 respectively (p for trend <0.0001). In 2018, 7.62% of metabolic syndrome cases had a significant risk for incident DM2 and 11.6% for CVD. Conclusion. It is estimated that there are 36.5 million Mexican adults living with metabolic syndrome, of which 2 million and 2.5 million have a high risk of developing T2DM or cardiovascular disease respectively, over the next 10 years.

Child awareness of and access to cigarettes: impacts of the point-of-sale display ban in England

2018 ◽  
Vol 28 (5) ◽  
pp. 526-531 ◽  
Author(s):  
Anthony A Laverty ◽  
Eszter Panna Vamos ◽  
Christopher Millett ◽  
Kiara C-M Chang ◽  
Filippos T Filippidis ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Drug Use ◽  
Regression Models ◽  
Multivariate Logistic Regression ◽  
Tobacco Advertising ◽  
Point Of Sale ◽  
Logistic Regression Models ◽  
Annual Survey ◽  
Perceived Difficulty ◽  
Ease Of Access

IntroductionEngland introduced a tobacco display ban for shops with >280 m2 floor area (‘partial ban’) in 2012, then a total ban in 2015. This study assessed whether these were linked to child awareness of and access to cigarettes.MethodsData come from the Smoking, Drinking and Drug Use survey, an annual survey of children aged 11–15 years for 2010–2014 and 2016. Multivariate logistic regression models assessed changes in having seen cigarettes on display, usual sources and ease of access to cigarettes in shopsResultsDuring the partial display ban in 2012, 89.9% of children reported seeing cigarettes on display in the last year, which was reduced to 86.0% in 2016 after the total ban (adjusted OR 0.58, 95% CI 0.50 to 0.66). Reductions were similar in small shops (84.1% to 79.3%)%) and supermarkets (62.6% to 57.3%)%). Although the ban was associated with a reduction in the proportion of regular child smokers reporting that they bought cigarettes in shops (57.0% in 2010 to 39.8% in 2016), we did not find evidence of changes in perceived difficulty or being refused sale among those who still did.DiscussionTobacco point-of-sale display bans in England reduced the exposure of children to cigarettes in shops and coincided with a decrease in buying cigarettes in shops. However, children do not report increased difficulty in obtaining cigarettes from shops, highlighting the need for additional measures to tackle tobacco advertising, stronger enforcement of existing laws and measures such as licencing for tobacco retailers.

Abstract MP57: A South Asian Mediterranean-style Diet Pattern Is Associated With Favorable Measures Of Adiposity And A Lower Risk Of Incident Diabetes: Findings From The Masala Study

Circulation ◽  
2021 ◽  
Vol 143 (Suppl_1) ◽  
Author(s):  
Sharan K Rai ◽  
Alka M Kanaya ◽  
Namratha Kandula ◽  
Qi Sun ◽  
Shilpa N Bhupathiraju
Keyword(s):  
South Asian ◽  
South Asians ◽  
Subclinical Atherosclerosis ◽  
Cultural Beliefs ◽  
P Value ◽  
Inverse Association ◽  
Processed Meats ◽  
Lower Likelihood ◽  
Diet Pattern

Introduction: South Asians are at a disproportionately high risk for cardiometabolic disease. The Mediterranean diet is associated with reduced risks of type 2 diabetes (T2D) and cardiovascular disease in certain populations, although data among South Asians are lacking. Therefore, we evaluated the association between a novel South Asian Mediterranean style (SAM) diet pattern and a broad panel of cardiometabolic markers from the MASALA study, an ongoing prospective cohort of South Asians in the US. Methods: We included 891 participants who completed the baseline visit (2010-13) with reliable responses to a validated ethnic-specific food frequency questionnaire (mean age 55 y; 47% female). We created the SAM score by grouping foods including those specific to this population’s cuisine into 9 pre-defined categories (vegetables, fruits, legumes, nuts, whole grains, red/processed meats, fish, alcohol, and monounsaturated to saturated fat ratio). Participants above the median intake received 1 point per category; red/processed meats were reverse scored and those with alcohol intake 5-25 g/d received 1 point. We summed these for a score from 0-9, with higher scores reflecting greater adherence to a Mediterranean style diet. Participants underwent a clinical exam, carotid ultrasound, cardiac and abdominal CT, and fasting blood tests. We used multivariable linear and logistic regression to examine cross-sectional associations between the SAM score and cardiometabolic risk, adjusting for age, sex, calories, physical activity, smoking status, medical history, income, education level, and cultural beliefs. We additionally adjusted for body mass index (BMI) in the full model. Finally, we examined the association between the SAM score and incident T2D at follow-up (~5 y later). Results: Participants with higher SAM scores tended to be older, more likely to have a bachelor’s degree, less likely to report experiences of discrimination, and less likely to be smokers. At baseline, the SAM score was inversely associated with pericardial fat volume (-1.22 ± 0.55 cm 3 per 1-unit increase in SAM score; p value=0.03) in the fully adjusted model. We observed an inverse association between the SAM score and visceral fat, but it was attenuated after additionally adjusting for BMI. There were no associations with subclinical atherosclerosis, glycemia measures, lipids, inflammatory markers, or uric acid. The SAM score was associated with a lower likelihood of obesity (odds ratio [OR] 0.88, 95% confidence interval [CI] 0.79 to 0.98) and fatty liver (OR 0.82, 95% CI 0.68 to 0.98), but not with hypertension. Finally, the SAM score was associated with lower odds of incident T2D (OR 0.75, 95% CI 0.59 to 0.95) at follow-up. Conclusion: A greater intake of a Mediterranean style diet that incorporates traditional South Asian foods was associated with favorable measures of adiposity and a lower likelihood of incident T2D.

Abstract TP321: Is Weekend Admission Associated With Increased 30-day Stroke Mortality? The Effect of Adjustment Using a Claims-Based Stroke Severity Index

Stroke ◽  
2016 ◽  
Vol 47 (suppl_1) ◽  
Author(s):  
Cheng-Yang Hsieh ◽  
Sheng-Feng Sung
Keyword(s):  
Logistic Regression ◽  
Regression Models ◽  
Severity Index ◽  
Case Mix ◽  
Stroke Severity ◽  
Stroke Mortality ◽  
Multivariate Logistic Regression ◽  
Stroke Patients ◽  
Logistic Regression Models ◽  
Case Mix Adjustment

Introduction: Whether weekend admission is associated with increased stroke mortality in Taiwan remains uncertain, partly because of an inadequate case-mix adjustment in other studies using an insurance claims databases. Hypothesis: Adding the 7-item claims-based stroke severity index (SSI) to a multivariate logistic regression model might alter the analysis of the effect of weekend admission on 30-day stroke mortality. Methods: We identified, in the Taiwan Longitudinal Health Insurance Database, which is linked with the National Death Registry, patients hospitalized for acute ischemic stroke between 2001 and 2013. The primary outcome was mortality 30 days post-admission. In base logistic regression models with and without the SSI, we tested the odds ratio (OR) of 30-day mortality in patient admitted on weekends using the covariates of age, sex, year of admission, Charlson’s comorbidity index, brain surgery, physician specialty and surgical volume, hospital ownership, accreditation, and patient volume. Results: We analyzed 46,007 consecutive hospitalized stroke patients (mean age: 68.8 ± 12.0 years; male: 59%), with an SSI of 7.5 ± 5.3 (range: 4.1-27.1), 23.0% were admitted on the weekend, and 4.2% died within 30 days. Patients who died within 30 days were more likely to have been admitted on a weekend (4.9% vs. 4.0%, p < 0.001). Nevertheless, patients admitted on a weekend had a higher SSI than those admitted on a weekday (7.8 vs. 7.4, p < 0.001). In multivariate logistic regression models, weekend admission was associated with 30-day mortality (OR: 1.22, 95% CI: 1.10-1.35) in the base model but not in the base model plus SSI (OR: 1.07, 95% CI: 0.95-1.20). Conclusions: We confirmed that, after stroke severity had been adjust by adding the SSI, weekend admission did not increase the 30-day mortality of stroke patients in Taiwan. A case-mix adjustment in comparative outcome studies of stroke patients is important when using an insurance claims database.

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