scholarly journals A Predictive Model for Severe Covid-19 in the Medicare Population: A Tool for Prioritizing Scarce Vaccine Supply

2020 ◽  
Author(s):  
Bettina Experton ◽  
Hassan A. Tetteh ◽  
Nicole Lurie ◽  
Peter Walker ◽  
Colin J. Carroll ◽  
...  
Keyword(s):  
Risk Factors ◽  
Predictive Model ◽  
Low Income ◽  
Social Vulnerability ◽  
Risk Model ◽  
Chronic Obstructive ◽  
Term Care ◽  
Risk Levels ◽  
Medicare Population ◽  
Zip Code

ABSTRACTBackgroundRecommendations for prioritizing populations for COVID-19 vaccination have focused on front-line health care personnel and residents in long term care, followed by other individuals at higher risk for severe disease. Existing models for identifying higher risk individuals including those over age 65 lack the needed integration of socio-demographic and clinical risk factors to ensure equitable vaccine allocation.MethodsWe developed a predictive model for severe COVID-19 using clinical data from de-identified Medicare claims for 16 million Medicare fee-for-service beneficiaries, including 1 million COVID-19 cases, and socio-economic data from the CDC Social Vulnerability Index. To identify risk factors for severe COVID-19, we used multivariate logistic regression and random forest modeling. Predicted individual probabilities of COVID-19 hospitalization were then calculated for population risk stratification and COVID-19 vaccine prioritization, and for mapping of population risk levels at the county and zip code levels on a nationwide dashboard.ResultsThe leading Covid-19 hospitalization risk factors driving the risk model were: Non-white ethnicity (particularly North American Native, Black, and Hispanic), end-stage renal disease, advanced age (particularly age over 85), prior hospitalization, leukemia, morbid obesity, chronic kidney disease, lung cancer, chronic liver disease, pulmonary fibrosis or pulmonary hypertension, and chemotherapy. However, previously reported risk factors such as chronic obstructive pulmonary disease and diabetes conferred modest hospitalization risk. Among all social vulnerability factors analyzed, residence in a low-income zip code was the only risk factor independently predicting Covid-19 hospitalization. The mapped hospitalization risk levels showed significant correlations with the cumulative COVID-19 case hospitalization rates at the zip code level in the fifteen most populous U.S. major metropolitan areas.ConclusionThis multi-factor risk model which predicts severe Covid-19and its population risk dashboard can be used to optimize Covid-19 vaccine allocation in the higher risk Medicare population where socio-demographic and comorbidity risk factors need to be considered concurrently.

scholarly journals A Predictive Model for Severe COVID-19 in the Medicare Population: A Tool for Prioritizing Primary and Booster COVID-19 Vaccination

Biology ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 1185
Author(s):  
Bettina Experton ◽  
Hassan A. Tetteh ◽  
Nicole Lurie ◽  
Peter Walker ◽  
Adrien Elena ◽  
...  
Keyword(s):  
Risk Factors ◽  
Predictive Model ◽  
Low Income ◽  
Social Vulnerability ◽  
Risk Model ◽  
Severe Disease ◽  
The Elderly ◽  
Chronic Obstructive ◽  
Social Vulnerability Index ◽  
Medicare Population

Recommendations for prioritizing COVID-19 vaccination have focused on the elderly at higher risk for severe disease. Existing models for identifying higher-risk individuals lack the needed integration of socio-demographic and clinical risk factors. Using multivariate logistic regression and random forest modeling, we developed a predictive model of severe COVID-19 using clinical data from Medicare claims for 16 million Medicare beneficiaries and socio-economic data from the CDC Social Vulnerability Index. Predicted individual probabilities of COVID-19 hospitalization were then calculated for population risk stratification and vaccine prioritization and mapping. The leading COVID-19 hospitalization risk factors were non-white ethnicity, end-stage renal disease, advanced age, prior hospitalization, leukemia, morbid obesity, chronic kidney disease, lung cancer, chronic liver disease, pulmonary fibrosis or pulmonary hypertension, and chemotherapy. However, previously reported risk factors such as chronic obstructive pulmonary disease and diabetes conferred modest hospitalization risk. Among all social vulnerability factors, residence in a low-income zip code was the only risk factor independently predicting hospitalization. This multifactor risk model and its population risk dashboard can be used to optimize COVID-19 vaccine allocation in the higher-risk Medicare population.

scholarly journals A literature review on depression and its risk factors among people suffering from chronic obstructive pulmonary disease in Asian sub-continent

2020 ◽  
Vol 7 (11) ◽  
pp. 4653
Author(s):  
Amrit Sharma
Keyword(s):  
Risk Factors ◽  
Chronic Obstructive Pulmonary Disease ◽  
Pulmonary Disease ◽  
Low Income ◽  
Airflow Obstruction ◽  
Airflow Limitation ◽  
Chronic Obstructive ◽  
Obstructive Pulmonary Disease ◽  
Chronic Inflammatory Response ◽  
Basic Activity

Chronic obstructive pulmonary disease (COPD) is defined as persistent airflow limitation that is usually progressive and associated with an enhanced chronic inflammatory response in the airways and the lung to noxious particles or gases. It has been suggested that emotional disturbances such as depression and anxiety are common among patients with COPD. This review aims to highlight the presence of depression and associated risk factors among patients suffering from COPD in Asia. Fifty-eight observational studies were retrieved through data sources like PubMed, Medical subject heading (MeSH) search and Google scholar. After thorough screening total thirteen studies were identified and included in this review. Based on the results of these studies, the south and west Asian countries had higher proportion of depression. However, risk factor results were mixed which includes severity of obstruction/global initiative for obstructive lung disease (GOLD) criteria, Stage 2 COPD, teetotallers, smoking, alcohol consumption, body mass index, airflow obstruction, dyspnoea, and exercise (BODE) index, urban residence, female gender, education level, dyspnoea, low income, poor Quality of life (QOL) scores, age, poor self-reported health, basic activity of daily living (BADL) disability. Further superior research studies with larger sample size are required on Asian population. All in all, it is recommended that early diagnosis and treatment of depression should be included as a part of management in COPD as it can help to minimize the risk of morbidity and mortality in the patients.

scholarly journals Area-Based Socioeconomic Disparities in Survival of Children with Newly Diagnosed Acute Myeloid Leukemia: A Report from the Children's Oncology Group

Blood ◽  
2019 ◽  
Vol 134 (Supplement_1) ◽  
pp. 703-703
Author(s):  
Lena E. Winestone ◽  
Kelly D Getz ◽  
Kira O Bona ◽  
Brian T. Fisher ◽  
Alan S Gamis ◽  
...  
Keyword(s):  
Risk Factors ◽  
Educational Attainment ◽  
Low Income ◽  
Myeloid Leukemia ◽  
High Income ◽  
Phase 3 ◽  
Insurance Type ◽  
Low Education ◽  
Pediatric Aml ◽  
Zip Code

Introduction: Income, education, and health insurance coverage have been shown to influence access to appropriate oncology care, impacting detection and treatment. We sought to evaluate the role of area-based measures of socioeconomic status in contributing to outcome disparities on the two most recent Children's Oncology Group (COG) Phase 3 clinical trials for acute myeloid leukemia (AML), AAML0531 and AAML1031. We hypothesized that pediatric AML patients from low income and low education zip codes have inferior five-year overall survival (OS) and event-free survival (EFS) relative to patients from middle income and more educated zip codes. Methods: Patients enrolled on AAML0531 and AAML1031 were included. Patients with Down syndrome (n=5), FLT3/ITD high allelic ratio (n=264), in AAML1031 Arm D (n=332), and patients whose zip code was not able to be mapped to a US Census area were excluded (n=60). Patients were observed from enrollment on study through last available follow up. Zip code level median annual household income was the primary exposure and was categorized as follows: Poverty: <$24,250 (federal poverty line); Low: $24,250-56,516; Middle/High >$56,516. Secondary exposures of interest included zip code level educational attainment and insurance type (Medicaid Only vs other insurance) at AML diagnosis. Standard descriptive statistics were used to compare patient characteristics by levels of exposure; the Kaplan Meier method was used to estimate OS (defined as time from study entry to death) and EFS (time from study entry until failure to achieve CR during induction, relapse, or death). Cox proportional hazards models were used to estimate hazard ratios (HR) for OS and EFS. Measures of association were adjusted for known risk factors for mortality including cytogenetic/mutation risk group, gemtuzumab (GO) receipt, race, and age. Logistic regression analyses were used to estimate odds ratios (OR) for early mortality (defined as death during induction). Results: Of 2387 patients enrolled on AAML0531 and AAML1031, 1726 met inclusion criteria for the overall analysis. Due to missing covariate data, 1467 patients were included in the final model. Race/ethnicity differed significantly by area-based income, area-based education, and insurance type with a higher proportion of Black and Hispanic patients living in poverty, low income, and low education areas, and having Medicaid only insurance. Lower area-based income was associated with lower OS (43% in poverty vs. 61% in low income vs. 68% in middle/high income; p = 0.004) and EFS (34% in poverty vs. 46% in low income vs. 54% in middle/high income; p = 0.005), shown in Figure 1. Lower area-based educational attainment was also associated with lower OS (58% in Quartile 4 (lower education) vs. 70% in Quartile 1 (higher education); p = 0.005 across quartiles) and EFS (44% in Q4 vs. 54% in Q1; p = 0.03 across quartiles). Patients with Medicaid Only insurance had lower OS (59 ± 5% vs. 66 ± 3%: p = 0.01) but similar EFS (48 ± 5% vs. 50 ± 3%: p = 0.33). In a full multivariable model, differences in survival by area-based educational attainment and insurance type resolved suggesting that observed crude associations were explained by confounding by area-based income combined with established risk factors. Patients from middle/high income areas experienced 25% lower risk of mortality compared to patients from low income areas (OS: crude HR 0.74 95% CI 0.62, 0.89; adjusted HR 0.79 95% CI 0.63, 0.99) with similar differences in EFS (crude HR 0.79 95% CI 0.69, 0.92; adjusted HR 0.77 95% CI 0.65, 0.89). There was no meaningful confounding of the income-survival association detected as evidenced by unchanged magnitudes of association following adjustment for area-based education, insurance, and established risk factors. Area-based low income was associated with both higher risk of early death (crude OR: 2.43 95% CI 1.04, 5.69) and treatment-related mortality on therapy (11.1 ± 10.5% vs. 3.7 ± 2.5%, p = 0.03) compared to area-based middle/high income. Conclusions: Lower area-based income and education were associated with significantly inferior EFS and OS among patients with AML on the last two Phase 3 COG trials. Moreover, zip-code based low SES is an independent risk factor for mortality in pediatric AML. Additional studies to understand mechanisms of observed socioeconomic disparities in treatment outcomes will inform interventions that may mitigate these inequities. Disclosures Fisher: Pfizer: Research Funding; Astellas: Other: Data Safety Monitoring Board Chair for an antifungal study; Merck: Research Funding.

Developmental patterns of childhood peer relations as predictors of externalizing behavior problems

1995 ◽  
Vol 7 (4) ◽  
pp. 825-843 ◽  
Author(s):  
Janis B. Kupersmidt ◽  
Margaret Burchinal ◽  
Charlotte J. Patterson
Keyword(s):  
Risk Factors ◽  
Behavior Problems ◽  
Peer Relations ◽  
Low Income ◽  
Externalizing Behavior ◽  
Risk Model ◽  
Externalizing Behavior Problems ◽  
Social Risk ◽  
Developmental Patterns ◽  
Best Friend

AbstractDevelopmental patterns of childhood peer relations were examined in the prediction of externalizing behavior problems in a 4-year multiple cohort longitudinal study. The participants consisted of 880 third- (M = 9.3 years) through seventh- (M = 13.4 years) grade students. Approximately half of the participants were female, one third were Black, and one third were from low-income homes. Developmental patterns of six indices of peer relations (including group acceptance, group rejection, having a reciprocated best friend, social support from best friend, conflict with best friend, and the aggressiveness of the best friend) were examined as predictors of aggression and delinquency using logistic regression analyses. Results suggest that both group and dyadic peer relations problems are risk factors for aggression and delinquency. Support was found for the cumulative risk model in the prediction of externalizing outcomes from multiple social risk factors that were additively associated with each negative outcome.

Chronic obstructive pulmonary disease and asthma

2021 ◽  
pp. 43-56
Author(s):  
Craig M. Riley ◽  
Jessica Bon ◽  
Alison Morris
Keyword(s):  
Risk Factors ◽  
Chronic Obstructive Pulmonary Disease ◽  
Pulmonary Disease ◽  
Low Income ◽  
Public Health Problem ◽  
Asthma Prevalence ◽  
Chronic Obstructive ◽  
Obstructive Pulmonary Disease ◽  
Middle Income ◽  
Potential Risk Factors

Chronic obstructive pulmonary disease (COPD) and asthma are highly prevalent, non-malignant respiratory conditions that have increased dramatically in the past half century, both in high-income and low-middle-income countries. COPD is the fourth leading cause of death worldwide, and both COPD and asthma have a profound impact on quality of life for patients and their families. Tobacco smoke remains the single most important cause of COPD, but occupational and indoor exposures have increasingly been recognized as risk factors, especially among middle- and low-income individuals. Different patterns of genetic susceptibility independent of exposure result in variability of disease expression with many patients not developing clinical COPD, although they may still develop respiratory symptoms. COPD prevalence differs greatly between countries even when controlling for smoking rates. While much progress has been made in understanding biological pathways involved in asthma, the understanding of why asthma initially develops remains elusive. Although a large number of potential risk factors have been identified, none can explain the global increases in asthma prevalence observed over the last few decades. Prevalence trends between countries have also varied, with some countries continuing to experience increases in asthma rates and some rates levelling off or even declining. These trends cannot be explained by divergent epidemiological methods or population makeup alone. Asthma control, especially for severe asthmatics and for those with non-allergic phenotypes, remains a public health problem with more efficient interventions needed to encourage smoking cessation, improve air quality, and reduce allergen exposure.

scholarly journals Sex differences in risk factors for depressive symptoms in patients with COPD: The 2014 and 2016 Korea National Health and Nutrition Examination Survey

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Ji Soo Choi ◽  
Se Hyun Kwak ◽  
Nak-Hoon Son ◽  
Jae Won Oh ◽  
San Lee ◽  
...  
Keyword(s):  
Risk Factors ◽  
Sex Differences ◽  
Depressive Symptoms ◽  
National Health ◽  
Low Income ◽  
Living Alone ◽  
Chronic Obstructive ◽  
Nutrition Examination Survey ◽  
Female Sex ◽  
Health And Nutrition

Abstract Background Although depression is a common comorbidity of chronic obstructive pulmonary disease (COPD), the role of sex remains unexplored. We evaluated sex differences of risk factors of depressive symptoms in adults with COPD. Methods This was a population-based cross-sectional study using data from the 2014 and 2016 Korea National Health and Nutrition Examination Survey. Spirometry was used to identify patients with COPD, defined as a FEV1/FVC ratio < 0.7. Presence of depressive symptoms was defined as a total score ≥ 5 on the Patient Health Questionnaire-9. Results 17.8% of participants expressed depressive symptoms. Relative regression analysis revealed that female sex (RR 2.38; 95% CI 1.55–3.66; p < 0.001), living alone (RR 1.46; 95% CI 1.08–1.97; p = 0.013), current smoker (RR 1.70; 95% CI 1.15–2.52; p = 0.008), underweight (RR 1.58 95% CI 1.00–2.49; p = 0.049), and GOLD Stage III/IV (RR 1.92; 95% CI 1.19–3.09; p = 0.007) were the risk factors for depressive symptoms. Low income, living alone, multiple chronic disorders, and low BMI were risk factors of depressive symptoms in male, whereas low educational attainment, urban living, and current smoking were risk factors in female. Conclusions Female sex is a main risk factor of depressive symptoms in adults with COPD. As risk factors of depressive symptoms in COPD patients vary according to their sex, different approaches are needed to manage depression in males and females with COPD.

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