scholarly journals SARS2 simplified scores to estimate risk of hospitalization and death among patients with COVID-19

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Hesam Dashti ◽  
Elise C. Roche ◽  
David William Bates ◽  
Samia Mora ◽  
Olga Demler
Keyword(s):  
Medical History ◽  
Linear Models ◽  
Smoking Status ◽  
Hospitalized Patients ◽  
Lower Socioeconomic Status ◽  
Derivation Cohort ◽  
Lower Socioeconomic ◽  
Detailed Medical History ◽  
History Of ◽  
Zip Code

AbstractAlthough models have been developed for predicting severity of COVID-19 from the medical history of patients, simplified models with good accuracy could be more practical. In this study, we examined utility of simpler models for estimating risk of hospitalization of patients with COVID-19 and mortality of these patients based on demographic characteristics (sex, age, race, median household income based on zip code) and smoking status of 12,347 patients who tested positive at Mass General Brigham centers. The corresponding electronic records were queried (02/26–07/14/2020) to construct derivation and validation cohorts. The derivation cohort was used to fit generalized linear models for estimating risk of hospitalization within 30 days of COVID-19 diagnosis and mortality within approximately 3 months for the hospitalized patients. In the validation cohort, the model resulted in c-statistics of 0.77 [95% CI 0.73–0.80] for hospitalization, and 0.84 [95% CI 0.74–0.94] for mortality among hospitalized patients. Higher risk was associated with older age, male sex, Black ethnicity, lower socioeconomic status, and current/past smoking status. The models can be applied to predict the absolute risks of hospitalization and mortality, and could aid in individualizing the decision making when detailed medical history of patients is not readily available.

scholarly journals SARS2 simplified scores to estimate risk of hospitalization and death among patients with COVID-19

2020 ◽  
Author(s):  
Hesam Dashti ◽  
Elise Roche ◽  
David Bates ◽  
Samia Mora ◽  
Olga Demler
Keyword(s):  
Medical History ◽  
Prediction Models ◽  
Smoking Status ◽  
Hospitalized Patients ◽  
Risk Prediction Models ◽  
Derivation Cohort ◽  
Lower Socioeconomic ◽  
Detailed Medical History ◽  
History Of ◽  
Aid Decision

Although models have been developed for predicting severity of COVID-19 based on the medical history of patients, simplified risk prediction models with good accuracy could be more practical. In this study, we examined utility of simpler models for estimating risk of hospitalization of patients with COVID-19 and mortality of these patients based on demographic characteristics (sex, age, race, median household income based on zip code) and smoking status of 12,347 patients who tested positive at Mass General Brigham centers. The corresponding electronic health records were queried from 02/26/2020 to 07/14/2020 to construct derivation and validation cohorts. The derivation cohort was used to fit a generalized linear model for estimating risk of hospitalization within 30 days of COVID-19 diagnosis and mortality within approximately 3 months for the hospitalized patients. On the validation cohort, the model resulted in c-statistics of 0.77 [95% CI: 0.73-0.80] for hospitalization outcome, and 0.72 [95% CI: 0.69-0.74] for mortality among hospitalized patients. Higher risk was associated with older age, male sex, black ethnicity, lower socioeconomic status, and current/past smoking status. The model can be applied to predict risk of hospitalization and mortality, and could aid decision making when detailed medical history of patients is not easily available.

scholarly journals Factors Associated With Hospitalization in Children and Adolescents With SARS-CoV-2 Infection

2021 ◽  
pp. 000992282110598
Author(s):  
Jerry Y. Chao ◽  
Ariel Sugarman ◽  
Atsumi Kimura ◽  
Steven Flamer ◽  
Tina T. Jing ◽  
...  
Keyword(s):  
Socioeconomic Status ◽  
Medical History ◽  
Bimodal Distribution ◽  
Hospitalized Children ◽  
Past Medical History ◽  
Lower Socioeconomic Status ◽  
Obesity And Diabetes ◽  
Lower Socioeconomic ◽  
History Of ◽  
Univariate Statistics

In this retrospective study of 319 children with laboratory-confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, we assessed whether age, asthma, obesity, diabetes, and socioeconomic status were associated with hospitalization for coronavirus disease 2019 (COVID-19). Demographic and clinical characteristics were assessed using univariate statistics, excluding incidental or unrelated positives. There was a bimodal distribution of age among hospitalized children. Obesity ( P < .001) and a past medical history of diabetes ( P = .001) were significantly more prevalent in hospitalized children, including cases of new-onset diabetes and diabetic ketoacidosis. Neither a past medical history of asthma nor lower socioeconomic status was associated with hospitalization. Although limited to a single center, the findings in this study may have important clinical implications. Targeted, proactive health outreach to children with obesity and diabetes, with prioritization of preventative efforts such as vaccination, may be important in preventing worse SARS-CoV-2 infection in this vulnerable group.

Is Fringe Baking A Component of Socially Determined Health?

2017 ◽  
Vol 32 (3) ◽  
Author(s):  
Courtney L Hundley ◽  
Richard W. Wilson ◽  
John Chenault ◽  
Jamie L. Smimble
Keyword(s):  
Socioeconomic Status ◽  
Health Status ◽  
Exploratory Study ◽  
Health It ◽  
Lower Socioeconomic Status ◽  
Health Measures ◽  
Lower Socioeconomic ◽  
Level Data ◽  
Indirect Association ◽  
Zip Code

This was an exploratory study to assess the association between density of fringe lenders (e.g.payday) and health status. For Louisville, Kentucky, ZIP code level data on hospitalizations and mortalityrates as health measures were compared to fringe bank locations. We found lower socioeconomic status(SES) positively correlated with greater frequency of fringe banks; rates of illness appear to be higher in ZIPcodes with more fringe banks, but this finding was not statistically significant. In conclusion, neighbor-hoods between higher frequencies of fringe banks appear to have poorer health; it is premature to rule in orrule out a direct or indirect association between neighborhood presence of fringe banks, but there is enoughevidence to justify additional research to put any conclusions on a firmer footing.

Introduction

2016 ◽  
Author(s):  
T. M. Luhrmann
Keyword(s):  
United States ◽  
The United States ◽  
Social Conditions ◽  
Lower Socioeconomic Status ◽  
Ethnic Density ◽  
Cultural Interpretation ◽  
Lower Socioeconomic ◽  
The Social ◽  
The Family ◽  
History Of

The introduction lays out what we know about the social context of schizophrenia from the epidemiological literature: that risk of schizophrenia is particularly high for immigrants from predominantly dark-skinned countries to Europe; that risk increases with lower socioeconomic status at birth and even at parent’s birth; that risk increases with urban dwelling and seems to increase the longer time is spent in cities; that risk increases as ethnic density in the neighborhood declines. The chapter presents a history of the way schizophrenia has been understood in the United States, and the diagnostic complexities of serious psychotic disorder. It then discusses what ethnographers have observed so far about the social conditions which may shape the experience of psychosis: the local cultural interpretation of mental illness; the role and presence of the family; the structure of work; and the basic social environment. This becomes the ground for our case studies.

An Evaluation of Seasonal Variation of Nonaccidental Fractures in Children Less Than 1 Year of Age

2017 ◽  
Vol 56 (14) ◽  
pp. 1345-1349 ◽  
Author(s):  
Laura Leaman ◽  
William Hennrikus ◽  
Adam Y. Nasreddine
Keyword(s):  
Seasonal Variation ◽  
Lower Socioeconomic Status ◽  
Accidental Injury ◽  
Fractures In Children ◽  
Lower Socioeconomic ◽  
Parental Unemployment ◽  
Socioeconomic Data ◽  
Radiographic Data ◽  
Zip Code ◽  
Nonaccidental Injury

The aim of this study was to identify seasonal variation in nonaccidental injury (NAI) in children <1 year of age. Fifty consecutive patients age ≤12 months with a fracture were identified between January 2010 and June 2012. Patients’ records were reviewed for demographic, clinical, and radiographic data. Zip code was used to collect socioeconomic data. Out of 50 patients included in the study, fractures in 16 (32%) patients were reported for abuse. NAI was reported in 2/13 (15%) fracture cases presenting in the spring, 5/6 (83%) in summer, 6/15 (40%) in autumn, and 3/14 (21%) in winter. The ratio of NAI to accidental injury was highest in the summer. Presentation in summer was associated with NAI ( P < .001). In addition, NAI was associated with parental unemployment, single parents, and lower socioeconomic status ( P < .001). Seasonal variation occurred, and the most common season for NAI was the summer; also, NAI in children <1 year of age was associated with parental unemployment, single parent, and poverty.

scholarly journals Socioeconomic inequalities in self-reported dental and general health in a Norwegian county study

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
H Lyshol ◽  
A Sen ◽  
T Natland Fagerhaug ◽  
A Jullumstrø Feuerhern ◽  
G Jakhelln ◽  
...  
Keyword(s):  
General Health ◽  
Linear Models ◽  
Dental Health ◽  
Age Groups ◽  
Lower Socioeconomic Status ◽  
Cross Sectional ◽  
National Education ◽  
Lower Socioeconomic ◽  
Interview Survey ◽  
Study Population

Abstract Background Studies have shown socioeconomic gradients in both dental health and general health, with poorer health in lower-socioeconomic status (SES) groups than in their higher-SES counterparts. We wanted to see if these gradients were present in our study population according to educational differences, and whether age or gender would have effect. Methods In 2015-16 a cross-sectional interview survey was carried out in three of Norway's then 19 counties. Questions about dental and general health were included. The respondents' educational level was available from linkages to the national education registry. 4551 men and 5141 women responded; a response rate of 42.7%. We included respondents aged 25-79. We compared the percentages reporting good/very good dental and general health by degree of education according to ISCED classification (0-2, 3-4 and 5-6) across the age groups 25-44, 45-66 and 67-79; by gender and county, in a regression with general linear models in STATA 15 Results Clear educational gradients were found for both general and dental health. Stratifying by gender and county, we found more consistent age gradients for general health than for dental health, and consistent educational gradients for both. Both general and dental health were expected to deteriorate with age, and age was weakly associated with dental health. In regression analyses, general health was (negatively) associated with age (RR 1.04, CI 1.02-1.07) and (positively) associated with education (RR 0.92, CI 0.89-0.94), but not with gender. Dental health was not associated with age, but with education (RR 0.93, CI 0.91-0.96). Conclusions Self-reported dental health varied more by education than by age, and showed clear gradients only by education. There were county variations, but the oldest people with the highest education reported better health, both dental and general, than the youngest people with the lowest education. This may be connected to other socio-economic differences. Key messages There is often a gradient for age within each educational group regarding general health, but more rarely so regarding dental health. Education has a stronger influence on both dental health and general health than age.

Treatment for Tobacco Dependence for Rural, Lower-Income Smokers: Outcomes, Predictors, and Measurement Considerations

2009 ◽  
Vol 23 (5) ◽  
pp. 328-338 ◽  
Author(s):  
Christine E. Sheffer ◽  
Maxine Stitzer ◽  
Thomas J. Payne ◽  
Bradford W. Applegate ◽  
David Bourne ◽  
...  
Keyword(s):  
Smoking Status ◽  
Behavioral Therapy ◽  
Tobacco Dependence ◽  
Evidence Based ◽  
Long Term Outcomes ◽  
Lower Socioeconomic Status ◽  
Intention To Treat ◽  
Lower Socioeconomic ◽  
Treat Analysis

Purpose. Outcomes from a statewide program that delivered evidence-based, intensive treatment for tobacco dependence to a rural population of lower socioeconomic status (SES) were evaluated. Factors that predicted success and measurement considerations were examined. Design and Analyses. Data were collected at intake, at all treatment sessions, and at 3- and 12-months posttreatment. Abstinence rates were calculated using complete-case analysis and intention-to-treat analysis, and they were estimated for all participants. Logistic regression was used to evaluate the predictive significance of demographic and clinical factors. Setting. Twenty health care sites across Arkansas. Participants. A total of 2,350 predominantly rural, lower SES, Arkansas residents. Intervention. Evidence-based, six-session, multi-component cognitive-behavioral therapy with relapse prevention. Results. The estimated percent abstinent was 26.47% at 3-months and 21.73% at 12-months posttreatment; 51.02%) of patients completed treatment and demonstrated markedly higher quit rates. Although numerous factors predicted outcomes at different points, self-efficacy and dependence levels at intake were robust predictors across time and methods of calculating outcomes. Sex, partner smoking status, and educational level were significant predictors of long-term abstinence. Conclusions. This study demonstrates that intensive, evidence-based treatment for tobacco dependence can be successfully delivered in a statewide program and can yield long-term outcomes that approximate those seen in more controlled settings. Overall sample estimates may be more appropriate for the assessment of outcomes in this context.

scholarly journals Level of education and multiple sclerosis risk after adjustment for known risk factors: The EnvIMS study

2015 ◽  
Vol 22 (1) ◽  
pp. 104-111 ◽  
Author(s):  
Kjetil Bjørnevik ◽  
Trond Riise ◽  
Marianna Cortese ◽  
Trygve Holmøy ◽  
Margitta T Kampman ◽  
...  
Keyword(s):  
Risk Factors ◽  
Multiple Sclerosis ◽  
Vitamin D ◽  
Disease Onset ◽  
Lower Socioeconomic Status ◽  
Level Of Education ◽  
Lower Socioeconomic ◽  
Vitamin D Levels ◽  
The Social ◽  
History Of

Background: Several recent studies have found a higher risk of multiple sclerosis (MS) among people with a low level of education. This has been suggested to reflect an effect of smoking and lower vitamin D status in the social class associated with lower levels of education. Objective: The objective of this paper is to investigate the association between level of education and MS risk adjusting for the known risk factors smoking, infectious mononucleosis, indicators of vitamin D levels and body size. Methods: Within the case-control study on Environmental Factors In MS (EnvIMS), 953 MS patients and 1717 healthy controls from Norway reported educational level and history of exposure to putative environmental risk factors. Results: Higher level of education were associated with decreased MS risk ( p trend = 0.001) with an OR of 0.53 (95% CI 0.41–0.68) when comparing those with the highest and lowest level of education. This association was only moderately reduced after adjusting for known risk factors (OR 0.61, 95% CI 0.44–0.83). The estimates remained similar when cases with disease onset before age 28 were excluded. Conclusion: These findings suggest that factors related to lower socioeconomic status other than established risk factors are associated with MS risk.

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