Clinical Features and Outcomes Differ between Skeletal and Extraskeletal Osteosarcoma.

Background. Extraskeletal osteosarcoma (ESOS) is a rare subtype of osteosarcoma. We investigated patient characteristics, overall survival, and prognostic factors in ESOS. Methods. We identified cases of high-grade osteosarcoma with known tissue of origin in the Surveillance, Epidemiology, and End Results database from 1973 to 2009. Demographics were compared using univariate tests. Overall survival was compared with log-rank tests and multivariate analysis using Cox proportional hazards methods. Results. 256/4,173 (6%) patients with high-grade osteosarcoma had ESOS. Patients with ESOS were older, were more likely to have an axial tumor and regional lymph node involvement, and were female. Multivariate analysis showed ESOS to be favorable after controlling for stage, age, tumor site, gender, and year of diagnosis [hazard ratio 0.75 (95% CI 0.62 to 0.90); p = 0.002]. There was an interaction between age and tissue of origin such that older patients with ESOS had superior outcomes compared to older patients with skeletal osteosarcoma. Adverse prognostic factors in ESOS included metastatic disease, larger tumor size, older age, and axial tumor site. Conclusion. Patients with ESOS have distinct clinical features but similar prognostic factors compared to skeletal osteosarcoma. Older patients with ESOS have superior outcomes compared to older patients with skeletal osteosarcoma

Development and Validation of eRADAR: A Tool Using EHR Data to Detect Unrecognized Dementia.

ObjectivesEarly recognition of dementia would allow patients and their families to receive care earlier in the disease process, potentially improving care management and patient outcomes, yet nearly half of patients with dementia are undiagnosed. Our aim was to develop and validate an electronic health record (EHR)-based tool to help detect patients with unrecognized dementia (EHR Risk of Alzheimer's and Dementia Assessment Rule [eRADAR]).DesignRetrospective cohort study.SettingKaiser Permanente Washington (KPWA), an integrated healthcare delivery system.ParticipantsA total of 16 665 visits among 4330 participants in the Adult Changes in Thought (ACT) study, who undergo a comprehensive process to detect and diagnose dementia every 2 years and have linked KPWA EHR data, divided into development (70%) and validation (30%) samples.MeasurementsEHR predictors included demographics, medical diagnoses, vital signs, healthcare utilization, and medications within the previous 2 years. Unrecognized dementia was defined as detection in ACT before documentation in the KPWA EHR (ie, lack of dementia or memory loss diagnosis codes or dementia medication fills).ResultsOverall, 1015 ACT visits resulted in a diagnosis of incident dementia, of which 498 (49%) were unrecognized in the KPWA EHR. The final 31-predictor model included markers of dementia-related symptoms (eg, psychosis diagnoses, antidepressant fills), healthcare utilization pattern (eg, emergency department visits), and dementia risk factors (eg, cerebrovascular disease, diabetes). Discrimination was good in the development (C statistic = .78; 95% confidence interval [CI] = .76-.81) and validation (C statistic = .81; 95% CI = .78-.84) samples, and calibration was good based on plots of predicted vs observed risk. If patients with scores in the top 5% were flagged for additional evaluation, we estimate that 1 in 6 would have dementia.ConclusionThe eRADAR tool uses existing EHR data to detect patients with good accuracy who may have unrecognized dementia. J Am Geriatr Soc 68:103-111, 2019

Coronary Risk Assessment by Point-Based vs. Equation-Based Framingham Models: Significant Implications for Clinical Care

US cholesterol guidelines use original and simplified versions of the Framingham model to estimate future coronary risk and thereby classify patients into risk groups with different treatment strategies. We sought to compare risk estimates and risk group classification generated by the original, complex Framingham model and the simplified, point-based version. We assessed 2,543 subjects age 20–79 from the 2001–2006 National Health and Nutrition Examination Surveys (NHANES) for whom Adult Treatment Panel III (ATP-III) guidelines recommend formal risk stratification. For each subject, we calculated the 10-year risk of major coronary events using the original and point-based Framingham models, and then compared differences in these risk estimates and whether these differences would place subjects into different ATP-III risk groups (<10% risk, 10–20% risk, or >20% risk). Using standard procedures, all analyses were adjusted for survey weights, clustering, and stratification to make our results nationally representative. Among 39 million eligible adults, the original Framingham model categorized 71% of subjects as having “moderate” risk (<10% risk of a major coronary event in the next 10 years), 22% as having “moderately high” (10–20%) risk, and 7% as having “high” (>20%) risk. Estimates of coronary risk by the original and point-based models often differed substantially. The point-based system classified 15% of adults (5.7 million) into different risk groups than the original model, with 10% (3.9 million) misclassified into higher risk groups and 5% (1.8 million) into lower risk groups, for a net impact of classifying 2.1 million adults into higher risk groups. These risk group misclassifications would impact guideline-recommended drug treatment strategies for 25–46% of affected subjects. Patterns of misclassifications varied significantly by gender, age, and underlying CHD risk. Compared to the original Framingham model, the point-based version misclassifies millions of Americans into risk groups for which guidelines recommend different treatment strategies

Preimplantation Mouse Embryo Selection Guided by Light-Induced Dielectrophoresis

Selection of optimal quality embryos for in vitro fertilization (IVF) transfer is critical to successful live birth outcomes. Currently, embryos are chosen based on subjective assessment of morphologic developmental maturity. A non-invasive means to quantitatively measure an embryo's developmental maturity would reduce the variability introduced by the current standard. We present a method that exploits the scaling electrical properties of pre-transfer embryos to quantitatively discern embryo developmental maturity using light-induced dielectrophoresis (DEP). We show that an embryo's DEP response is highly correlated with its developmental stage. Uniquely, this technique allows one to select, in sequence and under blinded conditions, the most developmentally mature embryos among a mixed cohort of morphologically indistinguishable embryos cultured in optimized and sub-optimal culture media. Following assay, embryos continue to develop normally in vitro. Light-induced dielectrophoresis provides a non-invasive, quantitative, and reproducible means to select embryos for applications including IVF transfer and embryonic stem cell harvest

Discrimination in Healthcare Settings is Associated with Disability in Older Adults: Health and Retirement Study, 2008–2012

BACKGROUNDAs our society ages, improving medical care for an older population will be crucial. Discrimination in healthcare may contribute to substandard experiences with the healthcare system, increasing the burden of poor health in older adults. Few studies have focused on the presence of healthcare discrimination and its effects on older adults.OBJECTIVEWe aimed to examine the relationship between healthcare discrimination and new or worsened disability.DESIGNThis was a longitudinal analysis of data from the nationally representative Health and Retirement Study administered in 2008 with follow-up through 2012.PARTICIPANTSSix thousand and seventeen adults over the age of 50 years (mean age 67years, 56.3% female, 83.1% white) were included in this study.MAIN MEASURESHealthcare discrimination assessed by a 2008 report of receiving poorer service or treatment than other people by doctors or hospitals (never, less than a year=infrequent; more than once a year=frequent). Outcome was self-report of new or worsened disability by 2012 (difficulty or dependence in any of six activities of daily living). We used a Cox proportional hazards model adjusting for age, race/ethnicity, gender, net worth, education, depression, high blood pressure, diabetes, cancer, lung disease, heart disease, stroke, and healthcare utilization in the past 2years.KEY RESULTSIn all, 12.6 % experienced discrimination infrequently and 5.9% frequently. Almost one-third of participants (29%) reporting frequent healthcare discrimination developed new or worsened disability over 4years, compared to 16.8% of those who infrequently and 14.7% of those who never experienced healthcare discrimination (p < 0.001). In multivariate analyses, compared to no discrimination, frequent healthcare discrimination was associated with new or worsened disability over 4years (aHR = 1.63, 95% CI 1.16–2.27).CONCLUSIONSOne out of five adults over the age of 50 years experiences discrimination in healthcare settings. One in 17 experience frequent healthcare discrimination, and this is associated with new or worsened disability by 4years. Future research should focus on the mechanisms by which healthcare discrimination influences disability in older adults to promote better health outcomes for an aging population.Electronic supplementary materialThe online version of this article (doi:10.1007/s11606-015-3233-6) contains supplementary material, which is available to authorized users

Association of Social and Behavioral Risk Factors With Mortality Among US Veterans With COVID-19

Importance The US Department of Veterans Affairs (VA) offers programs that reduce barriers to care for veterans and those with housing instability, poverty, and substance use disorder. In this setting, however, the role that social and behavioral risk factors play in COVID-19 outcomes is unclear. Objective To examine whether social and behavioral risk factors were associated with mortality among US veterans with COVID-19 and whether this association might be modified by race/ethnicity. Design, Setting, and Participants This cohort study obtained data from the VA Corporate Data Warehouse to form a cohort of veterans who received a positive COVID-19 test result between March 2 and September 30, 2020, in a VA health care facility. All veterans who met the inclusion criteria were eligible to participate in the study, and participants were followed up for 30 days after the first SARS-CoV-2 or COVID-19 diagnosis. The final follow-up date was October 31, 2020. Exposures Social risk factors included housing problems and financial hardship. Behavioral risk factors included current tobacco use, alcohol use, and substance use. Main Outcomes and Measures The primary outcome was all-cause mortality in the 30-day period after the SARS-CoV-2 or COVID-19 diagnosis date. Multivariable logistic regression was used to estimate odds ratios, clustering for health care facilities and adjusting for age, sex, race, ethnicity, marital status, clinical factors, and month of COVID-19 diagnosis. Results Among 27 640 veterans with COVID-19 who were included in the analysis, 24 496 were men (88.6%) and the mean (SD) age was 57.2 (16.6) years. A total of 3090 veterans (11.2%) had housing problems, 4450 (16.1%) had financial hardship, 5358 (19.4%) used alcohol, and 3569 (12.9%) reported substance use. Hospitalization occurred in 7663 veterans (27.7%), and 1230 veterans (4.5%) died. Housing problems (adjusted odds ratio [AOR], 0.96; 95% CI, 0.77-1.19; P = .70), financial hardship (AOR, 1.13; 95% CI, 0.97-1.31; P = .11), alcohol use (AOR, 0.82; 95% CI, 0.68-1.01; P = .06), current tobacco use (AOR, 0.85; 95% CI, 0.68-1.06; P = .14), and substance use (AOR, 0.90; 95% CI, 0.71-1.15; P = .41) were not associated with higher mortality. Interaction analyses by race/ethnicity did not find associations between mortality and social and behavioral risk factors. Conclusions and Relevance Results of this study showed that, in an integrated health system such as the VA, social and behavioral risk factors were not associated with mortality from COVID-19. Further research is needed to substantiate the potential of an integrated health system to be a model of support services for households with COVID-19 and populations who are at risk for the disease

A Telehealth-Based Randomized Controlled Trial: A Model for Outpatients Trials of Off-Label Medications During the COVID-19 Pandemic

The study was registered at clinicaltrials.gov: NCT0436320