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Collecting neighborhood data can both be time- and resource-intensive, especially across broad geographies. In this study, we leveraged 1.4 million publicly available Google Street View (GSV) images from Utah to construct indicators of the neighborhood built environment and evaluate their associations with 2017–2019 health outcomes of approximately one-third of the population living in Utah. The use of electronic medical records allows for the assessment of associations between neighborhood characteristics and individual-level health outcomes while controlling for predisposing factors, which distinguishes this study from previous GSV studies that were ecological in nature. Among 938,085 adult patients, we found that individuals living in communities in the highest tertiles of green streets and non-single-family homes have 10–27% lower diabetes, uncontrolled diabetes, hypertension, and obesity, but higher substance use disorders—controlling for age, White race, Hispanic ethnicity, religion, marital status, health insurance, and area deprivation index. Conversely, the presence of visible utility wires overhead was associated with 5–10% more diabetes, uncontrolled diabetes, hypertension, obesity, and substance use disorders. Our study found that non-single-family and green streets were related to a lower prevalence of chronic conditions, while visible utility wires and single-lane roads were connected with a higher burden of chronic conditions. These contextual characteristics can better help healthcare organizations understand the drivers of their patients' health by further considering patients' residential environments, which present both risks and resources. [ABSTRACT FROM AUTHOR]

Introduction: The introduction of the protein-specific antigen (PSA) test in care means that prostate cancer (PCa) is being detected earlier and more frequently. The result of increased screening using PSA, digital rectal examination and awareness of prostate was an increase in the number of men with low risk cancers. Active surveillance has become a viable alternative to immediate treatment with surgery, radiation and other forms of localized treatment. Evidence suggests that there is no significant difference in mortality rates between AS and surgery. In addition, patients may potentially delay other complications associated with surgery, radiation or deprivation therapy. Methods: This quality improvement study using a delivery system science framework describes the electronic identification of AS candidates given an evidence-based identification criteria based upon national guidelines and clinical judgement. The study population (n=649) was drawn from health records of all patients who received a prostate biopsy (n=1731) at Intermountain Healthcare from 1/1/2013 to 12/31/2014. Automated and manual abstraction was performed. Receiver operating characteristic (ROC) analysis was used to compare AS-eligible patients to the actual treatment received to identify potential care improvement opportunities. Among those with complete data, 24.7% of this population (n=160) met "AS-eligible" criteria. 39.1% of the population had not received surgery, radiation or androgen deprivation therapy and were considered as being treated using an AS approach. 9% of AS-eligible patients did not receive AS; 27% of patients who did not meet AS-eligible criteria received AS. Estimated guideline adherence measured using area under the curve was 0.70 (95% CI: 0.66-0.73). Modest variation in criteria parameters for identifying AS-eligible patients did not significantly change estimated adherence levels. Conclusion: Implementation of evidence-based criteria for detection of AS candidates is feasible using electronic health record data and provides a reasonable basis for delivery system evaluation of practice patterns and for quality improvement. [ABSTRACT FROM AUTHOR]

Non-invasive imaging techniques are highly desirable as an alternative to conventional biopsy for the characterization of the remodeling of tissues associated with disease progression, including end-stage heart failure. Cardiac diffusion tensor imaging (DTI) has become an established method for the characterization of myocardial microstructure. However, the relationships between diffuse myocardial fibrosis, which is a key biomarker for staging and treatment planning of the failing heart, and measured DTI parameters have yet to be investigated systematically. In this study, DTI was performed on left ventricular specimens collected from patients with chronic end-stage heart failure as a result of idiopathic dilated cardiomyopathy ( n = 14) and from normal donors ( n = 5). Scalar DTI parameters, including fractional anisotropy (FA) and mean (MD), primary ( D1), secondary ( D2) and tertiary ( D3) diffusivities, were correlated with collagen content measured by digital microscopy. Compared with hearts from normal subjects, the FA in failing hearts decreased by 22%, whereas the MD, D2 and D3 increased by 12%, 14% and 24%, respectively ( P < 0.01). No significant change was detected for D1 between the two groups. Furthermore, significant correlation was observed between the DTI scalar indices and quantitative histological measurements of collagen (i.e. fibrosis). Pearson's correlation coefficients ( r) between collagen content and FA, MD, D2 and D3 were -0.51, 0.59, 0.56 and 0.62 ( P < 0.05), respectively. The correlation between D1 and collagen content was not significant ( r = 0.46, P = 0.05). Computational modeling analysis indicated that the behaviors of the DTI parameters as a function of the degree of fibrosis were well explained by compartmental exchange between myocardial and collagenous tissues. Combined, these findings suggest that scalar DTI parameters can be used as metrics for the non-invasive assessment of diffuse fibrosis in failing hearts. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Background: Nearly 25% of patients with peripartum cardiomyopathy (PPCM) will require cardiac transplantation. Whether post-transplant outcomes differ among patients with PPCM compared with other recipients remains unsettled. Methods: The United Network for Organ Sharing database was queried for cardiac transplants, comparing characteristics and outcomes for PPCM, other women, and all others. Results: Between 1987 and 2010, 42,406 patients (9,419 women and 32,987 men) received a heart transplant. Of these, 485 women who had PPCM as the indication were younger (p < 0.001), had higher sensitization (p < 0.001), required higher intensity of cardiovascular support pre-transplant (p = 0.026), and had higher listing status (p < 0.001). Those with PPCM had more post-transplant rejection during the index transplant hospitalization (p < 0.001) and during the first year (p = 0.003). Comparing PPCM with other women and all others, graft survival was inferior (p = 0.004 and p < 0.003, respectively) and age-adjusted survival was lower (p < 0.001 and p = 0.02, respectively). Conclusions: This large report shows outcomes of graft failure and death are inferior for recipients with PPCM, which may be partly explained by younger age, higher allosensitization, higher pre-transplant acuity, and increased rejection. More research is needed to determine management strategies to improve outcomes in PPCM heart transplant recipients. [ABSTRACT FROM AUTHOR]

Left ventricular assist device (LVAD) implantation before heart transplantation has been associated with formation of antibodies directed against human leukocyte antigens (HLA), often referred to as sensitization. This study investigated whether prior sensitization or LVAD type affected the degree of post-implantation sensitization. The records of consecutive HeartMate (HM) I and HM II LVAD patients were reviewed. Panel reactive antibody (PRA) was assessed before LVAD implantation and biweekly thereafter. Sensitization was defined as PRA > 10%, and high-degree sensitization was defined as PRA > 90%. An HM LVAD was implanted in 64 patients, and 11 received a HM II LVAD as a bridge to transplant. Ten HM I patients (16%) were sensitized before LVAD implantation (HM I-S), and 54 (84%) were not (HM I-Non-S). Nine HM I-S patients (90%) became highly sensitized (PRA > 90%) compared with 9 HM I-Non-S patients (16.7%; p < 0.001). The PRA remained elevated (> 90%) in 8 of the 9 (88.9%) highly sensitized HM I-S patients vs 5 of the 9 (55.6%) HM I-Non-S highly sensitized patients. The PRA levels in the rest of the HM I-S highly sensitized patients declined from 93% ± 4% to 55% ± 15% (p = 0.01). Among the 11 HM II patients, 1 (9%) was sensitized before LVAD implantation (PRA, 40%) and the PRA moderately increased to 80%. No other HM II patient became sensitized after implantation. Thus, 1 of 11 (9%) HM II patients became sensitized compared with 29 of 64 (45%) HM I patients (p = 0.04). Pre-sensitized patients are at higher risk for becoming and remaining highly HLA-allosensitized after LVAD implantation. The HeartMate II LVAD appears to cause less sensitization than HeartMate I. [Copyright &y& Elsevier]

Deep learning and, specifically, convoltional neural networks (CNN) represent a class of powerful models that facilitate the understanding of many problems in computer vision. When combined with a reasonable amount of data, CNNs can outperform traditional models for many tasks, including image classification. In this work, we utilize these powerful tools with imagery data collected through Google Street View images to perform virtual audits of neighborhood characteristics. We further investigate different architectures for chronic disease prevalence regression through networks that are applied to sets of images rather than single images. We show quantitative results and demonstrate that our proposed architectures outperform the traditional regression approaches.

Objectives: To determine predictors of physician assistants (PAs) to retire or to permanently leave clinical practice. The intent was to create a measure of retention and attrition for purposes of forecasting PA supply., Study Design: All PAs 55 years or older who were nationally certified in 2011 were surveyed., Methods: Statistical analysis included descriptive measures utilizing means, standard deviations, range, and proportions for all survey questions. Univariable analysis using χ² test for the categorical variables determined gender differences in participants' intent to retire. A studentized t test analysis for continuous variables was used to compare differences across genders. The estimated time interval until retirement was calculated using reported values from participants and then subtracting their projected retirement age from current age. The same calculation was used for estimating PA career length from date of graduation to retirement. For all analyses, a P value < .05 was considered statistically significant., Results: A total of 12,005 were eligible and surveyed online; 4767 responded (38%). The mean age was 60 years and the years in clinical practice was 25. When asked to predict a retirement date or age, the mean duration of working beyond age 55 years was 12 years (range 5 to 21). Most respondents reported being confident they were on track to retire with an adequate income. The significant differences that emerged were that men were more confident than women in preparing to retire, having enough money for medical expenses, and being able to live comfortably in retirement. Men more than women stated that, if forced to retire, they were more confident in the preparation to do so., Conclusions: PAs 55 years and older report they are likely to delay retirement from practice until age 67 years, on average. Women were less confident than men in retirement preparation. This age prediction expands career projections and refines forecasting models for the profession. Correlations based on expectation-action chain of events should be developed by periodically measuring how often intent and reality coalesce.