The Ties that Bind: The Role of Place in Racial Identity Formation, Social Cohesion, Accord, and Discord in Two Historic, Black Gentrifying Atlanta Neighborhoods

Recent research has uncovered a new phenomenon in some distressed areas, black gentrification. Black gentrification follows the same pattern as mainstream gentrification with one notable exception: In black gentrifying neighborhoods both the poor and working class residents who resided in the neighborhood prior to its “gentrification” and the new residents of greater economic means are black. An additional hallmark of black gentrification that distinguishes it from traditional gentrification is that black gentrifiers in black gentrifying neighborhoods often feel a responsibility or obligation to their lower income black neighbors. Prior to the economic downturn in the United States, some in-town Atlanta neighborhoods were undergoing black gentrification. Amidst the current mortgage foreclosure epidemic facing the U.S., distressed urban areas like the ones under study, which began to gentrify in the last ten to twenty years, can easily fall prey to mortgage fraud and/or further decline. Sustained revitalization efforts require that the neighborhoods maintain a critical density level; therefore, neighborhoods cannot afford to lose more citizens. My dissertation focuses on two historic, black gentrifying in-town Atlanta neighborhoods: the Old Fourth Ward and the West End. The Old Fourth Ward is the location of the birth home of one of Atlanta’s most celebrated sons, Dr. Martin Luther King Jr. The West End, once a center of black consciousness in the city, now boasts one of the highest mortgage fraud rates in the nation. Revitalization efforts in both communities are in jeopardy. This dissertation explores ways to strengthen social and economic cohesion in these gentrifying black communities. Specifically, I argue that attachment to the neighborhood space (something I term “place affinity”) has the potential to obviate social tensions in gentrifying black communities and bind residents to each other and the social space they all occupy

At-admission prediction of mortality and pulmonary embolism in an international cohort of hospitalised patients with COVID-19 using statistical and machine learning methods

By September 2022, more than 600 million cases of SARS-CoV-2 infection have been reported globally, resulting in over 6.5 million deaths. COVID-19 mortality risk estimators are often, however, developed with small unrepresentative samples and with methodological limitations. It is highly important to develop predictive tools for pulmonary embolism (PE) in COVID-19 patients as one of the most severe preventable complications of COVID-19. Early recognition can help provide life-saving targeted anti-coagulation therapy right at admission. Using a dataset of more than 800,000 COVID-19 patients from an international cohort, we propose a cost-sensitive gradient-boosted machine learning model that predicts occurrence of PE and death at admission. Logistic regression, Cox proportional hazards models, and Shapley values were used to identify key predictors for PE and death. Our prediction model had a test AUROC of 75.9% and 74.2%, and sensitivities of 67.5% and 72.7% for PE and all-cause mortality respectively on a highly diverse and held-out test set. The PE prediction model was also evaluated on patients in UK and Spain separately with test results of 74.5% AUROC, 63.5% sensitivity and 78.9% AUROC, 95.7% sensitivity. Age, sex, region of admission, comorbidities (chronic cardiac and pulmonary disease, dementia, diabetes, hypertension, cancer, obesity, smoking), and symptoms (any, confusion, chest pain, fatigue, headache, fever, muscle or joint pain, shortness of breath) were the most important clinical predictors at admission. Age, overall presence of symptoms, shortness of breath, and hypertension were found to be key predictors for PE using our extreme gradient boosted model. This analysis based on the, until now, largest global dataset for this set of problems can inform hospital prioritisation policy and guide long term clinical research and decision-making for COVID-19 patients globally. Our machine learning model developed from an international cohort can serve to better regulate hospital risk prioritisation of at-risk patients

Stereotactic or conformal radiotherapy for adrenal metastases: patient characteristics and outcomes in a multicenter analysis

To report outcome (freedom from local progression: FFLP, overall survival: OS, and toxicity) after stereotactic, palliative, or highly conformal fractionated (> 12) radiotherapy (SBRT, Pall-RT, 3DCRT/IMRT) for adrenal metastases in a retrospective multicenter cohort within the framework of the German Society for Radiation Oncology (DEGRO). Adrenal metastases treated with SBRT (≤ 12 fractions, biologically effective dose, (BED10) ≥ 50 Gy), 3DCRT/IMRT (> 12 fractions, BED10 ≥ 50 Gy) or Pall-RT (BED10 < 50 Gy) were eligible for this analysis. In addition to unadjusted FFLP (Kaplan-Meier/Log-rank), we calculated the competing-risk-adjusted local recurrence rate (CRA-LRR). 326 patients with 366 metastases were included by 21 centers (median follow-up: 11.7 months). Treatment was SBRT, 3DCRT/IMRT, and Pall-RT in 260, 27, and 79 cases, respectively. Most frequent primary tumors were non-small-cell lung cancer (NSCLC; 52.5%), SCLC (16.3%), and melanoma (6.7%). Unadjusted FFLP was higher after SBRT v. Pall-RT (p = 0.026) while numerical differences in CRA-LRR between groups did not reach statistical significance (1-year CRA-LRR: 13.8%, 17.4%, and 27.7%). OS was longer after SBRT v. other groups (p < 0.05) and increased in patients with locally-controlled metastases in a landmark analysis (p < 0.0001). Toxicity was mostly mild; notably, 4 cases of adrenal insufficiency occurred, 2 of which were likely caused by immunotherapy or tumor progression. RT for adrenal metastases was associated with a mild toxicity profile in all groups and a favorable 1-year CRA-LRR after SBRT or 3DCRT/IMRT. 1-year FFLP was associated with longer OS. Dose-response analyses for the dataset are underway

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Proceedings of the 3rd Biennial Conference of the Society for Implementation Research Collaboration (SIRC) 2015: advancing efficient methodologies through community partnerships and team science

It is well documented that the majority of adults, children and families in need of evidence-based behavioral health interventionsi do not receive them [1, 2] and that few robust empirically supported methods for implementing evidence-based practices (EBPs) exist. The Society for Implementation Research Collaboration (SIRC) represents a burgeoning effort to advance the innovation and rigor of implementation research and is uniquely focused on bringing together researchers and stakeholders committed to evaluating the implementation of complex evidence-based behavioral health interventions. Through its diverse activities and membership, SIRC aims to foster the promise of implementation research to better serve the behavioral health needs of the population by identifying rigorous, relevant, and efficient strategies that successfully transfer scientific evidence to clinical knowledge for use in real world settings [3]. SIRC began as a National Institute of Mental Health (NIMH)-funded conference series in 2010 (previously titled the “Seattle Implementation Research Conference”; $150,000 USD for 3 conferences in 2011, 2013, and 2015) with the recognition that there were multiple researchers and stakeholdersi working in parallel on innovative implementation science projects in behavioral health, but that formal channels for communicating and collaborating with one another were relatively unavailable. There was a significant need for a forum within which implementation researchers and stakeholders could learn from one another, refine approaches to science and practice, and develop an implementation research agenda using common measures, methods, and research principles to improve both the frequency and quality with which behavioral health treatment implementation is evaluated. SIRC’s membership growth is a testament to this identified need with more than 1000 members from 2011 to the present.ii SIRC’s primary objectives are to: (1) foster communication and collaboration across diverse groups, including implementation researchers, intermediariesi, as well as community stakeholders (SIRC uses the term “EBP champions” for these groups) – and to do so across multiple career levels (e.g., students, early career faculty, established investigators); and (2) enhance and disseminate rigorous measures and methodologies for implementing EBPs and evaluating EBP implementation efforts. These objectives are well aligned with Glasgow and colleagues’ [4] five core tenets deemed critical for advancing implementation science: collaboration, efficiency and speed, rigor and relevance, improved capacity, and cumulative knowledge. SIRC advances these objectives and tenets through in-person conferences, which bring together multidisciplinary implementation researchers and those implementing evidence-based behavioral health interventions in the community to share their work and create professional connections and collaborations

COVID-19 symptoms at hospital admission vary with age and sex: results from the ISARIC prospective multinational observational study

Background: The ISARIC prospective multinational observational study is the largest cohort of hospitalized patients with COVID-19. We present relationships of age, sex, and nationality to presenting symptoms. Methods: International, prospective observational study of 60 109 hospitalized symptomatic patients with laboratory-confirmed COVID-19 recruited from 43 countries between 30 January and 3 August 2020. Logistic regression was performed to evaluate relationships of age and sex to published COVID-19 case definitions and the most commonly reported symptoms. Results: ‘Typical’ symptoms of fever (69%), cough (68%) and shortness of breath (66%) were the most commonly reported. 92% of patients experienced at least one of these. Prevalence of typical symptoms was greatest in 30- to 60-year-olds (respectively 80, 79, 69%; at least one 95%). They were reported less frequently in children (≤ 18 years: 69, 48, 23; 85%), older adults (≥ 70 years: 61, 62, 65; 90%), and women (66, 66, 64; 90%; vs. men 71, 70, 67; 93%, each P < 0.001). The most common atypical presentations under 60 years of age were nausea and vomiting and abdominal pain, and over 60 years was confusion. Regression models showed significant differences in symptoms with sex, age and country. Interpretation: This international collaboration has allowed us to report reliable symptom data from the largest cohort of patients admitted to hospital with COVID-19. Adults over 60 and children admitted to hospital with COVID-19 are less likely to present with typical symptoms. Nausea and vomiting are common atypical presentations under 30 years. Confusion is a frequent atypical presentation of COVID-19 in adults over 60 years. Women are less likely to experience typical symptoms than men