Respecting Autonomy and Enabling Diversity: The Effect of Eligibility and Enrollment on Research Data Demographics

Many promising advances in precision health and other Big Data research rely on large data sets to analyze correlations among genetic variants, behavior, environment, and outcomes to improve population health. But these data sets are generally populated with demographically homogeneous cohorts. We conducted a retrospective cohort study of patients at a major academic medical center during 2012–19 to explore how recruitment and enrollment approaches affected the demographic diversity of participants in its research biospecimen and data bank. We found that compared with the overall clinical population, patients who consented to enroll in the research data bank were significantly less diverse in terms of age, sex, race, ethnicity, and socioeconomic status. Compared with patients who were recruited for the data bank, patients who enrolled were younger and less likely to be Black or African American, Asian, or Hispanic. The overall demographic diversity of the data bank was affected as much (and in some cases more) by which patients were considered eligible for recruitment as by which patients consented to enroll. Our work underscores the need for systemic commitment to diversify data banks so that different communities can benefit from research

Placental Growth Factor:A Promising Diagnostic Biomarker for Tubal Ectopic Pregnancy

CONTEXT: Tubal ectopic pregnancy is common but accurate diagnosis is difficult and costly. There is currently no serum test to differentiate tubal from intrauterine implantation and an effective biomarker of ectopic pregnancy would be a major clinical advance. OBJECTIVE: A key feature of successful intrauterine implantation is the establishment of a supportive vascular network and this has been associated with the activity of placental growth factor (PIGF). We hypothesized that the local decidual environment facilitates PIGF-dependent angiogenesis and that this pathway is not active in tubal implantation. We aimed to determine whether tubal implantation is manifest by an attenuation of the normal trophoblast PIGF-response and whether serum PIGF levels are different in ectopic compared to intrauterine pregnancy. DESIGN: Tissue and serum analysis. SETTING: A large UK teaching hospital. PATIENTS: Gestation-matched pregnant women undergoing surgical termination of pregnancy (viable intrauterine) (n=15), evacuation of uterus for embryonic missed miscarriage (non-viable intrauterine) (n=10) and surgery for tubal ectopic pregnancy (n=15). INTERVENTIONS: Trophoblast was examined by immunohistochemistry and quantitative RT-PCR, and serum was analyzed by ELISA. RESULTS: PIGF was localized to the cytotrophoblast cells. Expression of PIGF mRNA was reduced in trophoblast isolated from women with ectopic compared to intrauterine pregnancies (P<0.05). Serum PIGF was undetectable in women with tubal ectopic pregnancies and reduced, or undetectable, in miscarriage compared to viable intrauterine pregnancies (P<0.01). CONCLUSIONS: Serum PIGF is a promising novel diagnostic biomarker for early pregnancy location and outcome, and large-scale studies are now required to determine its clinical utility

The Science of Mission Assurance

The intent of this article is to describe—and prescribe—a scientific frameworkfor assuring mission essential functions in a contested cyber environment.Such a framework has profound national security implicationsas the American military increasingly depends on cyberspace to executecritical mission sets. In setting forth this prescribed course of action, thearticle will first decompose information systems into atomic processesthat manipulate information at all six phases of the information lifecycle,then systematically define the mathematical rules that govern missionassurance

تأثير أخلاقيات العمل في تحسين الأداء التسويقي (دراسة ميدانية في المصارف الخاصة في محافظة اللاذقية)

هدفت الدراسة بشكل رئيس إِلى تحديد تأثير أخلاقيات العمل بأبعادها (الأمانة والاستقامة، النزاهة والشفافية، الاستقلالية والموضوعية) في تحسين الأداء التسويقي في المصارف الخاصة في محافظة اللَّاذقيَّة.  اتَّبعت الباحثة المنهج الوصفي التحليلي، ومجموعة طرائق منها الاعتماد على البيانات الثَّانوية، والأوليَّة من خلال استبانة تمَّ تصميمها، وتمَّ توزيعها على (120) مبحوث، استردت منها (115)، وكانت (99) استبانة صالحة للتَّحليل، وتكوَّن مجتمع البحث من كادر العاملين في المصارف الخاصة في محافظة اللاذقية، ثم تمَّ الاعتماد على برنامج الـــ SPSS كأداة لتحليل البيانات المتوَّفرة. توصلت الدراسة إلى وجود تأثير معنوي لأخلاقيات العمل في تحسين الأداء التسويقي للمصارف الخاصة في اللاذقية، ولا يتجنب العامل أي علاقات قد تبدو أنها تفقد الموضوعية والاستقلالية عند القيام بالأعمال، ولا يسعى المصرف باستمرار إلى الحفاظ على حصته السوقية وتوسيعها، ولا يسعى المصرف إلى زيادة مبيعاته من خلال استراتيجياته التسويقي

Augmenting existing deterioration indices with chest radiographs to predict clinical deterioration

IMPORTANCE: When hospitals are at capacity, accurate deterioration indices could help identify low-risk patients as potential candidates for home care programs and alleviate hospital strain. To date, many existing deterioration indices are based entirely on structured data from the electronic health record (EHR) and ignore potentially useful information from other sources. OBJECTIVE: To improve the accuracy of existing deterioration indices by incorporating unstructured imaging data from chest radiographs. DESIGN, SETTING, AND PARTICIPANTS: Machine learning models were trained to predict deterioration of patients hospitalized with acute dyspnea using existing deterioration index scores and chest radiographs. Models were trained on hospitalized patients without coronavirus disease 2019 (COVID-19) and then subsequently tested on patients with COVID-19 between January 2020 and December 2020 at a single tertiary care center who had at least one radiograph taken within 48 hours of hospital admission. MAIN OUTCOMES AND MEASURES: Patient deterioration was defined as the need for invasive or non-invasive mechanical ventilation, heated high flow nasal cannula, IV vasopressor administration or in-hospital mortality at any time following admission. The EPIC deterioration index was augmented with unstructured data from chest radiographs to predict risk of deterioration. We compared discriminative performance of the models with and without incorporating chest radiographs using area under the receiver operating curve (AUROC), focusing on comparing the fraction and total patients identified as low risk at different negative predictive values (NPV). RESULTS: Data from 6278 hospitalizations were analyzed, including 5562 hospitalizations without COVID-19 (training cohort) and 716 with COVID-19 (216 in validation, 500 in held-out test cohort). At a NPV of 0.95, the best-performing image-augmented deterioration index identified 49 more (9.8%) individuals as low-risk compared to the deterioration index based on clinical data alone in the first 48 hours of admission. At a NPV of 0.9, the EPIC image-augmented deterioration index identified 26 more individuals (5.2%) as low-risk compared to the deterioration index based on clinical data alone in the first 48 hours of admission. CONCLUSION AND RELEVANCE: Augmenting existing deterioration indices with chest radiographs results in better identification of low-risk patients. The model augmentation strategy could be used in the future to incorporate other forms of unstructured data into existing disease models