Using network projections to explore co-incidence and context in large clinical datasets: Application to homelessness among U.S. Veterans

Backgrounds and perspectives of San Antonio street sleepers

Background

The question of what brings someone to homelessness and keeps them there has many varied and complex answers. The authors believe the answers lie within the persons experiencing homelessness (PEH).

Methods

This is an interpretive approach study based on convenience sampling of the San Antonio, TX, unsheltered population, utilizing semi-structured interviews from January 2022 through November 2022.

Results

The six most common themes that emerged from the subjects' backgrounds were 1) jail or prison time or other personally significant legal issues; 2) personal substance abuse or addiction struggles; 3) physical and mental health challenges as an adult; 4) disdain of shelters and preference for rough sleeping; 5) a problematic childhood; 6) did not enjoy school as a child or young adult.

Conclusion

To gain more insight into a situation as complex as the state of homelessness, researchers should meet with those on the frontline of this epidemic and hear first-hand their personal histories, challenges, successes, and suggestions. Though not a novel approach, the researchers found limited previous literature in regard to approach, scope and in relation of causation related to homelessness, especially about the U.S. unsheltered population. The ultimate goal is for such research to help guide outreach services and legislation related to PEH.

3D Cephalometric Normality Range: Auto Contractive Maps (ACM) Analysis in Selected Caucasian Skeletal Class I Age Groups

The objective of this paper is to define normal values of a novel 3D cephalometric analysis and to define the links through an artificial neural network (ANN). Methods: One hundred and fifteen CBCTs of Class I young patients, distributed among gender-adjusted developmental groups, were selected. Three operators identified 18 cephalometric landmarks from which 36 measurements were obtained. The repeatability was assessed through the ICC. Two-dimensional values were extracted by an automatic function, and the mean value and standard deviation were compared by paired Student’s t-tests. Correlation coefficient gave the relationships between 2D and 3D measurements for each group. The values were computed with the ANN to evaluate the parameters normality link and displayed by Pajek software. Results: The ICC assessed an excellent (≥0.9) repeatability. Normal values were extracted, and compared with 2D measurements, they showed a high correlation on the mid-sagittal plane, reaching 1.00, with the lowest 0.71 on the lateral plane. The ANN showed strong links between the values with the centrality of the go-sagittal plane compared to the rest. Conclusions: The study provides a set of 3D cephalometric values obtained by the upper and lower 95% CI for the mean divided into the developmental stage subgroups. The two-dimensional measurements showed variable concordance, while the ANN showed a centrality between the parameters.

Characterizing chronological accumulation of comorbidities in healthy veterans: a computational approach

Understanding patient accumulation of comorbidities can facilitate healthcare strategy and personalized preventative care. We applied a directed network graph to electronic health record (EHR) data and characterized comorbidities in a cohort of healthy veterans undergoing screening colonoscopy. The Veterans Affairs Cooperative Studies Program #380 was a prospective longitudinal study of screening and surveillance colonoscopy. We identified initial instances of three-digit ICD-9 diagnoses for participants with at least 5 years of linked EHR history (October 1999 to December 2015). For diagnoses affecting at least 10% of patients, we calculated pairwise chronological relative risk (RR). iGraph was used to produce directed graphs of comorbidities with RR > 1, as well as summary statistics, key diseases, and communities. A directed graph based on 2210 patients visualized longitudinal development of comorbidities. Top hub (preceding) diseases included ischemic heart disease, inflammatory and toxic neuropathy, and diabetes. Top authority (subsequent) diagnoses were acute kidney failure and hypertensive chronic kidney failure. Four communities of correlated comorbidities were identified. Close analysis of top hub and authority diagnoses demonstrated known relationships, correlated sequelae, and novel hypotheses. Directed network graphs portray chronologic comorbidity relationships. We identified relationships between comorbid diagnoses in this aging veteran cohort. This may direct healthcare prioritization and personalized care.