Identifying and Assisting Burn Patients and Their Families With Needs Through Administration of an Assessment Tool on Admission

Using a modified Safe Environment for Every Kid Questionnaire (Needs Survey), we previously showed a significant correlation between adverse childhood experiences (ACEs) and family needs. Herein, we retrospectively assessed whether patients' and their families' needs identified using the Needs Survey were addressed prior to discharge. We hypothesized that, without the knowledge gained by administering this tool, many basic needs may not have been fully addressed. Seventy-nine burn patients and families previously enrolled in our ACE studies were included. Answers to the Needs Surveys were reviewed to identify families with needs. Medical records were reviewed to determine if a social worker assessment (SWA) was completed per standard of care and if their needs were addressed prior to discharge. Of the 79 burn patients who received inpatient care and completed the Needs Survey, family needs were identified in 67 (84.8%); 42 (62.7%) received an SWA, and 25 (37.3%) did not. Those who did not receive a SWA had a shorter hospitalization and suffered less severe burns. Demographics, socioeconomics, ACEs, and identified needs were similar between the groups. Our study showed that SWA was performed on many patients with basic needs. However, with the focus of SWAs being on discharge arrangements, not all needs were addressed, and individualized resources were often not provided. Administering the Needs Survey on admission may help our social workers streamline and expedite this process to help support successful recovery for our burn patients and their families.

Congenital Human Cytomegalovirus Infection Is Associated With Decreased Transplacental IgG Transfer Efficiency Due to Maternal Hypergammaglobulinemia

BACKGROUND

Placentally transferred maternal immunoglobulin G (IgG) protects against pathogens in early life, yet vertically transmitted infections can interfere with transplacental IgG transfer. Although human cytomegalovirus (HCMV) is the most common placentally-transmitted viral infection worldwide, the impact of congenital HCMV (cCMV) infection on transplacental IgG transfer has been underexplored.

METHODS

We evaluated total and antigen-specific maternal and cord blood IgG levels and transplacental IgG transfer efficiency in a US-based cohort of 93 mother-infant pairs including 27 cCMV-infected and 66 cCMV-uninfected pairs, of which 29 infants were born to HCMV-seropositive nontransmitting mothers and 37 to HCMV-seronegative mothers. Controls were matched on sex, race/ethnicity, maternal age, and delivery year.

RESULTS

Transplacental IgG transfer efficiency was decreased by 23% (95% confidence interval [CI] 10-36%, P = .0079) in cCMV-infected pairs and 75% of this effect (95% CI 28-174%, P = .0085) was mediated by elevated maternal IgG levels (ie, hypergammaglobulinemia) in HCMV-transmitting women. Despite reduced transfer efficiency, IgG levels were similar in cord blood from infants with and without cCMV infection.

CONCLUSIONS

Our results indicate that cCMV infection moderately reduces transplacental IgG transfer efficiency due to maternal hypergammaglobulinemia; however, infants with and without cCMV infection had similar antigen-specific IgG levels, suggesting comparable protection from maternal IgG acquired via transplacental transfer.

Links Between Inflammation, Mood, and Physical Function Among Older Adults With HIV

OBJECTIVES

People living with human immunodeficiency virus (PLWH) treated with antiretrovirals have life spans similar to their HIV-negative peers. Yet, they experience elevated inflammation-related multimorbidity. Drawing on biopsychosocial determinants of health may inform interventions, but these links are understudied in older PLWH. We investigated cross-sectional relationships between psychosocial factors (mood, loneliness, and stigma), inflammatory markers, and age-related health outcomes among 143 PLWH aged 54-78 years.

METHOD

Participants provided blood samples for serum cytokine and C-reactive protein (CRP) analyses, completed surveys assessing psychosocial factors and health, and completed frailty assessments. Regression models tested relationships between key psychosocial-, inflammation, and age-related health variables, adjusting for relevant sociodemographic and clinical factors.

RESULTS

Participants with more depressive symptoms had higher composite cytokine levels than those with fewer depressive symptoms (β = 0.22, t(126) = 2.71, p = .008). Those with higher cytokine levels were more likely to be prefrail or frail (adjusted odds ratio = 1.72, 95% confidence interval = 1.01-2.93) and reported worse physical function (β = -0.23, t(129) = -2.64, p = .009) and more cognitive complaints (β = -0.20, t(129) = -2.16, p = .03) than those with lower cytokine levels. CRP was not significantly related to these outcomes; 6-month fall history was not significantly related to inflammatory markers.

DISCUSSION

Novel approaches are needed to manage comorbidities and maximize quality of life among older PLWH. Illustrating key expected biopsychosocial links, our findings highlight several factors (e.g., depressive symptoms, poorer physical function) that may share bidirectional relationships with chronic inflammation, a key factor driving morbidity. These links may be leveraged to modify factors that drive excessive health risk among older PLWH.

ReCiter: An open source, identity-driven, authorship prediction algorithm optimized for academic institutions

Academic institutions need to maintain publication lists for thousands of faculty and other scholars. Automated tools are essential to minimize the need for direct feedback from the scholars themselves who are practically unable to commit necessary effort to keep the data accurate. In relying exclusively on clustering techniques, author disambiguation applications fail to satisfy key use cases of academic institutions. Algorithms can perfectly group together a set of publications authored by a common individual, but, for them to be useful to an academic institution, they need to programmatically and recurrently map articles to thousands of scholars of interest en masse. Consistent with a savvy librarian’s approach for generating a scholar’s list of publications, identity-driven authorship prediction is the process of using information about a scholar to quantify the likelihood that person wrote certain articles. ReCiter is an application that attempts to do exactly that. ReCiter uses institutionally-maintained identity data such as name of department and year of terminal degree to predict which articles a given scholar has authored. To compute the overall score for a given candidate article from PubMed (and, optionally, Scopus), ReCiter uses: up to 12 types of commonly available, identity data; whether other members of a cluster have been accepted or rejected by a user; and the average score of a cluster. In addition, ReCiter provides scoring and qualitative evidence supporting why particular articles are suggested. This context and confidence scoring allows curators to more accurately provide feedback on behalf of scholars. To help users to more efficiently curate publication lists, we used a support vector machine analysis to optimize the scoring of the ReCiter algorithm. In our analysis of a diverse test group of 500 scholars at an academic private medical center, ReCiter correctly predicted 98% of their publications in PubMed.