Faculty Bibliography

Rationale & Objectives/UNASSIGNED:Recent data demonstrate that center volume is not a factor in the outcomes of adult kidney transplant recipients. This study assessed whether center volume affects graft survival in pediatric patients who received a kidney transplant. Study Design/UNASSIGNED:Case-cohort study. Setting & Participants/UNASSIGNED:Kidney transplantation centers, recipients younger than 18 years. Results/UNASSIGNED: = 0.02. Although outcomes for deceased donor kidney recipients were similar in the 3 volume categories, outcomes in patients who received a living kidney donation were better in the high-volume centers. Low household income was associated with poorer outcomes. However, 3-year graft survival was similar in the 3 center volume categories in high and low mean household income states. Limitations/UNASSIGNED:Lack of information for complications and individual family household income of recipients. Conclusions/UNASSIGNED:Transplantation outcomes are worse in pediatric patients treated at lower-volume centers. The difference was more pronounced for patients receiving living versus deceased donor kidneys. The distribution of household income in pediatric transplant recipients may also be a factor that contributes to lower 3-year graft survival in low-volume centers.

PURPOSE:Cohort participants usually have lower mortality rates than nonparticipants, but it is unclear if this survival advantage decreases or increases as cohort studies age. METHODS:We used a 1975 private census of Washington County, Maryland, to compare mortality among cohort participants to nonparticipants for three cohorts, Campaign Against Cancer and Stroke (CLUE I), Campaign Against Cancer and Heart Disease (CLUE II), and Atherosclerosis Risk In Communities (ARIC) initiated in 1974, 1989, and 1986, respectively. We analyzed mortality risk using time-truncated Cox regression models. RESULTS:Participants had lower mortality risk in the first 10 years of follow-up compared with nonparticipants (fully adjusted average hazard ratio [95% confidence intervals] were 0.72 [0.68, 0.77] in CLUE I, 0.69 [0.65, 0.73] in CLUE II, and 0.74 [0.63, 0.86] in ARIC), which persisted over 20 years of follow-up (0.81 [0.78, 0.84] in CLUE I, 0.87 [0.84, 0.91] in CLUE II, and 0.90 [0.83, 0.97] in ARIC). This lower average hazard for mortality among participants compared with nonparticipants attenuated with longer follow-up (0.99 [0.96, 1.01] after 30+ years in CLUE I, 1.02 [0.99, 1.05] after 30 years in CLUE II, and 0.95 [0.89, 1.00] after 30+ years in ARIC). In ARIC, participants who did not attend visits had higher mortality, but those who did attend visits had similar mortality to the community. CONCLUSIONS:Our results suggest the volunteer selection for mortality in long-standing epidemiologic cohort studies often diminishes as the cohort ages.

OBJECTIVE:To explore the impact of an adapted goals-of-care communications skills workshop created for ED physicians from the physicians' perspective. METHODS:Semi-structured, one-on-one audio-recorded interviews lasting 30-60 min were conducted with twelve physicians who had completed the training workshop. Interviews explored the experience of undertaking the workshop, its impact on their clinical practice and their ability to teach new skills to other clinicians using learnt techniques. Descriptive content analysis was performed on interview transcripts. RESULTS:Participants reported positive experiences of the workshop. The analysis identified four main themes and ten subthemes dealing with workshop content and its impact on subsequent ED-based clinical practice. There were: 1) value and future improvements for the course; 2) value of the course to practice; 3) value of the course for teaching residents and 4) barriers to application of learning. Specifically recommended components include the use of mnemonics, mechanisms to introduce difficult conversations and a positive feedback environment. Participant-recommended refinements to the workshop included emphasising urgency, replicating the chaotic ED environment and expanding content to include more ED-focused goals-of-care discussions. CONCLUSION/CONCLUSIONS:A short, focused training workshop directed at improving palliative care communication skills among ED clinicians appears to be welcomed and useful.

Directed acyclic graphs (DAGs), a prominent tool for expressing assumptions in epidemiologic research, are most useful when the hypothetical data generating structure is correctly encoded. Understanding a study's data generating structure and translating that data structure into a DAG can be challenging, but these skills are often glossed over in training. Campbell and Stanley's framework for causal inference has been extraordinarily influential in social science training programs but has received less attention in epidemiology. Their work, along with subsequent revisions and enhancements based on practical experience conducting empirical studies, presents a catalog of 37 threats to validity describing reasons empirical studies may fail to deliver causal effects. We interpret most of these threats to study validity as suggestions for common causal structures. Threats are organized into issues of statistical conclusion validity, internal validity, construct validity, or external validity. To assist epidemiologists in drawing the correct DAG for their application, we map the correspondence between threats to validity and epidemiologic concepts that can be represented with DAGs. Representing these threats as DAGs makes them amenable to formal analysis with d-separation rules and breaks down cross-disciplinary language barriers in communicating methodologic issues.

The Association of Schools and Programs of Public Health convened a Task Force on Zero Tolerance of Harassment and Discrimination in 2019 to develop a policy statement and strategies for addressing harassment of all types in institutions offering public health education. We outline the premises and scholarly foundation for the development of the Statement of Commitment to Zero Tolerance of Harassment and Discrimination, the statement itself, and future plans for realizing the aspiration established in the statement. The development of this living document is predicated on the belief that it is the core responsibility of academic institutions to build the knowledge and that it is the responsibility of leaders, namely deans of schools of public health and directors of public health programs, to lead in building the shared knowledge and insist on the practices that create institutions for a better future free of harassment and discrimination. Our statement is informed by the knowledge that aggressions in the form of harassment and discrimination undermine the health and well-being of individuals, the public, and populations.

Impairments in both executive function and parent-child interactions are associated with child externalizing behavior, but few studies have tested the uniqueness of these associations in the first years of life. Addressing these gaps, the current study involved an international sample (N = 438; 218 boys) who, at 14 and 24 months, completed an innovative battery of executive function tasks and were filmed at home in dyadic interaction with their mothers, enabling detailed observational ratings of maternal support. In addition, parents rated infant temperament at 4 months and externalizing behavior at 14 and 24 months. Cross-lagged longitudinal analysis showed a unidirectional developmental association between executive function at 14 months and externalizing behavior at 24 months. In addition, infant negative affect moderated the inverse association between maternal support at 14 months and externalizing behavior at 24 months. The benefits of maternal support were only evident for children with low levels of negative affect in infancy. We discuss this finding in relation to theoretical models that highlight child effects (e.g., models of vantage sensitivity).

BACKGROUND:Internet data can be used to improve infectious disease models. However, the representativeness and individual-level validity of internet-derived measures are largely unexplored as this requires ground truth data for study. OBJECTIVE:This study sought to identify relationships between Web-based behaviors and/or conversation topics and health status using a ground truth, survey-based dataset. METHODS:This study leveraged a unique dataset of self-reported surveys, microbiological laboratory tests, and social media data from the same individuals toward understanding the validity of individual-level constructs pertaining to influenza-like illness in social media data. Logistic regression models were used to identify illness in Twitter posts using user posting behaviors and topic model features extracted from users' tweets. RESULTS:Of 396 original study participants, only 81 met the inclusion criteria for this study. Of these participants' tweets, we identified only two instances that were related to health and occurred within 2 weeks (before or after) of a survey indicating symptoms. It was not possible to predict when participants reported symptoms using features derived from topic models (area under the curve [AUC]=0.51; P=.38), though it was possible using behavior features, albeit with a very small effect size (AUC=0.53; P≤.001). Individual symptoms were also generally not predictable either. The study sample and a random sample from Twitter are predictably different on held-out data (AUC=0.67; P≤.001), meaning that the content posted by people who participated in this study was predictably different from that posted by random Twitter users. Individuals in the random sample and the GoViral sample used Twitter with similar frequencies (similar @ mentions, number of tweets, and number of retweets; AUC=0.50; P=.19). CONCLUSIONS:To our knowledge, this is the first instance of an attempt to use a ground truth dataset to validate infectious disease observations in social media data. The lack of signal, the lack of predictability among behaviors or topics, and the demonstrated volunteer bias in the study population are important findings for the large and growing body of disease surveillance using internet-sourced data.

BACKGROUND:Osteopenia is common in the elderly, increasing their risk of sustaining cervical fractures after ground level falls (GLFs). We sought to examine the incidence of blunt cerebrovascular injury (BCVI) and subsequent stroke in elderly GLF patients as compared with other higher injury mechanisms. MATERIALS AND METHODS/METHODS:The Trauma Quality Improvement Program database (2011-2016) was used to identify blunt trauma patients with isolated (other body region abbreviated injury scale <3) cervical spine (C1-C7) fractures. Patients were stratified into three groups: nonelderly patients (<65) with all mechanisms of injury, elderly patients (≥65) with GLF, and elderly patients with all other mechanism of injury. Multivariable logistic regression was used to determine predictors for BCVI, stroke, spinal cord injury, and acute kidney injury. RESULTS:Seventeen thousand six hundred twenty-eight patients with cervical spine injuries were identified. BCVI was highest in the <65 group (0.8%) and lowest in elderly patients with GLF (0.3%, P = 0.001). When controlling for other factors, elderly patients with GLF were less likely to sustain BCVI (adjusted odds ratio: 0.46, P = 0.03) but had comparable rates of stroke attributable to BCVI (18.2% versus 6.5%, P = 0.184) and comparable rate of acute kidney injury compared with elderly patients with other mechanism of injury. CONCLUSIONS:In elderly patients with isolated cervical spine fracture after GLF, BCVI occurs less frequently but is associated with a comparable rate of stroke as compared with other mechanisms. Low injury mechanism should not preclude BCVI screening in the presence of cervical spine fractures.

SARS-CoV-2 is the virus that causes coronavirus disease (COVID-19) which has reached pandemic levels resulting in significant morbidity and mortality affecting every inhabited continent. The large number of patients requiring intensive care threatens to overwhelm healthcare systems globally. Likewise, there is a compelling need for a COVID-19 disease severity test to prioritize care and resources for patients at elevated risk of mortality. Here, an integrated point-of-care COVID-19 Severity Score and clinical decision support system is presented using biomarker measurements of C-reactive protein (CRP), N-terminus pro B type natriuretic peptide (NT-proBNP), myoglobin (MYO), D-dimer, procalcitonin (PCT), creatine kinase-myocardial band (CK-MB), and cardiac troponin I (cTnI). The COVID-19 Severity Score combines multiplex biomarker measurements and risk factors in a statistical learning algorithm to predict mortality. The COVID-19 Severity Score was trained and evaluated using data from 160 hospitalized COVID-19 patients from Wuhan, China. Our analysis finds that COVID-19 Severity Scores were significantly higher for the group that died versus the group that was discharged with median (interquartile range) scores of 59 (40-83) and 9 (6-17), respectively, and area under the curve of 0.94 (95% CI 0.89-0.99). These promising initial models pave the way for a point-of-care COVID-19 Severity Score system to impact patient care after further validation with externally collected clinical data. Clinical decision support tools for COVID-19 have strong potential to empower healthcare providers to save lives by prioritizing critical care in patients at high risk for adverse outcomes.