Faculty Bibliography

We sought to find clinical subtypes of posttraumatic stress disorder (PTSD) in veterans 6-10 years post-trauma exposure based on current symptom assessments and to examine whether blood biomarkers could differentiate them. Samples were males deployed to Iraq and Afghanistan studied by the PTSD Systems Biology Consortium: a discovery sample of 74 PTSD cases and 71 healthy controls (HC), and a validation sample of 26 PTSD cases and 36 HC. A machine learning method, random forests (RF), in conjunction with a clustering method, partitioning around medoids, were used to identify subtypes derived from 16 self-report and clinician assessment scales, including the clinician-administered PTSD scale for DSM-IV (CAPS). Two subtypes were identified, designated S1 and S2, differing on mean current CAPS total scores: S2 = 75.6 (sd 14.6) and S1 = 54.3 (sd 6.6). S2 had greater symptom severity scores than both S1 and HC on all scale items. The mean first principal component score derived from clinical summary scales was three times higher in S2 than in S1. Distinct RFs were grown to classify S1 and S2 vs. HCs and vs. each other on multi-omic blood markers feature classes of current medical comorbidities, neurocognitive functioning, demographics, pre-military trauma, and psychiatric history. Among these classes, in each RF intergroup comparison of S1, S2, and HC, multi-omic biomarkers yielded the highest AUC-ROCs (0.819-0.922); other classes added little to further discrimination of the subtypes. Among the top five biomarkers in each of these RFs were methylation, micro RNA, and lactate markers, suggesting their biological role in symptom severity.

BACKGROUND:Cystic fibrosis (CF) is a life-limiting genetic disease that causes chronic lung infections. We developed an internet-based decision aid (DA) to help patients with CF make better informed decisions regarding treatments and advance care planning. We built the DA around two major treatment decisions: whether to have a lung transplant and whether to agree to invasive mechanical ventilation (intubation). OBJECTIVE:This study aims to conduct usability testing of the InformedChoices CF DA among key stakeholder groups. METHODS:We performed a patient needs assessment using think-aloud usability testing with patients with CF, their surrogates, and CF clinicians. Think-aloud participants provided feedback while navigating the DA, and after viewing, they answered surveys. Transcripts from the think-aloud sessions and survey results were categorized into common, generalizable themes and optimizations for improving content, comprehension, and navigation. We assessed the ease of use of the DA (System Usability Scale) and also assessed the participants' perceptions regarding the overall tone, with an emphasis on emotional reactions to the DA content, level of detail, and usefulness of the information for making decisions about either intubation or lung transplantation, including how well they understood the information and were able to apply it to their own decision-making process. We also assessed the DA's ease of navigation, esthetics, and whether participants were able to complete a series of usability tasks (eg, locating specific information in the DA or using the interactive survival estimates calculator) to ensure that the website was easy to navigate during the clinic-based advance care planning discussions. RESULTS:A total of 12 participants from 3 sites were enrolled from March 9 to August 30, 2018, for the usability testing: 5 CF clinicians (mean age 48.2, SD 12.0 years), 5 adults with CF, and 2 family and surrogate caregivers of people with CF (mean age of CF adults and family and surrogate caregivers 38.8, SD 10.8 years). Among the 12 participants, the average System Usability Scale score for the DA was 88.33 (excellent). Think-aloud analysis identified 3 themes: functionality, visibility and navigation, and content and usefulness. Areas for improvement included reducing repetition, enhancing comprehension, and changing the flow. Several changes to improve the content and usefulness of the DA were recommended, including adding information about alternatives to childbearing, such as adoption and surrogacy. On the basis of survey responses, we found that the navigation of the site was easy for clinicians, patients, and surrogates who participated in usability testing. CONCLUSIONS:Usability testing revealed areas of potential improvement. Testing also yielded positive feedback, suggesting the DA's future success. Integrating changes before implementation should improve the DA's comprehension, navigation, and usefulness and lead to greater adoption.

BACKGROUND:-associated nephropathy currently exists. METHODS:-associated nephropathy in a future when treatment is available. A systematic literature search of the MEDLINE and Embase databases was conducted to identify relevant evidence published from January 1, 2009 to July 14, 2020. RESULTS:-associated nephropathy and on features of a successful education program to raise awareness among the patient community. The group also highlighted the unmet need for a specific treatment and agreed on best practice for management of these patients should a treatment become available. CONCLUSIONS:-associated nephropathy.

BACKGROUND:Chronic exposure to air pollutants is associated with increased risk of cardiovascular disease (CVD) among adults. However, little is known about how air pollution may affect the development of subclinical atherosclerosis in younger populations. Carotid artery intima-media thickness (CIMT) is a measure of subclinical atherosclerosis that provides insight into early CVD pathogenesis. METHODS:) by road class (modeled using the CALINE4 line source dispersion model). Traffic density was calculated within a 300-m residential buffer. RESULTS:exposure (β: 2.24 μm/yr, 95% CI: 0.84-3.63) and traffic density (β: 2.11 μm/yr, 95% CI: 0.79-3.43). Traffic exposures were also related to increases in attained CIMT in early adulthood. No associations of CIMT change or attained level were observed with ambient pollutants. CONCLUSIONS:exposure and traffic density in our study population. While these results must be cautiously interpreted given the limited sample size, the observed associations of traffic measures with CIMT suggest a need for future studies to more fully explore this relationship.

Big Events are periods during which abnormal large-scale events like war, economic collapse, revolts, or pandemics disrupt daily life and expectations about the future. They can lead to rapid change in health-related norms, beliefs, social networks and behavioural practices. The world is undergoing such Big Events through the interaction of COVID-19, a large economic downturn, massive social unrest in many countries, and ever-worsening effects of global climate change. Previous research, mainly on HIV/AIDS, suggests that the health effects of Big Events can be profound, but are contingent: Sometimes Big Events led to enormous outbreaks of HIV and associated diseases and conditions such as injection drug use, sex trading, and tuberculosis, but in other circumstances, Big Events did not do so. This paper discusses and presents hypotheses about pathways through which the current Big Events might lead to better or worse short and long term outcomes for various health conditions and diseases; considers how pre-existing societal conditions and changing 'pathway' variables can influence the impact of Big Events; discusses how to measure these pathways; and suggests ways in which research and surveillance might be conducted to improve human capacity to prevent or mitigate the effects of Big Events on human health.

COVID-19 RT-PCR employee-testing was implemented across NYU Langone. Over eight-weeks, 14,764 employees were tested: 33% of symptomatic employees, 8% of asymptomatic employees reporting COVID-19 exposure, 3% of employees returning to work were positive. Positivity rates declined over time possibly reflecting the importance of community transmission and efficacy of PPE.

BACKGROUND:The large-scale social distancing efforts to reduce SARS-CoV-2 transmission have dramatically changed human behaviors associated with traumatic injuries. Trauma centers have reported decreases in trauma volume, paralleled by changes in injury mechanisms. We aimed to quantify changes in trauma epidemiology at an urban Level I trauma center in a county that instituted one of the earliest shelter-in-place orders to inform trauma care during future pandemic responses. METHODS:A single-center interrupted time-series analysis was performed to identify associations of shelter-in-place with trauma volume, injury mechanisms, and patient demographics in San Francisco, California. To control for short-term trends in trauma epidemiology, weekly level data were analyzed 6 months before shelter-in-place. To control for long-term trends, monthly level data were analyzed 5 years before shelter-in-place. RESULTS:Trauma volume decreased by 50% in the week following shelter-in-place (p < 0.01), followed by a linear increase each successive week (p < 0.01). Despite this, trauma volume for each month (March-June 2020) remained lower compared with corresponding months for all previous 5 years (2015-2019). Pediatric trauma volume showed similar trends with initial decreases (p = 0.02) followed by steady increases (p = 0.05). Reductions in trauma volumes were due entirely to changes in nonviolent injury mechanisms, while violence-related injury mechanisms remained unchanged (p < 0.01). CONCLUSION:Although the shelter-in-place order was associated with an overall decline in trauma volume, violence-related injuries persisted. Delineating and addressing underlying factors driving persistent violence-related injuries during shelter-in-place orders should be a focus of public health efforts in preparation for future pandemic responses. LEVEL OF EVIDENCE:Epidemiological study, level III.