Faculty Bibliography

Active-duty Army personnel can be exposed to traumatic warzone events and are at increased risk for developing post-traumatic stress disorder (PTSD) compared with the general population. PTSD is associated with high individual and societal costs, but identification of predictive markers to determine deployment readiness and risk mitigation strategies is not well understood. This prospective longitudinal naturalistic cohort study-the Fort Campbell Cohort study-examined the value of using a large multidimensional dataset collected from soldiers prior to deployment to Afghanistan for predicting post-deployment PTSD status. The dataset consisted of polygenic, epigenetic, metabolomic, endocrine, inflammatory and routine clinical lab markers, computerized neurocognitive testing, and symptom self-reports. The analysis was computed on active-duty Army personnel (N = 473) of the 101st Airborne at Fort Campbell, Kentucky. Machine-learning models predicted provisional PTSD diagnosis 90-180 days post deployment (random forest: AUC = 0.78, 95% CI = 0.67-0.89, sensitivity = 0.78, specificity = 0.71; SVM: AUC = 0.88, 95% CI = 0.78-0.98, sensitivity = 0.89, specificity = 0.79) and longitudinal PTSD symptom trajectories identified with latent growth mixture modeling (random forest: AUC = 0.85, 95% CI = 0.75-0.96, sensitivity = 0.88, specificity = 0.69; SVM: AUC = 0.87, 95% CI = 0.79-0.96, sensitivity = 0.80, specificity = 0.85). Among the highest-ranked predictive features were pre-deployment sleep quality, anxiety, depression, sustained attention, and cognitive flexibility. Blood-based biomarkers including metabolites, epigenomic, immune, inflammatory, and liver function markers complemented the most important predictors. The clinical prediction of post-deployment symptom trajectories and provisional PTSD diagnosis based on pre-deployment data achieved high discriminatory power. The predictive models may be used to determine deployment readiness and to determine novel pre-deployment interventions to mitigate the risk for deployment-related PTSD.

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We propose a randomized controlled trial to evaluate the effectiveness of a community health worker-led decision-coaching program to facilitate shared decision-making for prostate cancer screening decisions by Black men at a primary care federally qualified health center.

OBJECTIVES:To describe challenges and lessons learned in conducting a remote behavioral weight loss trial. METHODS:The Personal Diet Study is an ongoing randomized clinical trial which aims to compare two mobile health (mHealth) weight loss approaches, standardized diet vs. personalized feedback, on glycemic response. Over a six-month period, participants attended dietitian-led group meetings via remote videoconferencing and were encouraged to self-monitor dietary intake using a smartphone app. Descriptive statistics were used to report adherence to counseling sessions and self-monitoring. Challenges were tracked during weekly project meetings. RESULTS:Challenges in connecting to and engaging in the videoconferencing sessions were noted. To address these issues, we provided a step-by-step user manual and video tutorials regarding use of WebEx, encouraged alternative means to join sessions, and sent reminder emails/texts about the WebEx sessions and asking participants to join sessions early. Self-monitoring app-related issue included inability to find specific foods in the app database. To overcome this, the study team incorporated commonly consumed foods as "favorites" in the app database, provided a manual and video tutorials regarding use of the app and checked the self-monitoring app dashboard weekly to identify nonadherent participants and intervened as appropriate. Among 135 participants included in the analysis, the median attendance rate for the 14 remote sessions was 85.7% (IQR: 64.3%-92.9%). CONCLUSIONS:Experience and lessons shared in this report may provide critical and timely guidance to other behavioral researchers and interventionists seeking to adapt behavioral counseling programs for remote delivery in the age of COVID-19.

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BACKGROUND:Previous studies show that obesity predisposes patients to higher risks of adverse pregnancy outcomes. Data on the relationship between increasing degrees of obesity and risks of severe maternal morbidity, including mortality, are limited. OBJECTIVE:We examined the association of increasing classes of obesity, especially super obesity, with the risk of severe maternal morbidity and mortality at the time of delivery hospitalization. STUDY DESIGN:Using New York City linked birth certificates and hospital discharge data, we conducted a retrospective cohort study. This study identified delivery hospitalizations for singleton, live births in 2008-2012. Women were classified as having obesity (class I, II, III, or super obesity), as opposed to normal weight or overweight, based on prepregnancy body mass index. Cases of severe maternal morbidity were identified based on International Classification of Diseases, Ninth Revision diagnosis and procedure codes according to Centers for Disease Control and Prevention criteria. Multivariable logistic regression was used to evaluate the association between obesity classes and severe maternal morbidity, adjusting for maternal sociodemographic characteristics. RESULTS:During 2008-2012, there were 570,997 live singleton births with available information on prepregnancy body mass index that met all inclusion criteria. After adjusting for maternal characteristics, women with class II (adjusted odds ratio, 1.14; 95% confidence interval, 1.05-1.23), class III (adjusted odds ratio, 1.34; 95% confidence interval, 1.21-1.49), and super obesity (adjusted odds ratio, 1.99; 95% confidence interval, 1.57-2.54) were all significantly more likely to have severe maternal morbidity than normal and overweight women. Super obesity was associated with specific severe maternal morbidity indicators, including renal failure, air and thrombotic embolism, blood transfusion, heart failure, and the need for mechanical ventilation. CONCLUSION:There is a significant dose-response relationship between increasing obesity class and the risk of severe maternal morbidity at delivery hospitalization. The risks of severe maternal morbidity are highest for women with super obesity. Given that this is a modifiable risk factor, women with prepregnancy obesity should be counseled on the specific risks associated with pregnancy before conception to optimize their pregnancy outcomes.

CONTEXT/BACKGROUND:Clinical practice guideline (CPG) uptake does not occur spontaneously and requires active implementation, especially for long-term implementation. Social media (SoMe) with its power of rapid and global information exchange among physicians, patients, organizations, and stakeholders in the medical field can open up unprecedented opportunities for CPG dissemination. OBJECTIVE:The aim of this review was to assess the current use of SoMe in CPG dissemination across different medical specialties. EVIDENCE ACQUISITION/METHODS:A systematic review (SR) of the literature was conducted using Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines. Medline, Embase, and Cochrane databases and the general platform Google were searched for all relevant publications (no limitation for publication time and no language restrictions). The search revealed 1881 citations; following title and abstract review, 22 studies were identified; and five studies were finally included after full-text review. EVIDENCE SYNTHESIS/RESULTS:All included studies were published in the past 5 yr; there was a significant improvement in knowledge, awareness, compliance, and positive behavior toward CPGs with the use of SoMe dissemination compared with traditional methods. A large audience (healthcare professionals and patients) viewed and engaged with the SoMe process of CPG dissemination, and expressed an intent to engage in this method in the future. The studies included in the SR reported variable methods of SoMe use and similarly variable methods of analyzing the outcomes. CONCLUSIONS:Owing to the recent application of SoMe in the context of CPG dissemination, there is no standardized format for its use, and the data available are variable and limited. However, encouraging preliminary results have been reported using SoMe for CPG dissemination in multiple fields, and we have provided a pragmatic method of SoMe usage in CPG dissemination based on the review. It is vital to ensure a uniform method of application and assessment of SoMe use in CPG dissemination and implementation going forward. PATIENT SUMMARY/RESULTS:Social media (SoMe) plays an important role in rapid and global information exchange among physicians, patients, organizations, and stakeholders in the medical field, and its power can be harnessed in the dissemination of evidence-based clinical practice guidelines (CPGs) that guide clinicians in practice. Our review reveals that SoMe use for CPG dissemination is a relatively new concept published approximately 5 yr ago, and it has led to significant improvement in knowledge, awareness, compliance, and positive behavior with respect to the CPGs compared with traditional methods. A large audience (healthcare professionals and patients) viewed and engaged with the SoMe process. We have produced a pragmatic method of using SoMe in CPG dissemination. Considering the importance of CPGs in practice and the ever increasing role of SoMe in the medical profession, a new role for SoMe in CPG dissemination could be established.

BACKGROUND:Little is known about disparities in pain treatment associated with weight status despite prior research on weight-based discrepancies in other realms of healthcare and stigma among clinicians. OBJECTIVE:To investigate the association between weight status and the receipt of prescription analgesics in a nationally representative sample of adults with back pain, adjusting for the burden of pain. DESIGN/METHODS:Cross-sectional analyses using the Medical Expenditure Panel Survey (2010-2017). PARTICIPANTS/METHODS:Five thousand seven hundred ninety-one civilian adults age ≥ 18 with back pain. MAIN MEASURES/METHODS:We examine the odds of receiving prescription analgesics for back pain by weight status using logistic regression. We study the odds of receiving (1) any pain prescription, (2) three pain prescription categories (opioid only, non-opioid only, the combination of both), and (3) opioids conditional on having a pain prescription. KEY RESULTS/RESULTS:The odds of receiving pain prescriptions increase monotonically across weight categories, when going from normal weight to obesity II/III, despite adjustments for the burden of pain. Relative to normal weight, higher odds of receiving any pain prescription is associated with obesity I (OR = 1.30 [95% CI = 1.04-1.63]) and obesity II/III (OR = 1.72 [95% CI = 1.36-2.18]). Obesity II/III is also associated with higher odds of receiving opioids only (OR = 1.53 [95% CI = 1.16-2.02]), non-opioids only (OR = 1.77 [95% CI = 1.21-2.60]), and a combination of both (OR = 2.48 [95% CI = 1.44-4.29]). Obesity I is associated with increased receipt of non-opioids only (OR = 1.55 [95% CI = 1.07-2.23]). Conditional on having a pain prescription, the odds of receiving opioids are comparable across weight categories. CONCLUSIONS:This study suggests that, relative to those with normal weight, adults with obesity are more likely to receive prescription analgesics for back pain, despite adjustments of the burden of pain. Hence, the possibility of weight-based undertreatment is not supported. These findings are reassuring because individuals with obesity generally experience a higher prevalence of back pain. The possibility of over-treatment associated with obesity, however, may warrant further investigation.

BACKGROUND:Proteomic profiling may allow identification of plasma proteins that associate with subsequent changesin kidney function, elucidating biologic processes underlying the development and progression of CKD. METHODS:We quantified the association between 4877 plasma proteins and a composite outcome of ESKD or decline in eGFR by ≥50% among 9406 participants in the Atherosclerosis Risk in Communities (ARIC) Study (visit 3; mean age, 60 years) who were followed for a median of 14.4 years. We performed separate analyses for these proteins in a subset of 4378 participants (visit 5), who were followed at a later time point, for a median of 4.4 years. For validation, we evaluated proteins with significant associations (false discovery rate <5%) in both time periods in 3249 participants in the Chronic Renal Insufficiency Cohort (CRIC) and 703 participants in the African American Study of Kidney Disease and Hypertension (AASK). We also compared the genetic determinants of protein levels with those from a meta-analysis genome-wide association study of eGFR. RESULTS:-trace protein. Of these proteins, 12 were also significantly associated in CRIC, and nine were significantly associated in AASK. Higher levels of each protein associated with higher risk of 50% eGFR decline or ESKD. We found genetic evidence for a causal role for one protein, lectin mannose-binding 2 protein (LMAN2). CONCLUSIONS:Large-scale proteomic analysis identified both known and novel proteomic risk factors for eGFR decline.