Faculty Bibliography

BACKGROUND:Interprofessional education is increasingly recognized as essential for health education worldwide. Although effective management, innovation, and entrepreneurship are necessary to improve health systems, business schools have been underrepresented in global health education. Central America needs more health professionals trained in health management and innovation to respond to health disparities, especially in rural communities. OBJECTIVE:This paper explores the impact of the Health Innovation Fellowship (HIF), a new training program for practicing health professionals offered jointly by the Central American Healthcare Initiative and INCAE Business School, Costa Rica. Launched in 2014, HIF's goal is to create a network of highly trained interdisciplinary health professionals in competencies to improve health of Central American communities through better health management. METHODS:The program's fellows carried out innovative healthcare projects in their local regions. The first three annual cohorts (total of 43 fellows) represented all health-related professions and sectors (private, public, and civil society) from six Central American countries. All fellows attended four 1-week, on-site modular training sessions, received ongoing mentorship, and stayed connected through formal and informal networks and webinars through which they exchange knowledge and support each other. CAHI stakeholders supported HIF financially. RESULTS:Impact evaluation of the three-year pilot training program is positive: fellows improved their health management skills and more than 50% of the projects found either financial or political support for their implementation. CONCLUSIONS:HIF's strengths include that both program leaders and trainees come from the Global South, and that HIF offers a platform to collaborate with partners in the Global North. By focusing on promoting innovation and management at a top business school in the region, HIF constitutes a novel capacity-building effort within global health education. HIF is a capacity-building effort that can be scaled up in the region and other low- and middle-income countries.

Hepatitis C virus (HCV) infection is endemic in people who inject drugs (PWID), with prevalence estimates above 60% for PWID in the United States. Previous modeling studies suggest that direct acting antiviral (DAA) treatment can lower overall prevalence in this population, but treatment is often delayed until the onset of advanced liver disease (fibrosis stage 3 or later) due to cost. Lower cost interventions featuring syringe access (SA) and medically assisted treatment (MAT) have shown mixed results in lowering HCV rates below current levels. However. little is known about the potential cumulative effects of combining DAA and MAT treatment. While simulation experiments can reveal likely long-term effects, most prior simulations have been performed on closed populations of model agents-a scenario quite different from the open, mobile populations known to most health agencies. This paper uses data from the Centers for Disease Control's National HIV Behavioral Surveillance project, IDU round 3, collected in New York City in 2012 to parameterize simulations of open populations. To test the effect of combining DAA treatment with SA/MAT participation, multiple, scaled implementations of the two intervention strategies were simulated. Our results show that, in an open population, SA/MAT by itself has only small effects on HCV prevalence, while DAA treatment by itself can lower both HCV and HCV-related advanced liver disease prevalence. More importantly, the simulation experiments suggest that combinations of the two strategies can, when implemented together and at sufficient levels, dramatically reduce HCV incidence. We conclude that adopting SA/MAT implementations alongside DAA interventions can play a critical role in reducing the long-term consequences of ongoing HCV infection.

United States Veterans are at excess risk for type 2 diabetes, but population differentials in risk have not been characterized. We determined risk of type 2 diabetes in relation to prediabetes and dyslipidemic profiles in Veterans at the VA New York Harbor (VA NYHHS) during 2004-2014. Prediabetes was based on American Diabetes Association hemoglobin A1c (HbA1c) testing cut-points, one of several possible criteria used to define prediabetes. We evaluated transition to type 2 diabetes in 4,297 normoglycemic Veterans and 7,060 Veterans with prediabetes. Cox proportional hazards regression was used to relate HbA1c levels, lipid profiles, demographic, anthropometric and comorbid cardiovascular factors to incident diabetes (Hazard Ratio [HR] and 95% confidence intervals). Compared to normoglycemic Veterans (HbA1c: 5.0-5.6%; 31-38 mmol/mol), risks for diabetes were >2-fold in the moderate prediabetes risk group (HbA1c: 5.7-5.9%; 39-41 mmol/mol) (HR 2.37 [1.98-2.85]) and >5-fold in the high risk prediabetes group (HbA1c: 6.0-6.4%; 42-46 mmol/mol) (HR 5.59 [4.75-6.58]). Risks for diabetes were increased with elevated VLDL (≥40mg/dl; HR 1.31 [1.09-1.58]) and TG/HDL (≥1.5mg/dl; HR 1.34 [1.12-1.59]), and decreased with elevated HDL (≥35mg/dl; HR 0.80 [0.67-0.96]). Transition to diabetes in Veterans was related in age-stratified risk score analyses to HbA1c, VLDL, HDL and TG/HDL, BMI, hypertension and race, with 5-year risk differentials of 62% for the lowest (5-year risk, 13.5%) vs. the highest quartile (5-year risk, 21.9%) of the risk score. This investigation identified substantial differentials in risk of diabetes in Veterans, based on a readily-derived risk score suitable for risk stratification for type 2 diabetes prevention.

Introduction/UNASSIGNED:Biomarkers of metabolic syndrome expressed soon after World Trade Center (WTC) exposure predict development of WTC Lung Injury (WTC-LI). The metabolome remains an untapped resource with potential to comprehensively characterise many aspects of WTC-LI. This case-control study identified a clinically relevant, robust subset of metabolic contributors of WTC-LI through comprehensive high-dimensional metabolic profiling and integration of machine learning techniques. Methods/UNASSIGNED:Never-smoking, male, WTC-exposed firefighters with normal pre-9/11 lung function were segregated by post-9/11 lung function. Cases of WTC-LI (forced expiratory volume in 1s <lower limit of normal, n=15) and controls (n=15) were identified from previous cohorts. The metabolome of serum drawn within 6 months of 9/11 was quantified. Machine learning was used for dimension reduction to identify metabolites associated with WTC-LI. Results/UNASSIGNED:580 metabolites qualified for random forests (RF) analysis to identify a refined metabolite profile that yielded maximal class separation. RF of the refined profile correctly classified subjects with a 93.3% estimated success rate. 5 clusters of metabolites emerged within the refined profile. Prominent subpathways include known mediators of lung disease such as sphingolipids (elevated in cases of WTC-LI), and branched-chain amino acids (reduced in cases of WTC-LI). Principal component analysis of the refined profile explained 68.3% of variance in five components, demonstrating class separation. Conclusion/UNASSIGNED:Analysis of the metabolome of WTC-exposed 9/11 rescue workers has identified biologically plausible pathways associated with loss of lung function. Since metabolites are proximal markers of disease processes, metabolites could capture the complexity of past exposures and better inform treatment. These pathways warrant further mechanistic research.

 Obstructive sleep apnea (OSA) and Alzheimer's disease (AD) are highly prevalent conditions with growing impact on our aging society. While the causes of OSA are now better characterized, the mechanisms underlying AD are still largely unknown, challenging the development of effective treatments. Cognitive impairment, especially affecting attention and executive functions, is a recognized clinical consequence of OSA. A deeper contribution of OSA to AD pathogenesis is now gaining support from several lines of research. OSA is intrinsically associated with disruptions of sleep architecture, intermittent hypoxia and oxidative stress, intrathoracic and hemodynamic changes as well as cardiovascular comorbidities. All of these could increase the risk for AD, rendering OSA as a potential modifiable target for AD prevention. Evidence supporting the relevance of each of these mechanisms for AD risk, as well as a possible effect of AD in OSA expression, will be explored in this review.

BACKGROUND:The aim of this study is to determine the clinical characteristics and predictors of survival for patients with multiple metachronous esophageal tumors (MMET) and to compare the survival with patients that have single esophageal tumor (SET). METHOD:We identified all cases of primary esophageal cancer from the Surveillance, Epidemiology and End Results program database from 2000 to 2013. The primary outcome was the development of a second esophageal cancer six months after the diagnosis of the first tumor. A secondary outcome was disease-specific death from esophageal cancer. Chi-square test was used to compare the tumor and demographic characteristics of patients with SET versus the first and second tumor characteristics of patients with MMET. Logistic regression was used to obtain the odds ratios between patients with secondary tumors and those with primary tumors. Accelerated life model was performed for patients with MMET to determine the predictors of survival. RESULTS:Patients with MMET were more likely to have localized stage disease compared to those with SET (P < 0.0001). Distant stage disease for both first tumor (β = -0.402, P = 0.003) and second tumor (β = -0.301, P = 0.033) were predictors of increased mortality. The interval between the first and second tumor affected survival. Intervals of 2-5 years and > 5 years were associated with a reduced hazard with a β = 0.53 and 1.13, P < 0.0001, respectively. CONCLUSION:Early development of a second tumor in MMET is associated with poorer survival. Patients with MMET may benefit from regular follow-up and intervention to prevent the development of a second tumor.

Substantial effort has been devoted to explaining secular trends in childhood obesity and metabolic risks to unhealthy diet and physical activity. While some studies have suggested these factors may play a role in the obesity epidemic, even these studies have only been able to conclude that these factors have a moderate role. Given that a single-generation transformation in the human genome is even more unlikely to have transformed susceptibility to excess weight gain in early life, we are left with the reality that environmental influences represent important risks for obesity and dysmetabolism. In contrast to diet and physical activity, which can require intensive attention, effort and costs to modify through behavioral and other interventions, government action can fundamentally transform the environment and prevent disease and disability. The costs of regulations to limit environmental obesogens can also be much lower than the benefits to society.