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Concordance and Discordance in the Geographic Distribution of Childhood Obesity and Pediatric Type 2 Diabetes in New York City

Osorio, Marcela; Koziatek, Christian A; Gallagher, Mary Pat; Recaii, Jessie; Weinstein, Meryle; Thorpe, Lorna E; Elbel, Brian; Lee, David C
OBJECTIVE:s rates of childhood obesity and pediatric type 2 diabetes (T2D) increase, a better understanding is needed of how these two conditions relate, and which subgroups of children are more likely to develop diabetes with and without obesity. METHODS:To compare hotspots of childhood obesity and pediatric T2D in New York City, we performed geospatial clustering analyses on obesity estimates obtained from surveys of school-aged children and diabetes estimates obtained from healthcare claims data, from 2009-2013. Analyses were performed at the Census tract level. We then used multivariable regression analysis to identify sociodemographic and environmental factors associated with these hotspots. RESULTS:We identified obesity hotspots in Census tracts with a higher proportion of Black or Hispanic residents, with low median household income, or located in a food swamp. 51.1% of pediatric T2D hotspots overlapped with obesity hotspots. For pediatric T2D, hotspots were identified in Census tracts with a higher proportion of Black residents and a lower proportion of Hispanic residents. CONCLUSIONS:Non-Hispanic Black neighborhoods had a higher probability of being hotspots of both childhood obesity and pediatric type 2 diabetes. However, we identified a discordance between hotspots of childhood obesity and pediatric diabetes in Hispanic neighborhoods, suggesting either under-detection or under-diagnosis of diabetes, or that obesity may influence diabetes risk differently in these two populations. These findings warrant further investigation of the relationship between childhood obesity and pediatric diabetes among different racial and ethnic groups, and may help guide pediatric public health interventions to specific neighborhoods.
PMID: 32275954
ISSN: 1876-2867
CID: 4379092

A Case of COVID-19 Pneumonia in a Young Male with Full Body Rash as a Presenting Symptom

Hunt, Madison; Koziatek, Christian
BACKGROUND:In December 2019 the coronavirus disease of 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2, was identified in Wuhan, China. In the ensuing months, the COVID-19 pandemic has spread globally and case load is exponentially increasing across the United States. Emergency departments have adopted screening and triage procedures to identify potential cases and isolate them during evaluation. CASE PRESENTATION/METHODS:We describe a case of COVID-19 pneumonia requiring hospitalization that presented with fever and extensive rash as the primary presenting symptoms. Rash has only been rarely reported in COVID-19 patients, and has not been previously described.
PMID: 32282312
ISSN: 2474-252x
CID: 4401642

Hyperbaric oxygen therapy for COVID-19 patients with respiratory distress: treated cases versus propensity-matched controls

Gorenstein, Scott A; Castellano, Michael L; Slone, Eric S; Gillette, Brian; Liu, Helen; Alsamarraie, Cindy; Jacobson, Alan M; Wall, Stephen P; Adhikari, Samrachana; Swartz, Jordan L; McMullen, Jenica J S; Osorio, Marcela; Koziatek, Christian A; Lee, David C
Objective/UNASSIGNED:Given the high mortality and prolonged duration of mechanical ventilation of COVID-19 patients, we evaluated the safety and efficacy of hyperbaric oxygen for COVID-19 patients with respiratory distress. Methods/UNASSIGNED:This is a single-center clinical trial of COVID-19 patients at NYU Winthrop Hospital from March 31 to April 28, 2020. Patients in this trial received hyperbaric oxygen therapy at 2.0 atmospheres of pressure in monoplace hyperbaric chambers for 90 minutes daily for a maximum of five total treatments. Controls were identified using propensity score matching among COVID-19 patients admitted during the same time period. Using competing-risks survival regression, we analyzed our primary outcome of inpatient mortality and secondary outcome of mechanical ventilation. Results/UNASSIGNED:We treated 20 COVID-19 patients with hyperbaric oxygen. Ages ranged from 30 to 79 years with an oxygen requirement ranging from 2 to 15 liters on hospital days 0 to 14. Of these 20 patients, two (10%) were intubated and died, and none remain hospitalized. Among 60 propensity-matched controls based on age, sex, body mass index, coronary artery disease, troponin, D-dimer, hospital day, and oxygen requirement, 18 (30%) were intubated, 13 (22%) have died, and three (5%) remain hospitalized (with one still requiring mechanical ventilation). Assuming no further deaths among controls, we estimate that the adjusted subdistribution hazard ratios were 0.37 for inpatient mortality (p=0.14) and 0.26 for mechanical ventilation (p=0.046). Conclusion/UNASSIGNED:Though limited by its study design, our results demonstrate the safety of hyperbaric oxygen among COVID-19 patients and strongly suggests the need for a well-designed, multicenter randomized control trial.
PMID: 32931666
ISSN: 1066-2936
CID: 4591182

Improving the geographical precision of rural chronic disease surveillance by using emergency claims data: a cross-sectional comparison of survey versus claims data in Sullivan County, New York

Lee, David C; Feldman, Justin M; Osorio, Marcela; Koziatek, Christian A; Nguyen, Michael V; Nagappan, Ashwini; Shim, Christopher J; Vinson, Andrew J; Thorpe, Lorna E; McGraw, Nancy A
OBJECTIVES/OBJECTIVE:Some of the most pressing health problems are found in rural America. However, the surveillance needed to track and prevent disease in these regions is lacking. Our objective was to perform a comprehensive health survey of a single rural county to assess the validity of using emergency claims data to estimate rural disease prevalence at a sub-county level. DESIGN/METHODS:We performed a cross-sectional study of chronic disease prevalence estimates using emergency department (ED) claims data versus mailed health surveys designed to capture a substantial proportion of residents in New York's rural Sullivan County. SETTING/METHODS:Sullivan County, a rural county ranked second-to-last for health outcomes in New York State. PARTICIPANTS/METHODS:Adult residents of Sullivan County aged 25 years and older who responded to the health survey in 2017-2018 or had at least one ED visit in 2011-2015. OUTCOME MEASURES/METHODS:We compared age and gender-adjusted prevalence of hypertension, hyperlipidaemia, diabetes, cancer, asthma and chronic obstructive pulmonary disease/emphysema among nine sub-county areas. RESULTS:Our county-wide mailed survey obtained 6675 completed responses for a response rate of 30.4%. This sample represented more than 12% of the estimated 53 020 adults in Sullivan County. Using emergency claims data, we identified 34 576 adults from Sullivan County who visited an ED at least once during 2011-2015. At a sub-county level, prevalence estimates from mailed surveys and emergency claims data correlated especially well for diabetes (r=0.90) and asthma (r=0.85). Other conditions were not well correlated (range: 0.23-0.46). Using emergency claims data, we created more geographically detailed maps of disease prevalence using geocoded addresses. CONCLUSIONS:For select conditions, emergency claims data may be useful for tracking disease prevalence in rural areas and providing more geographically detailed estimates. For rural regions lacking robust health surveillance, emergency claims data can inform how to geographically target efforts to prevent chronic disease.
PMID: 31740475
ISSN: 2044-6055
CID: 4193142

Age Disparities Among Patients With Type 2 Diabetes and Associated Rates of Hospital Use and Diabetic Complications

Lee, David C; Young, Ta'Loria; Koziatek, Christian A; Shim, Christopher J; Osorio, Marcela; Vinson, Andrew J; Ravenell, Joseph E; Wall, Stephen P
INTRODUCTION/BACKGROUND:Although screening for diabetes is recommended at age 45, some populations may be at greater risk at earlier ages. Our objective was to quantify age disparities among patients with type 2 diabetes in New York City. METHODS:Using all-payer hospital claims data for New York City, we performed a cross-sectional analysis of patients with type 2 diabetes identified from emergency department visits during the 5-year period 2011-2015. We estimated type 2 diabetes prevalence at each year of life, the age distribution of patients stratified by decade, and the average age of patients by sex, race/ethnicity, and geographic location. RESULTS:We identified 576,306 unique patients with type 2 diabetes. These patients represented more than half of all people with type 2 diabetes in New York City. Patients in racial/ethnic minority groups were on average 5.5 to 8.4 years younger than non-Hispanic white patients. At age 45, type 2 diabetes prevalence was 10.9% among non-Hispanic black patients and 5.2% among non-Hispanic white patients. In our geospatial analyses, patients with type 2 diabetes were on average 6 years younger in hotspots of diabetes-related emergency department use and inpatient hospitalizations. The average age of patients with type 2 diabetes was also 1 to 2 years younger in hotspots of microvascular diabetic complications. CONCLUSION/CONCLUSIONS:We identified profound age disparities among patients with type 2 diabetes in racial/ethnic minority groups and in neighborhoods with poor health outcomes. The younger age of these patients may be due to earlier onset of diabetes and/or earlier death from diabetic complications. Our findings demonstrate the need for geographically targeted interventions that promote earlier diagnosis and better glycemic control.
PMID: 31370917
ISSN: 1545-1151
CID: 4011382

Associations between age disparities in type 2 diabetes and rates of diabetes-related hospital use and diabetic complications [Meeting Abstract]

Lee, D C; Young, T; Koziatek, C A; Shim, C J; Osorio, M; Vinson, A J; Ravenell, J; Wall, S P
Background: Current guidelines for diabetes screening start at age 45, but disparities in certain subgroups exist and poor diabetic outcomes are known to cluster in specific neighborhoods. The objective of this study was to quantify disparities in the age distribution of patients with type 2 diabetes by sex, race/ethnicity, and geographic location. We also studied how patient age relates to diabetes-related hospital use and development of diabetic complications.
Method(s): Using all-payer hospital claims data, we performed a cross-sectional analysis of patients with type 2 diabetes. Our study included patients in New York City as identified by geocoded home address. Patients aged 10 to 100 years old were identified as having type 2 diabetes based on diagnosis codes from emergency claims data from 2011-2015. Our main measures included the estimated prevalence of type 2 diabetes at each year of life, the age distribution of patients as stratified by decade, and the comparison of patient age in geographic hotspots of frequent diabetes-related hospital use and diabetic complications.
Result(s): We identified 576,306 unique patients diagnosed with type 2 diabetes, which represented over half of all cases in New York City. Minority subgroups were on average 5.5 to 8.4 years younger than non-Hispanic White patients. Males with type 2 diabetes were 2.6 years younger than females. At 45 years of age, the estimated prevalence of type 2 diabetes was 10.9% among Black patients compared to 5.2% among White patients. In our geospatial analyses, patients with type 2 diabetes were on average 5.9 years younger in hotspots of diabetes-related emergency department use and inpatient hospitalizations. The average age of patients with type 2 diabetes was 1.5 to 2.2 years younger in hotspots of microvascular diabetic complications.
Conclusion(s): We identified profound disparities in the age of patients with type 2 diabetes among minorities and in neighborhoods with poor health outcomes. The younger age of these patients may be due to earlier onset of diabetes and/or earlier death from diabetes-related complications. Our findings demonstrate the need for geographically targeted interventions that promote earlier diagnosis and better glycemic control to reduce disparities in diabetes burden. [Figure Presented] Age Distribution of Patients with Type 2 Diabetes by Race and Ethnicity
EMBASE:629001355
ISSN: 1525-1497
CID: 4053252

Implementing emergency department test result push notifications to decrease time to decision making [Meeting Abstract]

Swartz, Jordan; Koziatek, Christian; Iturrate, Eduardo; Levy-Lambert, Dina; Testa, Paul
Background: Emergency department (ED) care decisions often hinge on the result of a diagnostic test. Frequently there is a lag time between a test result becoming available for review, and physician decision-making based on that result. Push notifications to physician smartphones have demonstrated improvement in this lag time in chest pain patients, but have not been studied in other ED patients. We implemented a system by which ED providers can subscribe to electronic alerts when test results are available for review via a smartphone or smartwatch push notification, and hypothesized that this would reduce the time to make clinical decisions. Method(s): This was a retrospective, multicenter, observational study in three emergency departments of an urban health system. We assessed push notification impact on time to disposition or time to follow-up order in six clinical scenarios of interest: chest x-ray (CXR) to disposition, basic metabolic panel (BMP) to disposition, urinalysis (UA) to disposition, respiratory pathogen panel (RPP) to disposition, hemoglobin (Hb) to blood transfusion order, and D-dimer to computed tomography pulmonary angiography (CTPA) order. All adult ED patients during a one-year period of push notification availability were included in the study. The primary outcome was median time from result availability to disposition order or defined follow-up order. Median times with interquartile ranges were determined in each scenario and the Mann Whitney (Wilcoxon) test for unpaired data was used to determine statistical significance. Result(s): During the study period there were 6,115 push notifications from 4,183 eligible ED encounters (2.7% of all ED encounters). All six scenarios studied were associated with a decrease in median time from test result availability to patient disposition, or from test result availability to follow-up order, when push notifications were employed: CXR to disposition (24 minutes, p<0.01), BMP to disposition (12 minutes, p<0.01), UA to disposition (50 minutes, p<0.01), RPP to disposition (43 minutes, p<0.01), D-dimer to CTPA (8 minutes, p<0.01), Hb to blood transfusion (19 minutes, p=0.73). Conclusion(s): Implementation of a push notification system for test result availability in the ED was associated with a decrease in lag time between test result availability and physician decision-making
EMBASE:627695792
ISSN: 1553-2712
CID: 3967012

Experience with dalbavancin for cellulitis in the emergency department and emergency observation unit [Letter]

Koziatek, Christian; Mohan, Sanjay; Caspers, Christopher; Swaminathan, Anand; Swartz, Jordan
PMID: 29157791
ISSN: 1532-8171
CID: 2791382

Using Indirect Measures to Identify Geographic Hot Spots of Poor Glycemic Control: Cross-sectional Comparisons With an A1C Registry

Lee, David C; Jiang, Qun; Tabaei, Bahman P; Elbel, Brian; Koziatek, Christian A; Konty, Kevin J; Wu, Winfred Y
OBJECTIVE:Focusing health interventions in places with suboptimal glycemic control can help direct resources to neighborhoods with poor diabetes-related outcomes, but finding these areas can be difficult. Our objective was to use indirect measures versus a gold standard, population-based A1C registry to identify areas of poor glycemic control. RESEARCH DESIGN AND METHODS/METHODS:Census tracts in New York City were characterized by race, ethnicity, income, poverty, education, diabetes-related emergency visits, inpatient hospitalizations, and proportion of adults with diabetes having poor glycemic control, based on A1C >9.0% (75 mmol/mol). Hot spot analyses were then performed, using the Getis-Ord Gi* statistic for all measures. We then calculated the sensitivity, specificity, positive and negative predictive values, and accuracy of using the indirect measures to identify hot spots of poor glycemic control found using the A1C Registry data. RESULTS:Using A1C Registry data, we identified hot spots in 42.8% of 2,085 NYC census tracts analyzed. Hot spots of diabetes-specific inpatient hospitalizations, diabetes-specific emergency visits, and age-adjusted diabetes prevalence estimated from emergency department data, respectively, had 88.9, 89.6, and 89.5% accuracy for identifying the same hot spots of poor glycemic control found using A1C Registry data. No other indirect measure tested had accuracy >80% except for the proportion of minority residents, which was 86.2%. CONCLUSIONS:Compared with demographic and socioeconomic factors, health care utilization measures more accurately identified hot spots of poor glycemic control. In places without a population-based A1C Registry, mapping diabetes-specific health care utilization may provide actionable evidence for targeting health interventions in areas with the highest burden of uncontrolled diabetes.
PMCID:6014542
PMID: 29691230
ISSN: 1935-5548
CID: 3052352

Assessing the Reliability of Performing Citywide Chronic Disease Surveillance Using Emergency Department Data from Sentinel Hospitals

Lee, David C; Swartz, Jordan L; Koziatek, Christian A; Vinson, Andrew J; Athens, Jessica K; Yi, Stella S
Given the inequalities in the distribution of disease burden, geographically detailed methods of disease surveillance are needed to identify local hot spots of chronic disease. However, few data sources include the patient-level addresses needed to perform these studies. Given that individual hospitals would have access to this geographically granular data, this study assessed the reliability of estimating chronic disease prevalence using emergency department surveillance at specific hospitals. Neighborhood-level diabetes, hypertension, and asthma prevalence were estimated using emergency claims data from each individual hospital in New York City from 2009-2012. Estimates were compared to prevalence obtained from a traditional health survey. A multivariable analysis also was performed to identify which individual hospitals were more accurate at estimating citywide disease prevalence. Among 52 hospitals, variation was found in the accuracy of disease prevalence estimates using emergency department surveillance. Estimates at some hospitals, such as NYU Langone Medical Center, had strong correlations for all diseases studied (diabetes: 0.81, hypertension: 0.84, and asthma: 0.84). Hospitals with patient populations geographically distributed throughout New York City had better accuracy in estimating citywide disease prevalence. For diabetes and hypertension, hospitals with racial/ethnic patient distributions similar to Census estimates and higher fidelity of diagnosis coding also had more accurate prevalence estimates. This study demonstrated how citywide chronic disease surveillance can be performed using emergency data from specific sentinel hospitals. The findings may provide an alternative means of mapping chronic disease burden by using existing data, which may be critical in regions without resources for geographically detailed health surveillance.
PMCID:5709695
PMID: 28338425
ISSN: 1942-7905
CID: 2499662