Faculty Bibliography

BACKGROUND:Bariatric procedures are safe and effective treatments for obesity, inducing rapid and sustained loss of excess body weight. Laparoscopic adjustable gastric banding (LAGB) is unique among bariatric interventions in that it is a reversible procedure in which normal gastrointestinal anatomy is maintained. Knowledge regarding how LAGB effects change at the metabolite level is limited. OBJECTIVES/OBJECTIVE:To delineate the impact of LAGB on fasting and postprandial metabolite responses using targeted metabolomics. SETTING/METHODS:Individuals undergoing LAGB at NYU Langone Medical Center were recruited for a prospective cohort study. METHODS:We prospectively analyzed serum samples from 18 subjects at baseline and 2 months after LAGB under fasting conditions and after a 1-hour mixed meal challenge. Plasma samples were analyzed on a reverse-phase liquid chromatography time-of-flight mass spectrometry metabolomics platform. The main outcome measure was their serum metabolite profile. RESULTS:We quantitatively detected over 4,000 metabolites and lipids. Metabolite levels were altered in response to surgical and prandial stimuli, and metabolites within the same biochemical class tended to behave similarly in response to either stimulus. Plasma levels of lipid species and ketone bodies were statistically decreased after surgery whereas amino acid levels were affected more by prandial status than surgical condition. CONCLUSIONS:Changes in lipid species and ketone bodies postoperatively suggest improvements in the rate and efficiency of fatty acid oxidation and glucose handling after LAGB. Further investigation is necessary to understand how these findings relate to surgical response, including long term weight maintenance, and obesity-related comorbidities such as dysglycemia and cardiovascular disease.

BACKGROUND:Little is known about the epidemiology of diagnosis in primary care. METHODS:A prospective observational cohort study was conducted of adults presenting between August and December 2018 to primary care clinics across two health systems with an undiagnosed medical problem. Primary outcomes were (1) likelihood of a definitive diagnosis by 12 months and (2) time to diagnosis. Multivariate logistic regression was used to assess for factors associated with the likelihood of reaching a diagnosis, and multivariable Cox regression was used to assess for factors associated with time to diagnosis. Bivariate models were used to explore unadjusted relationships between the cases' organ systems and likelihood of and time to diagnosis. RESULTS:Among 410 cases in a diverse patient population, 206 (50.2%) reached a final diagnosis within 12 months, with a median time to diagnosis of 5 days (interquartile range = 0-46). Among these cases, 32.4% reached a diagnosis within the first month. A majority of cases not diagnosed within a month of the first presentation remained undiagnosed at 12 months. The likelihood of diagnosis and time to diagnosis did not differ by clinician or patient characteristics, clinicians' level of diagnostic uncertainty, chronicity of the medical issue, or visit type. There were no significant associations between organ system and likelihood of time to diagnosis. CONCLUSION/CONCLUSIONS:Patients presenting with new or unresolved problems in ambulatory primary care often remain undiagnosed after a year. There were no provider or patient-level variables associated with such lack of diagnosis. The causes, contributors, and consequences of lack of timely diagnosis and potential solutions require further research.

OBJECTIVE:To evaluate whether children conceived using assisted reproductive technology (ART) or ovulation induction (OI) have greater cardiometabolic risk than children conceived without treatment. DESIGN/METHODS:Clinical assessments in 2018-2019 in the Upstate KIDS cohort. SETTING/METHODS:Clinical sites in New York. PATIENT(S)/METHODS:Three hundred thirty-three singletons and 226 twins from 448 families. INTERVENTION(S)/METHODS:Mothers reported their use of fertility treatment and its specific type at baseline and approximately 4 months after delivery. High validity of the self-reported use of ART was previously confirmed. The children were followed up from infancy through 8-10 years of age. A subgroup was invited to participate in clinic visits. MAIN OUTCOME MEASURE(S)/METHODS:The measurements of blood pressure (BP), arterial stiffness using pulse wave velocity, anthropometric measures, and body fat using bioelectrical impedance analysis were performed (n = 559). The levels of plasma lipids, C-reactive protein, and hemoglobin A1c were measured using blood samples obtained from 263 children. RESULT(S)/RESULTS:The average age of the children was 9.4 years at the time of the clinic visits Approximately 39% were conceived using fertility treatment (18% using ART and 21% using OI). Singletons conceived using fertility treatment (any type or using ART or OI specifically) did not statistically differ in systolic or diastolic BP, heart rate, or pulse wave velocity. Singletons conceived using OI were smaller than singletons conceived without treatment, but the average body mass index of the latter was higher (z-score: 0.41 [SD, 1.24]) than the national norms. Twins conceived using either treatment had lower BP than twins conceived without treatment. However, twins conceived using OI had significantly higher arterial stiffness (0.59; 95% CI, 0.03-1.15 m/s), which was attenuated after accounting for maternal BP (0.29; 95% CI, -0.03 to 0.46 m/s). Twins did not significantly differ in size or fat measures across the groups. The mode of conception was not associated with the levels of lipids, C-reactive protein, or glycosylated hemoglobin. CONCLUSION(S)/CONCLUSIONS:Clinical measures at the age of 9 years did not indicate greater cardiometabolic risk in children conceived using ART or OI compared with that in children conceived without treatment. CLINICAL TRIAL REGISTRATION NUMBER/BACKGROUND:ClinicalTrials.gov #NCT03106493.

BACKGROUND:There is pressing need to improve hospital-based addiction care. Various models for integrating substance use disorder care into hospital settings exist, but there is no framework for describing, selecting, or comparing models. We sought to fill that gap by constructing a taxonomy of hospital-based addiction care models based on scoping literature review and key informant interviews. METHODS:Methods included a scoping review of the literature on US hospital-based addiction care models and interventions for adults, published between January 2000 and July 2021. We conducted semi-structured interviews with 15 key informants experienced in leading, implementing, evaluating, andpracticing hospital-based addiction care to explore model characteristics, including their perceived strengths, limitations, and implementation considerations. We synthesized findings from the literature review and interviews to construct a taxonomy of model types. RESULTS:Searches identified 2,849 unique abstracts. Of these, we reviewed 280 full text articles, of which 76 were included in the final review. We added 8 references from reference lists and informant interviews, and 4 gray literature sources. We identified six distinct hospital-based addiction care models. Those classified as addiction consult models include (1) interprofessional addiction consult services, (2) psychiatry consult liaison services, and (3) individual consultant models. Those classified as practice-based models, wherein general hospital staff integrate addiction care into usual practice, include (4) hospital-based opioid treatment and (5) hospital-based alcohol treatment. The final type was (6) community-based in-reach, wherein community providers deliver care. Models vary in their target patient population, staffing, and core clinical and systems change activities. Limitations include that some models have overlapping characteristics and variable ways of delivering core components. DISCUSSION/CONCLUSIONS:A taxonomy provides hospital clinicians and administrators, researchers, and policy-makers with a framework to describe, compare, and select models for implementing hospital-based addiction care and measure outcomes.

Accumulating evidence suggests that maternal exposure to objectively stressful events and subjective distress during pregnancy may have intergenerational impacts on children's mental health, yet evidence is limited. In a multisite longitudinal cohort (N = 454), we used multi-variable linear regression models to evaluate the predictive value of exposure to stressful events and perceived distress in pregnancy for children's internalizing problems, externalizing problems, and adaptive skills at age 4. We also explored two- and three-way interactions between stressful events, distress, and child sex. Both objective and subjective maternal stress independently predicted children's behavior, with more stressful events and higher distress predicting more internalizing and externalizing problems and worse adaptability; stress types did not significantly interact. There was some evidence that more stressful events predicted higher externalizing behaviors only for girls. Three-way interactions were not significant. The current findings highlight the importance of considering the type of stress measurement being used (e.g., counts of objective event exposure or subjective perceptions), suggest prenatal stress effects may be transdiagnostic, and meet calls for rigor and reproducibility by confirming these independent main effects in a relatively large group of families across multiple U.S. regions. Results point to adversity prevention having a two-generation impact and that pre- and postnatal family-focused intervention targets may help curb the rising rates of children's mental health problems.

The use of social media continues to increase in health care and academia. Health care practice, particularly the oncologic field, is constantly changing because of new knowledge, evidence-based research, clinical trials, and government policies. Therefore, oncology trainees and professionals continue to strive to stay up-to-date with practice guidelines, research, and skills. Although social media as an educational and professional development tool is no longer completely new to medicine and has been embraced, it is still under-researched in terms of various outcomes. Social media plays several key roles in professional development and academic advancement. We reviewed the literature to evaluate how social media can be used for professional development and academic promotion of oncology professionals.

BACKGROUND AND AIMS:A recent trial reported that patients with peripheral artery disease (PAD) without coronary heart disease or stroke (CHD/stroke) had worse prognosis than those with CHD/stroke without PAD. However, community-based data are lacking. The purpose of this study was to compare mortality according to the status of PAD and CHD/stroke in the general population. METHODS:In 6780 participants (aged ≥40 years) from the National Health and Nutrition Examination Surveys 1999-2004, we compared mortality risk according to PAD (ankle-brachial index ≤0.9) and CHD/stroke (self-report) at baseline using the Kaplan-Meier method and multivariable Cox models accounting for sampling weights. RESULTS:The prevalence of having both PAD and CHD/stroke was 1.6%. The prevalence of PAD without CHD/stroke and CHD/stroke without PAD was 4.1% and 8.5%, respectively (85.8% without PAD or CHD/stroke). Over a median follow-up of 12.8 years, 21.2% died. Individuals with both PAD and CHD/stroke had the worst survival (25.5% at 12 years). Those with PAD without CHD/stroke had the second worst prognosis (47.7%), followed by those with CHD/stroke without PAD (53.2%) and those without CHD/stroke or PAD (87.2%). Adjusted hazard ratio of mortality was 2.70 (95% CI, 2.07-3.53) for PAD with CHD/stroke, 1.81 (1.54-2.12) in CHD/stroke without PAD, and 1.68 (1.35-2.08) in PAD without CHD/stroke vs. no CHD/stroke or PAD. CONCLUSIONS:In the US adults, PAD contributed to increased mortality in persons with and without CHD/stroke. The prognosis of PAD without CHD/stroke was no better than that of CHD/stroke without PAD. These results suggest the importance of recognizing the presence of PAD in the community.

The United States Preventive Services Task Force is perhaps America's best-known source of evidence-based medicine (EBM) recommendations. This paper reviews aspects of the history of one such recommendation-screening for colorectal cancer (CRC)-to explore how the Task Force evaluates the best available evidence to reach its conclusions.Although the Task Force initially believed there was inadequate evidence to recommend CRC screening in the 1980s, it later changed its mind. Indeed, by 2002, it was recommending screening colonoscopy for those aged 50 and older, "extrapolating" from the existing evidence as there were no randomized controlled trials of the procedure. By 2016, due in part to the use of an emerging analytic modality known as modeling, the Task Force supported four additional CRC screening tests that lacked randomized data. Among the reasons the Task Force gave for these decisions was the desire to improve adherence for a strategy-screening healthy, asymptomatic individuals-that it believed saved lives.During these same years, the Task Force diverged from other organizations by declining to advocate screening otherwise healthy Black patients earlier than age 50-despite the fact that such individuals had higher rates of CRC than the general population, higher mortality from the disease and earlier onset of the disease. In declining to extrapolate in this instance, the Task Force underscored the lack of reliable data that proved that the benefits of such testing would outweigh the harms.The history of CRC screening reminds us that scientific evaluation relies not only on methodological sophistication but also on a combination of intellectual, cognitive and social processes. General internists-and their patients-should realize that EBM recommendations are often not definitive but rather thoughtful data-based advice.

The quality of a cluster analysis of unlabeled units depends on the quality of the between units dissimilarity measures. Data dependent dissimilarity is more objective than data independent geometric measures such as Euclidean distance. As suggested by Breiman, many data driven approaches are based on decision tree ensembles, such as a random forest (RF), that produce a proximity matrix that can easily be transformed into a dissimilarity matrix. A RF can be obtained using labels that distinguish units with real data from units with synthetic data. The resulting dissimilarity matrix is input to a clustering program and units are assigned labels corresponding to cluster membership. We introduce a General Iterative Cluster (GIC) algorithm that improves the proximity matrix and clusters of the base RF. The cluster labels are used to grow a new RF yielding an updated proximity matrix which is entered into the clustering program. The process is repeated until convergence. The same procedure can be used with many base procedures such as the Extremely Randomized Tree ensemble. We evaluate the performance of the GIC algorithm using benchmark and simulated data sets. The properties measured by the Silhouette Score are substantially superior to the base clustering algorithm. The GIC package has been released in R: https://cran.r-project.org/web/packages/GIC/index.html.