Faculty Bibliography

OBJECTIVE:Examine factors impacting U.S. parents' intention to vaccinate their children against COVID-19. METHODS:Data were collected February-May 2021 from parents living in six geographically diverse locations. The COVID-19 Exposure and Family Impact Survey assessed perceived susceptibility and severity to adverse outcomes from the pandemic. Semi-structured interviews assessed perceptions about benefits and risks of vaccinating children. RESULTS:Fifty parents of 106 children (newborn-17 years) were included; half were Spanish-speaking and half English-speaking. 62% were hesitant about vaccinating their children against COVID-19. Efficacy and safety were the main themes that emerged: some parents perceived them as benefits while others perceived them as risks to vaccination. Parent hesitancy often relied on social media, and was influenced by narrative accounts of vaccination experiences. Many cited the lower risk of negative outcomes from COVID-19 among children, when compared with adults. Some also cited inaccurate and constantly changing information about COVID-19 vaccines. CONCLUSION/CONCLUSIONS:Main drivers of parent hesitancy regarding child COVID-19 vaccination include perceived safety and efficacy of the vaccines and lower severity of illness in children. PRACTICE IMPLICATIONS/CONCLUSIONS:Many vaccine-hesitant parents may be open to vaccination in the future and welcome additional discussion and data.

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:The prevalence of aortic valve calcification (AVC) increases with age. However, the sex-and race-specific burden of AVC and associated cardiovascular risk factors among adults ≥75 years are not well studied. METHODS:We calculated the sex-and race-specific burden of AVC among 2283 older Black and White adults (mean age:80.5 [SD:4.3] years) without overt coronary heart disease from the Atherosclerosis Risk in Communities Study who underwent non-contrast cardiac-gated CT-imaging at visit 7 (2018-2019). Using Poisson regression with robust variance, we calculated the adjusted prevalence ratios (aPR) of the association of AVC with cardiovascular risk factors. RESULTS:The overall AVC prevalence was 44.8%, with White males having the highest prevalence at 58.2%. The prevalence was similar for Black males (40.5%), White females (38.9%), and Black females (36.8%). AVC prevalence increased significantly with age among all race-sex groups. The probability of any AVC at age 80 years was 55.4%, 40.0%, 37.3%, and 36.2% for White males, Black males, White females, and Black females, respectively. Among persons with prevalent AVC, White males had the highest median AVC score (100.9 Agatston Units [AU]), followed by Black males (68.5AU), White females (52.3AU), and Black females (46.5AU). After adjusting for cardiovascular risk factors, Black males (aPR:0.53; 95%CI:0.33-0.83), White females (aPR:0.68; 95%CI:0.61-0.77), and Black females (aPR:0.49; 95%CI:0.31-0.77) had lower AVC prevalence compared to White males. In addition, systolic blood pressure, non-HDL-cholesterol, and lipoprotein (a) were independently associated with AVC, with no significant race/sex interactions. CONCLUSIONS:AVC, although highly prevalent, was not universally present in this cohort of older adults. White males had ∼50-60% higher prevalence than other race-sex groups. Moreover, cardiovascular risk factors measured in older age showed significant association with AVC.

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.