Faculty Bibliography

BACKGROUND:Smoking cessation is the most effective means of slowing the decline of lung function associated with chronic obstructive pulmonary disease (COPD). While effective smoking cessation treatments are available, they are underutilized and nearly half of people with COPD continue to smoke. By addressing both nicotine and behavioral dependence, electronic cigarettes (EC) could help people with COPD reduce the harm of combustible cigarettes (CC) through reductions in number of Cigarettes per Day (CPD) or quitting CC completely. The purpose of this pilot study is to identify barriers and facilitators to the use of and assess the preliminary effectiveness of EC as a harm reduction strategy among people with COPD. METHODS:In an open-label two-arm randomized controlled trial pilot study, 60 patients identified as smokers with a COPD diagnosis via electronic health records from a large urban health center are randomized in a 1:1 ratio to either standard care [counseling + nicotine replacement therapy (NRT)] or counseling + EC. The NRT arm will receive nicotine patches and nicotine lozenges for 12 weeks. The EC arm will receive EC for 12 weeks. Both cohorts will receive counseling from a licensed mental health counselor. Using ecological momentary assessment, participants will report their use of CC in both arms and EC use in the EC arm daily via text message. Primary outcomes will be feasibility and acceptability of intervention, and secondary outcomes will be reduction in CPD and change in COPD symptoms as measured by COPD Assessment Tool (CAT) score at 12-weeks. EC displacement of CC. To explore attitudes towards the use of EC as a harm-reduction strategy for patients with COPD, interviews will be performed with a sample of participants from both study arms. DISCUSSION/CONCLUSIONS:Despite decades of availability of smoking cessation medications, nearly half of people with COPD still smoke. This study aims to address the unmet need for feasible and effective strategies for reducing CC use among those with COPD, which has the potential to significantly improve the health of people with COPD who smoke. Trial Registration ClinicalTrials.gov Identifier: NCT04465318.

While definitions vary, endocrine-disrupting chemicals (EDCs) have two fundamental features: their disruption of hormone function and their contribution to disease and disability. The unique vulnerability of children to low-level EDC exposures has eroded the notion that only the dose makes the thing a poison, requiring a paradigm shift in scientific and policy practice. In this review, we discuss the unique vulnerability of children as early as fetal life and provide an overview of epidemiological studies on programming effects of EDCs on neuronal, metabolic, and immune pathways as well as on endocrine, reproductive, and renal systems. Building on this accumulating evidence, we dispel and address existing myths about the health effects of EDCs with examples from child health research. Finally, we provide a list of effective actions to reduce exposure, and subsequent harm that are applicable to individuals, communities, and policy-makers. Expected final online publication date for the Annual Review of Pharmacology and Toxicology, Volume 62 is January 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Importance:Identifying which patients with COVID-19 are likely to benefit from COVID-19 convalescent plasma (CCP) treatment may have a large public health impact. Objective:To develop an index for predicting the expected relative treatment benefit from CCP compared with treatment without CCP for patients hospitalized for COVID-19 using patients' baseline characteristics. Design, Setting, and Participants:This prognostic study used data from the COMPILE study, ie, a meta-analysis of pooled individual patient data from 8 randomized clinical trials (RCTs) evaluating CCP vs control in adults hospitalized for COVID-19 who were not receiving mechanical ventilation at randomization. A combination of baseline characteristics, termed the treatment benefit index (TBI), was developed based on 2287 patients in COMPILE using a proportional odds model, with baseline characteristics selected via cross-validation. The TBI was externally validated on 4 external data sets: the Expanded Access Program (1896 participants), a study conducted under Emergency Use Authorization (210 participants), and 2 RCTs (with 80 and 309 participants). Exposure:Receipt of CCP. Main Outcomes and Measures:World Health Organization (WHO) 11-point ordinal COVID-19 clinical status scale and 2 derivatives of it (ie, WHO score of 7-10, indicating mechanical ventilation to death, and WHO score of 10, indicating death) at day 14 and day 28 after randomization. Day 14 WHO 11-point ordinal scale was used as the primary outcome to develop the TBI. Results:A total of 2287 patients were included in the derivation cohort, with a mean (SD) age of 60.3 (15.2) years and 815 (35.6%) women. The TBI provided a continuous gradation of benefit, and, for clinical utility, it was operationalized into groups of expected large clinical benefit (B1; 629 participants in the derivation cohort [27.5%]), moderate benefit (B2; 953 [41.7%]), and potential harm or no benefit (B3; 705 [30.8%]). Patients with preexisting conditions (diabetes, cardiovascular and pulmonary diseases), with blood type A or AB, and at an early COVID-19 stage (low baseline WHO scores) were expected to benefit most, while those without preexisting conditions and at more advanced stages of COVID-19 could potentially be harmed. In the derivation cohort, odds ratios for worse outcome, where smaller odds ratios indicate larger benefit from CCP, were 0.69 (95% credible interval [CrI], 0.48-1.06) for B1, 0.82 (95% CrI, 0.61-1.11) for B2, and 1.58 (95% CrI, 1.14-2.17) for B3. Testing on 4 external datasets supported the validation of the derived TBIs. Conclusions and Relevance:The findings of this study suggest that the CCP TBI is a simple tool that can quantify the relative benefit from CCP treatment for an individual patient hospitalized with COVID-19 that can be used to guide treatment recommendations. The TBI precision medicine approach could be especially helpful in a pandemic.

Importance:COVID-19 convalescent plasma (CCP) is a potentially beneficial treatment for COVID-19 that requires rigorous testing. Objective:To compile individual patient data from randomized clinical trials of CCP and to monitor the data until completion or until accumulated evidence enables reliable conclusions regarding the clinical outcomes associated with CCP. Data Sources:From May to August 2020, a systematic search was performed for trials of CCP in the literature, clinical trial registry sites, and medRxiv. Domain experts at local, national, and international organizations were consulted regularly. Study Selection:Eligible trials enrolled hospitalized patients with confirmed COVID-19, not receiving mechanical ventilation, and randomized them to CCP or control. The administered CCP was required to have measurable antibodies assessed locally. Data Extraction and Synthesis:A minimal data set was submitted regularly via a secure portal, analyzed using a prespecified bayesian statistical plan, and reviewed frequently by a collective data and safety monitoring board. Main Outcomes and Measures:Prespecified coprimary end points-the World Health Organization (WHO) 11-point ordinal scale analyzed using a proportional odds model and a binary indicator of WHO score of 7 or higher capturing the most severe outcomes including mechanical ventilation through death and analyzed using a logistic model-were assessed clinically at 14 days after randomization. Results:Eight international trials collectively enrolled 2369 participants (1138 randomized to control and 1231 randomized to CCP). A total of 2341 participants (median [IQR] age, 60 [50-72] years; 845 women [35.7%]) had primary outcome data as of April 2021. The median (IQR) of the ordinal WHO scale was 3 (3-6); the cumulative OR was 0.94 (95% credible interval [CrI], 0.74-1.19; posterior probability of OR <1 of 71%). A total of 352 patients (15%) had WHO score greater than or equal to 7; the OR was 0.94 (95% CrI, 0.69-1.30; posterior probability of OR <1 of 65%). Adjusted for baseline covariates, the ORs for mortality were 0.88 at day 14 (95% CrI, 0.61-1.26; posterior probability of OR <1 of 77%) and 0.85 at day 28 (95% CrI, 0.62-1.18; posterior probability of OR <1 of 84%). Heterogeneity of treatment effect sizes was observed across an array of baseline characteristics. Conclusions and Relevance:This meta-analysis found no association of CCP with better clinical outcomes for the typical patient. These findings suggest that real-time individual patient data pooling and meta-analysis during a pandemic are feasible, offering a model for future research and providing a rich data resource.

Purpose/UNASSIGNED:Growing evidence suggests that dendrite retraction or degeneration in a subpopulation of the retinal ganglion cells (RGCs) may precede detectable soma abnormalities and RGC death in glaucoma. Visualization of the lamellar structure of the inner plexiform layer (IPL) could advance clinical management and fundamental understanding of glaucoma. We investigated whether visible-light optical coherence tomography (vis-OCT) could detect the difference in the IPL sublayer thicknesses between small cohorts of healthy and glaucomatous subjects. Method/UNASSIGNED:We imaged nine healthy and five glaucomatous subjects with vis-OCT. Four of the healthy subjects were scanned three times each in two separate visits, and five healthy and five glaucoma subjects were scanned three times during a single visit. IPL sublayers were manually segmented using averaged A-line profiles. Results/UNASSIGNED:The mean ages of glaucoma and healthy subjects are 59.6 ± 13.4 and 45.4 ± 14.4 years (P = 0.02.) The visual field mean deviations (MDs) are -26.4 to -7.7 dB in glaucoma patients and -1.6 to 1.1 dB in healthy subjects (P = 0.002). Median coefficients of variation (CVs) of intrasession repeatability for the entire IPL and three sublayers are 3.1%, 5.6%, 6.9%, and 5.6% in healthy subjects and 1.8%, 6.0%, 7.7%, and 6.2% in glaucoma patients, respectively. The mean IPL thicknesses are 36.2 ± 1.5 µm in glaucomatous and 40.1 ± 1.7 µm in healthy eyes (P = 0.003). Conclusions/UNASSIGNED:IPL sublayer analysis revealed that the middle sublayer could be responsible for the majority of IPL thinning in glaucoma. Vis-OCT quantified IPL sublayers with good repeatability in both glaucoma and healthy subjects.

PURPOSE/OBJECTIVE:To outline a method for obtaining more accurate estimates of drug use in the United States (US) general population by correcting survey data for underreported and unknown drug use. METHODS:We simulated a population (n=100,000) reflecting the demographics of the US adult population per the 2018 American Community Survey. Within this population, we simulated the "true" and self-reported prevalence of past-month cannabis and cocaine use by using available estimates of underreporting. We applied our algorithm to samples of the simulated population to correct self-reported estimates and recover the "true" population prevalence, validating our approach. We applied this same method to 2018 National Survey on Drug Use and Health data to produce a range of underreporting-corrected estimates. RESULTS:Simulated self-report sensitivities varied by drug and sampling method (cannabis: 77.6-78.5%, cocaine: 14.3-22.1%). Across repeated samples, mean corrected prevalences (calculated by dividing self-reported prevalence by estimated sensitivity) closely approximated simulated "true" prevalences. Applying our algorithm substantially increased 2018 NSDUH estimates (self-report: cannabis=10.5%, cocaine=0.8%; corrected: cannabis=15.6-16.6%, cocaine=2.7-5.5%). CONCLUSION/CONCLUSIONS:National drug use prevalence estimates can be corrected for underreporting using a simple method. However, valid application of this method requires accurate data on the extent and correlates of misclassification in the general US population.

BACKGROUND:African American (AA) recipients of deceased-donor (DD) kidney transplants (KT) have shorter allograft survival than recipients of other ethnic groups. Reasons for this disparity encompass complex interactions between donors and recipients characteristics. METHODS:Outcomes from 3872 AA and 19,719 European American (EA) DDs who had one kidney transplanted in an AA recipient and one in an EA recipient were analyzed. Four donor/recipient pair groups (DRP) were studied, AA/AA, AA/EA, EA/AA, and EA/EA. Survival random forests and Cox proportional hazard models were fitted to rank and evaluate modifying effects of DRP on variables associated with allograft survival. These analyses sought to identify factors contributing to the observed disparities in transplant outcomes among AA and EA DDKT recipients. RESULTS:Transplant era, discharge serum creatinine, delayed graft function, and DRP were among the top predictors of allograft survival and mortality among DDKT recipients. Interaction effects between DRP with the kidney donor risk index and transplant era showed significant improvement in allograft survival over time in EA recipients. However, AA recipients appeared to have similar or poorer outcomes for DDKT performed after 2010 versus before 2001; allograft survival hazard ratios (95% CI) were 1.15 (0.74, 1.76) and 1.07 (0.8, 1.45) for AA/AA and EA/AA, compared to 0.62 (0.54, 0.71) and 0.5 (0.41, 0.62) for EA/EA and AA/EA DRP, respectively. Recipient mortality improved over time among all DRP, except unemployed AA/AAs. Relative to DDKT performed pre-2001, employed AA/AAs had HR = 0.37 (0.2, 0.69) versus 0.59 (0.31, 1.11) for unemployed AA/AA after 2010. CONCLUSION/CONCLUSIONS:Relative to DDKT performed before 2001, similar or worse overall DCAS was observed among AA/AAs, while EA/EAs experienced considerable improvement regardless of employment status, KDRI, and EPTS. AA recipients of an AA DDKT, especially if unemployed, had worse allograft survival and mortality and did not appear to benefit from advances in care over the past 20 years.

In this Ethics Rounds we present a conflict regarding discharge planning for a febrile infant in the emergency department. The physician believes discharge would be unsafe and would constitute a discharge against medical advice. The child's mother believes her son has been through an already extensive and painful evaluation and would prefer to monitor her well-appearing son closely at home with a safety plan and a next-day outpatient visit. Commentators assess this case from the perspective of best interest, harm-benefit, conflict management, and nondiscriminatory care principles and prioritize a high-quality informed consent process. They characterize the formalization of discharge against medical advice as problematic. Pediatricians, a pediatric resident, ethicists, an attorney, and mediator provide a range of perspectives to inform ethically justifiable options and conflict resolution practices.

Air quality management is increasingly focused not only on across-the-board reductions in ambient pollution concentrations but also on identifying and remediating elevated exposures that often occur in traditionally disadvantaged communities. Remote sensing of ambient air pollution using data derived from satellites has the potential to better inform management decisions that address environmental disparities by providing increased spatial coverage, at high-spatial resolutions, compared to air pollution exposure estimates based on ground-based monitors alone. Daily PM2.5 estimates for 2015"“2018 were estimated at a 1 km2 resolution, derived from NASA"™s Moderate Resolution Imaging Spectroradiometer (MODIS) satellite instrument and the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm in order to assess the utility of highly refined spatiotemporal air pollution data in 92 California cities and in the 13 communities included in the California Community Air Protection Program. The identification of pollution hot-spots within a city is typically not possible relying solely on the regulatory monitoring networks; however, day-to-day temporal variability was shown to be generally well represented by nearby ground-based monitoring data even in communities with strong spatial gradients in pollutant concentrations. An assessment of within-ZIP Code variability in pollution estimates indicates that high-resolution pollution estimates (i.e., 1 km2) are not always needed to identify spatial differences in exposure but become increasingly important for larger geographic areas (approximately 50 km2). Taken together, these findings can help inform strategies for use of remote sensing data for air quality management including the screening of locations with air pollution exposures that are not well represented by existing ground-based air pollution monitors.