Examining air pollution exposure dynamics in disadvantaged communities through high-resolution mapping.

This study bridges gaps in air pollution research by examining exposure dynamics in disadvantaged communities. Using cutting-edge machine learning and massive data processing, we produced high-resolution (100 meters) daily air pollution maps for nitrogen dioxide (NO2), fine particulate matter (PM2.5), and ozone (O3) across California for 2012-2019. Our findings revealed opposite spatial patterns of NO2 and PM2.5 to that of O3. We also identified consistent, higher pollutant exposure for disadvantaged communities from 2012 to 2019, although the most disadvantaged communities saw the largest NO2 and PM2.5 reductions and the advantaged neighborhoods experienced greatest rising O3 concentrations. Further, day-to-day exposure variations decreased for NO2 and O3. The disparity in NO2 exposure decreased, while it persisted for O3. In addition, PM2.5 showed increased day-to-day variations across all communities due to the increase in wildfire frequency and intensity, particularly affecting advantaged suburban and rural communities.

Organ Offer Review Cards: Improving Transparency on the Kidney Transplant Waitlist.

INTRODUCTION: The 2022 National Academy of Sciences, Engineering, and Medicine report on equity in organ transplantation highlighted limited transparency and accountability for organ offer declines and recommended prioritizing patient engagement in decisions regarding organ offers. Yet, there is no guidance on how to incorporate patients in organ offers. We elected to study the experiences of patients on the waitlist and their perception of a novel Organ Offer Review Card (OORC). METHODS: A prototype OORC was created using Donornet refusal codes. Sixty randomly selected kidney waitlist patients at a single center were asked to participate in a web-based survey focusing on current medical decision-making preferences and perceptions of the prototype OORC. RESULTS: Among the 43 patients reached, 17 (39.5%) completed the survey. Most participants (88.2%) expressed it was important to be involved in the decision-making about organ offers, with 100.0% of respondents wanting to know why an organ was declined. Regarding the prototype OORC, 94.1% thought it helped them understand the factors and priorities considered when selecting an organ, and 88.2% said it increased their belief that their team was acting in their best interest. CONCLUSION: An OORC could increase transparency and communication during the waitlist process while enhancing trust in the transplant team.

Health effects of air pollution on respiratory symptoms: A longitudinal study using digital health sensors.

Previous studies of air pollution and respiratory disease often relied on aggregated or lagged acute respiratory disease outcome measures, such as emergency department (ED) visits or hospitalizations, which may lack temporal and spatial resolution. This study investigated the association between daily air pollution exposure and respiratory symptoms among participants with asthma and chronic obstructive pulmonary disease (COPD), using a unique dataset passively collected by digital sensors monitoring inhaled medication use. The aggregated dataset comprised 456,779 short-acting beta-agonist (SABA) puffs across 3,386 people with asthma or COPD, between 2012 and 2019, across the state of California. Each rescue use was assigned space-time air pollution values of nitrogen dioxide (NO2), fine particulate matter with diameter ≤ 2.5 µm (PM2.5) and ozone (O3), derived from highly spatially resolved air pollution surfaces generated for the state of California. Statistical analyses were conducted using linear mixed models and random forest machine learning. Results indicate that daily air pollution exposure is positively associated with an increase in daily SABA use, for individual pollutants and simultaneous exposure to multiple pollutants. The advanced linear mixed model found that a 10-ppb increase in NO2, a 10 µg m-3 increase in PM2.5, and a 30-ppb increase in O3 were respectively associated with incidence rate ratios of SABA use of 1.025 (95 % CI: 1.013-1.038), 1.054 (95 % CI: 1.041-1.068), and 1.161 (95 % CI: 1.127-1.233), equivalent to a respective 2.5 %, 5.4 % and 16 % increase in SABA puffs over the mean. The random forest machine learning approach showed similar results. This study highlights the potential of digital health sensors to provide valuable insights into the daily health impacts of environmental exposures, offering a novel approach to epidemiological research that goes beyond residential address. Further investigation is warranted to explore potential causal relationships and to inform public health strategies for respiratory disease management.

Global Burden of Chronic Obstructive Pulmonary Disease Through 2050.

Importance: Chronic obstructive pulmonary disease (COPD) is a respiratory condition that is associated with significant health and economic burden worldwide. Previous studies assessed the global current-day prevalence of COPD, but to better facilitate resource planning and intervention development, long-term projections are needed. Objective: To assess the global burden of COPD through 2050, considering COPD risk factors. Design, Setting, and Participants: In this modeling study, historical data on COPD prevalence was extracted from a recent meta-analysis on 2019 global COPD prevalence, and 2010 to 2018 historical prevalence was estimated using random-effects meta-analytical models. COPD risk factor data were obtained from the Global Burden of Disease database. Main Outcomes and Measures: To project global COPD prevalence to 2050, generalized additive models were developed, including smoking prevalence, indoor and outdoor air pollution, and development indices as predictors, and stratified by age, sex, and World Bank region. Results: The models estimated that the number of COPD cases globally among those aged 25 years and older will increase by 23% from 2020 to 2050, approaching 600 million patients with COPD globally by 2050. Growth in the burden of COPD was projected to be the largest among women and in low- and middle-income regions. The number of female cases was projected to increase by 47.1% (vs a 9.4% increase for males), and the number of cases in low- and middle-income regions was expected to be more than double that of high-income regions by 2050. Conclusions and Relevance: In this modeling study of future COPD burden, projections indicated that COPD would continue to affect hundreds of millions of people globally, with disproportionate growth among females and in low-middle income regions through 2050. Further research, prevention, and advocacy are needed to address these issues so that adequate preparation and resource allocation can take place.

Prediction of short-acting beta-agonist usage in patients with asthma using temporal-convolutional neural networks.

Objective: Changes in short-acting beta-agonist (SABA) use are an important signal of asthma control and risk of asthma exacerbations. Inhaler sensors passively capture SABA use and may provide longitudinal data to identify at-riskpatients. We evaluate the performance of several ML models in predicting daily SABA use for participants with asthma and determine relevant features for predictive accuracy. Methods: Participants with self-reported asthma enrolled in a digital health platform (Propeller Health, WI), which included a smartphone application and inhaler sensors that collected the date and time of SABA use. Linear regression, random forests, and temporal convolutional networks (TCN) were applied to predict expected SABA puffs/person/day from SABA usage and environmental triggers. The models were compared with a simple baseline model using explained variance (R2), as well as using average precision (AP) and area under the receiving operator characteristic curve (ROC AUC) for predicting days with ≥1-10 puffs. Results: Data included 1.2 million days of data from 13 202 participants. A TCN outperformed other models in predicting puff count (R2 = 0.562) and day-over-day change in puff count (R2 = 0.344). The TCN predicted days with ≥10 puffs with an ROC AUC score of 0.952 and an AP of 0.762 for predicting a day with ≥1 puffs. SABA use over the preceding 7 days had the highest feature importance, with a smaller but meaningful contribution from air pollutant features. Conclusion: Predicted SABA use may serve as a valuable forward-looking signal to inform early clinical intervention and self-management. Further validation with known exacerbation events is needed.

Relationship between Self-reported Sleepiness and Positive Airway Pressure Treatment Adherence in Obstructive Sleep Apnea.

Rationale: Positive airway pressure (PAP) is the first-choice treatment for obstructive sleep apnea (OSA). However, its real-world effectiveness is often questioned because of usage issues. The relationship between patient sleepiness and PAP usage has been assessed in relatively small and selected populations within the research context. Objectives: To assess the impact of patient-reported sleep outcomes, particularly self-reported sleepiness and its change during therapy, on PAP usage in the real-world setting. Methods: Deidentified data for U.S.-based patients receiving PAP therapy were examined. Eligible patients were registered in the myAir app and provided self-reported sleepiness at baseline and after 7, 14, 21, and 28 days of PAP between November 2019 and April 2020. Results: A total of 95,397 registered patients met all eligibility criteria and were included in the analysis (mean age, 49.6 ± 13.0 yr; 61.6% male). Daytime sleepiness was the most common reason for PAP therapy initiation (57.1% of patients), and 42.2% of all patients had self-reported moderate to severe OSA. Self-reported sleepiness improved with PAP therapy in most patients over the assessment period, with 62.1% of patients reporting "no" or "slight" sleepiness at Day 28. There was a dose-dependent association between improvement in self-reported sleepiness at Day 28 and PAP usage, and this finding was maintained at Day 360. Self-reported sleepiness at Day 28 was associated with achieving U.S. Centers for Medicare & Medicaid Services compliance at 90 days (approximately 90% for those with no or slight sleepiness vs. <70% for those with residual very or extreme sleepiness); average daily PAP usage over 360 days was ⩾5.0 and ⩽3.7 hours, respectively, for those with no or slight versus very or extreme sleepiness. Conclusions: This study demonstrates the feasibility of capturing patient-reported outcomes via a digital platform. Patient-reported outcomes appear to be associated with PAP usage, especially self-reported sleepiness and its response to therapy. Capturing patient-reported outcomes using digital solutions during the course of treatment has the potential to enhance patient outcomes by providing actionable insights.

Retrospective assessment of a collaborative digital asthma program for Medicaid-enrolled children in southwest Detroit: reductions in short-acting beta-agonist (SABA) medication use.

BACKGROUND: Real-world evidence for digitally-supported asthma programs among Medicaid-enrolled children remains limited. Using data from a collaborative quality improvement program, we evaluated the impact of a digital intervention on asthma inhaler use among children in southwest Detroit. METHODS: Children (6-13 years) enrolled with Kids Health Connection (KHC), a program involving home visits with an asthma educator, were invited to participate in a digital self-management asthma program (Propeller Health). Patients were provided with a sensor to capture short-acting beta-agonist (SABA) medication use, and given access to a paired mobile app to track usage. Patients' healthcare providers and caregivers ("followers") were invited to view data as well. Retrospective paired t-tests assessed change in mean SABA use and SABA-free days (SFD) over time, and regressions explored the relationship between followers and medication use. RESULTS: Fifty-one patients were assessed. Mean program participation was nine months, and patients had on average 3 followers. From the first to last participation month, mean SABA use decreased from 0.68 to 0.25 puffs/day (p < 0.001), and mean SFD increased from 25.2 to 28.1 days/month (p < 0.001). 76% of patients had an increase in the number of SFD. There was a positive, but non-significant, relationship between the number of followers and reductions in SABA inhaler use. CONCLUSIONS: We observed a significant reduction in SABA inhaler use and an increase in the number of SABA-free days among Medicaid-enrolled children enrolled in a multi-modal digital asthma program.

Analysis of Donor Pancreata Defines the Transcriptomic Signature and Microenvironment of Early Neoplastic Lesions.

The adult healthy human pancreas has been poorly studied given the lack of indication to obtain tissue from the pancreas in the absence of disease and rapid postmortem degradation. We obtained pancreata from brain dead donors, thus avoiding any warm ischemia time. The 30 donors were diverse in age and race and had no known pancreas disease. Histopathologic analysis of the samples revealed pancreatic intraepithelial neoplasia (PanIN) lesions in most individuals irrespective of age. Using a combination of multiplex IHC, single-cell RNA sequencing, and spatial transcriptomics, we provide the first-ever characterization of the unique microenvironment of the adult human pancreas and of sporadic PanIN lesions. We compared healthy pancreata to pancreatic cancer and peritumoral tissue and observed distinct transcriptomic signatures in fibroblasts and, to a lesser extent, macrophages. PanIN epithelial cells from healthy pancreata were remarkably transcriptionally similar to cancer cells, suggesting that neoplastic pathways are initiated early in tumorigenesis. SIGNIFICANCE: Precursor lesions to pancreatic cancer are poorly characterized. We analyzed donor pancreata and discovered that precursor lesions are detected at a much higher rate than the incidence of pancreatic cancer, setting the stage for efforts to elucidate the microenvironmental and cell-intrinsic factors that restrain or, conversely, promote malignant progression. See related commentary by Hoffman and Dougan, p. 1288. This article is highlighted in the In This Issue feature, p. 1275.

"I Came up Short on the Academic Ladder": A Grounded Theory Study of Careerism in Academic Surgery.

OBJECTIVE: This study aims to explore the definition of career success in academic surgery. BACKGROUND: Career success in academic surgery is frequently defined as the achievement of a specific title, from full professor to department chair. This type of definition is convenient and established but potentially incomplete. The business literature has a more nuanced view of the relationship between titles and success, but this relationship has not been studied in medicine. METHODS: Semi-structured interviews were conducted from May to November 2020. Data were analyzed in an iterative fashion using grounded theory methodology to develop a conceptual model. RESULTS: We conducted 26 semi-structured interviews with practicing surgeons differing in years of experience; 12 (46%) participants were female, mean age of 48. Participants included 5 chairs of surgery, 6 division chiefs, and 7 past or current presidents of national societies. Four themes emerged on the importance of titles: Some study participants reported that (1) titles are a barometer of success; others argued that (2) titles are not a sufficient metric to define success; (3) titles are a means to an end; and (4) there is a desire to achieve the title of a respected mentor. CONCLUSIONS: As the definition of career success in academic surgery changes to encompass a broader range of interests and ambitions, the traditional markers of success must come into review. Academic surgeons see the value of titles as a marker of success and as a means to achieving other goals, but overwhelmingly our interviewees felt that titles were a double-edged sword and that a more inclusive definition of academic success was needed.

Successful living donor liver transplantation in a patient with hemophilia A and factor VIII inhibitor: A case report with perioperative recommendations.

Liver transplantation in patients with end-stage liver disease and coexisting hemophilia A has been described. Controversy exists over perioperative management of patients with factor VIII inhibitor predisposing patients to hemorrhage. We describe the case of a 58-year-old man with a history of hemophilia A and factor VIII inhibitor, eradicated with rituximab prior to living donor liver transplantation without recurrence of inhibitor. We also provide perioperative management recommendations from our successful multidisciplinary approach.

Analysis of donor pancreata defines the transcriptomic signature and microenvironment of early pre-neoplastic pancreatic lesions.

The adult healthy human pancreas has been poorly studied given lack of indication to obtain tissue from the pancreas in the absence of disease and rapid postmortem degradation. We obtained pancreata from brain dead donors thus avoiding any warm ischemia time. The 30 donors were diverse in age and race and had no known pancreas disease. Histopathological analysis of the samples revealed PanIN lesions in most individuals irrespective of age. Using a combination of multiplex immunohistochemistry, single cell RNA sequencing, and spatial transcriptomics, we provide the first ever characterization of the unique microenvironment of the adult human pancreas and of sporadic PanIN lesions. We compared healthy pancreata to pancreatic cancer and peritumoral tissue and observed distinct transcriptomic signatures in fibroblasts, and, to a lesser extent, macrophages. PanIN epithelial cells from healthy pancreata were remarkably transcriptionally similar to cancer cells, suggesting that neoplastic pathways are initiated early in tumorigenesis. Statement of significance: The causes underlying the onset of pancreatic cancer remain largely unknown, hampering early detection and prevention strategies. Here, we show that PanIN are abundant in healthy individuals and present at a much higher rate than the incidence of pancreatic cancer, setting the stage for efforts to elucidate the microenvironmental and cell intrinsic factors that restrain, or, conversely, promote, malignant progression.

Improvement in symptom-related disruptions is associated with fewer days of short-acting beta-agonist use in asthma.

Significant indirect healthcare costs are related to uncontrolled asthma, including productivity loss. Days with short-acting beta-agonist (SABA) use is associated with symptom-related disruptions at work, home, and school. Digital self-management platforms may support fewer days with SABA medication use and may reduce symptom-related disruptions.

Perceptions of Environmental Influence and Environmental Information-Seeking Behavior Among People With Asthma and COPD.

Environmental exposures and socioeconomic status (SES) are associated with asthma and chronic obstructive pulmonary disease (COPD) morbidity and mortality. Despite efforts to reduce the impact of environmental exposures through regulation and education, knowledge gaps remain. We sought to understand how adults with asthma and COPD perceive and seek information about environmental factors, and how these responses varied by disease or socioeconomic characteristics. Participants with self-reported asthma or COPD enrolled in a digital platform for respiratory disease self-management, consisting of sensors to track medication use and a companion smartphone app, completed an electronic survey exploring perceptions of environmental factors. Using mixed-method analyses, we evaluated differences in responses by disease (asthma vs. COPD), education (≤ vs. > some college), annual household income (< vs. ≥ $50,000), and mean annual residential air pollutant exposure (> vs. ≤80th percentile). Survey responses from 698 participants [500 asthma (72%) and 198 COPD (28%)] were analyzed. A high percentage of participants perceived that environmental factors could influence their symptoms, including: pollen (93% for asthma vs. 86% for COPD), mold (89 vs. 85%), second-hand smoke (89 vs. 83%), and air pollution (84% for both). Participants reported seeking environmental information daily from an average of three sources, preferring mobile apps and television (TV) programs. Significant differences were identified by disease. Conclusion: Participants with asthma and COPD perceive a relationship between their respiratory symptoms and their environment and regularly seek out environmental information. This information can help inform digital health development for respiratory education and self-management.

Disseminated Intravascular Coagulation During Induction Treatment With Rabbit-Derived Antithymocyte Globulin For Kidney Transplant.

Rabbit antithymocyte globulin is a lymphocytedepleting agent commonly used as induction therapy in kidney transplants. Although its use is generally safe and well tolerated, serious side effects can occur. Here, we describe a case of a severe immune complex hypersensitivity reaction with disseminated intravascular coagulation in response to rabbit antithymocyte globulin infusion. Immediate treatment required return to the operating room, massive transfusion of blood products, and plasmapheresis. The patient's posttransplant course was significant for volume overload, prolonged respiratory failure, and delayed graft function that required hemodialysis, but within 10 weeks the patient had made a full recovery and kidney allograft function had returned to normal.

Identifying impacts of air pollution on subacute asthma symptoms using digital medication sensors.

BACKGROUND: Objective tracking of asthma medication use and exposure in real-time and space has not been feasible previously. Exposure assessments have typically been tied to residential locations, which ignore exposure within patterns of daily activities. METHODS: We investigated the associations of exposure to multiple air pollutants, derived from nearest air quality monitors, with space-time asthma rescue inhaler use captured by digital sensors, in Jefferson County, Kentucky. A generalized linear mixed model, capable of accounting for repeated measures, over-dispersion and excessive zeros, was used in our analysis. A secondary analysis was done through the random forest machine learning technique. RESULTS: The 1039 participants enrolled were 63.4% female, 77.3% adult (>18) and 46.8% White. Digital sensors monitored the time and location of over 286 980 asthma rescue medication uses and associated air pollution exposures over 193 697 patient-days, creating a rich spatiotemporal dataset of over 10 905 240 data elements. In the generalized linear mixed model, an interquartile range (IQR) increase in pollutant exposure was associated with a mean rescue medication use increase per person per day of 0.201 [95% confidence interval (CI): 0.189-0.214], 0.153 (95% CI: 0.136-0.171), 0.131 (95% CI: 0.115-0.147) and 0.113 (95% CI: 0.097-0.129), for sulphur dioxide (SO2), nitrogen dioxide (NO2), fine particulate matter (PM2.5) and ozone (O3), respectively. Similar effect sizes were identified with the random forest model. Time-lagged exposure effects of 0-3 days were observed. CONCLUSIONS: Daily exposure to multiple pollutants was associated with increases in daily asthma rescue medication use for same day and lagged exposures up to 3 days. Associations were consistent when evaluated with the random forest modelling approach.

The relationship between objective app engagement and medication adherence in asthma and COPD: a retrospective analysis.

Digital health tools can promote disease self-management, but the association of smartphone app engagement and medication adherence is unclear. We assessed the relationship between objective smartphone app engagement and controller medication use in adults with asthma and COPD. We retrospectively analyzed data from participants enrolled in a digital self-management platform for asthma and COPD. Eligible adults had a smartphone and a paired electronic medication monitor (EMM). Longitudinal, mixed-effects logistic regressions estimated the relationship between daily app engagement (app opens, session duration) and daily controller medication use. Data from 2309 participants (71% asthma; 29% COPD) was analyzed. Opening the app (vs. not opening the app) was associated with significantly greater odds (OR (95% CI)) of using controller medications in asthma (2.08 (1.98, 2.19)) and COPD (1.61 (1.49, 1.75). Longer session duration was also associated with greater odds of using controller medications in asthma and COPD, but the odds of use attenuated with longer session duration in COPD. This study presents a novel assessment of the relationship between objectively-measured smartphone app engagement and controller medication use in asthma and COPD. Such insights may help develop targeted digital health tools and interventions.

Concurrent Improvement Observed in Patient-Reported Burden and Sensor-Collected Medication Use Among Patients Enrolled in a COPD Digital Health Program.

Background: The COPD assessment test (CAT) is an 8-item questionnaire widely used in clinical practice to assess patient burden of disease. Digital health platforms that leverage electronic medication monitors (EMMs) are used to track the time and date of maintenance and short-acting beta-agonist (SABA) inhaler medication use and record patient-reported outcomes. The study examined changes in CAT and SABA inhaler use in COPD to determine whether passively collected SABA and CAT scores changed in a parallel manner. Methods: Patients with self-reported COPD enrolled in a digital health program, which provided EMMs to track SABA and maintenance inhaler use, and a companion smartphone application ("app") to provide medication feedback and reminders. Patients completing the CAT questionnaire in the app at enrollment and at 6 months were included in the analysis. Changes in CAT burden category [by the minimally important difference (MID)] and changes in EMM-recorded mean SABA inhaler use per day were quantified at baseline and 6 months. Results: The analysis included 611 patients. At 6 months, mean CAT improved by -0.9 (95% CI: -1.4, -0.4; p < 0.001) points, and mean SABA use decreased by -0.6 (-0.8, -0.4; p < 0.001) puffs/day. Among patients with higher burden (CAT ≥ 21) at enrollment, CAT improved by -2.0 (-2.6, -1.4; p < 0.001) points, and SABA use decreased by -0.8 (-1.1, -0.6; p < 0.001) puffs/day. Conclusion: Significant and parallel improvement in CAT scores and SABA use at 6 months were noted among patients enrolled in a digital health program, with greater improvement for patients with higher disease burden.