Identification of gaps in the delivery of high-quality care of patients with eosinophilic esophagitis.

Quality indicators (QIs) are standardized metrics that can be used to quantify health care delivery and identify important areas for practice improvement. Nine QIs pertaining to the diagnosis and management of eosinophilic esophagitis (EoE) were recently established. We therefore aimed to identify existing gaps in care using these QIs. This is a retrospective, multicenter study utilizing recently established EoE QIs to evaluate practice patterns among adult gastroenterologists in the diagnosis and management of EoE. Three patient cohorts of 30 patients each presenting with dysphagia, food impaction, and new diagnosis of EoE, respectively, were obtained, yielding 120 patients per site to assess for every QI. Summary statistics were reported across two main themes: diagnosis and management. Subsequent analysis of gaps in care was then performed. The domain of diagnosis of EoE (QI 1 and 2) had the most notable gap in care with only 55% of the presenting patients undergoing appropriate evaluation for EoE. The domain of management of EoE had overall higher QI fulfillment-however it also contained significant intra-category variation in care. Notably, while 79% of patients had clinical follow-up within 1 year from remission, only 54% underwent surveillance endoscopy within 2 years of remission. In contrast, 100% of patients with symptomatic strictures independent of histologic response underwent endoscopic dilation (QI 4). Management approaches for EoE are evolving and variation in care delivery exists. We identified significant gaps in both diagnosis of EoE especially amongst patients presenting with index food impaction and long term management of EoE, when retrospectively evaluating care patterns using newly established QIs. This is the first study of its kind to utilize these previously established QIs to objectively identify care gaps that exist in EoE amongst several institutions. These findings also highlight the importance of QIs and standardization of management of complex chronic diseases like EoE to help bridge these gaps and provide a framework to measure adherence to these best practices.

How Do Presenting Symptoms and Outcomes Differ by Race/Ethnicity Among Hospitalized Patients With Coronavirus Disease 2019 Infection? Experience in Massachusetts.

BACKGROUND: Population-based literature suggests severe acute respiratory syndrome coronavirus 2 infection may disproportionately affect racial/ethnic minorities; however, patient-level observations of hospitalization outcomes by race/ethnicity are limited. Our aim in this study was to characterize coronavirus disease 2019 (COVID-19)-associated morbidity and in-hospital mortality by race/ethnicity. METHODS: This was a retrospective analysis of 9 Massachusetts hospitals including all consecutive adult patients hospitalized with laboratory-confirmed COVID-19. Measured outcomes were assessed and compared by patient-reported race/ethnicity, classified as white, black, Latinx, Asian, or other. Student t test, Fischer exact test, and multivariable regression analyses were performed. RESULTS: A total of 379 patients (aged 62.9 ± 16.5 years; 55.7% men) with confirmed COVID-19 were included (49.9% white, 13.7% black, 29.8% Latinx, 3.7% Asian), of which 376 (99.2%) were insured (34.3% private, 41.2% public, 23.8% public with supplement). Latinx patients were younger, had fewer cardiopulmonary disorders, were more likely to be obese, more frequently reported fever and myalgia, and had lower D-dimer levels compared with white patients (P < .05). On multivariable analysis controlling for age, gender, obesity, cardiopulmonary comorbidities, hypertension, and diabetes, no significant differences in in-hospital mortality, intensive care unit admission, or mechanical ventilation by race/ethnicity were found. Diabetes was a significant predictor for mechanical ventilation (odds ratio [OR], 1.89; 95% confidence interval [CI], 1.11-3.23), while older age was a predictor of in-hospital mortality (OR, 4.18; 95% CI, 1.94-9.04). CONCLUSIONS: In this multicenter cohort of hospitalized COVID-19 patients in the largest health system in Massachusetts, there was no association between race/ethnicity and clinically relevant hospitalization outcomes, including in-hospital mortality, after controlling for key demographic/clinical characteristics. These findings serve to refute suggestions that certain races/ethnicities may be biologically predisposed to poorer COVID-19 outcomes.

Predictors of Ustekinumab Failure in Crohn's Disease After Dose Intensification.

BACKGROUND: Many patients with Crohn's disease (CD) who lose response to the standard ustekinumab dose interval of every 8 weeks (q8w) undergo dose intensification to q4w or q6w. However, baseline factors that predict success or failure after dose intensification are unknown. We sought to identify predictors of failure of ustekinumab after dose intensification for patients with CD. METHODS: This was a retrospective cohort study of adult CD patients undergoing ustekinumab dose intensification at a tertiary referral center between January 1, 2016, and January 31, 2019. Electronic health records were reviewed to obtain patient demographics, CD history, and laboratory data. The primary outcome was failure to achieve corticosteroid-free remission (Harvey-Bradshaw Index <5) within 12 months after intensification. The secondary outcome assessed was time to new biologic therapy after dose intensification. We used multivariable logistic regression and Cox regression to identify predictors of these outcomes. RESULTS: We included 123 patients who underwent ustekinumab dose intensification to q4w (n = 64), q5w (n = 1), q6w (n = 55), or q7w (n = 3). Multivariable logistic regression demonstrated that perianal disease, Harvey-Bradshaw Index, and opioid use at time of intensification were associated with failure to achieve remission. Cox regression demonstrated that perianal disease and corticosteroid use at time of intensification were associated with shorter time to a new biologic. CONCLUSION: Perianal disease, Harvey-Bradshaw Index, current opioid use, and current corticosteroid use are associated with ustekinumab failure after dose intensification in CD. Larger, prospective studies are needed to corroborate these findings and guide therapeutic strategies for patients who lose response to standard ustekinumab dosing.

Development and external validation of a prediction risk model for short-term mortality among hospitalized U.S. COVID-19 patients: A proposal for the COVID-AID risk tool.

BACKGROUND: The 2019 novel coronavirus disease (COVID-19) has created unprecedented medical challenges. There remains a need for validated risk prediction models to assess short-term mortality risk among hospitalized patients with COVID-19. The objective of this study was to develop and validate a 7-day and 14-day mortality risk prediction model for patients hospitalized with COVID-19. METHODS: We performed a multicenter retrospective cohort study with a separate multicenter cohort for external validation using two hospitals in New York, NY, and 9 hospitals in Massachusetts, respectively. A total of 664 patients in NY and 265 patients with COVID-19 in Massachusetts, hospitalized from March to April 2020. RESULTS: We developed a risk model consisting of patient age, hypoxia severity, mean arterial pressure and presence of kidney dysfunction at hospital presentation. Multivariable regression model was based on risk factors selected from univariable and Chi-squared automatic interaction detection analyses. Validation was by receiver operating characteristic curve (discrimination) and Hosmer-Lemeshow goodness of fit (GOF) test (calibration). In internal cross-validation, prediction of 7-day mortality had an AUC of 0.86 (95%CI 0.74-0.98; GOF p = 0.744); while 14-day had an AUC of 0.83 (95%CI 0.69-0.97; GOF p = 0.588). External validation was achieved using 265 patients from an outside cohort and confirmed 7- and 14-day mortality prediction performance with an AUC of 0.85 (95%CI 0.78-0.92; GOF p = 0.340) and 0.83 (95%CI 0.76-0.89; GOF p = 0.471) respectively, along with excellent calibration. Retrospective data collection, short follow-up time, and development in COVID-19 epicenter may limit model generalizability. CONCLUSIONS: The COVID-AID risk tool is a well-calibrated model that demonstrates accuracy in the prediction of both 7-day and 14-day mortality risk among patients hospitalized with COVID-19. This prediction score could assist with resource utilization, patient and caregiver education, and provide a risk stratification instrument for future research trials.

Impact of chronic liver disease on outcomes of hospitalized patients with COVID-19: A multicentre United States experience.

Liver injury has been described with COVID-19, and early reports suggested 2%-11% of patients had chronic liver disease (CLD). In this multicentre retrospective study, we evaluated hospitalized adults with laboratory-confirmed COVID-19 and the impact of CLD on relevant clinical outcomes. Of 363 patients included, 19% had CLD, including 15.2% with NAFLD. Patients with CLD had longer length of stay. After controlling for age, gender, obesity, cardiac diseases, hypertension, hyperlipidaemia, diabetes and pulmonary disorders, CLD and NAFLD were independently associated with ICU admission ([aOR 1.77, 95% CI 1.03-3.04] and [aOR 2.30, 95% CI 1.27-4.17]) and mechanical ventilation ([aOR 2.08, 95% CI 1.20-3.60] and [aOR 2.15, 95% CI 1.18-3.91]). Presence of cirrhosis was an independent predictor of mortality (aOR 12.5, 95% CI 2.16-72.5). Overall, nearly one-fifth of hospitalized COVID-19 patients had CLD, which was associated with more critical illness. Future studies are needed to identify interventions to improve clinical outcomes.