Up-regulation of gasdermin C in mouse small intestine is associated with lytic cell death in enterocytes in worm-induced type 2 immunity.

"Taste-like" tuft cells in the intestine trigger type 2 immunity in response to worm infection. The secretion of interleukin-13 (IL-13) from type 2 innate lymphoid cells (ILC2) represents a key step in the tuft cell-ILC2 cell-intestinal epithelial cell circuit that drives the clearance of worms from the gut via type 2 immune responses. Hallmark features of type 2 responses include tissue remodeling, such as tuft and goblet cell expansion, and villus atrophy, yet it remains unclear if additional molecular changes in the gut epithelium facilitate the clearance of worms from the gut. Using gut organoids, we demonstrated that IL-4 and IL-13, two type 2 cytokines with similar functions, not only induced the classical type 2 responses (e.g., tuft cell expansion) but also drastically up-regulated the expression of gasdermin C genes (Gsdmcs). Using an in vivo worm-induced type 2 immunity model, we confirmed the up-regulation of Gsdmcs in Nippostrongylus brasiliensis-infected wild-type C57BL/6 mice. Consistent with gasdermin family members being principal effectors of pyroptosis, overexpression of Gsdmc2 in human embryonic kidney 293 (HEK293) cells triggered pyroptosis and lytic cell death. Moreover, in intestinal organoids treated with IL-4 or IL-13, or in wild-type mice infected with N. brasiliensis, lytic cell death increased, which may account for villus atrophy observed in worm-infected mice. Thus, we propose that the up-regulated Gsdmc family may be major effectors for type 2 responses in the gut and that Gsdmc-mediated pyroptosis may provide a conduit for the release of antiparasitic factors from enterocytes to facilitate the clearance of worms.

Defining Multiple Chronic Conditions for Quality Measurement.

BACKGROUND/OBJECTIVE: Patients with multiple chronic conditions (MCCs) are a critical but undefined group for quality measurement. We present a generally applicable systematic approach to defining an MCC cohort of Medicare fee-for-service beneficiaries that we developed for a national quality measure, risk-standardized rates of unplanned admissions for Accountable Care Organizations. RESEARCH DESIGN: To define the MCC cohort we: (1) identified potential chronic conditions; (2) set criteria for cohort conditions based on MCC framework and measure concept; (3) applied the criteria informed by empirical analysis, experts, and the public; (4) described "broader" and "narrower" cohorts; and (5) selected final cohort with stakeholder input. SUBJECTS: Subjects were patients with chronic conditions. Participants included 21.8 million Medicare fee-for-service beneficiaries in 2012 aged 65 years and above with ≥1 of 27 Medicare Chronic Condition Warehouse condition(s). RESULTS: In total, 10 chronic conditions were identified based on our criteria; 8 of these 10 were associated with notably increased admission risk when co-occurring. A broader cohort (2+ of the 8 conditions) included 4.9 million beneficiaries (23% of total cohort) with an admission rate of 70 per 100 person-years. It captured 53% of total admissions. The narrower cohort (3+ conditions) had 2.2 million beneficiaries (10%) with 100 admissions per 100 person-years and captured 32% of admissions. Most stakeholders viewed the broader cohort as best aligned with the measure concept. CONCLUSIONS: By systematically narrowing chronic conditions to those most relevant to the outcome and incorporating stakeholder input, we defined an MCC admission measure cohort supported by stakeholders. This approach can be used as a model for other MCC outcome measures.

Differences in Colonoscopy Quality Among Facilities: Development of a Post-Colonoscopy Risk-Standardized Rate of Unplanned Hospital Visits.

BACKGROUND & AIMS: Colonoscopy is a common procedure, yet little is known about variations in colonoscopy quality among outpatient facilities. We developed an outcome measure to profile outpatient facilities by estimating risk-standardized rates of unplanned hospital visits within 7 days of colonoscopy. METHODS: We used a 20% sample of 2010 Medicare outpatient colonoscopy claims (331,880 colonoscopies performed at 8140 facilities) from patients ≥65 years or older, and developed a patient-level logistic regression model to estimate the risk of unplanned hospital visits (ie, emergency department visits, observation stays, and inpatient admissions) within 7 days of colonoscopy. We then used the patient-level risk model variables and hierarchical logistic regression to estimate facility rates of risk-standardized unplanned hospital visits using data from the Healthcare Cost and Utilization Project (325,811 colonoscopies at 992 facilities), from 4 states containing 100% of colonoscopies per facility. RESULTS: Outpatient colonoscopies were followed by 5412 unplanned hospital visits within 7 days (16.3/1000 colonoscopies). Hemorrhage, abdominal pain, and perforation were the most common causes of unplanned hospital visits. Fifteen variables were independently associated with unplanned hospital visits (c = 0.67). A history of fluid and electrolyte imbalance (odds ratio [OR] = 1.43; 95% confidence interval [CI]: 1.29-1.58), psychiatric disorders (OR = 1.34; 95% CI: 1.22-1.46), and, in the absence of prior arrhythmia, increasing age past 65 years (aged >85 years vs 65-69 years: OR = 1.87; 95% CI: 1.54-2.28) were most strongly associated. The facility risk-standardized unplanned hospital visits calculated using Healthcare Cost and Utilization Project data showed significant variation (median 12.3/1000; 5th-95th percentile, 10.5-14.6/1000). Median risk-standardized unplanned hospital visits were comparable between ambulatory surgery centers and hospital outpatient departments (each was 10.2/1000), and ranged from 16.1/1000 in the Northeast to 17.2/1000 in the Midwest. CONCLUSIONS: We calculated a risk-adjusted measure of outpatient colonoscopy quality, which shows important variation in quality among outpatient facilities. This measure can make transparent the extent to which patients require follow-up hospital care, help inform patient choices, and assist in quality-improvement efforts.

Risk-standardized Acute Admission Rates Among Patients With Diabetes and Heart Failure as a Measure of Quality of Accountable Care Organizations: Rationale, Methods, and Early Results.

BACKGROUND: Population-based measures of admissions among patients with chronic conditions are important quality indicators of Accountable Care Organizations (ACOs), yet there are challenges in developing measures that enable fair comparisons among providers. METHODS: On the basis of consensus standards for outcome measure development and with expert and stakeholder input on methods decisions, we developed and tested 2 models of risk-standardized acute admission rates (RSAARs) for patients with diabetes and heart failure using 2010-2012 Medicare claims data. Model performance was assessed with deviance R; score reliability was tested with intraclass correlation coefficient. We estimated RSAARs for 114 Shared Savings Program ACOs in 2012 and we assigned ACOs to 3 performance categories: no different, worse than, and better than the national rate. RESULTS: The diabetes and heart failure cohorts included 6.5 and 2.6 million Medicare Fee-For-Service beneficiaries aged 65 years and above, respectively. Risk-adjustment variables were age, comorbidities, and condition-specific severity variables, but not socioeconomic status or other contextual factors. We selected hierarchical negative binomial models with the outcome of acute, unplanned hospital admissions per 100 person-years. For the diabetes and heart failure measures, respectively, the models accounted for 22% and 12% of the deviance in outcomes and score reliability was 0.89 and 0.81. For the diabetes measure, 51 (44.7%) ACOs were no different, 45 (39.5%) were better, and 18 (15.8%) were worse than the national rate. The distribution of performance for the heart failure measure was 61 (53.5%), 37 (32.5%), and 16 (14.0%), respectively. CONCLUSION: Measures of RSAARs for patients with diabetes and heart failure meet criteria for scientific soundness and reveal important variation in quality across ACOs.

Development of a Hospital Outcome Measure Intended for Use With Electronic Health Records: 30-Day Risk-standardized Mortality After Acute Myocardial Infarction.

BACKGROUND: Electronic health records (EHRs) offer the opportunity to transform quality improvement by using clinical data for comparing hospital performance without the burden of chart abstraction. However, current performance measures using EHRs are lacking. METHODS: With support from the Centers for Medicare & Medicaid Services (CMS), we developed an outcome measure of hospital risk-standardized 30-day mortality rates for patients with acute myocardial infarction for use with EHR data. As no appropriate source of EHR data are currently available, we merged clinical registry data from the Action Registry-Get With The Guidelines with claims data from CMS to develop the risk model (2009 data for development, 2010 data for validation). We selected candidate variables that could be feasibly extracted from current EHRs and do not require changes to standard clinical practice or data collection. We used logistic regression with stepwise selection and bootstrapping simulation for model development. RESULTS: The final risk model included 5 variables available on presentation: age, heart rate, systolic blood pressure, troponin ratio, and creatinine level. The area under the receiver operating characteristic curve was 0.78. Hospital risk-standardized mortality rates ranged from 9.6% to 13.1%, with a median of 10.7%. The odds of mortality for a high-mortality hospital (+1 SD) were 1.37 times those for a low-mortality hospital (-1 SD). CONCLUSIONS: This measure represents the first outcome measure endorsed by the National Quality Forum for public reporting of hospital quality based on clinical data in the EHR. By being compatible with current clinical practice and existing EHR systems, this measure is a model for future quality improvement measures.

Development and use of an administrative claims measure for profiling hospital-wide performance on 30-day unplanned readmission.

BACKGROUND: Existing publicly reported readmission measures are condition-specific, representing less than 20% of adult hospitalizations. An all-condition measure may better measure quality and promote innovation. OBJECTIVE: To develop an all-condition, hospital-wide readmission measure. DESIGN: Measure development study. SETTING: 4821 U.S. hospitals. PATIENTS: Medicare fee-for-service beneficiaries aged 65 years or older. MEASUREMENTS: Hospital-level, risk-standardized unplanned readmissions within 30 days of discharge. The measure uses Medicare fee-for-service claims and is a composite of 5 specialty-based, risk-standardized rates for medicine, surgery/gynecology, cardiorespiratory, cardiovascular, and neurology cohorts. The 2007-2008 admissions were randomly split for development and validation. Models were adjusted for age, principal diagnosis, and comorbid conditions. Calibration in Medicare and all-payer data was examined, and hospital rankings in the development and validation samples were compared. RESULTS: The development data set contained 8 018 949 admissions associated with 1 276 165 unplanned readmissions (15.9%). The median hospital risk-standardized unplanned readmission rate was 15.8 (range, 11.6 to 21.9). The 5 specialty cohort models accurately predicted readmission risk in both Medicare and all-payer data sets for average-risk patients but slightly overestimated readmission risk at the extremes. Overall hospital risk-standardized readmission rates did not differ statistically in the split samples (P = 0.71 for difference in rank), and 76% of hospitals' validation-set rankings were within 2 deciles of the development rank (24% were more than 2 deciles). Of hospitals ranking in the top or bottom deciles, 90% remained within 2 deciles (10% were more than 2 deciles) and 82% remained within 1 decile (18% were more than 1 decile). LIMITATION: Risk adjustment was limited to that available in claims data. CONCLUSION: A claims-based, hospital-wide unplanned readmission measure for profiling hospitals produced reasonably consistent results in different data sets and was similarly calibrated in both Medicare and all-payer data. PRIMARY FUNDING SOURCE: Centers for Medicare & Medicaid Services.

Lymphocytic colitis can be transcriptionally divided into channelopathic and inflammatory lymphocytic colitis.

BACKGROUND: The pathobiology of the non-destructive inflammatory bowel disease (IBD) lymphocytic colitis (LC) is poorly understood. We aimed to define an LC-specific mucosal transcriptome to gain insight into LC pathology, identify unique genomic signatures, and uncover potentially druggable disease pathways. METHODS: We performed bulk RNA-sequencing of LC and collagenous colitis (CC) colonic mucosa from patients with active disease, and healthy controls (n = 4-10 per cohort). Differential gene expression was analyzed by gene-set enrichment and deconvolution analyses to identify pathologically relevant pathways and cells, respectively, altered in LC. Key findings were validated using reverse transcription quantitative PCR and/or immunohistochemistry. Finally, we compared our data with a previous cohort of ulcerative colitis and Crohn's disease patients (n = 4 per group) to distinguish non-destructive from classic IBD. RESULTS: LC can be subdivided into channelopathic LC, which is governed by organic acid and ion transport dysregulation, and inflammatory LC, which is driven by microbial immune responses. Inflammatory LC displays an innate and adaptive immunity that is limited compared to CC and classic IBD. Conversely, we noted a distinct induction of regulatory non-coding RNA species in inflammatory LC samples. Moreover, compared with CC, water channel and cell adhesion molecule gene expression decreased in channelopathic LC, whereas it was accentuated in inflammatory LC and associated with reduced intestinal epithelial cell proliferation. CONCLUSIONS: We conclude that LC can be subdivided into channelopathic LC and inflammatory LC that could be pathomechanistically distinct subtypes despite their shared clinical presentation. Inflammatory LC exhibits a dampened immune response compared to CC and classic IBDs. Our results point to regulatory micro-RNAs as a potential disease-specific feature that may be amenable to therapeutic intervention.

Fried meat intake is a risk factor for lung adenocarcinoma in a prospective cohort of Chinese men and women in Singapore.

Probable human carcinogens are generated during Chinese-style high-temperature cooking of meat and have been detected in the ambient air and on the meat surface. Although the inhalation of these compounds is an established risk factor for lung cancer, exposure via fried meat consumption has not yet been prospectively evaluated as a risk factor. The relationship between fried meat intake and lung cancer risk was investigated using data from a prospective cohort study among Chinese in Singapore. Lung cancer cases (n = 1130) were identified from 61 321 men and women, 70% of whom were lifetime never smokers. Proportional hazards regression methods were used to calculate adjusted hazard ratios (HRs) and 95% confidence intervals (CIs). Overall, there was no association between fried meat intake and risk of all lung cancers combined. For lung adenocarcinoma, fried meat intake had a statistically significant association with increased risk. The association between fried meat intake and risk of lung adenocarcinoma became stronger when analyses were restricted to lifetime never smokers. Compared with the lowest tertile of fried meat intake, the HRs (95% CIs) for the second and third tertiles were 1.43 (0.98, 2.08) and 1.51 (1.03, 2.22), respectively (P for trend = 0.04). The positive association was present among both men and women. There was no association between fried meat intake and risk of non-adenocarcinomas of the lung. Our prospective results for fried meat intake support consumption as an important route of exposure to compounds from Chinese-style high-temperature cooking for the development of lung adenocarcinoma.

Green and black tea intake in relation to prostate cancer risk among Singapore Chinese.

PURPOSE: Tea is one of the most commonly consumed beverages worldwide. To date, observational data from prospective cohort studies investigating the relationship between green and black tea intake and prostate cancer risk are sparse and equivocal. In a population-based, prospective cohort study of Chinese men in Singapore, we investigated the relationship between green and black tea intake and prostate cancer risk. METHODS: Tea consumption data for 27,293 men were collected at baseline (between 1993 and 1998) using a validated food frequency questionnaire. After an average of 11.2 years of follow-up, 298 men had developed prostate cancer. Proportional hazards regression methods were used to assess the associations between tea intake and prostate cancer risk. RESULTS: There was no association between daily green tea intake and prostate cancer risk, compared with no green tea intake [hazard ratio (HR) = 1.08; 95 % confidence interval (CI) 0.79, 1.47]. For black tea, a statistically significant positive association and trend were observed for daily intake compared with no black tea intake (HR = 1.41, 95 % CI 1.03, 1.92; p for trend <0.01) CONCLUSIONS: Few prospective data are available from populations that have both a high level and wide range of black and green tea intake; this study represents a unique opportunity to evaluate their individual effects on prostate cancer risk. Our findings support the notion that green tea intake does not protect against prostate cancer and that black tea intake may increase prostate cancer risk.

Development and Validation of an Algorithm to Identify Planned Readmissions From Claims Data.

BACKGROUND: It is desirable not to include planned readmissions in readmission measures because they represent deliberate, scheduled care. OBJECTIVES: To develop an algorithm to identify planned readmissions, describe its performance characteristics, and identify improvements. DESIGN: Consensus-driven algorithm development and chart review validation study at 7 acute-care hospitals in 2 health systems. PATIENTS: For development, all discharges qualifying for the publicly reported hospital-wide readmission measure. For validation, all qualifying same-hospital readmissions that were characterized by the algorithm as planned, and a random sampling of same-hospital readmissions that were characterized as unplanned. MEASUREMENTS: We calculated weighted sensitivity and specificity, and positive and negative predictive values of the algorithm (version 2.1), compared to gold standard chart review. RESULTS: In consultation with 27 experts, we developed an algorithm that characterizes 7.8% of readmissions as planned. For validation we reviewed 634 readmissions. The weighted sensitivity of the algorithm was 45.1% overall, 50.9% in large teaching centers and 40.2% in smaller community hospitals. The weighted specificity was 95.9%, positive predictive value was 51.6%, and negative predictive value was 94.7%. We identified 4 minor changes to improve algorithm performance. The revised algorithm had a weighted sensitivity 49.8% (57.1% at large hospitals), weighted specificity 96.5%, positive predictive value 58.7%, and negative predictive value 94.5%. Positive predictive value was poor for the 2 most common potentially planned procedures: diagnostic cardiac catheterization (25%) and procedures involving cardiac devices (33%). CONCLUSIONS: An administrative claims-based algorithm to identify planned readmissions is feasible and can facilitate public reporting of primarily unplanned readmissions.