Contributing Factors to the Clinical and Economic Burden of Patients with Laboratory-Confirmed Carbapenem-Nonsusceptible Gram-Negative Urinary Tract Infections.

PURPOSE: We explored patient- and hospital-level predictor variables for worse clinical and economic outcomes in carbapenem-nonsusceptible urinary tract infections (UTIs). PATIENTS AND METHODS: We used electronic data (January 2013-September 2015; 78 US hospitals) from a large multicenter clinical database. Nonduplicate gram-negative isolates were considered carbapenem-nonsusceptible if they had resistant/intermediate susceptibility. Potential predictors of outcomes (mortality, 30-day readmissions, length of stay [LOS], hospital total cost, and net gain/loss per case) were examined using generalized linear mixed models. Significant predictors were identified based on statistical significance and model goodness-of-fit criteria. RESULTS: A total of 1439 carbapenem-nonsusceptible urine cases were identified. The mortality rate was 5.5%; the hospital readmission rate was 25.0%. Mean (standard deviation [SD]) LOS, total cost, and loss per case were 12 (14) days, $21,502 ($37,172), and $5828 ($26,540), respectively. Hospital-onset (vs community-onset) infection significantly impacted all outcomes: mortality (odds ratio [OR], 2.21; 95% confidence interval [CI], 1.19-4.11; P=.01), 30-day readmissions (OR, 2.35; 95% CI, 1.49-3.71; P<.001), LOS (25.7 vs 10.2 days; P<.001), hospital total cost ($67,810 vs $22,141; P<.001), and loss per case (-$28,054 vs -$10,809; P<.001). Mechanical ventilation/intensive care unit status, neoplasms, and other underlying diseases were also common predictors for worse outcomes overall; polymicrobial infection was significantly associated with worse economic outcomes. Other key predictors were >1 prior hospitalization for 30-day readmissions, high Acute Laboratory Risk of Mortality Score for mortality, LOS, cost, and hospital teaching status for cost. CONCLUSION: Hospital-onset infections, polymicrobial infections, higher clinical severity, and underlying diseases are key predictors for worsened overall burden of carbapenem-nonsusceptible gram-negative UTIs.

Diagnosis of Chronic Pancreatitis Incorporating Endosonographic Features, Demographics, and Behavioral Risk.

OBJECTIVES: Diagnosing chronic pancreatitis remains challenging. Endoscopic ultrasound (EUS) is utilized to evaluate pancreatic disease. Abnormal pancreas function test is considered the "nonhistologic" criterion standard for chronic pancreatitis. We derived a prediction model for abnormal endoscopic pancreatic function test (ePFT) by enriching EUS findings with patient demographic and pancreatitis behavioral risk characteristics. METHODS: Demographics, behavioral risk characteristics, EUS findings, and peak bicarbonate results were collected from patients evaluated for pancreatic disease. Abnormal ePFT was defined as peak bicarbonate of less than 75 mEq/L. We fit a logistic regression model and converted it to a risk score system. The risk score was validated using 1000 bootstrap simulations. RESULTS: A total of 176 patients were included; 61% were female with median age of 48 years (interquartile range, 38-57 years). Abnormal ePFT rate was 39.2% (69/176). Four variables formulated the risk score: alcohol or smoking status, number of parenchymal abnormalities, number of ductal abnormalities, and calcifications. Abnormal ePFT occurred in 10.7% with scores 4 or less versus 92.0% scoring 20 or greater. The model C-statistic was 0.78 (95% confidence interval, 0.71-0.85). CONCLUSIONS: Number of EUS pancreatic duct and parenchymal abnormalities, presence of calcification, and smoking/alcohol status were predictive of abnormal ePFT. This simple model has good discrimination for ePFT results.

Global Health Education in Gastroenterology Fellowship: A National Survey.

BACKGROUND: Interest in global health (GH) education is increasing across disciplines. AIMS: To assess exposure to and perception of GH training among gastroenterology fellows and program directors across the USA. METHODS: Design: Electronic survey study. SETTING: The questionnaire was circulated to accredited US gastroenterology fellowship programs, with the assistance of the American Gastroenterological Association. PARTICIPANTS: Gastroenterology program directors and fellows. RESULTS: The questionnaire was returned by 127 respondents (47 program directors, 78 fellows) from 55 training programs (36 % of all training programs). 61 % of respondents had prior experience in GH. 17 % of programs offered GH curriculum with international elective (13 %), didactic (9 %), and research activity (7 %) being the most common. Fellows had adequate experience managing hepatitis B (93 %), cholangiocarcinoma (84 %), and intrahepatic duct stones (84 %). 74, 69 and 68 % reported having little to no experience managing hepatitis E, tuberculosis mesenteritis, or epidemic infectious enteritis, respectively. Most fellows would participate in an elective in an underserved area locally (81 %) or a 4-week elective abroad (71 %), if available. 44 % of fellows planned on working or volunteering abroad after fellowship. Barriers to establishing GH curriculum included funding (94 %), scheduling (88 %), and a lack of standardized objectives (78 %). Lack of interest, however, was not a concern. Fellows (49 %), more than faculty (29 %) (χ 2 = 21.9; p = 0.03), believed that GH education should be included in fellowship curriculum. CONCLUSIONS: Program directors and trainees recognize the importance of GH education. However, only 17 % of ACGME-approved fellowship programs offer the opportunity. Global health curriculum may enhance gastroenterology training.

Development and validation of a disease-specific risk adjustment system using automated clinical data.

OBJECTIVE: To develop and validate a disease-specific automated inpatient mortality risk adjustment system primarily using computerized numerical laboratory data and supplementing them with administrative data. To assess the values of additional manually abstracted data. METHODS: Using 1,271,663 discharges in 2000-2001, we derived 39 disease-specific automated clinical models with demographics, laboratory findings on admission, ICD-9 principal diagnosis subgroups, and secondary diagnosis-based chronic conditions. We then added manually abstracted clinical data to the automated clinical models (manual clinical models). We compared model discrimination, calibration, and relative contribution of each group of variables. We validated these 39 models using 1,178,561 discharges in 2004-2005. RESULTS: The overall mortality was 4.6 percent (n = 58,300) and 4.0 percent (n = 47,279) for derivation and validation cohorts, respectively. Common mortality predictors included age, albumin, blood urea nitrogen or creatinine, arterial pH, white blood counts, glucose, sodium, hemoglobin, and metastatic cancer. The average c-statistic for the automated clinical models was 0.83. Adding manually abstracted variables increased the average c-statistic to 0.85 with better calibration. Laboratory results displayed the highest relative contribution in predicting mortality. CONCLUSIONS: A small number of numerical laboratory results and administrative data provided excellent risk adjustment for inpatient mortality for a wide range of clinical conditions.

Candidemia on presentation to the hospital: development and validation of a risk score.

INTRODUCTION: Candidemia results in substantial morbidity and mortality, especially if initial antifungal therapy is delayed or is inappropriate; however, candidemia is difficult to diagnose because of its nonspecific presentation. METHODS: To develop a risk score for identifying hospitalized patients with candidemia, we performed a retrospective analysis of a large database of 176 acute-care hospitals in the United States. We studied 64,019 patients with bloodstream infection (BSI) on presentation from 2000 through 2005 (derivation cohort) and 24,685 from 2006 to 2007 (validation cohort). We used recursive partitioning (RPART) to identify the best discriminators for Candida as the cause of BSI. We compared three sets of models (equal-weight, unequal-weight, vs full model with additional variables from logistic regression model) for sensitivity analysis. RESULTS: The RPART identified 6 variables as the best discriminators: age < 65 years, temperature 0.10, indicating predicted and observed candidemia rates did not differ significant across the 7 risk stratus). The full model with 16 risk factors had slightly higher AUROCs (0.74 versus 0.73 for derivation versus validation); however, 7 variables were no longer significant in the recalibrated model for the validation cohort, indicating that the additional items did not materially enhance the model. CONCLUSIONS: A simple equal-weight risk score differentiated patients' risk for candidemia in a graded fashion upon hospital presentation.