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AbstractBackgroundGastrointestinal (GI) and non‐GI disorders are associated with altered intestinal permeability, which can be measured in vivo by urinary excretion after oral lactulose and mannitol ingestion. Inadvertent dietary consumption of 12Carbon (12C, regular) mannitol in food or from other sources may interfere with the test's interpretation. 13Carbon (13C) constitutes 1% of carbon in nature and 13C mannitol is a stable isotope. Our aim was to determine the performance of 13C mannitol for measurement of intestinal permeability.MethodsTen healthy volunteers underwent intestinal permeability assay using coadministered 12C mannitol, 13C mannitol and lactulose, followed by timed urine collections. Urinary sugar concentrations were measured using tandem high performance liquid chromatography–mass spectrometry.Key resultsWe found that 13C mannitol can be distinguishable from 12C mannitol on tandem mass spectrometry. In addition, 13C mannitol had ~20‐fold lower baseline contamination compared to 12C mannitol. We describe here the 13C mannitol assay method for the measurement of intestinal permeability.Conclusions & InferencesIn conclusion, 13C mannitol is superior to 12C mannitol for measurement of intestinal permeability. It avoids issues with baseline contamination and erratic excretions during the testing period.

Numerical laboratory data at admission have been proposed for enhancement of inpatient predictive modeling from administrative claims. In this study, predictive models for inpatient/30-day postdischarge mortality and for risk-adjusted prolonged length of stay, as a surrogate for severe inpatient complications of care, were designed with administrative data only and with administrative data plus numerical laboratory variables. A comparison of resulting inpatient models for acute myocardial infarction, congestive heart failure, coronary artery bypass grafting, and percutaneous cardiac interventions demonstrated improved discrimination and calibration with administrative data plus laboratory values compared to administrative data only for both mortality and prolonged length of stay. Improved goodness of fit was most apparent in acute myocardial infarction and percutaneous cardiac intervention. The emergence of electronic medical records should make the addition of laboratory variables to administrative data an efficient and practical method to clinically enhance predictive modeling of inpatient outcomes of care.

AbstractObjectivesFatigue is a common symptom of chronic inflammatory diseases. The objective of this study was to investigate fatigue in patients with Behçet's syndrome (BS) and to examine the relationship between fatigue and disease activity, quality of life, anxiety and depression.MethodsThis is a cross‐sectional study of 123 BS patients and 71 healthy controls in Turkey. All subjects completed the Multidimensional Assessment of Fatigue (MAF) questionnaire, Short form‐36 (SF‐36), Hospital Anxiety and Depression (HADS) scale and Health Assessment Questionnaire (HAQ). Disease activity among BS patients was assessed using the Behçet Syndrome Activity Scale (BSAS) and the physician's global assessment (PGA).ResultsBS patients had significantly higher MAF, HADS‐depression (HADS‐D) and HADS‐anxiety (HADS‐A) scores than the healthy controls (P < 0.001). Both the physical and mental components of the SF‐36 scale were impaired in BS patients (P = 0.0001). BS patients with active disease, depression and anxiety had significantly higher MAF scores compared to BS patients without active disease, depression and anxiety (P = 0.0001). MAF scores showed positive correlations with HADS‐A, HADS‐D, HAQ scores and negative correlations with SF‐36 mental and physical components. In regression analyses, depression, anxiety and physical dysfunction were significantly associated with fatigue, after adjusting for age, sex, SF‐36 physical and mental scores, HAQ, HADS‐A, HADS‐D and BSAS scores (P < 0.05). Decreases in SF‐36 physical and mental scores were significant predictive factors for high MAF score in healthy controls (P < 0.05).ConclusionsFatigue is common in clinically active BS patients compared with healthy controls and inactive BS patients. Depression, anxiety and physical dysfunction were significantly associated with fatigue.

Key Points Agents that inhibit both complexes containing the mammalian target of rapamycin are particularly toxic to acute lymphocytic leukemia cells. This killing reflects engagement of a 4EBP1/c-MYC/PUMA axis downstream of mTORC1 and an NF-κB/EGR1/BIM axis downstream of mTORC2.

ObjectiveThe aim of our study was to study the impact of glycoprotein IIb/IIIa inhibitors (GPI) on in‐hospital outcomes.BackgroundThere is paucity of data regarding the impact of GPI on the outcomes following peripheral endovascular interventions.MethodsThe study cohort was derived from Healthcare Cost and Utilization Project (HCUP) Nationwide Inpatient Sample (NIS) database between the years 2006 and 2011. Peripheral endovascular interventions and GPI utilization were identified using appropriate ICD‐9 Diagnostic and procedural codes. Two‐level hierarchical multivariate mixed models were created. The study outcomes were: primary (in‐hospital mortality and amputation studied separately) and secondary (composite of in‐hospital mortality and postprocedural complications). Hospitalization costs were also assessed.ResultsGPI utilization (OR, 95% CI, P‐value) was independently predictive of lower amputation rates (0.36, 0.27–0.49, <0.001). There was no significant difference in terms of in‐hospital mortality (0.59, 0.31–1.14, P 0.117), although GPI use predicted worse secondary outcomes (1.23, 1.03–1.47, 0.023). Following propensity matching, the amputation rate was lower (3.2% vs. 8%, P < 0.001), while hospitalization costs were higher in the cohort that received GPI ($21,091 ± 404 vs. 19,407 ± 133, P < 0.001).ConclusionsMultivariate analysis revealed GPI use in peripheral endovascular interventions to be suggestive of an increase in composite end‐point of in‐hospital mortality and postprocedural complications, no impact on in‐hospital mortality alone, significantly lower rate of amputation, and increase in hospitalization costs. © 2016 Wiley Periodicals, Inc.

Background: Hospitals’ risk-standardized mortality rates and outlier status (significantly higher/lower rates) are reported by the Centers for Medicare and Medicaid Services (CMS) for acute myocardial infarction (AMI) patients using Medicare claims data. New York now has AMI claims data with blood pressure and heart rate added. Objective: The objective of this study was to see whether the appended database yields different hospital assessments than standard claims data. Methods: New York State clinically appended claims data for AMI were used to create 2 different risk models based on CMS methods: 1 with and 1 without the added clinical data. Model discrimination was compared, and differences between the models in hospital outlier status and tertile status were examined. Results: Mean arterial pressure and heart rate were both significant predictors of mortality in the clinically appended model. The C statistic for the model with the clinical variables added was significantly higher (0.803 vs. 0.773, P<0.001). The model without clinical variables identified 10 low outliers and all of them were percutaneous coronary intervention hospitals. When clinical variables were included in the model, only 6 of those 10 hospitals were low outliers, but there were 2 new low outliers. The model without clinical variables had only 3 high outliers, and the model with clinical variables included identified 2 new high outliers. Conclusion: Appending even a small number of clinical data elements to administrative data resulted in a difference in the assessment of hospital mortality outliers for AMI. The strategy of adding limited but important clinical data elements to administrative datasets should be considered when evaluating hospital quality for procedures and other medical conditions.