Defining the relative contribution of health care environmental components to patient outcomes in the model of 30-day readmission after coronary artery bypass graft (CABG)

BackgroundPatient outcomes following health care interventions may be dependent on a variety of factors: patient, surgeon, hospital, information technology, and temporal, cultural, and socioeconomic factors, among others. In this study, we characterize the relative contribution of each of these factors using a model of 30-day readmission following coronary artery bypass graft.MethodsThe Healthcare Cost and Utilization Project, the American Hospital Association Annual Health Survey Databases, the Healthcare Information and Management Systems Society, and the Distressed Communities Index from 2010 to 2013 were linked for Florida, Iowa, Massachusetts, Maryland, New York, and Washington. Logistic regression, random forest, decision tree, gradient boosting, k-nearest-neighbors classification, and XGBoost tree models were implemented. Modeling results were compared on the basis of predictive accuracy, sensitivity, specificity, and area under the curve. Decision tree performed best and was selected for further analysis. A gradient-boosted model was used to quantify factor contribution.ResultsThe model had 45,352 patients, 54,096 admissions, and a 16.2% 30-day readmission rate after coronary artery bypass graft. The top 10 predictors were disposition at discharge, number of chronic conditions, total procedures, median household income, adults without high school diplomas, primary payer method, Agency for Healthcare Research and Quality comorbidity: renal failure, patient location (urban-rural), admission type, and age categories. The top 3 socioeconomic predictors were estimated state median household income, adults without high school diplomas, and patient location (urban versus rural designation). The relative contribution of patient/temporal, socioeconomic, hospital information technology, and hospital factors to readmission is 83.45%, 5.71%, 6.34%, and 4.31%, respectively.ConclusionIn this model, the contribution of socioeconomic factors is substantive but lags significantly behind patient/temporal factors. With ever increasing availability of data, identification of contributors to patient outcomes within the overall health care macroenvironment will allow prioritization of interventions.     

β-blocker therapy for infantile hemangioma

ABSTRACT

Introduction

Fifteen percent of proliferating infantile hemangioma (IH) require intervention because of the threat to function or life, ulceration, or tissue distortion. Propranolol is the mainstay treatment for problematic proliferating IH. Other β-blockers and angiotensin-converting enzyme (ACE) inhibitors have been explored as alternative treatments.     

Clinical implications of trials investigating drug-drug interactions between cannabidiol and enzyme inducers or inhibitors or common antiseizure drugs

Highly purified cannabidiol (CBD) has demonstrated efficacy with an acceptable safety profile in patients with Lennox-Gastaut syndrome or Dravet syndrome in randomized, double-blind, add-on, controlled phase 3 trials. It is important to consider the possibility of drug-drug interactions (DDIs). Here, we review six trials of CBD (Epidiolex/Epidyolex; 100 mg/mL oral solution) in healthy volunteers or patients with epilepsy, which investigated potential interactions between CBD and enzymes involved in drug metabolism of common antiseizure drugs (ASDs). CBD did not affect CYP3A4 activity. Induction of CYP3A4 and CYP2C19 led to small reductions in exposure to CBD and its major metabolites. Inhibition of CYP3A4 activity did not affect CBD exposure and caused small increases in exposure to CBD metabolites. Inhibition of CYP2C19 activity led to a small increase in exposure to CBD and small decreases in exposure to CBD metabolites. One potentially clinically important DDI was identified: combination of CBD and clobazam (CLB) did not affect CBD or CLB exposure, but increased exposure to major metabolites of both compounds. Reduction of CLB dose may be considered if adverse reactions known to occur with CLB are experienced when it is coadministered with CBD. There was a small increase of exposure to stiripentol (STP) when coadministered with CBD. STP had no effect on CBD exposure but led to minor decreases in exposure to CBD metabolites. Combination of CBD and valproate (VPA) did not cause clinically important changes in the pharmacokinetics of either drug, or 2-propyl-4-pentenoic acid. Concomitant VPA caused small increases in exposure to CBD metabolites. Dose adjustments are not likely to be necessary when CBD is combined with STP or VPA. The safety results from these trials were consistent with the known safety profile of CBD. These trials indicate an overall low potential for DDIs between CBD and other ASDs, except for CLB.     

Clinic image surveillance reduces mortality in patients with primary hepato-gastrointestinal cancer who develop second primary lung cancer: A STROBE-compliant retrospective study

Second primary cancer is prevalent in patients with gastrointestinal (GI) cancer, for which lung cancer is the most common and associated with high lethality. Image screening for lung cancer was proved to be effective in early diagnosis and lower mortality. However, trials of screen for lung cancer generally excluded patients with a previous diagnosis of malignancy. The study aimed to investigate the outcome of second primary lung cancer and the factor that improve survival in patients with hepato-GI cancer.A total of 276 patients with secondary lung cancer were found among 3723 newly-diagnosed lung cancer patients diagnosed in Chang Gung Memorial Hospital, between 2010 and 2014. Patients’ clinical characteristics, stages and survival were recorded and analyzed. The patients were separated into 2 groups: Group I was defined as lung cancer detected in original primary cancer clinic and group II patients defined as lung cancer detected in other medical places.Sixty-nine cases with primary GI-hepatic and secondary lung cancer were diagnosed (42 (60.8%) in Group I and 27 (39.1%) in Group II). Although both groups had comparable primary cancer stages and treatment, more patients in Group I than Group II were diagnosed as early stage lung cancer (stage I-II: 40.5% vs 11.1%; P = .023). Group II had larger lung tumor sizes than Group I (4.7 vs 3.5 cm; P = .025). Group I showed better 5-year overall survival than Group II (P = .014, median survival: 27 vs 10 months). Among Group II, only 37% had received image follow up in clinic compared with 67% of Group I cases (P = .025). Patients with chest image follow up in clinics also had better 5-year overall survival (P = .043).GI-hepatic cancer was the most common primary malignancy in the lung cancer cohort. Patients had better survival outcome when secondary lung cancer was diagnosed in original primary cancer clinic. Chest image screening strategy may contribute better survival in secondary lung cancer due to detection at an earlier stage.