Mild chronic kidney dysfunction and treatment strategies for stable coronary artery disease

Objective: Our objective was to evaluate the association of chronic kidney dysfunction in patients with multi-vessel chronic coronary artery disease, preserved left ventricular function, and the possible interaction between received treatment and cardiovascular events. Methods: The glomerular filtration rate was determined at baseline on 611 patients who were randomized into three treatment groups: medical treatment, percutaneous coronary intervention, and coronary artery bypass surgery. Incidence of myocardial infarction, angina requiring a new revascularization procedure, and death were analyzed during 5 years in each group. Results: Of 611 patients, 112 (18%) were classified as having normal renal function, 349 (57%) were classified as having mild dysfunction, and 150 (25%) were classified as having moderate dysfunction. There were significant differences among the cumulative overall mortality curves among the three renal function groups. Death was observed more frequently in the moderate dysfunction group than the other two groups (P < .001). Interestingly, in patients with mild chronic kidney dysfunction, we observed that coronary artery bypass treatment presented a statistically higher percentage of event-free survival and lower percentage of mortality than did percutaneous coronary intervention or medical treatment Conclusions: Our results confirm that coronary artery disease accompanied by chronic kidney dysfunction has a worse prognosis, regardless of the therapeutic strategy for coronary artery disease, when renal function is at least mildly impaired. Additionally, our data suggest that the different treatment strategies available for stable coronary artery disease may have differential beneficial effects according to the range of glomerular filtration rate strata.

Homeopathic practice in Intensive Care Units: objective semiology, symptom selection and a series of sepsis cases

Homeopathy has been used for more than two hundred years to treat chronic disease using various approaches in a wide range of diseases. However, for acute disease and critical illness, application has been limited by inadequate training of homeopathic physicians and the small number of pertinent clinical studies. In view of the difficulty of practising homeopathy in Intensive Care Units (ICU), a protocol was developed to facilitate description of objective homeopathic symptoms with a ranking of symptoms appropriate for these situations (Protocol for Objective Homeopathic Semiology). Examples of favorable results with individualized homeopathic treatments for a series of cases of Systemic Inflammatory Response Syndrome (sepsis) are described. Homeopathy (2008) 97, 206-213.

A decision support system to facilitate management of patients with acute gastrointestinal bleeding

Objective: To develop a model to predict the bleeding source and identify the cohort amongst patients with acute gastrointestinal bleeding (GIB) who require urgent intervention, including endoscopy. Patients with acute GIB, an unpredictable event, are most commonly evaluated and managed by non-gastroenterologists. Rapid and consistently reliable risk stratification of patients with acute GIB for urgent endoscopy may potentially improve outcomes amongst such patients by targeting scarce health-care resources to those who need it the most. Design and methods: Using ICD-9 codes for acute GIB, 189 patients with acute GIB and all. available data variables required to develop and test models were identified from a hospital medical records database. Data on 122 patients was utilized for development of the model and on 67 patients utilized to perform comparative analysis of the models. Clinical data such as presenting signs and symptoms, demographic data, presence of co-morbidities, laboratory data and corresponding endoscopic diagnosis and outcomes were collected. Clinical data and endoscopic diagnosis collected for each patient was utilized to retrospectively ascertain optimal management for each patient. Clinical presentations and corresponding treatment was utilized as training examples. Eight mathematical models including artificial neural network (ANN), support vector machine (SVM), k-nearest neighbor, linear discriminant analysis (LDA), shrunken centroid (SC), random forest (RF), logistic regression, and boosting were trained and tested. The performance of these models was compared using standard statistical analysis and ROC curves. Results: Overall the random forest model best predicted the source, need for resuscitation, and disposition with accuracies of approximately 80% or higher (accuracy for endoscopy was greater than 75%). The area under ROC curve for RF was greater than 0.85, indicating excellent performance by the random forest model Conclusion: While most mathematical models are effective as a decision support system for evaluation and management of patients with acute GIB, in our testing, the RF model consistently demonstrated the best performance. Amongst patients presenting with acute GIB, mathematical models may facilitate the identification of the source of GIB, need for intervention and allow optimization of care and healthcare resource allocation; these however require further validation. (c) 2007 Elsevier B.V. All rights reserved.