Previous Percutaneous Coronary Intervention as Risk Factor for Coronary Artery Bypass Grafting

Background: Percutaneous coronary intervention (PCI) has increased as the initial revascularization strategy in chronic coronary artery disease. Consequently, more patients undergoing coronary artery bypass grafting (CABG) have history of coronary stent. Objective: Evaluate the impact of previous PCI on in-hospital mortality after CABG in patients with multivessel coronary artery disease. Methods: Between May/2007 and June/2009, 1099 consecutive patients underwent CABG on cardiopulmonary bypass. Patients with no PCI (n=938, 85.3%) were compared with patients with previous PCI (n=161, 14.6%). Logistic regression models and propensity score matching analysis were used to assess the risk-adjusted impact of previous PCI on in-hospital mortality. Results: Both groups were similar, except for the fact that patients with previous PCI were more likely to have unstable angina (16.1% x 9.9%, p=0.019). In-hospital mortality after CABG was higher in patients with previous PCI (9.3% x 5.1%, p=0.034) and it was comparable with EuroSCORE and 2000 Bernstein-Parsonnet risk score. Using multivariate logistic regression analysis, previous PCI emerged as an independent predictor of postoperative in-hospital mortality (odds ratio 1.94, 95% CI 1.02-3.68, p=0.044) as strong as diabetes (odds ratio 1.86, 95% CI 1.07-3.24, p=0.028). After computed propensity score matching based on preoperative risk factors, in-hospital mortality remained higher among patients with previous PCI (odds ratio 3.46, 95% CI 1.10-10.93, p=0.034). Conclusions: Previous PCI in patients with multivessel coronary artery disease is an independent risk factor for in-hospital mortality after CABG. This fact must be considered when PCI is indicated as initial alternative in patients with more severe coronary artery disease. (Arq Bras Cardiol 2012;99(1):586-595)

The Poisson-exponential regression model under different latent activation schemes

In this paper, a new family of survival distributions is presented. It is derived by considering that the latent number of failure causes follows a Poisson distribution and the time for these causes to be activated follows an exponential distribution. Three different activation schemes are also considered. Moreover, we propose the inclusion of covariates in the model formulation in order to study their effect on the expected value of the number of causes and on the failure rate function. Inferential procedure based on the maximum likelihood method is discussed and evaluated via simulation. The developed methodology is illustrated on a real data set on ovarian cancer.

A log-linear regression model for the beta-Birnbaum-Saunders distribution with censored data

The beta-Birnbaum-Saunders (Cordeiro and Lemonte, 2011) and Birnbaum-Saunders (Birnbaum and Saunders, 1969a) distributions have been used quite effectively to model failure times for materials subject to fatigue and lifetime data. We define the log-beta-Birnbaum-Saunders distribution by the logarithm of the beta-Birnbaum-Saunders distribution. Explicit expressions for its generating function and moments are derived. We propose a new log-beta-Birnbaum-Saunders regression model that can be applied to censored data and be used more effectively in survival analysis. We obtain the maximum likelihood estimates of the model parameters for censored data and investigate influence diagnostics. The new location-scale regression model is modified for the possibility that long-term survivors may be presented in the data. Its usefulness is illustrated by means of two real data sets. (C) 2011 Elsevier B.V. All rights reserved.

Indocyanine green angiography findings in patients with long-standing Vogt-Koyanagi-Harada disease: a cross-sectional study

Background: To investigate indocyanine green angiography (ICGA) findings in patients with long-standing Vogt-Koyanagi-Harada (VKH) disease and their correlation with disease activity on clinical examination as well as with systemic corticosteroid therapy. Methods: Twenty-eight patients (51 eyes) with long-standing (>= 6 months from disease onset) VKH disease whose treatment was tapered based only in clinical features were prospectively included at a single center in Brazil. All patients underwent standardized clinical evaluation, which included fundus photography, fluorescein angiography and ICGA. Clinical disease activity was determined based in the Standardization in Uveitis Nomenclature Working Group. Fisher exact test and logistic regression models were used for statistical analysis. Results: Disease-related choroidal inflammation on ICGA was observed in 72.5% (31 of 51 eyes). Angiographic findings suggestive of (choroidal and/or retinal) disease activity were not observed on FA. Clinically active disease based on clinical evaluation was observed in 41.2% (21 of 51 eyes). In these 21 eyes, disease-related choroidal inflammation on ICGA was observed in 76.2% (16 of 21 eyes); in the remaining eyes (without clinical active disease) disease-related choroidal inflammation on ICGA was observed in 70.0% (21 of 30 eyes). In respect to systemic corticosteroid therapy, 10 patients (18 of 51 eyes) were under treatment with prednisone. In these 10 (18 of 51 eyes) patients, disease-related choroidal inflammation on ICGA was observed in 83.3% (15 of 18 eyes); in the remaining patients (33 of 51 eyes) disease-related choroidal inflammation on ICGA was observed in 66.7% (22 of 33 eyes). Conclusion: ICGA findings suggestive of disease-related choroidal inflammation were observed in a considerable proportion of patients with long-standing VKH disease, independent of the inflammatory status of the disease on clinical examination or current use of systemic corticosteroid. Therefore, the current study reinforces the crucial role of ICGA to assist the management and treatment of patients with long-standing VKH disease.

The Real Importance of Pre-Existing Comorbidities on Long-Term Mortality after Acute Kidney Injury

Background: The causes of death on long-term mortality after acute kidney injury (AKI) have not been well studied. The purpose of the study was to evaluate the role of comorbidities and the causes of death on the long-term mortality after AKI. Methodology/Principal Findings: We retrospectively studied 507 patients who experienced AKI in 2005-2006 and were discharged free from dialysis. In June 2008 (median: 21 months after AKI), we found that 193 (38%) patients had died. This mortality is much higher than the mortality of the population of Sao Paulo City, even after adjustment for age. A multiple survival analysis was performed using Cox proportional hazards regression model and showed that death was associated with Khan's index indicating high risk [adjusted hazard ratio 2.54 (1.38-4.66)], chronic liver disease [1.93 (1.15-3.22)], admission to non-surgical ward [1.85 (1.30-2.61)] and a second AKI episode during the same hospitalization [1.74 (1.12-2.71)]. The AKI severity evaluated either by the worst stage reached during AKI (P=0.20) or by the need for dialysis (P=0.12) was not associated with death. The causes of death were identified by a death certificate in 85% of the non-survivors. Among those who died from circulatory system diseases (the main cause of death), 59% had already suffered from hypertension, 34% from diabetes, 47% from heart failure, 38% from coronary disease, and 66% had a glomerular filtration rate <60 previous to the AKI episode. Among those who died from neoplasms, 79% already had the disease previously. Conclusions: Among AKI survivors who were discharged free from dialysis the increased long-term mortality was associated with their pre-existing chronic conditions and not with the severity of the AKI episode. These findings suggest that these survivors should have a medical follow-up after hospital discharge and that all efforts should be made to control their comorbidities.

Decreasing the number of false positives in sequence classification

Abstract Background A large number of probabilistic models used in sequence analysis assign non-zero probability values to most input sequences. To decide when a given probability is sufficient the most common way is bayesian binary classification, where the probability of the model characterizing the sequence family of interest is compared to that of an alternative probability model. We can use as alternative model a null model. This is the scoring technique used by sequence analysis tools such as HMMER, SAM and INFERNAL. The most prevalent null models are position-independent residue distributions that include: the uniform distribution, genomic distribution, family-specific distribution and the target sequence distribution. This paper presents a study to evaluate the impact of the choice of a null model in the final result of classifications. In particular, we are interested in minimizing the number of false predictions in a classification. This is a crucial issue to reduce costs of biological validation. Results For all the tests, the target null model presented the lowest number of false positives, when using random sequences as a test. The study was performed in DNA sequences using GC content as the measure of content bias, but the results should be valid also for protein sequences. To broaden the application of the results, the study was performed using randomly generated sequences. Previous studies were performed on aminoacid sequences, using only one probabilistic model (HMM) and on a specific benchmark, and lack more general conclusions about the performance of null models. Finally, a benchmark test with P. falciparum confirmed these results. Conclusions Of the evaluated models the best suited for classification are the uniform model and the target model. However, the use of the uniform model presents a GC bias that can cause more false positives for candidate sequences with extreme compositional bias, a characteristic not described in previous studies. In these cases the target model is more dependable for biological validation due to its higher specificity.

Overall Survival Improvement in Patients with Lung Cancer and Bone Metastases Treated with Denosumab Versus Zoledronic Acid Subgroup Analysis from a Randomized Phase 3 Study

Introduction: Denosumab, a fully human anti-RANKL monoclonal antibody, reduces the incidence of skeletal-related events in patients with bone metastases from solid tumors. We present survival data for the subset of patients with lung cancer, participating in the phase 3 trial of denosumab versus zoledronic acid (ZA) in the treatment of bone metastases from solid tumors (except breast or prostate) or multiple myeloma. Methods: Patients were randomized 1:1 to receive monthly subcutaneous denosumab 120 mg or intravenous ZA 4 mg. An exploratory analysis, using Kaplan-Meier estimates and proportional hazards models, was performed for overall survival among patients with non-small-cell lung cancer (NSCLC) and SCLC. Results: Denosumab was associated with improved median overall survival versus ZA in 811 patients with any lung cancer (8.9 versus 7.7 months; hazard ratio [HR] 0.80) and in 702 patients with NSCLC (9.5 versus 8.0 months; HR 0.78) (p = 0.01, each comparison). Further analysis of NSCLC by histological type showed a median survival of 8.6 months for denosumab versus 6.4 months for ZA in patients with squamous cell carcinoma (HR 0.68; p = 0.035). Incidence of overall adverse events was balanced between treatment groups; serious adverse events occurred in 66.0% of denosumab-treated patients and 72.9% of ZA-treated patients. Cumulative incidence of osteonecrosis of the jaw was similar between groups (0.7% denosumab versus 0.8% ZA). Hypocalcemia rates were 8.6% with denosumab and 3.8% with ZA. Conclusion: In this exploratory analysis, denosumab was associated with improved overall survival compared with ZA, in patients with metastatic lung cancer.