Modeling Agreement between Binary Classifications of Multiple Raters in R and SAS

Cancer screening and diagnostic tests often are classified using a binary outcome such as diseased or not diseased. Recently large-scale studies have been conducted to assess agreement between many raters. Measures of agreement using the class of generalized linear mixed models were implemented efficiently in four recently introduced R and SAS packages in large-scale agreement studies incorporating binary classifications. Simulation studies were conducted to compare the performance across the packages and apply the agreement methods to two cancer studies

Multiple Imputation When Rate of Change Is The Outcome of Interest

Little research has been devoted to multiple imputation (MI) of derived variables. We investigated various MI approaches for the outcome, rate of change, when the analysis model is a two-stage linear regression. Our simulations showed that competitive approaches depended on the missing data mechanism and presence of auxiliary terms

Descending aortic calcification increases renal dysfunction and in-hospital mortality in cardiac surgery patients with intraaortic balloon pump counterpulsation placed perioperatively : a case control study

Introduction: Acute kidney injury (AKI) after cardiac surgery increases length of hospital stay and in-hospital mortality. A significant number of patients undergoing cardiac surgical procedures require perioperative intra-aortic balloon pump (IABP) support. Use of an IABP has been linked to an increased incidence of perioperative renal dysfunction and death. This might be due to dislodgement of atherosclerotic material in the descending thoracic aorta (DTA). Therefore, we retrospectively studied the correlation between DTA atheroma, AKI and in-hospital mortality. Methods: A total of 454 patients were retrospectively matched to one of four groups: -IABP/-DTA atheroma, +IABP/-DTA atheroma, -IABP/+DTA atheroma, +IABP/+DTA atheroma. Patients were then matched according to presence/absence of DTA atheroma, presence/absence of IABP, performed surgical procedure, age, gender and left ventricular ejection fraction (LVEF). DTA atheroma was assessed through standard transesophageal echocardiography (TEE) imaging studies of the descending thoracic aorta. Results: Basic patient characteristics, except for age and gender, did not differ between groups. Perioperative AKI in patients with -DTA atheroma/+IABP was 5.1% versus 1.7% in patients with -DTA atheroma/-IABP. In patients with +DTA atheroma/+IABP the incidence of AKI was 12.6% versus 5.1% in patients with +DTA atheroma/-IABP. In-hospital mortality in patients with +DTA atheroma/-IABP was 3.4% versus 8.4% with +DTA atheroma/+IABP. In patients with +DTA atheroma/+IABP in hospital mortality was 20.2% versus 6.4% with +DTA atheroma/-IABP. Multivariate logistic regression identified DTA atheroma > 1 mm (P = *0.002, odds ratio (OR) = 4.13, confidence interval (CI) = 1.66 to 10.30), as well as IABP support (P = *0.015, OR = 3.04, CI = 1.24 to 7.45) as independent predictors of perioperative AKI and increased in-hospital mortality. DTA atheroma in conjunction with IABP significantly increased the risk of developing acute kidney injury (P = 0.0016) and in-hospital mortality (P = 0.0001) when compared to control subjects without IABP and without DTA atheroma. Conclusions: Perioperative IABP and DTA atheroma are independent predictors of perioperative AKI and in-hospital mortality. Whether adding an IABP in patients with severe DTA calcification increases their risk of developing AKI and mortality postoperatively cannot be clearly answered in this study. Nevertheless, when IABP and DTA are combined, patients are more likely to develop AKI and to die postoperatively in comparison to patients without IABP and DTA atheroma

Lung Injury Prediction Score for the Emergency Department: First Step Towards Prevention in Patients at Risk

Background: Early identification of patients at risk of developing acute lung injury (ALI) is critical for potential preventive strategies. We aimed to derive and validate an acute lung injury prediction score (EDLIPS) in a multicenter sample of emergency department (ED) patients. Methods: We performed a subgroup analysis of 4,361 ED patients enrolled in the previously reported multicenter observational study. ED risk factors and conditions associated with subsequent ALI development were identified and included in the EDLIPS model. Scores were derived and validated using logistic regression analyses. The model was assessed with the area under the receiver-operating curve (AUC) and compared to the original LIPS model (derived from a population of elective high-risk surgical and ED patients) and the Acute Physiology and Chronic Health Evaluation (APACHE II) score. Results: The incidence of ALI was 7.0% (303/4361). EDLIPS discriminated patients who developed ALI from those who did not with an AUC of 0.78 (95% CI 0.75, 0.82), better than the APACHE II AUC 0.70 (p ≤ 0.001) and similar to the original LIPS score AUC 0.80 (p = 0.07). At an EDLIPS cutoff of 5 (range −0.5, 15) positive and negative likelihood ratios (95% CI) for ALI development were 2.74 (2.43, 3.07) and 0.39 (0.30, 0.49), respectively, with a sensitivity 0.72(0.64, 0.78), specificity 0.74 (0.72, 0.76), and positive and negative predictive value of 0.18 (0.15, 0.21) and 0.97 (0.96, 0.98). Conclusion: EDLIPS may help identify patients at risk for ALI development early in the course of their ED presentation. This novel model may detect at-risk patients for treatment optimization and identify potential patients for ALI prevention trials

Trends in Anemia Care in Older Patients Approaching End-Stage Renal Disease in the United States (1995-2010)

Anemia is common in patients with advanced chronic kidney disease. While the treatment of anemia in patients with end-stage renal disease (ESRD) has attracted considerable attention, relatively little is known about patterns and trends in the anemia care received by patients before initiating maintenance dialysis or pre-emptive kidney transplantation

Towards Prevention of Acute Lung Injury: Frequency and Outcomes of Emergency Department Patients At-Risk: A Multicenter Cohort Study

Background: Few emergency department (ED) evaluations on acute lung injury (ALI) have been carried out; hence, we sought to describe a cohort of hospitalized ED patients at risk for ALI development. Methods: Patients presenting to the ED with at least one predisposing condition to ALI were included in this study, a subgroup analysis of a multicenter observational cohort study (USCIITG-LIPS 1). Patients who met ALI criteria within 6 h of initial ED assessment, received end-of-life care, or were readmitted during the study period were excluded. Primary outcome was frequency of ALI development; secondary outcomes were ICU and hospital mortality. Results: Twenty-two hospitals enrolled 4,361 patients who were followed from the ED to hospital discharge. ALI developed in 303 (7.0 %) patients at a median onset of 2 days (IQR 2–5). Of the predisposing conditions, frequency of ALI development was highest in patients who had aortic surgery (43 %) and lowest in patients with pancreatitis (2.8 %). Compared to patients who did not develop ALI, those who did had higher ICU (24 % vs. 3.0 %, p < 0.001) and hospital (28 % vs. 4.6 %, p < 0.001) mortality, and longer hospital length of stay (16 vs. 5 days, p < 0.001). Among the 22 study sites, frequency of ALI development varied from less than 1 % to more than 12 % after adjustment for APACHE II. Conclusions: Seven percent of hospitalized ED patients with at least one predisposing condition developed ALI. The frequency of ALI development varied significantly according to predisposing conditions and across institutions. Further research is warranted to determine the factors contributing to ALI development

Guidelines for generating right-censored outcomes from a cox model extended to accommodate time-varying covariates

Simulating studies with right-censored outcomes as functions of time-varying covariates is discussed. Guidelines on the use of an algorithm developed by Zhou and implemented by Hendry are provided. Through simulation studies, the sensitivity of the method to user inputs is considered

Comparative outcomes of predominant facility-level use of ferumoxytol versus other intravenous iron formulations in incident hemodialysis patients

Ferumoxytol was first approved for clinical use in 2009 solely based on data from trial comparisons with oral iron on biochemical anemia efficacy end points. To compare the rates of important patient outcomes (infection, cardiovascular events and death) between facilities predominantly using ferumoxytol versus iron sucrose (IS) or ferric gluconate (FG) in patients with end-stage renal disease (ESRD)-initiating hemodialysis (HD)

Longer-term Outcomes of Darbepoetin Alfa Versus Epoetin Alfa in Patients With ESRD Initiating Hemodialysis: A Quasi-experimental Cohort Study

Adequately-powered studies directly comparing hard clinical outcomes of darbepoetin alfa (DPO) versus epoetin alfa (EPO) in patients undergoing dialysis are lacking

A robust measure of correlation between two genes on a microarray

<p>Abstract</p> <p>Background</p> <p>The underlying goal of microarray experiments is to identify gene expression patterns across different experimental conditions. Genes that are contained in a particular pathway or that respond similarly to experimental conditions could be co-expressed and show similar patterns of expression on a microarray. Using any of a variety of clustering methods or gene network analyses we can partition genes of interest into groups, clusters, or modules based on measures of similarity. Typically, Pearson correlation is used to measure distance (or similarity) before implementing a clustering algorithm. Pearson correlation is quite susceptible to outliers, however, an unfortunate characteristic when dealing with microarray data (well known to be typically quite noisy.)</p> <p>Results</p> <p>We propose a resistant similarity metric based on Tukey's biweight estimate of multivariate scale and location. The resistant metric is simply the correlation obtained from a resistant covariance matrix of scale. We give results which demonstrate that our correlation metric is much more resistant than the Pearson correlation while being more efficient than other nonparametric measures of correlation (e.g., Spearman correlation.) Additionally, our method gives a systematic gene flagging procedure which is useful when dealing with large amounts of noisy data.</p> <p>Conclusion</p> <p>When dealing with microarray data, which are known to be quite noisy, robust methods should be used. Specifically, robust distances, including the biweight correlation, should be used in clustering and gene network analysis.</p