Objective iRENEX is a software module that incorporates scintigraphic and clinical data to interpret 99mTc- mercaptoacetyltriglycine (MAG3) diuretic studies and provide reasons for their conclusions. Our objectives were to compare iRENEX interpretations with those of expert physicians, use iRENEX to evaluate resident performance and determine if iRENEX could improve the diagnostic accuracy of experienced residents. Methods Baseline and furosemide 99mTc-MAG3 acquisitions of 50 patients with suspected obstruction (mean age ± SD, 58.7 ± 15.8 years, 60% female) were randomly selected from an archived database and independently interpreted by iRENEX, three expert readers and four nuclear medicine residents with one full year of residency. All raters had access to scintigraphic data and a text file containing clinical information and scored each kidney on a scale from +1.0 to -1.0. Scores ≥0.20 represented obstruction with higher scores indicating greater confidence. Scores +0.19 to -0.19 were indeterminate; scores ≤-0.20 indicated no obstruction. Several months later, residents reinterpreted the studies with access to iRENEX. Receiver operating characteristic (ROC) analysis and concordance correlation coefficient (CCC) quantified agreement. Results The CCC among experts was higher than that among residents, 0.84, versus 0.39, respectively, P < 0.001. When residents reinterpreted the studies with iRENEX, their CCC improved from 0.39 to 0.73, P < 0.001. ROC analysis showed significant improvement in the ability of residents to distinguish between obstructed and non-obstructed kidneys using iRENEX (P = 0.036). Conclusion iRENEX interpretations were comparable to those of experts. iRENEX reduced interobserver variability among experienced residents and led to better agreement between resident and expert interpretations.
BACKGROUND: Timely hospitalization of patients who are diagnosed with an acute coronary syndrome (ACS) at the emergency department (ED) is a crucial step to lower the risk of ACS mortality. We examined whether there are racial and ethnic differences in the risk of being discharged home among patients who received a diagnostic code of ACS at the ED and whether having health insurance plays a role. METHODS AND RESULTS: We examined 51022910 discharge records of ED visits in Florida, New York, and Utah in the years 2008, 2011, 2014, and 2016/2017 using state-specific data from the Healthcare Cost and Utilization Project. We identified ED admissions for acute myocardial infarction or unstable angina using the International Classification of Diseases, Ninth Revision (ICD-9)/International Statistical Classification of Diseases, Tenth Revision (ICD-10) diagnostic codes. We used generalized estimating equation models to compare the risk of being discharged home across racial and ethnic groups. We used Poisson marginal structural models to estimate the mediating role of health insurance status. The proportion discharged home with a diagnostic code of ACS was 12% among Black patients, 6% among White patients, 9% among Hispanic patients, and 9% among Asian/Pacific Islander patients. The incidence risk ratio for being discharged home was 1.26 (95% CI, 1.18–1.34) in Black patients, 1.23 (95% CI, 1.15–1.32) in Hispanic patients, and 1.11 (95% CI, 0.93–1.31) in Asian/Pacific Islander patients compared with White patients. Race and ethnicity were marginally associated with discharge home via pathways not mediated by health insurance. CONCLUSIONS: Racial and ethnic disparities exist in the hospitalization of patients who received a diagnostic code of ACS in the ED. Possible causes need to be investigated.
Existing missing data methods for functional data mainly focus on reconstructing missing measurements along a single function—a univariate functional data setting. Motivated by a renal study, we focus on a bivariate functional data setting, where each sampling unit is a collection of two distinct component functions, one of which may be missing. Specifically, we propose a Bayesian multiple imputation approach based on a bivariate functional latent factor model that exploits the joint changing patterns of the component functions to allow accurate and stable imputation of one component given the other. We further extend the framework to address multilevel bivariate functional data with missing components by modeling and exploiting inter-component and intra-subject correlations. We develop a Gibbs sampling algorithm that simultaneously generates multiple imputations of missing component functions and posterior samples of model parameters. For multilevel bivariate functional data, a partially collapsed Gibbs sampler is implemented to improve computational efficiency. Our simulation study demonstrates that our methods outperform other competing methods for imputing missing components of bivariate functional data under various designs and missingness rates. The motivating renal study aims to investigate the distribution and pharmacokinetic properties of baseline and post-furosemide renogram curves that provide further insights into the underlying mechanism of renal obstruction, with post-furosemide renogram curves missing for some subjects. We apply the proposed methods to impute missing post-furosemide renogram curves and obtain more refined insights.
The role of endothelium-derived hyperpolarizing factor (EDHF) in either the healthy circulation or in those with hypercholesterolemia is unknown. In healthy and hypercholesterolemic subjects, we measured forearm blood flow (FBF) using strain-gauge plethysmography at rest, during graded handgrip exercise, and after sodium nitroprusside infusion. Measurements were repeated after l-NMMA, tetraethylammonium (TEA), and combined infusions. At rest, l-NMMA infusion reduced FBF in healthy but not hypercholesterolemic subjects. At peak exercise, vasodilation was lower in hypercholesterolemic compared to healthy subjects (274% vs 438% increase in FBF, p=0.017). TEA infusion reduced exercise-induced vasodilation in both healthy and hypercholesterolemic subjects (27%, p<0.0001 and -20%, p<0.0001, respectively). The addition of l-NMMA to TEA further reduced FBF in healthy (-14%, p=0.012) but not in hypercholesterolemic subjects, indicating a reduced nitric oxide and greater EDHF-mediated contribution to exercise-induced vasodilation in hypercholesterolemia. In conclusion, exercise-induced vasodilation is impaired and predominantly mediated by EDHF in hypercholesterolemic subjects. Clinical Trial Registration Identifier: NCT00166166.
In a multivariable logistic regression setting where measuring a continuous exposure requires an expensive assay, a design in which the biomarker is measured in pooled samples from multiple subjects can be very cost effective. A logistic regression model for poolwise data is available, but validity requires that the assay yields the precise mean exposure for members of each pool. To account for errors, we assume the assay returns the true mean exposure plus a measurement error (ME) and/or a processing error (PE). We pursue likelihood-based inference for a binary health-related outcome modeled by logistic regression coupled with a normal linear model relating individual-level exposure to covariates and assuming that the ME and PE components are independent and normally distributed regardless of pool size. We compare this approach with a discriminant function-based alternative, and we demonstrate the potential value of incorporating replicates into the study design. Applied to a reproductive health dataset with pools of size 2 along with individual samples and replicates, the model fit with both ME and PE had a lower AIC than a model accounting for ME only. Relative to ignoring errors, this model suggested a somewhat higher (though still nonsignificant) adjusted log-odds ratio associating the cytokine MCP-1 with risk of spontaneous abortion. Simulations modeled after these data confirm validity of the methods, demonstrate how ME and particularly PE can reduce the efficiency advantage of a pooling design, and highlight the value of replicates in improving stability when both errors are present.
The purpose of the study was to compare diuresis renography scan interpretation generated by a renal expert system with the consensus interpretation of 3 expert readers.Methods
The expert system was evaluated in 95 randomly selected furosemide-augmented patient studies (185 kidneys) obtained for suspected obstruction; there were 55 males and 40 females with a mean age ± SD of 58.6 ± 16.5 y. Each subject had a baseline 99mTc-mercaptoacetyltriglycine (99mTc-MAG3) scan followed by furosemide administration and a separate 20-min acquisition. Quantitative parameters were automatically extracted from baseline and furosemide acquisitions and forwarded to the expert system for analysis. Three experts, unaware of clinical information, independently graded each kidney as obstructed/probably obstructed, equivocal, and probably nonobstructed/nonobstructed; experts resolved differences by a consensus reading. These 3 expert categories were compared with the obstructed, equivocal, and nonobstructed interpretations provided by the expert system. Agreement was assessed using weighted κ, and the predictive accuracy of the expert system compared with expert readers was assessed by the area under receiver-operating-characteristic (ROC curve) curves.
Results
The expert system agreed with the consensus reading in 84% (101/120) of nonobstructed kidneys, in 92% (33/36) of obstructed kidneys, and in 45% (13/29) of equivocal kidneys. The weighted κ between the expert system and the consensus reading was 0.72 and was comparable with the weighted κ between experts. There was no significant difference in the areas under the ROC curves when the expert system was compared with each expert using the other 2 experts as the gold standard.
Conclusion
The renal expert system showed good agreement with the expert interpretation and could be a useful educational and decision support tool to assist physicians in the diagnosis of renal obstruction. To better mirror the clinical setting, algorithms to incorporate clinical data must be designed, implemented, and tested.
OBJECTIVE
The purpose of this study was to compare the decisions regarding the need for furosemide made by two independent renal decision support systems, RENEX and CARTAN, with the need for furosemide determined in clinical practice and by expert reviewers using the baseline plus furosemide protocol.
SUBJECTS AND METHODS
RENEX and CARTAN are independent decision support systems that reach their conclusions without operator input. RENEX is a knowledge-based system and CARTAN is a statistical decision support system. Both were trained using the same pilot group of 31 adult patients (61 kidneys) referred for suspected obstruction. Subsequently, both systems were prospectively applied to 102 patients (200 kidneys) of whom 70 received furosemide; decisions regarding the need for furosemide were compared with the clinical decisions and the decisions of three experts who independently scored each kidney on the need for furosemide. Differences were resolved by consensus.
RESULTS
RENEX agreed with the clinical and experts’ decisions to give furosemide in 97% (68/70) and 98% (65/66) of patients, respectively, whereas CARTAN agreed in 90% (63/70) and 89% (59/66), respectively, p < 0.03. In contrast, CARTAN agreed with the experts’ decision to withhold furosemide in 78% of kidneys (87/111), whereas RENEX agreed in only 69% of kidneys (77/111), p = 0.008.
CONCLUSION
Use of RENEX or CARTAN as decision support tools in the baseline plus furosemide protocol has the potential to help the radiologist avoid unnecessary imaging and reduce the technologist, computer, camera, and physician time required to perform the procedure.
We derive a new functional representation of Broad Sense Agreement (BSA) index that evaluates the agreement/alignment between a continuous measurement and an ordinary measurement. Using this result, we develop an alternative BSA estimator, which can offer significant numerical advantages.
Rationale and Objectives
Decision support systems have the capacity to improve diagnostic performance and reduce physician errors. The purpose of this study was to evaluate the use of classification and regression trees (CART) with bootstrap aggregation as a decision support system in the baseline plus furosemide (F + 20) diuresis renography protocol to determine when obstruction can be excluded without the furosemide acquisition and to identify the key parameters for making this determination.
Materials and Methods
Patients with suspected ureteral obstruction were randomly assigned to a training set (80 patients, 157 kidneys) and a validation set (64 patients, 124 kidneys). Forty quantitative parameters (curve parameters, MAG3 clearance and voiding indices) were generated from each baseline Tc-99m mercaptoacetyltriglycine (MAG3) scan. Three expert readers independently evaluated each kidney regarding the need for furosemide and resolved differences by majority vote. CART with bootstrap aggregation was applied to the training set to generate prediction algorithms which were tested in the validation set.
Results
The algorithm agreed with the expert decision on the necessity of furosemide in 90% (111 of 124 kidneys), with misclassification rates of 10.0% and 10.9% for the left and right kidneys, respectively. The most important discriminators were the postvoid-to-maximum count ratio, the cortical 20-minute-to-maximum count ratio, and the postvoid-to-1-to-2-minute count ratio.
Conclusion
CART can identify the key parameters for discriminating between nonobstruction and possible obstruction, has the potential to serve as a decision support tool to avoid unnecessary furosemide imaging, and can be applied to more complex imaging problems.