Economic burden of acute pesticide poisoning in South Korea

Objectives To investigate the magnitude and characteristics of the economic burden resulting from acute pesticide poisoning (APP) in South Korea. Methods The total costs of APP from a societal perspective were estimated by summing the direct medical and non‐medical costs together with the indirect costs. Direct medical costs for patients assigned a disease code of pesticide poisoning were extracted from the Korean National Health Insurance Reimbursement Data. Direct non‐medical costs were estimated using the average transportation and caregiving costs from the Korea Health Panel Survey. Indirect costs, incurred by pre‐mature deaths and work loss, were obtained using 2009 Life Tables for Korea and other relevant literature. Results In 2009, a total of 11 453 patients were treated for APP and 1311 died, corresponding to an incidence of 23.1 per 100 000 population and a mortality rate of 2.6 per 100 000 population in South Korea. The total costs of APP were estimated at approximately US$ 150 million, 0.3% of the costs of total diseases. Costs due to pre‐mature mortality accounted for 90.6% of the total costs, whereas the contribution of direct medical costs was relatively small. Conclusion Costs from APP demonstrate a unique characteristic of a large proportion of the indirect costs originating from pre‐mature mortality. This finding suggests policy implications for restrictions on lethal pesticides and safe storage to reduce fatality and cost due to APP.     

Reliability of Skeletal Muscle Area Measurement on CT with Different Parameters: A Phantom Study

ObjectiveTo evaluate the reliability of CT measurements of muscle quantity and quality using variable CT parameters.Materials and MethodsA phantom, simulating the L2–4 vertebral levels, was used for this study. CT images were repeatedly acquired with modulation of tube voltage, tube current, slice thickness, and the image reconstruction algorithm. Reference standard muscle compartments were obtained from the reference maps of the phantom. Cross-sectional area based on the Hounsfield unit (HU) thresholds of muscle and its components, and the mean density of the reference standard muscle compartment, were used to measure the muscle quantity and quality using different CT protocols. Signal-to-noise ratios (SNRs) were calculated in the images acquired with different settings.ResultsThe skeletal muscle area (threshold, −29 to 150 HU) was constant, regardless of the protocol, occupying at least 91.7% of the reference standard muscle compartment. Conversely, normal attenuation muscle area (30–150 HU) was not constant in the different protocols, varying between 59.7% and 81.7% of the reference standard muscle compartment. The mean density was lower than the target density stated by the manufacturer (45 HU) in all cases (range, 39.0–44.9 HU). The SNR decreased with low tube voltage, low tube current, and in sections with thin slices, whereas it increased when the iterative reconstruction algorithm was used.ConclusionMeasurement of muscle quantity using HU threshold was reliable, regardless of the CT protocol used. Conversely, the measurement of muscle quality using the mean density and narrow HU thresholds were inconsistent and inaccurate across different CT protocols. Therefore, further studies are warranted in future to determine the optimal CT protocols for reliable measurements of muscle quality.     

Development of an algorithm to automatically compress a CT image to visually lossless threshold

Background

To develop an algorithm to predict the visually lossless thresholds (VLTs) of CT images solely using the original images by exploiting the image features and DICOM header information for JPEG2000 compression and to evaluate the algorithm in comparison with pre-existing image fidelity metrics.

Methods

Five radiologists independently determined the VLT for 206 body CT images for JPEG2000 compression using QUEST procedure. The images were divided into training (n?=?103) and testing (n?=?103) sets. Using the training set, a multiple linear regression (MLR) model was constructed regarding the image features and DICOM header information as independent variables and regarding the VLTs determined with median value of the radiologists’ responses (VLT_rad) as dependent variable, after determining an optimal subset of independent variables by backward stepwise selection in a cross-validation scheme.The performance was evaluated on the testing set by measuring absolute differences and intra-class correlation (ICC) coefficient between the VLT_rad and the VLTs predicted by the model (VLT_model). The performance of the model was also compared two metrics, peak signal-to-noise ratio (PSNR) and high-dynamic range visual difference predictor (HDRVDP). The time for computing VLTs between MLR model, PSNR, and HDRVDP were compared using the repeated ANOVA with a post-hoc analysis. P?<?0.05 was considered to indicate a statistically significant difference.

Results

The means of absolute differences with the VLT_rad were 0.58 (95% CI, 0.48, 0.67), 0.73 (0.61, 0.85), and 0.68 (0.58, 0.79), for the MLR model, PSNR, and HDRVDP, respectively, showing significant difference between them (p?<?0.01). The ICC coefficients of MLR model, PSNR, and HDRVDP were 0.88 (95% CI, 0.81, 0.95), 0.85 (0.79, 0.91), and 0.84 (0.77, 0.91). The computing times for calculating VLT per image were 1.5?±?0.1 s, 3.9?±?0.3 s, and 68.2?±?1.4 s, for MLR metric, PSNR, and HDRVDP, respectively.

Conclusions

The proposed MLR model directly predicting the VLT of a given CT image showed competitive performance to those of image fidelity metrics with less computational expenses. The model would be promising to be used for adaptive compression of CT images.

     

Small area estimation of receiver operating characteristic curves for ordinal data under stochastic ordering

There has been a recent increase in the diagnosis of diseases through radiographic images such as x-rays, magnetic resonance imaging, and computed tomography. The outcome of a radiological diagnostic test is often in the form of discrete ordinal data, and we usually summarize the performance of the diagnostic test using the receiver operating characteristic (ROC) curve and the area under the curve (AUC). The ROC curve will be concave and called proper when the outcomes of the diagnostic test in the actually positive subjects are higher than in the actually negative subjects. The diagnostic test for disease detection is clinically useful when a ROC curve is proper. In this study, we develop a hierarchical Bayesian model to estimate the proper ROC curve and AUC using stochastic ordering in several domains when the outcome of the diagnostic test is discrete ordinal data and compare it with the model without stochastic ordering. The model without stochastic ordering can estimate the improper ROC curve with a nonconcave shape or a hook when the true ROC curve of the population is a proper ROC curve. Therefore, the model with stochastic ordering is preferable over the model without stochastic ordering to estimate the proper ROC curve with clinical usefulness for ordinal data.     

Appendiceal Visualization on 2-mSv CT vs. Conventional-Dose CT in Adolescents and Young Adults with Suspected Appendicitis: An Analysis of Large Pragmatic Randomized Trial Data

ObjectiveWe compared appendiceal visualization on 2-mSv CT vs. conventional-dose CT (median 7 mSv) in adolescents and young adults and analyzed the undesirable clinical and diagnostic outcomes that followed appendiceal nonvisualization.Materials and MethodsA total of 3074 patients aged 15–44 years (mean ± standard deviation, 28 ± 9 years; 1672 female) from 20 hospitals were randomized to the 2-mSv CT or conventional-dose CT group (1535 vs. 1539) from December 2013 through August 2016. A total of 161 radiologists from 20 institutions prospectively rated appendiceal visualization (grade 0, not identified; grade 1, unsure or partly visualized; and grade 2, clearly and entirely visualized) and the presence of appendicitis in these patients. The final diagnosis was based on CT imaging and surgical, pathologic, and clinical findings. We analyzed undesirable clinical or diagnostic outcomes, such as negative appendectomy, perforated appendicitis, more extensive than simple appendectomy, delay in patient management, or incorrect CT diagnosis, which followed appendiceal nonvisualization (defined as grade 0 or 1) and compared the outcomes between the two groups.ResultsIn the 2-mSv CT and conventional-dose CT groups, appendiceal visualization was rated as grade 0 in 41 (2.7%) and 18 (1.2%) patients, respectively; grade 1 in 181 (11.8%) and 81 (5.3%) patients, respectively; and grade 2 in 1304 (85.0%) and 1421 (92.3%) patients, respectively (p < 0.001). Overall, undesirable outcomes were rare in both groups. Compared to the conventional-dose CT group, the 2-mSv CT group had slightly higher rates of perforated appendicitis (1.1% [17] vs. 0.5% [7], p = 0.06) and false-negative diagnoses (0.4% [6] vs. 0.0% [0], p = 0.01) following appendiceal nonvisualization. Otherwise, these two groups were comparable.ConclusionThe use of 2-mSv CT instead of conventional-dose CT impairs appendiceal visualization in more patients. However, appendiceal nonvisualization on 2-mSv CT rarely leads to undesirable clinical or diagnostic outcomes.     

Establishing cut-offs for urine erythrocyte and leukocyte dipstick tests

Urine erythrocyte (Ery) and leukocyte (Leu) dipstick tests are essential for detecting microhematuria and urinary tract infection. Currently, there is no suggestion for establishing the cut-off limits in an ordinal scale test. This study aimed to establish the cut-off limits for urine Ery and Leu dipstick tests via probit regression. From 1 January 2016 to 30 June 2016, laboratory data were collected from patients at one teaching hospital whose specimen had analytical results from both a urine dipstick test and an automated urine particle analyzer. Probit regression was used to estimate the probability of positive urine dipstick results as a function of log-transformed urine Ery and Leu concentrations. Based on the analysis of 22,122 specimens, the estimated concentration that yields 50% positive results (C₅₀) of the Ery weak+, 1+, 2+, 3+, and 4?+?dipstick results were 14.6, 40.4, 51.6, 136.3 and 219.0?×?10⁶/L, respectively. The estimated C₅₀ of the Leu 1+, 2+ and 3?+?dipstick results were 22.7, 67.9 and 283.9?×?10⁶/L, respectively. The estimated values were different from arbitrary concentrations provided for each dipstick category by the manufacturer. If a quantitative comparison method/procedure is available, the cut-off limits of an ordinal scale test can be established using probit regression. Each laboratory should investigate the transferability of the arbitrary concentrations provided by the manufacturer, and if necessary, determine its own cut-off limits of urine Ery and Leu dipstick tests.