BACKGROUND: Health Insurance reimbursement does not accurately reflect the cost of test items performed in a hospital, and it is particularly more difficult to introduce laboratory tests applying new technology. Ensuring the safety of blood bank tests is encumbered since the reimbursement rates for the blood bank items that are high risk are not properly set. In this study, we analyzed the validity of reimbursement through a cost analysis of testing performed in Severance Hospital blood bank. METHODS: Original cost and net income were calculated for the tests performed in Severance Hospital blood bank from 1 January, 2009 to 31 December 2009. RESULTS: The original cost and deficit of ABO & Rh(D) blood tests using an automated blood test analyzer was 4,588 won and 1,572 won (52% compared to reimbursement), respectively. Irregular antibody screening test was 3,416 won in original cost and 3,422 won profit. Lewis antigen test was 10,816 won in original cost, creating a 4,745 won deficit. Irregular antibody identification was 32,568 won in original cost and 17,189 won in deficit. CONCLUSION: Unless the original cost of blood bank tests is reflected in the reimbursement rates, hospital blood banks will run into a budget deficit and blood bank automation, which is used worldwide for patient safety, will not be used in domestic health care.
Automation ; Blood Banks ; Budgets ; Costs and Cost Analysis ; Delivery of Health Care ; Hematologic Tests ; Insurance, Health, Reimbursement ; Mass Screening ; Patient Safety

Background: Quantitation of urine protein is important in dogs with chronic kidney disease.Various analyzers are used to measure urine protein-to-creatinine ratios (UPCR). Objectives: This study aimed to compare the UPCR obtained by three types of analyzers (automated wet chemistry analyzer, in-house dry chemistry analyzer, and dipstick reading device) and investigate whether the differences could affect clinical decision process. Methods: Urine samples were collected from 115 dogs. UPCR values were obtained using three analyzers. Bland-Altman and Passing Bablok tests were used to analyze agreement between the UPCR values. Urine samples were classified as normal or proteinuria based on the UPCR values obtained by each analyzer and concordance in the classification evaluated with Cohen's kappa coefficient. Results: Passing and Bablok regression showed that there were proportional as well as constant difference between UPCR values obtained by a dipstick reading device and those obtained by the other analyzers. The concordance in the classification of proteinuria was very high (κ = 0.82) between the automated wet chemistry analyzer and in-house dry chemistry analyzer, while the dipstick reading device showed moderate concordance with the automated wet chemistry analyzer (κ = 0.52) and in-house dry chemistry analyzer (κ = 0.53). Conclusions Although the urine dipstick test is simple and a widely used point-of-care test, our results indicate that UPCR values obtained by the dipstick test are not appropriate for clinical use. Inter-instrumental variability may affect clinical decision process based on UPCR values and should be emphasized in veterinary practice.

A yeast-like strain was isolated from the brain abscess of a patient diagnosed with astrocytoma. Morphological and molecular analysis on D1/D2 domain in the 26S rRNA gene and internal transcript spacer region of the strain revealed that the strain belonged to the genus Pseudozyma. To the best of our knowledge, this is the first report on the isolation of a Pseudozyma strain from brain abscess.
Aged ; Astrocytoma/*complications ; Brain Abscess/complications/diagnosis/*microbiology ; Brain Diseases/*complications ; DNA, Fungal/genetics ; Humans ; Male ; Mycological Typing Techniques ; Phylogeny ; RNA, Ribosomal/genetics ; Ustilaginales/classification/genetics/*isolation &purification

Precise allergy diagnosis and effective allergen specific immunotherapy are largely dependent on the quality of allergen extract. A new extract of Dermatophagoides farinae was commercially developed by Prolagen. The allergenic properties of the new extract were compared with those of other commercial products. The allergenic properties of the new extract were compared according to protein concentration, protein profiles, major allergen (Der f 1) contents, and allergenic potency to those for three commercially available extracts imported in Korea (Jubilant HollisterStier Allergy, Lofarma S.p.A., and Stallergenes Greer). Protein concentrations varied up to 2.62-fold (0.404 to 1.057 mg/mL), and Der f 1 contents varied up to 11.3-fold (3.597 to 40.688 μg/mL). Protein profiles of the extracts showed no major discrepancies, although there were some differences in SDS-PAGE band intensities, reflecting protein concentrations. Allergen potency ranged from 37038 to 60491 PAU/mL. The Prolagen product was highest in terms of protein concentration and allergen potency. The Lofarma product displayed Der f 1 content similar to that in Prolagen (19.4 μg/mg vs. 19.3 μg/mg). Endotoxin levels varied 8.9-fold (1020 to 8985 EU/mL). The newly developed house dust mite extract showed equal or better allergenic properties than available commercial extracts. This new product may be useful for better diagnostics and allergen-specific immunotherapeutics.

Detecting sphenoid sinus fluid (SSF) is an additional finding in autopsies for diagnosing drowning. SSF can provide additional forensic evidence through laboratory tests such as diatom and electrolyte analyses. If drowning is suspected, accurately assessing the presence and volume of SSF during an autopsy is crucial. Utilizing postmortem computed tomography (PMCT) images could aid in accurately sampling SSF. Accurately segmenting the region of interest is essential for volume analysis using computed tomography images. However, manual segmentation techniques are labor-intensive and time-consuming, and their success depends on the experience of the observer. Therefore, this study aimed to develop a U-Net–based deep learning model for the automatic segmentation of SSF in drowning cases using PMCT images and to evaluate the performance of the model. We retrospectively reviewed 34 drowning cases in which both PMCT scans and forensic autopsies were performed at our institution. The U-Net architecture of deep learning was used for automatic segmentation. The proposed model achieved the Dice similarity coefficient (DSC) and Intersection over Union (IoU) of a maximum of 95.85% and 92.03%, a minimum of 0% and 0%, and an average of 77.15% and 67.18%, respectively. Although the average DSC and IoU did not show high similarity, this study showed that PMCT images can be used for automatic segmentation of SSF in drowning cases, which could improve the performance with sufficient dataset acquisition and further model training.

Mayo imaging classification (MIC) is a useful biomarker to predict disease progression in autosomal dominant polycystic kidney disease (ADPKD). This study was performed to validate MIC in the prediction of renal outcome in a prospective Korean ADPKD cohort and evaluate clinical parameters associated with rapid disease progression. Methods: A total of 178 ADPKD patients were enrolled and prospectively observed for an average duration of 6.2 ± 1.9 years. Rapid progressor was defined as MIC 1C through 1E while slow progressor was defined as 1A through 1B. Renal composite outcome (doubling of serum creatinine, 50% decline of estimated glomerular filtration rate [eGFR], or initiation of renal replacement therapy) as well as the annual percent change of height-adjusted total kidney volume (mHTKV-α), and eGFR decline (mGFR-α) were compared between groups. Results: A total of 110 patients (61.8%) were classified as rapid progressors. These patients were younger and showed a higher proportion of male patients. Rapid progressor was an independent predictor for renal outcome (hazard ratio, 4.09; 95% confidence interval, 1.23–13.54; p = 0.02). The mGFR-α was greater in rapid progressors (–3.58 mL/min per year in 1C, –3.7 in 1D, and –4.52 in 1E) compared with that in slow progressors (–1.54 in 1A and –2.06 in 1B). The mHTKV-α was faster in rapid progressors (5.3% per year in 1C, 9.4% in 1D, and 11.7% in 1E) compared with that in slow progressors (1.2% in 1A and 3.8% in 1B). Conclusion: MIC is a good predictive tool to define rapid progressors in Korean ADPKD patients.