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OBJECTIVE: Delta bilirubin (albumin-covalently bound bilirubin) may provide important clinical utility in identifying impaired hepatic excretion of conjugated bilirubin, but it cannot be measured in real-time for diagnostic purposes in clinical laboratories. METHODS: A total of 210 samples were collected, and their delta bilirubin levels were measured four times using high-performance liquid chromatography. Data collected included age, sex, diagnosis code, delta bilirubin, total bilirubin, direct bilirubin, total protein, albumin, globulin, aspartate aminotransferase, alanine transaminase, alkaline phosphatase, gamma-glutamyl transferase, lactate dehydrogenase, hemoglobin, serum hemolysis value, hemolysis index, icterus value (Iv), icterus index (Ii), lipemia value (Lv), and lipemia index. To conduct feature selection and identify the optimal combination of variables, linear regression machine learning was performed 1,000 times. RESULTS: The selected variables were total bilirubin, direct bilirubin, total protein, albumin, hemoglobin, Iv, Ii, and Lv. The best predictive performance for high delta bilirubin concentrations was achieved with the combination of albumin-direct bilirubin-hemoglobin-Iv-Lv. The final equation composed of these variables was as follows: delta bilirubin = 0.35 × Iv + 0.05 × Lv - 0.23 × direct bilirubin - 0.05 × hemoglobin - 0.04 × albumin + 0.10. CONCLUSION: The equation established in this study is practical and can be easily applied in real-time in clinical laboratories.

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Increased body fluids during pregnancy complicates the application of estimated glomerular filtration rate (eGFR) formulas that are based on body surface area. Furthermore, gestational renal dysfunction cannot be identified if the serum creatinine (SCr) concentration is within the non-pregnant reference interval (RI) despite inadequate pregnancy-related renal hyperfiltration. 1484 SCr measurements from 957 healthy pregnant women were collected. The average SCr value of gestational week (GW) 0-3 was the representative SCr value of non-pregnant status. While the distribution of SCr measurements varied across GWs, it was transformed into a normal distribution using the bootstrap resampling method. A polynomial linear regression method was applied to achieve a continuous and smooth transformation of values. The normally distributed SCr values of each GW were compared to the non-pregnant status, leading to the calculation of SCr hyperfiltration. The final equation, (2 - SCr (µmol/L) / 55.25) × 103.1 × 55.25/(56.7 - 0.223 × GW - 0.113 × GW2 + 0.00545 × GW3 - 0.0000653 × GW4), and reference intervals for both SCr and eGFR for each GW were obtained. These RIs and novel equations can be effectively used to monitor renal dysfunction in pregnant women.

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Pre-eclampsia (PE) is a pregnancy-related disease, causing significant threats to both mothers and babies. Numerous studies have identified the association between PE and renal dysfunction. However, in clinical practice, kidney problems in pregnant women are often overlooked due to physiologic adaptations during pregnancy, including renal hyperfiltration. Recent studies have reported serum creatinine (SCr) level distribution based on gestational age (GA) and demonstrated that deviations from the expected patterns can predict adverse pregnancy outcomes, including PE. This study aimed to establish a PE prediction model using expert knowledge and by considering renal physiologic adaptation during pregnancy. This retrospective study included pregnant women who delivered at the Wonju Severance Christian Hospital. Input variables, such as age, gestational weeks, chronic diseases, and SCr levels, were used to establish the PE prediction model. By integrating SCr, GA, GA-specific SCr distribution, and quartile groups of GA-specific SCr (GAQ) were made. To provide generalized performance, a random sampling method was used. As a result, GAQ improved the predictive performance for any cases of PE and triple cases, including PE, preterm birth, and fetal growth restriction. We propose a prediction model for PE consolidating readily available clinical blood test information and pregnancy-related renal physiologic adaptations.

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PURPOSE: Despite decreased prevalence of tuberculosis, the incidence of the diseases associated with nontuberculous mycobacteria (NTM) has been increasing in South Korea and around the world. The present retrospective study was conducted to determine longitudinal changes in the epidemiology and distribution of NTM over 13 years at a tertiary care hospital in Korea. MATERIALS AND METHODS: We retrospectively analyzed data on Mycobacterium species over 13 years (January 2007 to December 2019) by utilizing the laboratory information system. Mycobacterium species were identified using biochemical tests and PCR-restriction fragment length polymorphism and Mycobacteria GenoBlot assays. RESULTS: After excluding duplicates from the initial pool of 17996 mycobacterial isolates, 7674 strains were analyzed and 2984 (38.9%) NTM were isolated. The proportion of NTM continuously increased over the 13-year period, from 17.0% in 2007 to 57.5% in 2019. Among the NTM isolates, the most common species were Mycobacterium intracellulare (50.6%), M. avium (18.3%), M. fortuitumcomplex (4.9%), M. abscessus (4.5%), M. gordonae (3.3%), M. kansasii (1.1%), M. chelonae (1.0%), and M. massiliense (0.9%). In patients over the age of 70 years, the proportion of NTM among the isolates increased from 26.6% in 2007 to 62.0% in 2019, and that of M. intracellulare isolates among the NTM increased from 13.9% (11/79) in 2007 to 37.4% (175/468) in 2019. CONCLUSION: The number of NTM isolates continuously increased over the study period, and the increase in the proportion of M.intracellulare in patients aged over 70 years was notable.

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Carbapenemase-producing Enterobacteriaceae (CPE) is an important and increasing threat to global health. From July to September 2017, 20 inpatients at a tertiary care hospital in Korea were either colonized or infected with carbapenem-resistant Escherichia coli strains. All of E. coli isolates co-produced blaNDM-5 and blaOXA-181 carbapenemase genes and shared ≥88% clonal relatedness on the basis of a cladistic calculation of the distribution of pulsed-field gel electrophoresis patterns. Rapid detection of CPE is one of the most important factors to prevent CPE dissemination because it takes long time for CPE to become negative.

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Severe fever with thrombocytopenia syndrome (SFTS) is an emerging infectious zoonosis caused by the SFTS virus. Hemophagocytic lymphohistiocytosis (HLH) is a life-threatening syndrome associated with excessive immune activation. Cytokine storms are often seen in both SFTS and HLH, resulting in rapid disease progression and poor prognosis. The aim of this study was to identify whether SFTS cases complicated by HLH are related to higher rates of mortality. Descriptive analysis of the frequency of clinical and laboratory data, complications, treatment outcomes, and HLH-2004 criteria was performed. Cases presenting with five or more clinical or laboratory findings corresponding to the HLH-2004 diagnostic criteria were defined as SFTS cases complicated by HLH. Eighteen cases of SFTS were identified during a 2-year study period, with a case-fatality proportion of 22.2% (4 among 18 cases, 95% confidence interval 9%-45.2%). SFTS cases complicated by HLH were identified in 33.3% (6 among 18 cases). A mortality rate of 75% (3 among 4 cases) was recorded among SFTS cases complicated by HLH. Although there were no statistically significant differences in outcomes, fatal cases exhibited more frequent correlation with HLH-2004 criteria than non-fatal cases [3/14 (21.4%) vs. 3/4 (75%), p=0.083]. In conclusion, the present study suggests the possibility that SFTS cases complicated by HLH are at higher risk of poor prognosis.

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Rapid and accurate detection of rifampin-resistant Mycobacterium tuberculosis (MTB) is of primary importance for infection control and selection of anti-tuberculosis drugs. The aim of this study was to evaluate the usefulness of a newly developed multiplexed, bead-based bioassay (Quantamatrix Multiplexed Assay Platform, QMAP) for the direct detection of rifampin-resistant MTB in respiratory specimens. A total of 400 respiratory specimens collected from patients with clinically suspected tuberculosis or non-tuberculous mycobacteria (NTM) infections were tested with the culture-based conventional Mycobacterium species identification and QMAP system. Among 400 specimens, 154 samples were evaluated using phenotypic anti-tuberculosis drug susceptibility test (DST) and the QMAP system for the detection of rifampin resistance. Detection agreement rate between the culture-based conventional identification and QMAP system for MTB and NTM according to acid-fast bacillus smear positivity was as follows: 97.0% (131/135) and 93.6% (88/94) in 229 smear-positive samples and 69.4% (25/36) and 73.0% (65/89) in 171 smear-negative samples. Based on culture as the gold standard, the overall sensitivity and specificity of the QMAP system for Mycobacterium identification were 87.3 and 97.8%, respectively. The categorical agreement rate between phenotypic DST and QMAP system for rifampin was as follows: complete agreement, 92.9% (143/154); very major error, 0%; and major error, 0.6% (1/154). The overall sensitivity of the QMAP system for the detection of rifampin resistance was 97.1% (34/35). The QMAP system is a useful screening method for the early diagnosis of tuberculosis and selection of anti-tuberculosis drug, as it may detect rifampin-resistant MTB directly from respiratory specimens.

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False positive signals (FPSs) of continuous monitoring blood culture system (CMBCS) cause delayed reporting time and increased laboratory cost. This study aimed to analyze growth graphs digitally in order to identify specific patterns of FPSs and true positive signals (TPSs) and to find the method for improving positive predictive value (PPV) of FPS and TPS. 606 positive signal samples from the BACTEC FX (BD, USA) CMBCS with more than one hour of monitoring data after positive signal were selected, and were classified into FPS and TPS groups using the subculture results. The pattern of bacterial growth graph was analyzed in two steps: the signal stage recorded using the monitoring data until positive signal and the post-signal stage recorded using one additional hour of monitoring data gained after the positive signal. The growth graph before the positive signal consists of three periods; initial decline period, stable period, and steeping period. Signal stage analyzed initial decline period and stable period, and classified the graphs as standard, increasing, decreasing, irregular, or defective pattern, respectively. Then, all patterns were re-assigned as confirmed or suspicious pattern in the post-signal stage. Standard, increasing, and decreasing patterns with both initial decline period and stable period are typical patterns; irregular patterns lacking a smooth stable period and defective patterns without an initial decline period are false positive patterns. The false positive patterns have 77.2% of PPV for FPS. The confirmed patterns, showing a gradually increasing fluorescence level even after positive signal, have 97.0% of PPV for TPS.

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