Background: Hemolysis is an important preanalytical factor that influences laboratory test results. Because arterial blood gas analysis (ABGA) is performed using whole blood, it is difficult to visually check whether a specimen is hemolyzed, and even blood gas analyzers cannot detect hemolysis. However, there is insufficient consensus on the parameters that are influenced by hemolyzed specimens. This study aimed to determine the effect of hemolysis on ABGA results. Methods: One hundred residual arterial blood specimens were collected from Severance Hospital between March and April 2022. Samples were aliquoted into three groups for mechanical hemolysis. Hemolysis was induced using 16-, 22-, and 26-gauge needles and measured using the Profile pHOx Ultra Blood Gas Analyzer (Nova Biomedical, USA). The remaining blood was centrifuged, and the hemolysis index was determined using the plasma. Results: Among the parameters, pH and K increased, whereas pCO 2 , Na,Ca 2+ , and HCO 3− decreased. The values of Hb, Mg2+ , and Hct did not change with the degree of hemolysis, although there was a difference between the two groups. The values of pCO 2 , Hb, K, and Ca 2+ increased as the degree of hemolysis increased, with % biases exceeding the desirable bias. Conclusions This study confirmed that hemolysis significantly influences pH, pCO 2 , and K. Therefore, when clinical findings and blood gas analysis results are inconsistent, clinicians should be cautious of spurious hemolysis when interpreting the results.

Background: Hemolysis is an important preanalytical factor that influences laboratory test results. Because arterial blood gas analysis (ABGA) is performed using whole blood, it is difficult to visually check whether a specimen is hemolyzed, and even blood gas analyzers cannot detect hemolysis. However, there is insufficient consensus on the parameters that are influenced by hemolyzed specimens. This study aimed to determine the effect of hemolysis on ABGA results. Methods: One hundred residual arterial blood specimens were collected from Severance Hospital between March and April 2022. Samples were aliquoted into three groups for mechanical hemolysis. Hemolysis was induced using 16-, 22-, and 26-gauge needles and measured using the Profile pHOx Ultra Blood Gas Analyzer (Nova Biomedical, USA). The remaining blood was centrifuged, and the hemolysis index was determined using the plasma. Results: Among the parameters, pH and K increased, whereas pCO 2 , Na,Ca 2+ , and HCO 3− decreased. The values of Hb, Mg2+ , and Hct did not change with the degree of hemolysis, although there was a difference between the two groups. The values of pCO 2 , Hb, K, and Ca 2+ increased as the degree of hemolysis increased, with % biases exceeding the desirable bias. Conclusions This study confirmed that hemolysis significantly influences pH, pCO 2 , and K. Therefore, when clinical findings and blood gas analysis results are inconsistent, clinicians should be cautious of spurious hemolysis when interpreting the results.

Background: Hemolysis is an important preanalytical factor that influences laboratory test results. Because arterial blood gas analysis (ABGA) is performed using whole blood, it is difficult to visually check whether a specimen is hemolyzed, and even blood gas analyzers cannot detect hemolysis. However, there is insufficient consensus on the parameters that are influenced by hemolyzed specimens. This study aimed to determine the effect of hemolysis on ABGA results. Methods: One hundred residual arterial blood specimens were collected from Severance Hospital between March and April 2022. Samples were aliquoted into three groups for mechanical hemolysis. Hemolysis was induced using 16-, 22-, and 26-gauge needles and measured using the Profile pHOx Ultra Blood Gas Analyzer (Nova Biomedical, USA). The remaining blood was centrifuged, and the hemolysis index was determined using the plasma. Results: Among the parameters, pH and K increased, whereas pCO 2 , Na,Ca 2+ , and HCO 3− decreased. The values of Hb, Mg2+ , and Hct did not change with the degree of hemolysis, although there was a difference between the two groups. The values of pCO 2 , Hb, K, and Ca 2+ increased as the degree of hemolysis increased, with % biases exceeding the desirable bias. Conclusions This study confirmed that hemolysis significantly influences pH, pCO 2 , and K. Therefore, when clinical findings and blood gas analysis results are inconsistent, clinicians should be cautious of spurious hemolysis when interpreting the results.

Background: Hemolysis is an important preanalytical factor that influences laboratory test results. Because arterial blood gas analysis (ABGA) is performed using whole blood, it is difficult to visually check whether a specimen is hemolyzed, and even blood gas analyzers cannot detect hemolysis. However, there is insufficient consensus on the parameters that are influenced by hemolyzed specimens. This study aimed to determine the effect of hemolysis on ABGA results. Methods: One hundred residual arterial blood specimens were collected from Severance Hospital between March and April 2022. Samples were aliquoted into three groups for mechanical hemolysis. Hemolysis was induced using 16-, 22-, and 26-gauge needles and measured using the Profile pHOx Ultra Blood Gas Analyzer (Nova Biomedical, USA). The remaining blood was centrifuged, and the hemolysis index was determined using the plasma. Results: Among the parameters, pH and K increased, whereas pCO 2 , Na,Ca 2+ , and HCO 3− decreased. The values of Hb, Mg2+ , and Hct did not change with the degree of hemolysis, although there was a difference between the two groups. The values of pCO 2 , Hb, K, and Ca 2+ increased as the degree of hemolysis increased, with % biases exceeding the desirable bias. Conclusions This study confirmed that hemolysis significantly influences pH, pCO 2 , and K. Therefore, when clinical findings and blood gas analysis results are inconsistent, clinicians should be cautious of spurious hemolysis when interpreting the results.

Background: Hemolysis is an important preanalytical factor that influences laboratory test results. Because arterial blood gas analysis (ABGA) is performed using whole blood, it is difficult to visually check whether a specimen is hemolyzed, and even blood gas analyzers cannot detect hemolysis. However, there is insufficient consensus on the parameters that are influenced by hemolyzed specimens. This study aimed to determine the effect of hemolysis on ABGA results. Methods: One hundred residual arterial blood specimens were collected from Severance Hospital between March and April 2022. Samples were aliquoted into three groups for mechanical hemolysis. Hemolysis was induced using 16-, 22-, and 26-gauge needles and measured using the Profile pHOx Ultra Blood Gas Analyzer (Nova Biomedical, USA). The remaining blood was centrifuged, and the hemolysis index was determined using the plasma. Results: Among the parameters, pH and K increased, whereas pCO 2 , Na,Ca 2+ , and HCO 3− decreased. The values of Hb, Mg2+ , and Hct did not change with the degree of hemolysis, although there was a difference between the two groups. The values of pCO 2 , Hb, K, and Ca 2+ increased as the degree of hemolysis increased, with % biases exceeding the desirable bias. Conclusions This study confirmed that hemolysis significantly influences pH, pCO 2 , and K. Therefore, when clinical findings and blood gas analysis results are inconsistent, clinicians should be cautious of spurious hemolysis when interpreting the results.

The establishment and prompt reporting of critical values to patient care providers is one of the crucial requirements of clinical laboratories. Each laboratory is expected to individually establish the thresholds of critical values and periodically update the lists. In this study, we attempted to investigate the status of critical value reporting (CVR) systems in Korean clinical laboratories and develop adequate guidelines based on comparative reviews examining expert consensus. In responses from 11 clinical laboratories, the number of test items with a critical value threshold was 9.4 on average (standard deviation=5.0). Some of the test items, especially ammonia, lactate, and carboxyhemoglobin, lacked critical value thresholds despite having been recommended by expert opinions and guidelines. The upper limit of critical value thresholds showed variability, with glucose showing the largest difference among laboratories (range, 450–700 mg/ dL; coefficient of variation=14.7%). When evaluating the appropriateness of establishing critical value for a particular test, it is generally recommended to consider the “actionability” factors, which consist of effectiveness in decreasing mortality, availability of immediate response systems, and inclusion of the decision-making process in the institution’s critical pathway of standard patient care. As for the optimal value of individual thresholds, laboratory managers should review three quantitative markers: the ratio of CVR cases in total reported results, the ratio of confirmed CVR and responses by clinicians in total CVR cases, and the turnaround time of the tests assigned with critical value thresholds.

Background: Remdesivir is a US Food and Drug Administration-approved drug for coronavirus disease 2019 (COVID-19). Clinical trials were conducted under strictly controlled situations for a selected population, and their reported adverse events may not fully represent conditions in real-world patients. We aimed to estimate the incidence of adverse drug events (ADEs) associated with remdesivir in hospitalized patients with COVID-19, including vulnerable subpopulations, such as those with impaired renal or hepatic function and pregnant women. Methods: This retrospective observational study included hospitalized patients with confirmed COVID-19 treated with remdesivir between January and December 2021 at ten hospitals. ADEs and severe ADEs (Common Toxicity Criteria for Adverse Events grade ≥ 3) were operationally defined and analyzed through laboratory investigations. The incidence of ADEs was compared with that of each matched control in subpopulations with renal or hepatic impairment and pregnant women. Results: Among 2,140 patients, 1,416 (66.2%) and 295 (13.8%) experienced at least one ADE and severe ADE, respectively. The most frequent ADE was 'hepatic injury' (42.9%), followed by anemia (27.6%). The most common severe ADEs were 'hypokalemia' (5.3%), 'hepatic injury' (2.9%), and 'anemia' (3.6%). There was no significant difference in the incidence of ADEs in patients relative to their respective matched-control groups, including those with renal impairment (80.0% vs. control 71.8%, P = 0.063), hepatic impairment (70.4% vs. control 75.0%, P = 0.623) and pregnant women (78.6% vs. control 63.7%, P = 0.067). However, severe ADE incidence was significantly higher in patients with renal impairment (40.8% vs. 16.0%, P < 0.001). The most common severe ADEs in those were 'anemia' (15.3%), 'hypokalemia' (10.5%), and 'thrombocytopenia' (8.9%). There was no statistically significant difference in the incidence of severe ADEs in patients with hepatic impairment or in pregnancy (P = 0.230; P = 0.085). Conclusion A significant proportion of patients with COVID-19 treated with remdesivir experienced ADEs and severe ADEs. Given the high incidence of severe ADEs, caution is required in patients with renal impairment. Further studies are needed to investigate ADEs in pregnant women and patients with hepatic impairment.

Background: Accurate measurement of glycated hemoglobin (HbA1c) is crucial for a diabetes diagnosis and subsequent patient management. The detection method and presence of variant Hb can interfere with HbA1c measurements. We evaluated the HbA1c-measuring performance of the DxC 700 AU (Beckman Coulter, Brea, CA, USA) immunoassay-based device in comparison with another immunoassay device and the reference method. Methods: A total of 120 normal and 14 variant Hb samples were analyzed using the Cobas c 513 (Roche Diagnostics, Mannheim, Germany) and DxC 700 AU analyzers. Variant Hb samples were also analyzed using the reference method, along with 20 normal samples. The accuracy, precision, linearity, and carryover were determined. Results: DxC 700 AU results strongly correlated with those of Cobas c 513 and exhibited accuracy in comparison with the reference method. The within-run, between-run, between-day, and total imprecision (%CV) values for the low- and high-concentration control materials were below 2%. The results of DxC 700 AU were linear over a wide HbA1c range (3.39%–18.30%). Although DxC 700 AU performed well in the presence of variant Hb, the HbA1c concentration was underestimated in the presence of fetal Hb. The possibility of interference from a high HbH proportion could not be ruled out. Conclusions The overall analytical performance of DxC 700 AU was acceptable. The device is accurate, precise, and linear over a wide HbA1c concentration range. Although DxC 700 AU results highly correlated with those of Cobas c 513, caution should be exercised in cases of high HbF and HbH concentrations.

Background: Despite the superiority of non-HDL cholesterol (non-HDL-C) and apolipoprotein B (ApoB) as lipid markers for atherosclerotic cardiovascular disease (ASCVD), these are only suitable as secondary markers. We compared LDL cholesterol (LDL-C), non-HDL-C, and ApoB concentrations with respect to the occurrence of cardiovascular disease in adults enrolled in the Korean Genome and Epidemiology Study (KoGES). Methods: We used information on age; sex; medical history; family history of ASCVD; current lipid-lowering therapy; current smoking status; and creatinine, total cholesterol, HDL-C, LDL-C, triglyceride, and ApoB concentrations from 5,872 KoGES participants without ASCVD. New ASCVD development was monitored during the 8-year follow-up period. Adjusted hazard ratios (aHRs) for ASCVD of LDL-C, non-HDL-C, and ApoB concentrations were calculated based on the multivariate Cox regression analyses. The participants were also grouped as low and high according to the median values for each lipid marker, and calculated aHRs of each group combined by two lipid makers. Results: ApoB showed the highest aHR per 1-SD for ASCVD (1.26; 95% confidence interval [CI], 1.11–1.43), followed by non-HDL-C (1.25; 95% CI, 1.11–1.41) and LDL-C (1.20; 95% CI, 1.06–1.37). The group with low LDL-C and high ApoB concentrations had a significantly higher aHR for ASCVD (1.61; 95% CI, 1.05–2.48) compared to the reference group values (low LDL-C and low ApoB concentrations). The aHR for the group with high LDL-C and low ApoB concentrations was not significant (1.30; 95% CI, 0.79–2.16). Conclusions ApoB, non-HDL-C, and LDL-C are independent risk factors for ASCVD. Increases in the aHR per 1-SD for ASCVD were more strongly affected by ApoB, followed by non-HDL-C and LDL-C. Participants with low LDL-C and high ApoB concentrations showed increased ASCVD risk. For individuals with ASCVD risk factors, even those presenting normal LDL-C concentrations, measuring ApoB concentrations can provide useful information for better evaluation of ASCVD risk.