Background: The preanalytical phase is more vulnerable to errors. This study aimed to establish preanalytical quality indicators (QIs) suitable for Korean clinical laboratories and investigate the current status of preanalytical phase performance monitoring in Korea using these QIs. Methods: We reviewed previous studies investigating preanalytical QIs including the International Federation of Clinical Chemistry (IFCC) model of QIs, to establish a set of QIs for Korean clinical laboratories. An e-mail survey consisting of this QI set was sent to 90 clinical laboratories. The collected data were analyzed, and performance measures were evaluated according to the quality specifications defined by the IFCC and the sigmascale method. Results: A model consisting of 23 preanalytical phase QIs was established.Approximately 47% (42/90) of clinical laboratories responded to the survey.The average result submission rate for each QI was 56% (standard deviation, 26%). The QIs with the highest and lowest result submission rates were “rejected samples due to hemolysis” (95%) and “recollected sample due to errors caused outside the laboratory” (17%). The QIs with the highest and lowest error rates were “hemolyzed sample detected by hemolytic index” (median, 0.546%; sigma performance level, “good”) and “samples not received” (median, 0.001%; sigma performance level, “very good”), respectively. Conclusions This survey findings on preanalytical phase QIs could serve as a foundation for developing an external quality assessment program for clinical laboratories in Korea.

Background: The preanalytical phase is more vulnerable to errors. This study aimed to establish preanalytical quality indicators (QIs) suitable for Korean clinical laboratories and investigate the current status of preanalytical phase performance monitoring in Korea using these QIs. Methods: We reviewed previous studies investigating preanalytical QIs including the International Federation of Clinical Chemistry (IFCC) model of QIs, to establish a set of QIs for Korean clinical laboratories. An e-mail survey consisting of this QI set was sent to 90 clinical laboratories. The collected data were analyzed, and performance measures were evaluated according to the quality specifications defined by the IFCC and the sigmascale method. Results: A model consisting of 23 preanalytical phase QIs was established.Approximately 47% (42/90) of clinical laboratories responded to the survey.The average result submission rate for each QI was 56% (standard deviation, 26%). The QIs with the highest and lowest result submission rates were “rejected samples due to hemolysis” (95%) and “recollected sample due to errors caused outside the laboratory” (17%). The QIs with the highest and lowest error rates were “hemolyzed sample detected by hemolytic index” (median, 0.546%; sigma performance level, “good”) and “samples not received” (median, 0.001%; sigma performance level, “very good”), respectively. Conclusions This survey findings on preanalytical phase QIs could serve as a foundation for developing an external quality assessment program for clinical laboratories in Korea.

Background: The preanalytical phase is more vulnerable to errors. This study aimed to establish preanalytical quality indicators (QIs) suitable for Korean clinical laboratories and investigate the current status of preanalytical phase performance monitoring in Korea using these QIs. Methods: We reviewed previous studies investigating preanalytical QIs including the International Federation of Clinical Chemistry (IFCC) model of QIs, to establish a set of QIs for Korean clinical laboratories. An e-mail survey consisting of this QI set was sent to 90 clinical laboratories. The collected data were analyzed, and performance measures were evaluated according to the quality specifications defined by the IFCC and the sigmascale method. Results: A model consisting of 23 preanalytical phase QIs was established.Approximately 47% (42/90) of clinical laboratories responded to the survey.The average result submission rate for each QI was 56% (standard deviation, 26%). The QIs with the highest and lowest result submission rates were “rejected samples due to hemolysis” (95%) and “recollected sample due to errors caused outside the laboratory” (17%). The QIs with the highest and lowest error rates were “hemolyzed sample detected by hemolytic index” (median, 0.546%; sigma performance level, “good”) and “samples not received” (median, 0.001%; sigma performance level, “very good”), respectively. Conclusions This survey findings on preanalytical phase QIs could serve as a foundation for developing an external quality assessment program for clinical laboratories in Korea.

Background: The preanalytical phase is more vulnerable to errors. This study aimed to establish preanalytical quality indicators (QIs) suitable for Korean clinical laboratories and investigate the current status of preanalytical phase performance monitoring in Korea using these QIs. Methods: We reviewed previous studies investigating preanalytical QIs including the International Federation of Clinical Chemistry (IFCC) model of QIs, to establish a set of QIs for Korean clinical laboratories. An e-mail survey consisting of this QI set was sent to 90 clinical laboratories. The collected data were analyzed, and performance measures were evaluated according to the quality specifications defined by the IFCC and the sigmascale method. Results: A model consisting of 23 preanalytical phase QIs was established.Approximately 47% (42/90) of clinical laboratories responded to the survey.The average result submission rate for each QI was 56% (standard deviation, 26%). The QIs with the highest and lowest result submission rates were “rejected samples due to hemolysis” (95%) and “recollected sample due to errors caused outside the laboratory” (17%). The QIs with the highest and lowest error rates were “hemolyzed sample detected by hemolytic index” (median, 0.546%; sigma performance level, “good”) and “samples not received” (median, 0.001%; sigma performance level, “very good”), respectively. Conclusions This survey findings on preanalytical phase QIs could serve as a foundation for developing an external quality assessment program for clinical laboratories in Korea.

Background: The preanalytical phase is more vulnerable to errors. This study aimed to establish preanalytical quality indicators (QIs) suitable for Korean clinical laboratories and investigate the current status of preanalytical phase performance monitoring in Korea using these QIs. Methods: We reviewed previous studies investigating preanalytical QIs including the International Federation of Clinical Chemistry (IFCC) model of QIs, to establish a set of QIs for Korean clinical laboratories. An e-mail survey consisting of this QI set was sent to 90 clinical laboratories. The collected data were analyzed, and performance measures were evaluated according to the quality specifications defined by the IFCC and the sigmascale method. Results: A model consisting of 23 preanalytical phase QIs was established.Approximately 47% (42/90) of clinical laboratories responded to the survey.The average result submission rate for each QI was 56% (standard deviation, 26%). The QIs with the highest and lowest result submission rates were “rejected samples due to hemolysis” (95%) and “recollected sample due to errors caused outside the laboratory” (17%). The QIs with the highest and lowest error rates were “hemolyzed sample detected by hemolytic index” (median, 0.546%; sigma performance level, “good”) and “samples not received” (median, 0.001%; sigma performance level, “very good”), respectively. Conclusions This survey findings on preanalytical phase QIs could serve as a foundation for developing an external quality assessment program for clinical laboratories in Korea.

Background: and Purpose We investigated the impact of comorbidity burden on troponin elevation, with separate consideration of neurological conditions, in patients with acute ischemic stroke (AIS). Methods: This prospective, observational cohort study consecutively enrolled patients with AIS for 2 years. Serum cardiac troponin I was repeatedly measured, and disease-related biomarkers were collected for diagnosis of preassigned comorbidities, including atrial fibrillation (AF), ischemic heart disease (IHD), myocardial hypertrophy (MH), heart failure (HF), renal insufficiency (RI), and active cancer. The severity of neurological deficits and insular cortical ischemic lesions were assessed as neurological conditions. Adjusted associations between these factors and troponin elevation were determined using a multivariate ordinal logistic regression model and area under the receiver operating characteristic curve (AUC). Cox proportional hazards model was used to determine the prognostic significance of comorbidity beyond neurological conditions. Results: Among 1,092 patients (66.5±12.4 years, 63.3% male), 145 (13.3%) and 335 (30.7%) had elevated (≥0.040 ng/mL) and minimally-elevated (0.040–0.010 ng/mL) troponin, respectively. In the adjusted analysis, AF, MH, HF, RI, active cancer, and neurological deficits were associated with troponin elevation. The multivariate model with six comorbidities and two neurological conditions exhibited an AUC of 0.729 (95% confidence interval [CI], 0.698–0.759). In Cox regression, AF, IHD, and HF were associated with adverse cardio-cerebrovascular events, whereas HF and active cancer were associated with mortality. Conclusion Troponin elevation in patients with AIS can be explained by the burden of comorbidities in combination with neurological status, which explains the prognostic significance of troponin assay.

Background/Aims: To examine the prevalence and clinical characteristics of apparent treatment-resistant hypertension among ambulatory hypertensive patients. Methods: We enrolled adult ambulatory hypertensive patients at 13 well-qualified general hospitals in Korea from January to June 2012. Apparent resistant hypertension was defined as an elevated blood pressure > 140/90 mmHg with the use of three antihypertensive agents, including diuretics, or ≥ 4 antihypertensives, regardless of the blood pressure. Controlled hypertension was defined as a blood pressure within the target using three antihypertensives, including diuretics. Results: Among 16,915 hypertensive patients, 1,172 (6.9%) had controlled hypertension, and 1,514 (8.9%) had apparent treatment-resistant hypertension. Patients with apparent treatment-resistant hypertension had an earlier onset of hypertension (56.8 years vs. 58.8 years, p = 0.007) and higher body mass index (26.3 kg/m2 vs. 24.9 kg/m2, p < 0.001) than those with controlled hypertension. Drug compliance did not differ between groups. In the multivariable analysis, earlier onset of hypertension (odds ratio [OR], 0.98; 95% confidence interval [CI], 0.97 to 0.99; p < 0.001) and the presence of comorbidities (OR, 2.06; 95% CI, 1.27 to 3.35; p < 0.001), such as diabetes mellitus, ischemic heart disease, heart failure, and chronic kidney disease, were independent predictors. Among the patients with apparent treatment-resistant hypertension, only 5.2% were receiving ≥ 2 antihypertensives at maximally tolerated doses. Conclusions Apparent treatment-resistant hypertension prevalence is 8.9% among ambulatory hypertensive patients in Korea. An earlier onset of hypertension and the presence of comorbidities are independent predictors. Optimization of medical treatment may reduce the rate of apparent treatment-resistant hypertension.

Background/Aims: To examine the prevalence and clinical characteristics of apparent treatment-resistant hypertension among ambulatory hypertensive patients. Methods: We enrolled adult ambulatory hypertensive patients at 13 well-qualified general hospitals in Korea from January to June 2012. Apparent resistant hypertension was defined as an elevated blood pressure > 140/90 mmHg with the use of three antihypertensive agents, including diuretics, or ≥ 4 antihypertensives, regardless of the blood pressure. Controlled hypertension was defined as a blood pressure within the target using three antihypertensives, including diuretics. Results: Among 16,915 hypertensive patients, 1,172 (6.9%) had controlled hypertension, and 1,514 (8.9%) had apparent treatment-resistant hypertension. Patients with apparent treatment-resistant hypertension had an earlier onset of hypertension (56.8 years vs. 58.8 years, p = 0.007) and higher body mass index (26.3 kg/m2 vs. 24.9 kg/m2, p < 0.001) than those with controlled hypertension. Drug compliance did not differ between groups. In the multivariable analysis, earlier onset of hypertension (odds ratio [OR], 0.98; 95% confidence interval [CI], 0.97 to 0.99; p < 0.001) and the presence of comorbidities (OR, 2.06; 95% CI, 1.27 to 3.35; p < 0.001), such as diabetes mellitus, ischemic heart disease, heart failure, and chronic kidney disease, were independent predictors. Among the patients with apparent treatment-resistant hypertension, only 5.2% were receiving ≥ 2 antihypertensives at maximally tolerated doses. Conclusions Apparent treatment-resistant hypertension prevalence is 8.9% among ambulatory hypertensive patients in Korea. An earlier onset of hypertension and the presence of comorbidities are independent predictors. Optimization of medical treatment may reduce the rate of apparent treatment-resistant hypertension.

BACKGROUND: Extraction of cell-free DNA (cfDNA) is a key step for determining the quality of cfDNA-related molecular diagnostics. We evaluated the effect of sample containers and sample storage conditions on cfDNA extraction. METHODS: The cfDNA extraction using the MagMAX Cell-Free DNA Isolation Kit from five healthy controls and five lung cancer patients was evaluated according to the type of sample container and storage conditions: K2-EDTA container, <1, 6, 24, and 48 hr storage at 4℃ after immediate plasma separation; and Cell-Free DNA BCT container, <1, 3, 7, and 14 days stored at room temperature. Mutation analysis of EGFR exons 18–21 was performed. To assess the effect of a delay in centrifugation, EDTA whole blood samples from five healthy individuals were stored at 4℃ for 6, 12, and 24 hr before plasma separation. RESULTS: There was no significant difference in the amount and nucleic acid size of cfDNA in both controls and patients with cancer when EDTA plasma was stored at 4℃ up to 48 hr. The amount and size of cfDNA in the BCT container were not different up to 7 days; however, the 14-day sample showed an increase in cfDNA concentration due to genomic DNA contamination. EGFR mutations were detected on EDTA containers up to 48 hr and with BCT containers up to 14 days. When EDTA whole blood was stored at 4℃ and plasma separation was delayed, the cfDNA concentration increased from 24 hr. CONCLUSIONS: The cfDNA extraction was affected by the sample containers and storage conditions.
Biopsy ; Centrifugation ; DNA Contamination ; DNA ; Edetic Acid ; Exons ; Humans ; Lung Neoplasms ; Pathology, Molecular ; Plasma