Biomarkers in Heart Failure: From Research to Clinical Practice
Alexander E. Berezin 
, M.D., Ph.D. and Alexander A. Berezin , M.D.
Most Read (Last 3 years)
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Review Article2023-05-01 Clinical Chemistry
Abstract : The aim of this narrative review is to summarize contemporary evidence on the use of circulating cardiac biomarkers of heart failure (HF) and to identify a promising biomarker model for clinical use in personalized point-of-care HF management. We discuss the reported biomarkers of HF classified into clusters, including myocardial stretch and biomechanical stress; cardiac myocyte injury; systemic, adipocyte tissue, and microvascular inflammation; cardiac fibrosis and matrix remodeling; neurohumoral activation and oxidative stress; impaired endothelial function and integrity; and renal and skeletal muscle dysfunction. We focus on the benefits and drawbacks of biomarker-guided assistance in daily clinical management of patients with HF. In addition, we provide clear information on the role of alternative biomarkers and future directions with the aim of improving the predictive ability and reproducibility of multiple biomarker models and advancing genomic, transcriptomic, proteomic, and metabolomic evaluations.
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Review Article2023-01-01 Clinical Chemistry
Calibration Practices in Clinical Mass Spectrometry: Review and Recommendations
Wan Ling Cheng
Ann Lab Med 2023; 43(1): 5-18 , M.Sc., Corey Markus , M.Sc., Chun Yee Lim , Ph.D., Rui Zhen Tan , Ph.D., Sunil Kumar Sethi , MBBS., and Tze Ping Loh , MB.BCh.BAO.; for the IFCC Working Group on Method Evaluation ProtocolsAbstract : Background: Calibration is a critical component for the reliability, accuracy, and precision of mass spectrometry measurements. Optimal practice in the construction, evaluation, and implementation of a new calibration curve is often underappreciated. This systematic review examined how calibration practices are applied to liquid chromatography-tandem mass spectrometry measurement procedures. Methods: The electronic database PubMed was searched from the date of database inception to April 1, 2022. The search terms used were “calibration,” “mass spectrometry,” and “regression.” Twenty-one articles were identified and included in this review, following evaluation of the titles, abstracts, full text, and reference lists of the search results. Results: The use of matrix-matched calibrators and stable isotope-labeled internal standards helps to mitigate the impact of matrix effects. A higher number of calibration standards or replicate measurements improves the mapping of the detector response and hence the accuracy and precision of the regression model. Constructing a calibration curve with each analytical batch recharacterizes the instrument detector but does not reduce the actual variability. The analytical response and measurand concentrations should be considered when constructing a calibration curve, along with subsequent use of quality controls to confirm assay performance. It is important to assess the linearity of the calibration curve by using actual experimental data and appropriate statistics. The heteroscedasticity of the calibration data should be investigated, and appropriate weighting should be applied during regression modeling. Conclusions: This review provides an outline and guidance for optimal calibration practices in clinical mass spectrometry laboratories.
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Review Article2024-01-01 Clinical Chemistry
Bias in Laboratory Medicine: The Dark Side of the Moon
Abdurrahman Coskun
Ann Lab Med 2024; 44(1): 6-20, M.D.Abstract : Physicians increasingly use laboratory-produced information for disease diagnosis, patient monitoring, treatment planning, and evaluations of treatment effectiveness. Bias is the systematic deviation of laboratory test results from the actual value, which can cause misdiagnosis or misestimation of disease prognosis and increase healthcare costs. Properly estimating and treating bias can help to reduce laboratory errors, improve patient safety, and considerably reduce healthcare costs. A bias that is statistically and medically significant should be eliminated or corrected. In this review, the theoretical aspects of bias based on metrological, statistical, laboratory, and biological variation principles are discussed. These principles are then applied to laboratory and diagnostic medicine for practical use from clinical perspectives.
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Review Article2024-03-01 Clinical Chemistry
Exploring Renal Function Assessment: Creatinine, Cystatin C, and Estimated Glomerular Filtration Rate Focused on the European Kidney Function Consortium Equation
Hans Pottel
Ann Lab Med 2024; 44(2): 135-143, Ph.D., Pierre Delanaye , M.D., Ph.D., and Etienne Cavalier , Ph.D.Abstract : Serum creatinine and serum cystatin C are the most widely used renal biomarkers for calculating the estimated glomerular filtration rate (eGFR), which is used to estimate the severity of kidney damage. In this review, we present the basic characteristics of these biomarkers, their advantages and disadvantages, some basic history, and current laboratory measurement practices with state-of-the-art methodology. Their clinical utility is described in terms of normal reference intervals, graphically presented with age-dependent reference intervals, and their use in eGFR equations.
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Original Article2023-01-01 Clinical Microbiology
Serotype Distribution and Antimicrobial Resistance of Streptococcus pneumoniae Causing Invasive Pneumococcal Disease in Korea Between 2017 and 2019 After Introduction of the 13-Valent Pneumococcal Conjugate Vaccine
Gyu Ri Kim
Ann Lab Med 2023; 43(1): 45-54, Ph.D., Eun-Young Kim , Ph.D., Si Hyun Kim , Ph.D., Hae Kyung Lee , M.D., Jaehyeon Lee , M.D., Jong Hee Shin , M.D., Young Ree Kim , M.D., Sae Am Song , M.D., Joseph Jeong , M.D., Young Uh , M.D., Yu Kyung Kim , M.D., Dongeun Yong , M.D., Hyun Soo Kim , M.D., Sunjoo Kim , M.D., Young Ah Kim , M.D., Kyeong Seob Shin , M.D., Seok Hoon Jeong , M.D., Namhee Ryoo , M.D., and Jeong Hwan Shin , M.D.Abstract : Background: Streptococcus pneumoniae is a serious pathogen causing various infections in humans. We evaluated the serotype distribution and antimicrobial resistance of S. pneumoniae causing invasive pneumococcal disease (IPD) after introduction of pneumococcal conjugate vaccine (PCV)13 in Korea and investigated the epidemiological characteristics of multidrug-resistant (MDR) isolates. Methods: S. pneumoniae isolates causing IPD were collected from 16 hospitals in Korea between 2017 and 2019. Serotyping was performed using modified sequential multiplex PCR and the Quellung reaction. Antimicrobial susceptibility tests were performed using the broth microdilution method. Multilocus sequence typing was performed on MDR isolates for epidemiological investigations. Results: Among the 411 S. pneumoniae isolates analyzed, the most prevalent serotype was 3 (12.2%), followed by 10A (9.5%), 34 (7.3%), 19A (6.8%), 23A (6.3%), 22F (6.1%), 35B (5.8%), 11A (5.1%), and others (40.9%). The coverage rates of PCV7, PCV10, PCV13, and pneumococcal polysaccharide vaccine (PPSV)23 were 7.8%, 7.8%, 28.7%, and 59.4%, respectively. Resistance rates to penicillin, ceftriaxone, erythromycin, and levofloxacin were 13.1%, 9.2%, 80.3%, and 4.1%, respectively. MDR isolates accounted for 23.4% of all isolates. Serotypes 23A, 11A, 19A, and 15B accounted for the highest proportions of total isolates at 18.8%, 16.7%, 14.6%, and 8.3%, respectively. Sequence type (ST)166 (43.8%) and ST320 (12.5%) were common among MDR isolates. Conclusions: Non-PCV13 serotypes are increasing among invasive S. pneumoniae strains causing IPD. Differences in antimicrobial resistance were found according to the specific serotype. Continuous monitoring of serotypes and antimicrobial resistance is necessary for the appropriate management of S. pneumoniae infections.
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Review Article2024-03-01 Clinical Chemistry
The Use of Bone-Turnover Markers in Asia-Pacific Populations
Samuel Vasikaran
Ann Lab Med 2024; 44(2): 126-134, M.D., Subashini C. Thambiah , M.Path., Rui Zhen Tan , Ph.D., and Tze Ping Loh , M.B., B.ch., B.A.O.; APFCB Harmonization of Reference Interval Working GroupAbstract : Bone-turnover marker (BTM) measurements in the blood or urine reflect the bone-remodeling rate and may be useful for studying and clinically managing metabolic bone diseases. Substantial evidence supporting the diagnostic use of BTMs has accumulated in recent years, together with the publication of several guidelines. Most clinical trials and observational and reference-interval studies have been performed in the Northern Hemisphere and have mainly involved Caucasian populations. This review focuses on the available data for populations from the Asia-Pacific region and offers guidance for using BTMs as diagnostic biomarkers in these populations. The procollagen I N-terminal propeptide and β-isomerized C-terminal telopeptide of type-I collagen (measured in plasma) are reference BTMs used for investigating osteoporosis in clinical settings. Premenopausal reference intervals (established for use with Asia-Pacific populations) and reference change values and treatment targets (used to monitor osteoporosis treatment) help guide the management of osteoporosis. Measuring BTMs that are not affected by renal failure, such as the bone-specific isoenzyme alkaline phosphatase and tartrate-resistant acid phosphatase 5b, may be advantageous for patients with advanced chronic kidney disease. Further studies of the use of BTMs in individuals with metabolic bone disease, coupled with the harmonization of commercial assays to provide equivalent results, will further enhance their clinical applications.
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Original Article2023-01-01 Clinical Chemistry
Intuitive Modification of the Friedewald Formula for Calculation of LDL-Cholesterol
Jinyoung Hong
Ann Lab Med 2023; 43(1): 29-37, M.D., Hyunjung Gu , M.D., Juhee Lee , M.T., Woochang Lee , M.D., Sail Chun , M.D., Ki Hoon Han , M.D., and Won-Ki Min , M.D.Abstract : Background: High LDL-cholesterol (LDL-C) is an established risk factor for cardiovascular disease and is considered an important therapeutic target. It can be measured directly or calculated from the results of other lipid tests. The Friedewald formula is the most widely used formula for calculating LDL-C. We modified the Friedewald formula for a more accurate and practical estimation of LDL-C. Methods: Datasets, including measured triglyceride, total cholesterol, HDL-cholesterol, and LDL-C concentrations were collected and assigned to derivation and validation sets. The datasets were further divided into five groups based on triglyceride concentrations. In the modified formula, LDL-C was defined as total cholesterol − HDL-cholesterol − (triglyceride/adjustment factor). For each group, the adjustment factor that minimized the difference between measured LDL-C and calculated LDL-C using modified formula was obtained. For validation, measured LDL-C and LDL-C calculated using the modified formula (LDL-CM), Friedewald formula (LDL-CF), Martin-Hopkins formula (LDL-CMa), and Sampson formula (LDL-CS) were compared. Results: In the derivation set, the adjustment factors were 4.7, 5.9, 6.3, and 6.4 for the groups with triglyceride concentrations 300 mg/dL, respectively. In the validation set, the coefficient of determination (R2) between measured and calculated LDL-C was higher for LDL-CM than for LDL-CF (R2=0.9330 vs. 0.9206). The agreement according to the National Cholesterol Education Program Adult Treatment Panel III classification of LDL-C was 86.36%, 86.08%, 86.82%, and 86.15% for LDL-CM, LDL-CF, LDL-CMa, and LDL-CS, respectively. Conclusions: We proposed a practical, improved LDL-C calculation formula by applying different factors depending on the triglyceride concentration.
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Brief Communication2023-09-01 Diagnostic Hematology
Implications of the 5th Edition of the World Health Organization Classification and International Consensus Classification of Myeloid Neoplasm in Myelodysplastic Syndrome With Excess Blasts and Acute Myeloid Leukemia
Cheonghwa Lee
Ann Lab Med 2023; 43(5): 503-507, M.D., Ha Nui Kim , M.D., Ph.D., Jung Ah Kwon , M.D., Ph.D., Soo-Young Yoon , M.D., Ph.D., Min Ji Jeon , M.D., Ph.D., Eun Sang Yu , M.D., Dae Sik Kim , M.D., Ph.D., Chul Won Choi , M.D., Ph.D., and Jung Yoon , M.D., Ph.D.Abstract : The fifth edition of the WHO classification (2022 WHO) and the International Consensus Classification (2022 ICC) of myeloid neoplasms have been recently published. We reviewed the changes in the diagnosis distribution in patients with MDS with excess blasts (MDS-EB) or AML using both classifications. Forty-seven patients previously diagnosed as having AML or MDS-EB with available mutation analysis data, including targeted next-generation and RNA-sequencing data, were included. We reclassified 15 (31.9%) and 27 (57.4%) patients based on the 2022 WHO and 2022 ICC, respectively. One patient was reclassified as having a translocation categorized as a rare recurring translocation in both classifications. Reclassification was mostly due to the addition of mutation-based diagnostic criteria (i.e., AML, myelodysplasia-related) or a new entity associated with TP53 mutation. In both classifications, MDS diagnosis required the confirmation of multi-hit TP53 alterations. Among 14 patients with TP53 mutations, 11 harbored multi-hit TP53 alterations, including four with TP53 mutations and loss of heterozygosity. Adverse prognosis was associated with multi-hit TP53 alterations (P=0.009) in patients with MDS-EB, emphasizing the importance of detecting the mutations at diagnosis. The implementation of these classifications may lead to the identification of different subtypes from previously heterogeneous diagnostic categories based on genetic characteristics.
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Editorial2023-05-01
Apolipoprotein B, Non-HDL Cholesterol, and LDL Cholesterol as Markers for Atherosclerotic Cardiovascular Disease Risk Assessment
Yeo-Min Yun
Ann Lab Med 2023; 43(3): 221-222, M.D., Ph.D. -
Review Article2023-09-01 Clinical Chemistry
Artificial Intelligence in Point-of-Care Testing
Adil I. Khan
Ann Lab Med 2023; 43(5): 401-407, M.Sc., Ph.D., Mazeeya Khan , M.Sc., and Raheeb Khan , B.Sc.Abstract : With the projected increase in the global population, current healthcare delivery models will face severe challenges. Rural and remote areas, whether in developed or developing countries, are characterized by the same challenges: the unavailability of hospitals, lack of trained and skilled staff performing tests, and poor compliance with quality assurance protocols. Point-of-care testing using artificial intelligence (AI) is poised to be able to address these challenges. In this review, we highlight some key areas of application of AI in point-of-care testing, including lateral flow immunoassays, bright-field microscopy, and hematology, demonstrating this rapidly expanding field of laboratory medicine.
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