본문 바로가기
KERD
논문KCI 등재

Functional Reference Limits: Describing Physiological Relationships and Determination of Physiological Limits for Enhanced Interpretation of Laboratory Results

2

조회

0

다운로드

0

인용

0

참고문헌

키워드

주제분류병리학

초록

Functional reference limits describe key changes in the physiological relationship between a pair of physiologically related components. Statistically, this can be represented by a significant change in the curvature of a mathematical function or curve (e.g., an observed plateau). The point at which the statistical relationship changes significantly is the point of curvature inflection and can be mathematically modeled from the relationship between the interrelated biomarkers. Conceptually, they reside between reference intervals, which describe the statistical boundaries of a single biomarker within the reference population, and clinical decision limits that are often linked to the risk of morbidity or mortality and set as thresholds. Functional reference limits provide important physiological and pathophysiological insights that can aid laboratory result interpretation. Laboratory professionals are in a unique position to harness data from laboratory information systems to derive clinically relevant values. Increasing research on and reporting of functional reference limits in the literature will enhance their contribution to laboratory medicine and widen the evidence base used in clinical decision limits, which are currently almost exclusively contributed to by clinical trials. Their inclusion in laboratory reports will enhance the intellectual value of laboratory professionals in clinical care beyond the statistical boundaries of a healthy reference population and pave the way to them being considered in shaping clinical decision limits. This review provides an overview of the concepts related to functional reference limits, clinical examples of their use, and the impetus to include them in laboratory reports.

Abstract

Functional reference limits describe key changes in the physiological relationship between a pair of physiologically related components. Statistically, this can be represented by a significant change in the curvature of a mathematical function or curve (e.g., an observed plateau). The point at which the statistical relationship changes significantly is the point of curvature inflection and can be mathematically modeled from the relationship between the interrelated biomarkers. Conceptually, they reside between reference intervals, which describe the statistical boundaries of a single biomarker within the reference population, and clinical decision limits that are often linked to the risk of morbidity or mortality and set as thresholds. Functional reference limits provide important physiological and pathophysiological insights that can aid laboratory result interpretation. Laboratory professionals are in a unique position to harness data from laboratory information systems to derive clinically relevant values. Increasing research on and reporting of functional reference limits in the literature will enhance their contribution to laboratory medicine and widen the evidence base used in clinical decision limits, which are currently almost exclusively contributed to by clinical trials. Their inclusion in laboratory reports will enhance the intellectual value of laboratory professionals in clinical care beyond the statistical boundaries of a healthy reference population and pave the way to them being considered in shaping clinical decision limits. This review provides an overview of the concepts related to functional reference limits, clinical examples of their use, and the impetus to include them in laboratory reports.

참고문헌 (42)

  1. Miller WG, "Reference intervals: strengths, weaknesses, and challenges", Clin Chem, 62, pp.916~923 (2016)
  2. Ozarda Y, "Distinguishing reference intervals and clinical decision limits-a review by the IFCC Committee on Reference Intervals and Decision Limits", Crit Rev Clin Lab Sci, 55, pp.420~431 (2018)
  3. Jones G, "Reference intervals", Clin Biochem Rev, 29(Suppl 1), pp.S93~7 (2008)
  4. Billman GE, "Homeostasis : the underappreciated and far too often ignored central organizing principle of physiology", Front Physiol, 11, pp.200~ (2020)
  5. Rondon-Berrios H, "Physiology and pathophysiology of water homeostasis", Front Horm Res, 52, pp.8~23 (2019)
  6. Sikaris KA, "Physiology and its importance for reference intervals", Clin Biochem Rev, 35, pp.3~14 (2014)
  7. Sezgin G, "Functional reference limits : a case study of serum ferritin", J Lab Med, 45, pp.69~77 (2021)
  8. Tan RZ, "Comparison of 8 methods for univariate statistical exclusion of pathological subpopulations for indirect reference intervals and biological variation studies", Clin Biochem, 103, pp.16~24 (2022)
  9. Robert Hawkins, "Total 25-OH Vitamin D Concentrations in Chinese, Malays and Indians", Annals of Laboratory Medicine, 33(2), pp.156~158 (2013), 대한진단검사의학회
  10. Holick MF, "Evaluation, treatment, and prevention of vitamin D deficiency: an Endocrine Society clinical practice guideline", J Clin Endocrinol Metab, 96, pp.1911~1930 (2011)
  11. Howard A. Morris, "Vitamin D Activities for Health Outcomes", Annals of Laboratory Medicine, 34(3), pp.181~186 (2014), 대한진단검사의학회
  12. Ginde AA, "Defining vitamin D status by secondary hyperparathyroidism in the U.S. population", J Endocrinol Invest, 35, pp.42~48 (2012)
  13. Kirk LF Jr, "Cushing’s disease : clinical manifestations and diagnostic evaluation", Am Fam Physician, 62, pp.1119~1127 (2000)
  14. Carlton E, "Evaluation of high-sensitivity cardiac troponin I levels in patients with suspected acute coronary syndrome", JAMA Cardiol, 1, pp.405~412 (2016)
  15. Grundy SM, "2018 AHA", ACC, AAPA, pp.ABC, ACPM[DOI]
  16. American Diabetes Association Professional Practice Committee, "2. Classification and diagnosis of diabetes : standards of medical care in Diabetes-2022", Diabetes Care, 45, pp.S17~S38 (2022)
  17. Tan EH, "Outcome-based critical result thresholds in the adult patient population", Am J Clin Pathol, 152, pp.177~184 (2019)
  18. Du H, "Derivation of outcome-based pediatric critical values", Am J Clin Pathol, 149, pp.324~331 (2018)
  19. Agha F, "Serum ferritin levels in apparently healthy subjects", J Pak Med Assoc, 37, pp.63~66 (1987)
  20. Sezgin G, "Clinical thresholds for diagnosing iron deficiency : comparison of functional assessment of serum ferritin to population based centiles", Sci Rep, 10, pp.18233~ (2020)
  21. Markus C, "Ferritin as a functional biomarker of iron status in children and young adults", Br J Haematol, 184, pp.640~642 (2019)
  22. Foy BH, "Data-driven physiologic thresholds for iron deficiency associated with hematologic decline", Am J Hematol, 95, pp.302~309 (2020)
  23. Shah S, "Serum 25-hydroxyvitamin D insufficiency in search of a bone disease", J Clin Endocrinol Metab, 102, pp.2321~2328 (2017)
  24. Jones GRD, "Indirect methods for reference interval determination-review and recommendations", Clin Chem Lab Med, 57, pp.20~29 (2018)
  25. Kang Taewon, "Indirect Method for Estimation of Reference Intervals of Inflammatory Markers", Annals of Laboratory Medicine, 43(1), pp.55~63 (2023), 대한진단검사의학회[DOI]
  26. Sung Ji Yeon, "Establishment of Pediatric Reference Intervals for Routine Laboratory Tests in Korean Population: A Retrospective Multicenter Analysis", Annals of Laboratory Medicine, 41(2), pp.155~170 (2021), 대한진단검사의학회[DOI]
  27. Tan RZ, "Comparison of two(data mining)indirect approaches for between-subject biological variation determination", Clin Biochem, 105-106, pp.57~63 (2022)
  28. Tan RZ, "Comparison of four indirect(data mining)approaches to derive within-subject biological variation", Clin Chem Lab Med, 60, pp.636~644 (2022)
  29. Loh TP, "Derivation of pediatric within-individual biological variation by indirect sampling method : an LMS approach", Am J Clin Pathol, 142, pp.657~663 (2014)
  30. Loh TP, "Indirect estimation of pediatric between-individual biological variation data for 22 common serum biochemistries", Am J Clin Pathol, 143, pp.683~693 (2015)
  31. Chai JH, "Indirect derivation of biological variation data and analytical performance specifications for therapeutic drug monitoring activities", Pathology, 51, pp.281~285 (2019)
  32. Yang Z, "Relative criticalness of common laboratory tests for critical value reporting", J Clin Pathol, 72, pp.325~328 (2019)
  33. Loh TP, "Trends and physiology of common serum biochemistries in children aged 0-18 years", Pathology, 47, pp.452~461 (2015)
  34. Loh TP, "Development of paediatric biochemistry centile charts as a complement to laboratory reference intervals", Pathology, 46, pp.336~343 (2014)
  35. Krause JR, "Serum ferritin and bone marrow biopsy iron stores. II. Correlation with low serum iron and Fe", TIBC ratio less than 15%, 1980, pp.74, 461~464
  36. Åsberg A, "Lower hemoglobin with lower ferritin : it is not just a question of anemia", Scand J Clin Lab Invest, 73, pp.622~626 (2013)
  37. Abdullah K, "Re-evaluation of serum ferritin cut-off values for the diagnosis of iron deficiency in children aged 12-36 months", J Pediatr, 188, pp.287~290 (2017)
  38. Choy KW, "Assessment of analytical bias in ferritin assays and impact on functional reference limits", Pathology, 54, pp.302~307 (2022)
  39. Mrazek C, "Errors within the total laboratory testing process, from test selection to medical decision-making-a review of causes, consequences, surveillance and solutions", Biochem Med(Zagreb), 30, pp.020502~ (2020)
  40. Hickner J, "Primary care physicians’ challenges in ordering clinical laboratory tests and interpreting results", J Am Board Fam Med, 27, pp.268~274 (2014)
  41. Gandhi TK, "Missed and delayed diagnoses in the ambulatory setting : a study of closed malpractice claims", Ann Intern Med, 145, pp.488~496 (2006)
  42. Kachalia A, "Missed and delayed diagnoses in the emergency department : a study of closed malpractice claims from 4 liability insurers", Ann Emerg Med, 49, pp.196~205 (2007)

관련 논문AI추천

이 간행물의 다른 논문 (18건)