Journals / Türk Biyokimya Dergisi / 2015 / Cilt: 40 - Sayı: 3

Referans aralık hesaplamada alt grup belirleme yöntemi ve bir uygulama

Determination of sub-groups in reference interval calculations and an application

Pages
197–204
Publication Date
2022-11-05
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Harris&Boyd method was used for sex and age while the MARS method was used for the determination of age sub-groups.Results: According to the Harris&Boyd method, it was concluded that it is not necessary to create sub-groups for sex and age variables.

📌 3 Key Takeaways

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Objective & Hypothesis:Objective: The main objective of this study is to determine the methods used for dividing reference data into sub-groups and propose a new solution.
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Key Findings & Data:MARS 2.0 package software was used for the statistical analysis.
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Conclusion & Impact:Harris&Boyd method was used for sex and age while the MARS method was used for the determination of age sub-groups.Results: According to the Harris&Boyd method, it was concluded that it is not necessary to create sub-groups for sex and age variables.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Abstract

Objective: The main objective of this study is to determine the methods used for dividing reference data into sub-groups and propose a new solution. Therefore, the newly proposed method is used to determine age sub-groups while calculating the reference interval of AST variable.Methods: The data of this study are composed of the registered patients who applied only once to the polyclinics at the Health Research and Application Hospital, Clinical Bio-Chemistry Laboratory of Mersin University. The main variables selected for the study are sex, age and aspartate transaminase (AST). MARS 2.0 package software was used for the statistical analysis. Harris&Boyd method was used for sex and age while the MARS method was used for the determination of age sub-groups.Results: According to the Harris&Boyd method, it was concluded that it is not necessary to create sub-groups for sex and age variables. Age sub-groups are determined with the MARS method by taking into account the correlations between AST variables and age. Age sub-groups are calculated as 5-9, 10-18 and 19+. Correlation between the age and AST variable is investigated for these sub-groups. It is obtained that the correlation is statistically not significant for the 5-9 age group (p=0.3189), significant for the 10-18 age group (p

Özet

Amaç: Bu çalışmanın amacı referans verilerini alt gruplara ayırmada kullanılan yöntemleri belirlemek ve yeni bir yöntem önermektir. Bu amaçla yeni önerilen yöntem, AST değişkeninin referans aralığı hesaplanırken yaş alt gruplarının belirlenebilmesi amacı ile kullanılmıştır.Metod: Çalışmaya ait veriler, Mersin Üniversitesi Sağlık Araştırma ve Uygulama Hastanesi Klinik Biyokimya Laboratuvarında sadece bir kez polikliniğe başvuran hastaların kayıtlı verileri ile oluşturulmuştur. Bu çalışmada seçilen değişkenler cinsiyet, yaş ve aspartat transaminaz (AST)'dır. İstatistik analizlerde MARS 2.0 paket programı kullanılmıştır. Harris&Boyd yöntemi cinsiyet ve yaş, MARS yöntemi yaş alt grubunun belirlenmesinde kullanılmıştır.Bulgular: Harris&Boyd yöntemine göre cinsiyet ve yaş değişkeninde ayırmanın yapılmasına gerek olmadığı sonucu çıkmıştır. AST değişkeni ile yaş arasındaki ilişkilere bakılarak MARS yöntemi ile yaş alt grupları belirlendi. Yaş alt grupları 5-9; 10-18 ve 19 ve üzeri olarak hesaplandı. Bu alt gruplardaki yaş ile AST değişkeni arasındaki ilişkilere bakıldı. 5-9 yaş grubunda ilişki anlamsız (p=0.3189), 10-18 yaş grubunda ilişki anlamlı (p

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Cite This Article

TEMEL, G. O., KANIK, E. A., YİLDİRİM, D. D., OVLA, H. D., KALAFAT, H. (2022). Referans aralık hesaplamada alt grup belirleme yöntemi ve bir uygulama. Türk Biyokimya Dergisi, Cilt: 40 - Sayı: 3, 197–204. https://ajindex.com/articles/621145

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References (10)

  1. Shirts BH, Wilson AR, Jackson BR. Partitioning reference intervals by use of genetic information. Clin Chem 2011; (3):475-81.
  2. Katayev A, Balciza C, seccombe DW. Establishing reference intervals for clinical laboratory test results: is there a better way? Am J Clin Pathol 2010; 133(2):180-6. Clinical and Laboratory standards Institute. Defining, Establishing, and Verifying Reference Intervals in the Clinical Laboratory; Approved Guideline. Third Edition. CLsI document C28-A3. Wayne, PA: Clinical and Laboratory standards Institute; 2008. solberg HE. International Federation of Clinical Chemistry (IFCC), scientific Committee, Clinical section, Expert Panel on Theory of Reference Values, and International Committee for standardization in Haematology (ICsH), standing Committee on Reference Values. Approved Recommendation (1986) on the theory of reference values. Part 1. The concept of reference values. J Clin Chem Clin Biochem 1987; 25(5):337-42. Guidi GC, salvagno GL. Reference Intervals as a Toolfor Total Quality Managment. Biochemia Medica 2010; 20(2):165-72.
  3. Harris EK, Boyd JC. statistical Bases of Reference Values in Laboratory Medicine 1995;
  4. Newyork. sinton TJ, Cowley DM, Bryant sJ. Reference intervals for calcium, phosphate, and alkaline phosphatase as derived on the basis of multichannel-analyzer profiles. Clin Chem 1986; (1 Pt 1):76-9.
  5. Harris EK, Boyd JC. On dividing reference data into subgroups to produce separate reference ranges. Clin Chem 1990; (2):265-70.
  6. Lahti A, Hyltoft Petersen P, Boyd JC, Fraser CG, Jİrgensen N. Objective criteria for partitioning Gaussian-distributed reference values into subgroups. Clin Chem 2002; (2):338-52.
  7. Lahti A, Hyltoft Petersen P, Boyd JC. Impact of subgroup prevalences on partitioning of Gaussian-distributed reference values. Clin Chem 2002; 48(11):1987-99.
  8. Lahti A, Petersen PH, Boyd JC, Rustad P, Laake P, et al. Partitioning of nongaussian-distributed biochemical reference data into subgroups. Clin Chem 2004; 50(5):891-900. Rawlings J. Applied Regression Analyasis: A Research Tool pp. 1-7, 2nd edition. Brooks/Cole Publishing Company, America. Friedman JH. Multivariate Adaptive Regression splines (withdiscussion). Ann stat 1991; 19(March):1-141.
  9. Orekici Temel G, Ankaralı H, Yazıcı AC. An Alternative Approach to Regression Models: MARs. Turkiye Klinikleri J Biostat 2010; (2):58-66.
  10. Barnett V, Lewis T. Outliers in statistical Data 1979, John Wiley&sons. Fontes R, Coeli CR, Aguiar F, Vaisman M. Reference interval of th