Establishing Reference Intervals or Haematological, Biochemical, and Immunological Analytes among Urban Ghanaian Adult Population

Abstract

Background Reference intervals (RIs) refer to the upper and lower reference limits of laboratory test derived from healthy individuals recruited with well-defined criteria. RI serves as a comparison tool and an important determinant of whether an individual is healthy or not, which apparently remains the most extensively used decision-making tool in clinical settings. Considering the importance of RIs for the interpretation of laboratory test, the International Federation of Clinical Chemistry (IFCC) has recommended that each laboratory obtains its own reference values and estimate the corresponding RIs within defined procedures. Even though the recommendation from IFCC/Clinical laboratory standard institute (CLSI) is required, yet majority of diagnostic laboratories in Ghana are unable to implement their own RIs due to the cost and challenges involved in recruiting the reference population. For that reason, the majority of laboratories work with reference intervals that are based on guidelines developed by manufacturers of analyzers. Thus, the continual use of such existing RIs from different manufacturer analyzers affects clinical decision making and might lead wrong interpretation of laboratory results, which is a public health concern. Aim This study aimed to establish reference intervals for haematological, biochemical and immunological analytes that would inform context-specific clinical decision-making and interpretation of laboratory results for healthcare practice in Ghana. Methods In a cross-sectional study design; healthy individuals, aged 18 – 60+ years were recruited using a simple random sampling technique. A total of 501 apparently healthy subjects; from the Tamale and Accra Metropolis which are capital cities of the Northern and Greater Accra region respectively were recruited into the study. Structured questionnaires were administered to volunteers to collect data on demographics, lifestyles, dietary pattern and their clinical information. The selection of eligible participants was primarily based on well-defined inclusion and exclusion criteria, which were in accordance with the IFCC/C-RIDL protocol. A fasting blood sample of 24mL was drawn into two plastic evacuated tubes containing ethylene diamine tetra-acetic acid (EDTA), three serum separate tube (SST), one sodium fluoride (NaFl) tube and one lithium heparin tube for complete blood count (CBC) and clinical chemistry analysis. Whole blood samples were analyzed using Sysmex XN 1000 analyzer for haematology analytes while the clinical chemistry, immunoglobulin, hormones, and tumour marker analytes were analyzed using Beckman Coulter AU 480 analyzer, Roche Cobas e411 analyser and Centaur XP Siemens’ analyzer respectively. All laboratory investigations were carried out in accordance with the laboratory’s standard operating procedures (SOPs). Stata version 13 software (Stata Corp., College Station, Texas, United States) was used in analyzing the data. Multiple regression analysis was performed to determine the relationship between variables. Partitioning of reference values by sex and age was done by the computing standard deviation ratio (SDR) using 3-level nested ANOVA by StatFlex version 6.0 statistical software (Artech Inc., Osaka, Japan). Prior to the derivation of the RIs, the latent abnormal values exclusion (LAVE) method was conducted to exclude individuals with such latent diseases. The latent abnormal values exclusion (LAVE) method is a secondary exclusion procedure applied to refine the data. Using “Reference interval Master” software, RIs of each analyte were derived using the parametric method. Results The participants’ mean age was 41.3 ± 13.5 years. RIs derived for major analytes were haemoglobin (males=12.8 - 17.2; females=10.7 - 14.3 g/dL), haematocrit (39.4 - 52.1; 34.0 - 44.2%), platelet (male 115–339; female 157–402 ×1010/L), uric acid (males=231- 487; females=149 – 377Umol/L), GGT (male = 17-87 IU/L; female = 12-49 IU/L). SDR ≥ 0.4 was used as a critical value for the partitioning of RVs by sex for all erythrocyte parameters (RBC, Hb, Ht, Fe, Ferr) and platelet counts. No sex-related difference was observed in any leukocyte parameter except eosinophil counts. Again, with clinical chemistry analytes’ sex variation was observed in Ca, CK, UA, Tbil, Dbil, AST, ALT, GGT, Cre, Cl, IgM, Fe, Ferr, CA125 and the hormone analytes as their SDR ≥ 0.4. Also, age-related changes with SDR ≥ 0.4 was noted only for RBC in males for haematology analytes. Application of LAVE had a conspicuous effect on RIs for the majority of erythrocyte parameters as well as folate, Fe, Ferr, CRP, LDL-C, TG, TC, CK, Glu, AST, ALT, and GGT. Some of the RIs for Ghanaian adults are RBC (male = 4.57–6.50×1012/L; female = 4.00–5.46 ×1012/L), Hb (male =12.8–17.2 g/dL; female=10.7–14.3 g/dL), eosinophils (male =0.5–10.3%; male= 0.4–6.5%), CK (male = 93-502U/L; female 52 -276 U/L) and amylase (male= 42 – 177 Umol/L; female = 43-158 Umol/L). Conclusion The findings from the present study therefore, indicate that adopting these haematological and clinical chemistry RIs for clinical use will be beneficial to healthcare systems in Ghana since most of the RIs derived were significantly different from the ones currently in use. Sex, age and BMI related differences were mainly the sole determinants of variations among most analytes. This indicates that sex and age-specific RIs are required for the effective interpretation of some haematological and clinical chemistry analytes. The robust statistical technique used in this study makes the RI derived more reliable for clinical decision making and patient care in the country.