Gender- and age-specific reference intervals of common biochemical analytes in chinese population – derivation using real laboratory data

Abstract

Summary Background Indirect sampling methods are not only inexpensive but also efficient for establishing reference intervals (RIs) using clinical data. This study was conducted to select fully normal records to establish age- and gender-specific RIs for common biochemical analytes by laboratory data mining. Methods In total, 280,206 records from 2014 to 2018 were obtained from Peking Union Medical College Hospital. Common biochemical analytes [total protein, albumin, total bilirubin (TBil), direct bilirubin (DBil), alanine aminotransferase (ALT), glutamyltranspeptidase (GGT), alkaline phosphatase (ALP), aspartate aminotransferase (AST), lactate dehydrogenase (LDH), potassium, sodium, chlorine, calcium, urea, glucose, uric acid (UA), inorganic phosphorus, creatinine (Cr), total cholesterol, triglyceride, high-density lipoprotein cholesterol, and low-density lipoprotein cholesterol] were measured using an automatic analyzer. Sources of variation were identified by multiple regression analysis. The 2.5th and 97.5th percentiles were calculated as the lower and upper limits of the RIs, respectively. Results Metode indirektnog uzorkovanja nisu samo jeftine, već su i efikasne za uspostavljanje referentnih intervala (RI) korišćenjem velike količine kliničkih podataka. Ova studija je sprovedena sa ciljem da se odaberu potpuno normalni pojedinačni zapisi da bi se utvrdio RI za starost i pol za zajedničke biohemijske analite pomoću laboratorijski dobijenih podataka. Conclusions Ukupno je uzeto 280.206 pojedinačnih rezultata u periodu od 2014. do 2018. godine iz bolnice Peking Union Medical College-a. Uobičajeni biohemijski analiti [ukupni protein, albumin, ukupni bilirubin (TBil), direktni bilirubin (DBil), alanin aminotransferaza (ALT), glutamiltranspeptidaza (GGT), alkalna fosfataza (ALP), aspartat aminotransferaza (AST), laktat dehidrogenaza (LAT) kalijum, natrijum, hlor, kalcijum, ureja, glukoza, mokraćna kiselina (UA), neorganski fosfor, kreatinin (Cr), ukupni hole sterol, trigliceridi, lipoprotein holesterola visoke gustine i lipoprotein holesterola niske gustine] mereni su korišćenjem automatskog analizatora. Izvori varijacije identifikovani su višestrukom regresionom analizom. Postoci (2,5 i 97,5) su izračunati kao donja i gornja granica RI, svaki ponaosob.

Establishment of dry chemistry based reference intervals of renal function test parameters for the adult population of Kaski District, Nepal

“…This gender-based difference may be associated with the previously reported factors such as higher muscle and bone masses in males compared to females, including others such as differences in nutrition, and physiological status. Similar ndings have been reported in populations of North India, China, Tanzania, Uganda, Kericho; Kenya, and North-Rift Valley; Kenya [2,[10][11][12][13][14]. On the contrary, there was no signi cant gender difference for urea in a study conducted in the Nigerian population [15].…”

“…The dry chemistry based RIs that are provided in the kit inserts and currently being used at our laboratory reporting was found to be different than what we established for our local population of the Kaski district of Nepal. Not only these, but our RIs were also found to differ to some extent with the RIs determined elsewhere by the same methodology and analytical platforms [2,5,10,14]. These observed differences could be explained in the light of sample size, genetic, ethnic, demographic, geographical location, diet, lifestyle, cultural and seasonal differences among the studied populations [1,2,5,22].…”

“…This nding contradicts the ndings of a study conducted in China, North-Rift Valley; Kenya, and Rwanda where a signi cant difference in RI for sodium was observed between males and females. [10,14,16]. There was a signi cant gender difference for potassium with a high RI of potassium present among the female participants (Table 2).…”

“…These observed differences could be explained in the light of sample size, genetic, ethnic, demographic, geographical location, diet, lifestyle, cultural and seasonal differences among the studied populations [1,2,5,22]. This is the reason why several studies [5,10,23] and international guidelines [3,4] recommend every diagnostic laboratory establish their RIs speci c to the local population being served and not blindly follow the RIs for unrelated populations.…”

Establishment of Reference Intervals of Ten Commonly Used Clinical Chemistry Analytes: A Real-World Study in China

“…This real-world study using check-up data of apparently healthy population of Beijing, China estimated RIs of ten commonly used disease biomarkers that indicated different health issues: important body enzymes (CK, CK-MB, ALP, GGT), blood indicators of liver and kidney function (BUN) and biochemical markers of glucose and lipid metabolism, (glucose, TC, TG, Apo A1 and Apo B). The RIs established in our study was similar to those established in other studies conducted in Chinese population, which also used EP28-A3c guideline and had similar means of BMI, age and sex ratio with our study [9][10][11][12]. Appropriate population-based RIs are critical in the interpretation of clinical laboratory test results, and are important to support clinical decision making.…”