Data mining: Seasonal and temperature fluctuations in thyroid-stimulating hormone

Wang, Danchen; Cheng, Xinqi; Yu, Songlin; Qiu, Ling; Lian, Xiaolan; Guo, Xing; Hu, Yingying; Lu, Shanshan; Yang, Guohua; Liu, Huaicheng

doi:10.1016/j.clinbiochem.2018.08.008

Cited by 46 publications

(23 citation statements)

References 11 publications

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“…Otherwise, all measurements were performed according to our laboratory standard operating procedures. Our laboratory also takes part in external quality assessments by the National Center for Clinical Laboratories and the College of American Pathologists to guarantee the accuracy and reliability of our study (9).…”

Section: Discussionmentioning

confidence: 99%

“…Numerous studies have reported common RIs based on traceable results that can be used for analytes with good traceability from different manufacturers to the same higher-order references (4)(5)(6). Reliable RIs are determined in completely healthy individuals but show variations (7)(8)(9)(10). It is critical but difficult for each clinical laboratory to establish RIs (11), as it is not easy to recruit healthy individuals and ensure pre-analysis, mid-analysis, and post-analysis quality control.…”

Section: Introductionmentioning

confidence: 99%

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

Wang

Zou

et al. 2019

Journal of Medical Biochemistry

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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.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

Wang

Zou

et al. 2019

Journal of Medical Biochemistry

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“…Outlying values were identified using Tukey's method, which involves the computation of the 25th (Q1) and 75th (Q3) percentiles and the interquartile range (IQR=Q3-Q1). Outliers were excluded based on the following formula: Q1-3IQR and Q3+3IQR (15).…”

Section: Methodsmentioning

confidence: 99%

Comparative analysis of the serum proteome profiles of thyroid cancer: An initial focus on the lipid profile

Zhou

et al. 2019

Oncol Lett

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The serum lipid profile and clinical outcomes of cancer patients are commonly correlated in a wide range of carcinomas. However, few studies have investigated the serum lipid profile of patients with thyroid cancer (TC). The present study therefore aimed to analyze the lipid profiles of patients with TC. The serum proteomes of 31 participants with stage I-IV TC were screened using Orbitrap Q Exactive Plus. Analytical data collected between November 1, 2013 and November 11, 2018 from the laboratory information system included the total cholesterol (CHO), triglyceride (TG), high-density lipoprotein-cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), apolipoprotein A1 (ApoA1), lipoprotein (a) and apolipoprotein B (ApoB) levels that were used to validate the screening results. A total of 3875 outpatients were enrolled in this study. A number of 17 differentially expressed proteins were identified. An Ingenuity pathway analysis identified activation of the liver X receptor/retinoid X receptor (LXR/RXR) activation, which is a crucial pathway involved in lipid metabolism. The results demonstrated that the total CHO levels were significantly different between patients with TC and control groups, both in men and women. In women, the levels of TG, HDL-C, Apo A1 and LDL-C/HDL-C were significantly different between patients with TC and control groups (all P<0.05). Higher concentrations of TG and LDL-C/HDL-C were observed in the cancer group compared with the control group. However, lower levels of Apo A1 and HDL-C were observed in women from the cancer group compared with the control group. The results from the present study revealed the presence of a disordered lipid profile in patients with TC. The molecular mechanism underlying the association between lipid metabolism and cancer requires further investigation and may be used to develop novel diagnostic biomarkers and therapeutic targets in human cancers.

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“…The analytical sensitivity of this assay was 0.5 mU/L. Measurements were performed according to the standard operating procedure (SOP) 12,13 . The instrument was calibrated and prophylactically maintained every year.…”

Section: Methodsmentioning

confidence: 99%

“…Measurements were performed according to the standard operating procedure (SOP). 12,13 The instrument was calibrated and prophylactically maintained every year. Our laboratory also participated in external quality assessments by the National Center for Clinical Laboratories and the College of American Pathologists to guarantee the accuracy and reliability of results.…”

Section: Laboratory Measurementsmentioning

confidence: 99%

Comparison of four matrixes for diluting insulin in routine clinical measurements

Wang

Guo

et al. 2020

Clinical Laboratory Analysis

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Objective In our laboratory, 2.36% (6626/280765) samples obtained for insulin evaluation have serum insulin concentrations higher than 300 mU/L, resulting in curves outside the linear range in the insulin release test (IRT). Accordingly, using appropriate dilution protocols to determine insulin concentration accurately is important. Here, we compared the effectiveness and economy of four different solutions for diluting high‐insulin serum in routine clinical measurements. Method Residual serum samples with high‐insulin concentrations ranging from 200 to 300 mU/L were collected in Peking Union Medical College Hospital from August to November 2017. Four different matrixes including a Siemens original diluent, pure water, 0.9% NaCl, and low‐insulin serum (labeled as A to D, respectively) were used to dilute the serum in the ratios of 1:2, 1:5, and 1:10. Results We found that the linear correlation coefficients of A to D were higher than 0.9. The recovery rates of A to D were 86.4%–104.0%, 73.2%–99.3%, 76.4%–101.3%, and 84.2%–99.7%, respectively. We conclude that the use of 0.9% NaCl, pure water, or low‐insulin serum to dilute high‐serum insulin (>300 mU/L) is feasible and cost‐effective. Conclusion We recommend a dilution factor of 1:5 on a Siemens ADVIA Centaur XP® instrument. The clinically reported range was 0.5‐1500 mU/L. For specific samples (>1500 mU/L), we recommended using low‐insulin serum samples for dilution.

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Data mining: Seasonal and temperature fluctuations in thyroid-stimulating hormone

Cited by 46 publications

References 11 publications

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

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

Comparative analysis of the serum proteome profiles of thyroid cancer: An initial focus on the lipid profile

Comparison of four matrixes for diluting insulin in routine clinical measurements

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