Use of laboratory information system data for indirect estimation of reference interval for vitamin B12

2015 ◽  
Vol 39 (6) ◽  
Author(s):  
Mufide Oncel ◽  
Emel Sahin ◽  
Aysel Kiyici ◽  
Bahattin Adam
Keyword(s):  
Information System ◽  
Vitamin B12 ◽  
Clinical Laboratory ◽  
Reference Interval ◽  
Serum Levels ◽  
Reference Intervals ◽  
National Committee ◽  
Reference Ranges ◽  
Laboratory Information System ◽  
The One

AbstractIn common, clinical laboratories use reference intervals recommended by the manufacturers. Various factors affect laboratory tests such as age, sex, diet and genetics. So, it is recommended for each laboratory to determine its own reference ranges for each test used. We aimed to establish our reference interval for vitamin B12.The data archive of laboratory information system was searched for a 1-year period between January and December, 2013. Among 2526 subjects searched for vitamin B12, 2368 remained (1–70 years old, 512 male and 1856 female) when we excluded the outliers for estimation of reference range for vitamin B12 with nonparametric method according to National Committee for Clinical Laboratory Standards (NCCLS) C28-A3 guidelines. Serum levels of vitamin B12 were determined with electrochemiluminescent technique.New reference interval for vitamin B12 derived from our results was 101–702 pg/mL, and was not affected by gender.New reference interval was different from the one recommended by the manufacturer. We suggest that established reference interval reflects our population better than the values recommended by the manufacturer.

scholarly journals SUN-222 Pre- and Post-Pubertal Reference Ranges for Oxygenated Androgens in Saliva

2020 ◽  
Vol 4 (Supplement_1) ◽  
Author(s):  
Joanne Adaway ◽  
Graeme Eisenhofer ◽  
Angela Huebner ◽  
Nils Krone ◽  
Malcolm McTaggart ◽  
...  
Keyword(s):  
Reference Interval ◽  
Reference Intervals ◽  
Range Data ◽  
Reference Ranges ◽  
Non Invasive ◽  
Premature Adrenarche ◽  
Upper Limits ◽  
Males And Females ◽  
Monitoring Treatment ◽  
Ovarian Syndrome

Abstract Oxygenated androgens such as 11 β-hydroxyandrostenedione (11OHA4) and 11-ketotestosterone (11KT) contribute significantly to the androgen pool in humans and their measurement has been shown to be useful in diagnosing disorders such as polycystic ovarian syndrome or premature adrenarche and also in monitoring treatment of congenital adrenal hyperplasia, alongside the classical androgens. Their measurement in saliva is particularly advantageous due to the non-invasive nature of sampling, meaning samples can easily be taken regularly to monitor treatment; however reference range data is not currently available for 11OHA4 and 11KT, limiting their clinical use. These analytes were measured in saliva samples from pre and post-pubertal males and females to inform reference ranges for these analytes. Samples collected into salivettes as part of the PRIMMS study (Technische Universität Dresden) were used for this work. A total of 130 samples (35 from pre-pubertal females, 43 from post-pubertal females, 42 from pre-pubertal males and 20 from post-pubertal males) were analysed for 11OHA4 and 11KT by LC-MS/MS. The ages of the participants ranged from 3.77 to 14.0 years in the pre-pubertal samples and 13.9-17.9 years in the post-pubertal samples. Pubertal status was determined clinically. The upper cut-off of the reference interval for 11OHA4 was 560 pmol/L in pre-pubertal females and 590 pmol/L in males, whilst 11KT had an upper limit of 216 pmol/L in females and 205 pmol/L in males. The upper limits of the ranges were higher in post-pubertal samples, with ranges of up to 1542 pmol/L in females and 1775 pmol/L in males for 11OHA4; the ranges for 11KT were up to 654 pmol/L for post pubertal females and 585 pmol/L for post-pubertal males. The data shows, as expected, a rise in the 11 oxygenated androgens post puberty. The upper limits of reference intervals for both analytes were very similar in males and females both pre- and post pubertally. These data can be used to inform clinical interpretation of the 11-oxygenated androgens; further work is required with larger cohorts of samples to develop more robust reference ranges.

The development of a third generation system for entering microbiology data into a clinical laboratory information system

1988 ◽  
Vol 12 (6) ◽  
pp. 365-382 ◽  
Author(s):  
Arthur A. Eggert ◽  
Kenneth A. Emmerich ◽  
Carol A. Spiegel ◽  
Gary J. Smulka ◽  
Patricia A. Horstmeier ◽  
...  
Keyword(s):  
Information System ◽  
Clinical Laboratory ◽  
Third Generation ◽  
Laboratory Information System ◽  
Generation System

scholarly journals Reference Intervals (RIs) of Lipid Parameters for Nepalese Population

2018 ◽  
Vol 6 (4) ◽  
pp. 366-372
Author(s):  
R.V. Mahato ◽  
R.K. Singh ◽  
A. M. Dutta ◽  
K. Ichihara ◽  
M. Lamsal
Keyword(s):  
Total Cholesterol ◽  
Reference Values ◽  
Clinical Laboratory ◽  
Local Population ◽  
Density Lipoprotein ◽  
Physical Exertion ◽  
Hdl Cholesterol ◽  
Reference Interval ◽  
Reference Intervals ◽  
Lipoprotein Cholesterol

Introduction: Reference interval (RIs) is the range of values provided by laboratory scientists in a convenient and practical form to support clinician in interpreting observed values for diagnosis, treatment and monitoring of a disease. Laboratories in Nepal uses RIs, provided in the kit inserts by the manufacturers or from the scientific literature, established for western/European population. It is well known that population across the globe differs physiologically, genetically; race, ethnically, lifestyle, food habits and diet which have great impact on the reference values. Thus, it is inappropriate to use RIs that do not represent the local population. This approach highlights for establishing reference values in Nepalese population using the IFCC-CRIDL guidelines published in (C28-A3). Objectives: The objective of this study is to analyze blood lipids concentration in apparently healthy Nepalese population to set up reference values for total cholesterol (TC), triglycerides (TG), High Density Lipoprotein-cholesterol (HDL-C) and Low Density Lipoprotein-cholesterol (LDL-C) and compare with the internationally recommended values. Methods: Reference individuals selected from healthy volunteers according to the IFCC/C-RIDL protocol in (C28 –A3). Volunteers were requested to avoid excessive physical exertion/exercise/excessive eating and drinking and fast overnight for 10-12 hour. Blood samples were collected from 120 subjects from each five centers of the country between 7:00-10:00 am, serum were separated and refrigerated at -20 in a cryo-vials. Finally, 617 samples were transported to Yamaguchi University, Graduate School of Medicine, Ube, Japan for analysis in dry Ice and 30 parameters were measured by fully automated biochemistry analyzer, Beckman Coulter (BC480) in the clinical laboratory. Results: A reference interval for each parameter was calculated from the 95% reference intervals ranging from 2.5% and 97.5% percentiles and, arithmetic mean + 2 SD were also calculated. The 95% reference range for total cholesterol (2.53-6.14), triglyceride was(0.42-3.32),for HDL Cholesterol was (0.28-1.46), for LDL was(1.05-4.00) and for VLDL was (0.054-0.92) for Nepalese population. Conclusion: Nepalese clinicians can take into consideration of reference lipid values of this study for diagnosis, treatment and monitoring of disease. Int. J. Appl. Sci. Biotechnol. Vol 6(4): 366-372

A multi-stage Gaussian transformation algorithm for clinical laboratory data.

1982 ◽  
Vol 28 (8) ◽  
pp. 1735-1741 ◽  
Author(s):  
J C Boyd ◽  
D A Lacher
Keyword(s):  
Mean Squared Error ◽  
Clinical Laboratory ◽  
Statistical Tests ◽  
Random Noise ◽  
Laboratory Data ◽  
Reference Interval ◽  
Reference Intervals ◽  
Distributed Data ◽  
Multi Stage ◽  
Positive Coefficients

Abstract We have developed a multi-stage computer algorithm to transform non-normally distributed data to a normal distribution. This transformation is of value for calculation of laboratory reference intervals and for normalization of clinical laboratory variates before applying statistical procedures in which underlying data normality is assumed. The algorithm is able to normalize most laboratory data distributions with either negative or positive coefficients of skewness or kurtosis. Stepwise, a logarithmic transform removes asymmetry (skewness), then a Z-score transform and power function transform remove residual peakedness or flatness (kurtosis). Powerful statistical tests of data normality in the procedure help the user evaluate both the necessity for and the success of the data transformation. Erroneous assessments of data normality caused by rounded laboratory test values have been minimized by introducing computer-generated random noise into the data values. Reference interval endpoints that were estimated parametrically (mean +/- 2 SD) by using successfully transformed data were found to have a smaller root-mean-squared error than those estimated by the non-parametric percentile technique.

scholarly journals Indirect method for validating transference of reference intervals

2018 ◽  
Vol 56 (3) ◽  
pp. 463-470 ◽  
Author(s):  
Simon Lykkeboe ◽  
Claus Gyrup Nielsen ◽  
Peter Astrup Christensen
Keyword(s):  
Data Mining ◽  
Information System ◽  
Indirect Method ◽  
Good Health ◽  
Geographic Area ◽  
Reference Intervals ◽  
Laboratory Information System ◽  
Large Geographic Area ◽  
Reference Serum ◽  
Analytical Platforms

AbstractBackground:Transference of reference intervals (RIs) from multicentre studies are often verified by use of a small number of samples from reference individuals or by the use of one serum sample (Serum X for NORIP RI). Despite recommended and appropriate methods, both have inconveniencies and drawbacks. Several attempts have been made to develop an indirect method, which uses historical data from the laboratory. These methods are retrospective relying on older test results. A near prospective method would be preferable for the laboratories introducing new methods or changing analytical platforms.Methods:We performed a data mining experiment using results from our laboratory information system covering patients from a large geographic area. Request patterns for patients with assumed healthy characteristics were identified and used to extract laboratory results for calculation of new RI by an indirect method. Calculated RI and confidence intervals (CIs) were compared to transferred NORIP RI verified by NFKK Reference Serum X.Results:We found that our indirect method and NFKK Reference Serum X in general produced similar results when verifying transference of RI. The method produces results for all stratifications. Only single stratifications and one analyte showed unexplained incongruences to the NORIP RI.Conclusions:Our results suggest using request patterns as a surrogate measure for good health status. This allows for a data mining method for validation of RI or validating their transference, which is likely to be applicable in countries with similar healthcare and laboratory information system.

scholarly journals Effects of system tuning and RAM disk on the performance of a clinical laboratory information system

1989 ◽  
Vol 11 (3) ◽  
pp. 119-123 ◽  
Author(s):  
Arthur A. Eggert ◽  
Kenneth A. Emmerich ◽  
Thomas J. Blankenheim ◽  
Gary J. Smulka
Keyword(s):  
Operating System ◽  
Information System ◽  
Computer System ◽  
Clinical Laboratory ◽  
Storage Device ◽  
Laboratory Information System ◽  
Laboratory Computer ◽  
Before And After

Improvements in the performance of a laboratory computer system do not necessarily require the replacement of major portions of the system and may not require the acquisition of any hardware at all. Major bottlenecks may exist in the ways that the operating system manages its resources and the algorithm used for timesharing decisions. Moreover, significant throughput improvements may be attainable by switching to a faster storage device if substantial disk activity is performed. In this study the fractions of time used for each of the types of tasks a laboratory computer system performs (e.g. applications programs, disk transfer, queue cycler) are defined and measured. Methods for reducing the time fractions of the various types of overhead are evaluated by doing before and after studies. The combined results of the three studies indicated that a 50% improvement could be gained through system tuning and faster storage without replacement of the computer itself

scholarly journals Analisis dan Perancangan Sistem Informasi Laboratorium Rumah Sakit Kanker Dharmais Dengan Menggunakan Total Architecture Syntesis

2010 ◽  
Vol 1 (2) ◽  
pp. 561
Author(s):  
Michael Yoseph Ricky
Keyword(s):  
Information System ◽  
Design Methodology ◽  
Clinical Laboratory ◽  
Design Method ◽  
Current System ◽  
Laboratory Information System ◽  
Design And Implementation ◽  
Cancer Hospital ◽  
Analysis Design ◽  
Laboratory Information Systems

The purposes of this research are to design and implementation of laboratory information systems (LIS) at the Laboratory of Cancer Hospital Dharmais (Dharmais Cancer Hospital). The methods used are the method of analysis, design methodology using Total Architecture Synthesis (TAS) and database design methods. Methods include analysis of the survey directly into the clinical laboratory Dharmais Cancer Hospital, and interviews with users who running the current system in Dharmais Cancer Hospital Clinical Laboratory. The design method using TAS. The results of this study is a single integrated Laboratory Information System applications with other systems that exist in Dharmais Cancer Hospital and also the delivery of feature inspection results by using text service and email, in addition to be taken directly to Dharmais Cancer Hospital and sent to the address. The conclusions from this study are all the transactions contained in Dharmais Cancer Hospital Clinical Laboratory have been computerized and integrated. 

scholarly journals DETERMINING REFERENCE RANGES FOR TREC AND KREC ASSAYS IN IMMUNE DEFICIENCY SCREENING OF NEWBORNS IN RUSSIAN FEDERATION

2019 ◽  
Vol 21 (3) ◽  
pp. 527-538
Author(s):  
M. A. Gordukova ◽  
I. A. Korsunsky ◽  
Yu. V. Chursinova ◽  
M. M. Byakhova ◽  
I. P. Oscorbin ◽  
...  
Keyword(s):  
Reference Interval ◽  
Reference Population ◽  
Dried Blood Spots ◽  
Reference Intervals ◽  
Asymmetric Distribution ◽  
Reference Ranges ◽  
Individual Values ◽  
Experimental Values ◽  
Deficiency Screening ◽  
Guthrie Cards

In this work, we used a reference population of newborns and sampled dried blood spots on Guthrie cards of 2,739 individual samples to determine the reference intervals for TRECs and KRECs values, in order to diagnose primary immunodeficiency by means of neonatal screening. The median absolute values for TRECs and KRECs were 195 (CI95%: 185-206) and 185 (CI95%: 176-197) copies per μl, respectively; the normalized value for TRECs was 2780 (CI95%: 2690-2840), and for KRECs, 2790 (CI95%: 2700-2900) copies per 2 × 105 copies of the albumin gene or 105 cells. The reference interval was calculated for 99 and 99.9 percentiles of total TRECs and KRECs individual values. Due to asymmetric distribution of data, the outliers were filtered off, using the Tukey’s criterion applied after logarithmic transformation of the data. When analyzing absolute values for TREC/KREC (per μL of blood), no “drop-down” TRECs values were identified; for KRECs, 18 experimental values were excluded from further analysis (from 9.8 to 13.5). The outlying values were not identified among the normalized values of TRECs/KRECs. The obtained reference values for TRECs and KRECs (at the 0.1 percentile level) were, respectively, 458 and 32 per 105 cells, or 23 and 17 per μl of blood samples from neonates.

NUMBER: standardized reference intervals in the Netherlands using a ‘big data’ approach

2018 ◽  
Vol 0 (0) ◽  
Author(s):  
Wendy P.J. den Elzen ◽  
Nannette Brouwer ◽  
Marc H. Thelen ◽  
Saskia Le Cessie ◽  
Inez-Anne Haagen ◽  
...  
Keyword(s):  
General Chemistry ◽  
Big Data ◽  
The Netherlands ◽  
Clinical Laboratory ◽  
Reference Interval ◽  
Clinical Decision ◽  
Reference Intervals ◽  
Test Results ◽  
Study Population ◽  
Set Up

AbstractBackgroundExternal quality assessment (EQA) programs for general chemistry tests have evolved from between laboratory comparison programs to trueness verification surveys. In the Netherlands, the implementation of such programs has reduced inter-laboratory variation for electrolytes, substrates and enzymes. This allows for national and metrological traceable reference intervals, but these are still lacking. We have initiated a national endeavor named NUMBER (Nederlandse UniforMe Beslisgrenzen En Referentie-intervallen) to set up a sustainable system for the determination of standardized reference intervals in the Netherlands.MethodsWe used an evidence-based ‘big-data’ approach to deduce reference intervals using millions of test results from patients visiting general practitioners from clinical laboratory databases. We selected 21 medical tests which are either traceable to SI or have Joint Committee for Traceability in Laboratory Medicine (JCTLM)-listed reference materials and/or reference methods. Per laboratory, per test, outliers were excluded, data were transformed to a normal distribution (if necessary), and means and standard deviations (SDs) were calculated. Then, average means and SDs per test were calculated to generate pooled (mean±2 SD) reference intervals. Results were discussed in expert meetings.ResultsSixteen carefully selected clinical laboratories across the country provided anonymous test results (n=7,574,327). During three expert meetings, participants found consensus about calculated reference intervals for 18 tests and necessary partitioning in subcategories, based on sex, age, matrix and/or method. For two tests further evaluation of the reference interval and the study population were considered necessary. For glucose, the working group advised to adopt the clinical decision limit.ConclusionsUsing a ‘big-data’ approach we were able to determine traceable reference intervals for 18 general chemistry tests. Nationwide implementation of these established reference intervals has the potential to improve unequivocal interpretation of test results, thereby reducing patient harm.

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