Establishment of Reference Intervals for Alkaline Phosphatase in Pakistani Children Using a Data Mining Approach

2019 ◽  
Vol 51 (5) ◽  
pp. 484-490 ◽  
Author(s):  
Sibtain Ahmed ◽  
Jakob Zierk ◽  
Aysha Habib Khan
Keyword(s):  
Data Mining ◽  
Alkaline Phosphatase ◽  
Clinical Decision Making ◽  
Clinical Chemistry ◽  
Age Groups ◽  
Clinical Decision ◽  
German Society ◽  
Reference Intervals ◽  
Photometric Method ◽  
Data Mining Approach

Abstract Objective To establish reference intervals (RIs) for alkaline phosphatase (ALP) levels in Pakistani children using an indirect data mining approach. Methods ALP levels analyzed on a Siemens Advia 1800 analyzer using the International Federation of Clinical Chemistry’s photometric method for both inpatients and outpatients aged 1 to 17 years between January 2013 and December 2017, including patients from intensive care units and specialty units, were retrieved. RIs were calculated using a previously validated indirect algorithm developed by the German Society of Clinical Chemistry and Laboratory Medicine’s Working Group on Guide Limits. Results From a total of 108,845 results, after the exclusion of patients with multiple specimens, RIs were calculated for 24,628 males and 18,083 females with stratification into fine-grained age groups. These RIs demonstrate the complex age- and sex-related ALP dynamics occurring during physiological development. Conclusion The population-specific RIs serve to allow an accurate understanding of the fluctuations in analyte activity with increasing age and to support clinical decision making.

High-resolution pediatric reference intervals for 15 biochemical analytes described using fractional polynomials

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Jakob Zierk ◽  
Hannsjörg Baum ◽  
Alexander Bertram ◽  
Martin Boeker ◽  
Armin Buchwald ◽  
...  
Keyword(s):  
Information Systems ◽  
Laboratory Test ◽  
Clinical Decision Making ◽  
Age Groups ◽  
Clinical Decision ◽  
Reference Intervals ◽  
Test Results ◽  
Laboratory Test Results ◽  
Glutamyl Transferase ◽  
Laboratory Information Systems

Abstract Objectives Assessment of children’s laboratory test results requires consideration of the extensive changes that occur during physiological development and result in pronounced sex- and age-specific dynamics in many biochemical analytes. Pediatric reference intervals have to account for these dynamics, but ethical and practical challenges limit the availability of appropriate pediatric reference intervals that cover children from birth to adulthood. We have therefore initiated the multi-center data-driven PEDREF project (Next-Generation Pediatric Reference Intervals) to create pediatric reference intervals using data from laboratory information systems. Methods We analyzed laboratory test results from 638,683 patients (217,883–982,548 samples per analyte, a median of 603,745 test results per analyte, and 10,298,067 test results in total) performed during patient care in 13 German centers. Test results from children with repeat measurements were discarded, and we estimated the distribution of physiological test results using a validated statistical approach (kosmic). Results We report continuous pediatric reference intervals and percentile charts for alanine transaminase, aspartate transaminase, lactate dehydrogenase, alkaline phosphatase, γ-glutamyl-transferase, total protein, albumin, creatinine, urea, sodium, potassium, calcium, chloride, anorganic phosphate, and magnesium. Reference intervals are provided as tables and fractional polynomial functions (i.e., mathematical equations) that can be integrated into laboratory information systems. Additionally, Z-scores and percentiles enable the normalization of test results by age and sex to facilitate their interpretation across age groups. Conclusions The provided reference intervals and percentile charts enable precise assessment of laboratory test results in children from birth to adulthood. Our findings highlight the pronounced dynamics in many biochemical analytes in neonates, which require particular consideration in reference intervals to support clinical decision making most effectively.

Establishing and using reference intervals

2020 ◽  
Vol 45 (1) ◽  
pp. 1-10
Author(s):  
Yesim Ozarda
Keyword(s):  
Clinical Chemistry ◽  
Laboratory Data ◽  
Age Groups ◽  
Clinical Decision ◽  
Reference Population ◽  
External Source ◽  
Reference Intervals ◽  
Multicenter Studies ◽  
Indirect Methods ◽  
Laboratory Test Results

AbstractReference intervals (RIs) and clinical decision limits (CDLs) are fundamental tools used by healthcare and laboratory professionals to interpret patient laboratory test results. The traditional method for establishing RIs, known as the direct approach, is based on collecting samples from members of a preselected reference population, making the measurements and then determining the intervals. For challenging groups such as pediatric and geriatric age groups, indirect methods are appointed for the derivation of RIs in the EP28-A3c guideline. However, there has been an increasing demand to use the indirect methods of deriving RIs by the use of routine laboratory data stored in the laboratory information system. International Federation of Clinical Chemistry (IFCC), Committee on Reference Intervals and Decision Limits (C-RIDL) is currently working on the study for the comparison of the conventional (direct) and alternative (indirect) approaches for the determination of reference intervals. As a matter of fact that, the process of developing RIs is often beyond the capabilities of an individual laboratory due to the complex, expensive and time-consuming process to develop them. Therefore, a laboratory can alternatively transfer and verify RIs established by an external source (i.e. manufacturers’ package inserts, publications). IFCC, C-RIDL has focused primarily on RIs and has performed multicenter studies to obtain common RIs in recent years. However, as the broader responsibility of the Committee, from its name, includes “decision limits”, the C-RIDL also emphasizes the importance of the correct use of both RIs and CDLs and to encourage laboratories to specify the appropriate information to clinicians as needed.

Pediatric reference interval verification for endocrine and fertility hormone assays on the Abbott Alinity system

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Mary Kathryn Bohn ◽  
Siobhan Wilson ◽  
Alexandra Hall ◽  
Khosrow Adeli
Keyword(s):  
Clinical Decision Making ◽  
De Novo ◽  
Reference Interval ◽  
Clinical Decision ◽  
Reference Intervals ◽  
Healthy Children ◽  
Confidence Limits ◽  
Test Results ◽  
Serum Samples ◽  
Abbott Architect

Abstract Objectives The Canadian Laboratory Initiative on Pediatric Reference Intervals (CALIPER) has developed an extensive database of reference intervals (RIs) for several biomarkers on various analytical systems. In this study, pediatric RIs were verified for key immunoassays on the Abbott Alinity system based on the analysis of healthy children samples and comparison to comprehensive RIs previously established for Abbott ARCHITECT assays. Methods Analytical performance of Alinity immunoassays was first assessed. Subsequently, 100 serum samples from healthy children recruited with informed consent were analyzed for 16 Alinity immunoassays. The percentage of test results falling within published CALIPER ARCHITECT reference and confidence limits was determined. If ≥ 90% of test results fell within the confidence limits, they were considered verified based on CLSI guidelines. If <90% of test results fell within the confidence limits, additional samples were analyzed and new Alinity RIs were established. Results Of the 16 immunoassays assessed, 13 met the criteria for verification with test results from ≥ 90% of healthy serum samples falling within the published ARCHITECT confidence limits. New CALIPER RIs were established for free thyroxine and prolactin on the Alinity system. Estradiol required special considerations in early life. Conclusions Our data demonstrate excellent concordance between ARCHITECT and Alinity immunoassays, as well as the robustness of previously established CALIPER RIs for most immunoassays, eliminating the need for de novo RI studies for most parameters. Availability of pediatric RIs for immunoassays on the Alinity system will assist clinical laboratories using this new platform and contribute to improved clinical decision-making.

Combined data mining techniques based patient data outlier detection for healthcare safety

2016 ◽  
Vol 9 (1) ◽  
pp. 42-68 ◽  
Author(s):  
Gebeyehu Belay Gebremeskel ◽  
Chai Yi ◽  
Zhongshi He ◽  
Dawit Haile
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Patient Safety ◽  
Outlier Detection ◽  
Clinical Data ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Healthcare Services ◽  
Content Type ◽  
Outliers Detection

Purpose – Among the growing number of data mining (DM) techniques, outlier detection has gained importance in many applications and also attracted much attention in recent times. In the past, outlier detection researched papers appeared in a safety care that can view as searching for the needles in the haystack. However, outliers are not always erroneous. Therefore, the purpose of this paper is to investigate the role of outliers in healthcare services in general and patient safety care, in particular. Design/methodology/approach – It is a combined DM (clustering and the nearest neighbor) technique for outliers’ detection, which provides a clear understanding and meaningful insights to visualize the data behaviors for healthcare safety. The outcomes or the knowledge implicit is vitally essential to a proper clinical decision-making process. The method is important to the semantic, and the novel tactic of patients’ events and situations prove that play a significant role in the process of patient care safety and medications. Findings – The outcomes of the paper is discussing a novel and integrated methodology, which can be inferring for different biological data analysis. It is discussed as integrated DM techniques to optimize its performance in the field of health and medical science. It is an integrated method of outliers detection that can be extending for searching valuable information and knowledge implicit based on selected patient factors. Based on these facts, outliers are detected as clusters and point events, and novel ideas proposed to empower clinical services in consideration of customers’ satisfactions. It is also essential to be a baseline for further healthcare strategic development and research works. Research limitations/implications – This paper mainly focussed on outliers detections. Outlier isolation that are essential to investigate the reason how it happened and communications how to mitigate it did not touch. Therefore, the research can be extended more about the hierarchy of patient problems. Originality/value – DM is a dynamic and successful gateway for discovering useful knowledge for enhancing healthcare performances and patient safety. Clinical data based outlier detection is a basic task to achieve healthcare strategy. Therefore, in this paper, the authors focussed on combined DM techniques for a deep analysis of clinical data, which provide an optimal level of clinical decision-making processes. Proper clinical decisions can obtain in terms of attributes selections that important to know the influential factors or parameters of healthcare services. Therefore, using integrated clustering and nearest neighbors techniques give more acceptable searched such complex data outliers, which could be fundamental to further analysis of healthcare and patient safety situational analysis.

scholarly journals Toward harmonization of clinical molecular diagnostic reports: findings of an international survey

2018 ◽  
Vol 0 (0) ◽  
Author(s):  
Deborah A. Payne ◽  
Katarina Baluchova ◽  
Graciela Russomando ◽  
Parviz Ahmad-Nejad ◽  
Cyril Mamotte ◽  
...  
Keyword(s):  
Molecular Diagnostics ◽  
Clinical Decision Making ◽  
Clinical Chemistry ◽  
Clinical Decision ◽  
Molecular Diagnostic ◽  
Molecular Testing ◽  
End User ◽  
Iso 15189 ◽  
Reporting Practices ◽  
Reporting Phase

Abstract Background: The International Organization for Standardization (ISO) 15189 standard provides recommendations for the postexamination reporting phase to enhance quality in clinical laboratories. The purpose of this study was to encourage a broad discussion on current reporting practices for molecular diagnostic tests by conducting a global survey of such practices. Methods: The International Federation of Clinical Chemistry and Laboratory Medicine’s Committee for Molecular Diagnostics (IFCC C-MD) surveyed laboratories on selected ISO 15189 recommendations and topics. The survey addressed the following aspects: (1) laboratory demographics, (2) report format, (3) result reporting/layout, (4) comments in report and (5) interpretation and clinical decision-making information. Additionally, participants indicated categories needing standardization. Results: Sixteen responses from laboratories located in Asia, Europe, the Middle East, North America and South America were received. Several categories yielded 100% agreement between laboratories, whereas other categories had less than or equal to 50% concordance. Participants scored “nomenclature” and “description of methodologies” as the two most frequently cited aspects needing standardization. Conclusions: The postexamination phase requires extensive and consistent communication between the laboratory, the healthcare provider and the end user. Surveyed laboratories were most likely to follow explicit ISO 15189 recommendations vs. recommendations when the term(s) “where appropriate or where applicable” was used. Interpretation and reporting of critical values varied among participants. Although the outcome of this study may not fully represent the practices of all molecular testing laboratories in countries around the world, the survey identified and specified several recommendations that are requirements for harmonized reporting in molecular diagnostics.

Reference intervals for 21 clinical chemistry analytes in arterial and venous umbilical cord blood

1993 ◽  
Vol 39 (6) ◽  
pp. 1041-1044 ◽  
Author(s):  
S L Perkins ◽  
J F Livesey ◽  
J Belcher
Keyword(s):  
Alkaline Phosphatase ◽  
Umbilical Cord ◽  
Clinical Chemistry ◽  
Venous Blood ◽  
Reference Interval ◽  
Reference Intervals ◽  
Nonparametric Analysis ◽  
Term Infants ◽  
Male And Female ◽  
Gamma Glutamyltransferase

Abstract Reference intervals were determined for 21 clinical chemistry analytes in umbilical cord arterial and venous blood from healthy term infants. Nonparametric analysis (rank number) was used to determine the central 95% reference interval. No significant differences were observed between male and female infants. Reference intervals for glucose, urea, creatinine, urate, phosphate, calcium, albumin, total protein, cholesterol, triglycerides, alkaline phosphatase, alanine aminotransferase, aspartate aminotransferase, creatine kinase, lactate dehydrogenase, gamma-glutamyltransferase, and magnesium all were significantly different from adult values.

Total Amylase and Pancreatic Isoamylase in Serum and Urine: Considerations from Data on Biological Variation

1989 ◽  
Vol 26 (4) ◽  
pp. 335-340 ◽  
Author(s):  
Steven T Cummings ◽  
Callum G Fraser
Keyword(s):  
Clinical Decision Making ◽  
Amylase Activity ◽  
Clinical Decision ◽  
Population Based ◽  
Reference Intervals ◽  
Similar Data ◽  
Creatinine Ratio ◽  
Additional Information ◽  
Pancreatic Isoamylase ◽  
Urine Amylase

The analytical, within-subject and between-subject components of variation were estimated for amylase activity and pancreatic isoamylase activity in serum measured using newer analytical methods. Desirable analytical imprecisions based on within-subject variation were CV ≤ 4·4% and CV ≤ 7·0%, respectively. Conventional population-based reference intervals were not useful because of marked individuality; clinical decision-making points should be derived from the desired sensitivity and specificity. Serial results must change more than about 30% and 40% respectively before significance (P ≤ 0·05) can be claimed. Similar data on total amylase and pancreatic isoamylase activities in random and first morning urines showed that the use of conventional reference intervals was appropriate. Very large changes (> 100%) were required before a difference in serial results was significant. Calculation of the urine amylase/creatinine ratio appeared to confer no advantage. Derivation of the ratio of pancreatic isoamylase to total amylase activity in serum or urine was unlikely to provide additional information of value in either diagnosis or monitoring.

scholarly journals Data mining of pediatric reference intervals

2021 ◽  
Vol 45 (6) ◽  
pp. 311-317
Author(s):  
Jakob Zierk ◽  
Markus Metzler ◽  
Manfred Rauh
Keyword(s):  
Data Mining ◽  
Information Systems ◽  
Statistical Methods ◽  
Clinical Decision Making ◽  
Reference Intervals ◽  
Healthy Children ◽  
Test Results ◽  
Young Infants ◽  
Age Related ◽  
Laboratory Test Results

Abstract Laboratory tests are essential to assess the health status and to guide patient care in individuals of all ages. The interpretation of quantitative test results requires availability of appropriate reference intervals, and reference intervals in children have to account for the extensive physiological dynamics with age in many biomarkers. Creation of reference intervals using conventional approaches requires the sampling of healthy individuals, which is opposed by ethical and practical considerations in children, due to the need for a large number of blood samples from healthy children of all ages, including neonates and young infants. This limits the availability and quality of pediatric reference intervals, and ultimately negatively impacts pediatric clinical decision-making. Data mining approaches use laboratory test results and clinical information from hospital information systems to create reference intervals. The extensive number of available test results from laboratory information systems and advanced statistical methods enable the creation of pediatric reference intervals with an unprecedented age-related accuracy for children of all ages. Ongoing developments regarding the availability and standardization of electronic medical records and of indirect statistical methods will further improve the benefit of data mining for pediatric reference intervals.

scholarly journals Predicting Cardiovascular Risk in Athletes: Resampling Improves Classification Performance

2020 ◽  
Vol 17 (21) ◽  
pp. 7923
Author(s):  
Davide Barbieri ◽  
Nitesh Chawla ◽  
Luciana Zaccagni ◽  
Tonći Grgurinović ◽  
Jelena Šarac ◽  
...  
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Cardiovascular Risk ◽  
Clinical Decision Making ◽  
Characteristic Curve ◽  
Area Under The Curve ◽  
Clinical Decision ◽  
Classification Performance ◽  
Biomedical Data ◽  
Sport Practice

Cardiovascular diseases are the main cause of death worldwide. The aim of the present study is to verify the performances of a data mining methodology in the evaluation of cardiovascular risk in athletes, and whether the results may be used to support clinical decision making. Anthropometric (height and weight), demographic (age and sex) and biomedical (blood pressure and pulse rate) data of 26,002 athletes were collected in 2012 during routine sport medical examinations, which included electrocardiography at rest. Subjects were involved in competitive sport practice, for which medical clearance was needed. Outcomes were negative for the largest majority, as expected in an active population. Resampling was applied to balance positive/negative class ratio. A decision tree and logistic regression were used to classify individuals as either at risk or not. The receiver operating characteristic curve was used to assess classification performances. Data mining and resampling improved cardiovascular risk assessment in terms of increased area under the curve. The proposed methodology can be effectively applied to biomedical data in order to optimize clinical decision making, and—at the same time—minimize the amount of unnecessary examinations.

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