Quality in post-analytical phase: Indirect reference intervals for erythrocyte parameters of neonates

2013 ◽  
Vol 46 (7-8) ◽  
pp. 617-621 ◽  
Author(s):  
Daniela Stefania Grecu ◽  
Eugenia Paulescu
Keyword(s):  
Reference Intervals ◽  
Analytical Phase ◽  
Indirect Reference

scholarly journals Establishment of PIVKA-Ⅱ Reference Intervals From Hospital-stored Data: A Comparison Analysis

2021 ◽  
Author(s):  
Lewei Zhou ◽  
Qiyuan Su ◽  
Yan Yao ◽  
Meixian Xiang ◽  
Jiesheng Zhen ◽  
...  
Keyword(s):  
Clinical Laboratory ◽  
Reference Intervals ◽  
Female Group ◽  
Comparison Analysis ◽  
Test Items ◽  
Health Group ◽  
Significant Difference ◽  
The Difference ◽  
Gender Specific ◽  
Indirect Reference

Abstract Objective The authors aimed to explore methods to establish indirect reference intervals for PIVKA-II from hospital-stored data.Method 7623 patient specimens of the Renmin Hospital of Wuhan University were collected. Indirect reference intervals were established based on the hospital-stored data with four different methods, including the Hoffmann method (HM), revised Hoffmann method (HMCDF), E-M algorithm-based method (EMBCT), and a recent estimator (KOSMIC). According to CLSI C28-A3 guidelines, 369 healthy specimens were collected. The authors tested the difference between reference intervals of gender-specific and age-specific subgroups using Harris and Boyd's test. Finally, the averaging result of estimates was calculated according to how likely each model was.Results The indirect reference intervals of PIVKA-II based on LIS data were 0 to 35.30 mAU/mL (HM), 0 to 31.48 mAU/mL (HMCDF), 0 to 30.78 mAU/mL (EMBCT), 0 to 36.17 mAU/mL (KOSMIC) and 0 to 31.48 mAU/mL (averaging) respectively, and the reference intervals based on healthy group were 0 to 32 mAU/mL. Compared with HM, EMBCT and KOSMIC, HMCDF and the averaging result was closer to those of the health group. Significant difference was detected between gender-partitioned subgroups, and the reference upper limit in the female group was smaller than the male group.Conclusions The authors established the indirect reference intervals of PIVKA-II for the Wuhan population, which could be used to the clinical reference intervals. The framework proposed could help clinical laboratory set their reference intervals of test items.

Use of total patient data for indirect estimation of reference intervals for 40 clinical chemical analytes in Turkey

2006 ◽  
Vol 44 (7) ◽  
Author(s):  
Yesim Ozarda Ilcol ◽  
Diler Aslan
Keyword(s):  
Binding Capacity ◽  
Clinical Chemistry ◽  
Reference Intervals ◽  
Thyroid Stimulating Hormone ◽  
Patient Data ◽  
Clinical Chemical ◽  
Laboratory Results ◽  
Total Triiodothyronine ◽  
Iron Binding Capacity ◽  
Indirect Reference

AbstractIn the present study we used patient data to calculate laboratory-specific indirect reference intervals. These values were compared with reference intervals obtained for a healthy group according to recommendations of the International Federation of Clinical Chemistry and Laboratory Medicine and manufacturer suggestions. Laboratory results (422,919 records) from all subjects of 18–45years of age over a 1-year period were retrieved from our laboratory information system and indirect reference intervals for 40 common analytes were estimated using a modified Bhattacharya procedure. Indirect reference intervals for most of the biochemical analytes were comparable, with small differences in lower [alkaline phosphatase (ALP) (male), alanine aminotransferase (ALT), creatine kinase, iron (male), total iron-binding capacity, folic acid, calcium (female), lactate dehydrogenase (LDH), lipoprotein (a) [Lp(a)], thyroid-stimulating hormone (TSH), total triiodothyronine (TClin Chem Lab Med 2006;44:867–76.

scholarly journals Separating disease and health for indirect reference intervals

2021 ◽  
Vol 45 (2) ◽  
pp. 55-68 ◽  
Author(s):  
Kenneth A. Sikaris
Keyword(s):  
A Priori ◽  
Laboratory Data ◽  
Reference Interval ◽  
Statistical Technique ◽  
Reference Intervals ◽  
Large Databases ◽  
Statistical Issues ◽  
Physiological Variations ◽  
Indirect Reference ◽  
Apparently Healthy

Abstract The indirect approach to defining reference intervals operates ‘a posteriori’, on stored laboratory data. It relies on being able to separate healthy and diseased populations using one or both of clinical techniques or statistical techniques. These techniques are also fundamental in a priori, direct reference interval approaches. The clinical techniques rely on using clinical data that is stored either in the electronic health record or within the laboratory database, to exclude patients with possible disease. It depends on the investigators understanding of the data and the pathological impacts on tests. The statistical technique relies on identifying a dominant, apparently healthy, typically Gaussian distribution, which is unaffected by the overlapping populations with higher (or lower) results. It depends on having large databases to give confidence in the extrapolation of the narrow portion of overall distribution representing unaffected individuals. The statistical issues involved can be complex, and can result in unintended bias, particularly when the impacts of disease and the physiological variations in the data are under appreciated.

scholarly journals Indirect reference intervals for haematological parameters in capillary blood of pre-school children

2021 ◽  
Vol 31 (1) ◽  
pp. 134-142
Author(s):  
Jelena Vekic ◽  
Zorana Jelic-Ivanovic ◽  
Vesna Spasojevic-Kalimanovska ◽  
Aleksandra Zeljkovic ◽  
Zsófia Csuzdi Balog ◽  
...  
Keyword(s):  
School Children ◽  
Reference Intervals ◽  
Capillary Blood ◽  
Haematological Parameters ◽  
Percentile Method ◽  
Wbc Count ◽  
Gender Specific ◽  
Indirect Reference ◽  
Rbc Count

Introduction: Indirect estimation of reference intervals (RIs) is straightforward and inexpensive procedure for determination of intra-laboratory RIs. We applied the indirect approach to assess RIs for haematological parameters in capillary blood of pre-school children, using results stored in our laboratory database. Materials and methods: We extracted data from laboratory information system, for the results obtained by automatic haematology analyser in capillary blood of 154 boys and 146 girls during pre-school medical examination. Data distribution was tested, and logarithmic transformation was applied if needed. Reference intervals were calculated by the nonparametric percentile method. Results: Reference intervals were calculated for: RBC count (4.2-5.4 x1012/L), haemoglobin (114-146 g/L), MCH (25.0-29.4 pg), MCHC (321-368 g/L), RDW-SD (36.1-43.5 fL), WBC count (4.5-12.3 x109/L), neutrophils count (1.7-6.9 x109/L) and percentage (29.0-69.0%), lymphocytes count (1.6-4.4 x109/L) and percentage (21.9-60.7%), PLT (165-459 x109/L), MPV (8.1-11.4 fL) and PDW (9.2-14.4%). Gender specific RIs were calculated for monocytes count (male (M): 0.2-1.6 x109/L; female (F): 0.1-1.4 x109/L) and percentage (M: 2.5-18.3%; F: 1.8-16.7%), haematocrit (M: 0.34-0.42 L/L; F: 0.34-0.43 L/L), MCV (M: 73.4-84.6 fL; F: 75.5-84.2 fL) and RDW (M: 12.1-14.3%; F: 11.7-13.9%), due to observed gender differences in these parameters (P = 0.031, 0.028, 0.020, 0.012 and 0.001; respectively). Estimated RIs markedly varied from the literature based RIs that are used in the laboratory. Conclusions: Indirect method employed in this study enables straightforward assessment of RIs in pre-school children. Herein derived RIs differed from the literature-based ones, indicating the need for intra-laboratory determination of RIs for specific populations and sample types.

scholarly journals Estimation of indirect reference intervals for serum thyrotropin using hospital records

2017 ◽  
Vol 8 (3) ◽  
pp. 41-48 ◽  
Author(s):  
Kushal Bhattarai ◽  
Nilu Manandhar ◽  
Prabodh Shrestha ◽  
Sangita Thapa ◽  
Jharana Shrestha ◽  
...  
Keyword(s):  
Clinical Decision Making ◽  
Clinical Chemistry ◽  
Tertiary Care ◽  
Reference Intervals ◽  
Medical Sciences ◽  
Hospital Records ◽  
Clinical Databases ◽  
Test Kit ◽  
Indirect Reference ◽  
Serum Tsh

Background: Reference intervals of any biochemical analyte serve as an invaluable tool in clinical decision making. The IFCC (International Federation of Clinical Chemistry) guidelines for determining these values are not feasible in some hospital laboratory setting and have led to the development of alternative approaches.Aims and Objectives: To determine the indirect reference intervals for serum thyrotropin form the hospital records of individuals visiting a tertiary care center.Materials and Methods: In a hospital-record based, observational, cross-sectional study, data of serum TSH levels were collected from the hospital records of participants who underwent this test in the Central Clinical Laboratory, College of Medical Sciences and Teaching Hospital, Bharatpur, Chitwan, Nepal from July 2012 to June 2015. All the individuals, irrespective of their diagnoses of thyroid diseases and other possible comorbid conditions, were included in the study. Prior to the statistical analyses, partitioning was done in relation to gender, age, and ethnicity. The reference intervals for thyrotropin were established by non-parametric method.Results: Reference intervals for serum TSH best agreeing to those provided by the test kit suppliers were determined by combining the two strategies that used Tukey’s method of detection and removal of outliers, prior to the final analyses. Lower limit was best determined from the natural-log-transformed and upper limit from non-transformed TSH values with outliers removed by Tukey’s method in both. As such, for the cases with TSH in the range 0.02-98.8 mIU/L, the reference intervals were calculated as [0.31 (0.30-0.33) to 6.04 (5.97-6.12) mIU/L] and for the TSH in the range 0.102-9.99 mIU/L, [0.35 (0.34-0.37) to 5.81 (5.75-5.90) mIU/L].Conclusion: For establishing the indirect reference intervals from the hospital records, laboratory data can be combined with information stored in clinical databases for selecting subjects fulfilling stated clinical criteria.Asian Journal of Medical Sciences Vol.8(3) 2017 41-48

scholarly journals Indirect Reference Intervals Estimated from Hospitalized Population for Thyrotropin and Free Thyroxine

2010 ◽  
Vol 51 (2) ◽  
pp. 124-130 ◽  
Author(s):  
Tamer C. Inal ◽  
Mustafa Serteser ◽  
Abdurrahman Coşkun ◽  
Aysel Özpinar ◽  
Ibrahim Ünsal
Keyword(s):  
Reference Intervals ◽  
Free Thyroxine ◽  
Indirect Reference

scholarly journals Application of the TML method to big data analytics and reference interval harmonization

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Mary Kathryn Bohn ◽  
Khosrow Adeli
Keyword(s):  
Clinical Chemistry ◽  
A Priori ◽  
Big Data Analytics ◽  
Reference Interval ◽  
German Society ◽  
Reference Intervals ◽  
Indirect Methods ◽  
Advantages And Disadvantages ◽  
Result Interpretation ◽  
Indirect Reference

Abstract Significant variation in reported reference intervals across healthcare centers and networks for many well-standardized laboratory tests continues to exist, negatively impacting patient outcomes by increasing the risk of inappropriate and inconsistent test result interpretation. Reference interval harmonization has been limited by challenges associated with direct reference interval establishment as well as hesitancies to apply currently available indirect methodologies. The Truncated Maximum Likelihood (TML) method for indirect reference interval establishment developed by the German Society of Clinical Chemistry and Laboratory Medicine (DGKL) presents unique clinical and statistical advantages compared to traditional indirect methods (Hoffmann and Bhattacharya), increasing the feasibility of developing indirect reference intervals that are comparable to those determined using a direct a priori approach based on healthy reference populations. Here, we review the application of indirect methods, particularly the TML method, to reference interval harmonization and discuss their associated advantages and disadvantages. We also describe the CSCC Reference Interval Harmonization Working Group’s experience with the application of the TML method in harmonization of adult reference intervals in Canada.

Performance criteria of the post-analytical phase

2015 ◽  
Vol 53 (6) ◽  
Author(s):  
Kenneth Sikaris
Keyword(s):  
Procedural Knowledge ◽  
Clinical Information ◽  
Clinical Decision ◽  
Data Interpretation ◽  
Reference Intervals ◽  
Performance Criteria ◽  
Quality Data ◽  
Clinical Value ◽  
Analytical Phase ◽  
Quality In Healthcare

AbstractQuality in healthcare is ideally at an optimal benchmark, but must be at least above the minimal standards for care. While laboratory quality is ideally judged in clinical terms, laboratory medicine has also used biological variations and state-of-the-art criteria when, as is often the case, clinical outcome studies or clinical consensus are not available. The post-analytical phase involves taking quality technical results and providing the means for clinical interpretation in the report. Reference intervals are commonly used as a basis for data interpretation; however, laboratories vary in the reference intervals they use, even when analysis is similar. Reference intervals may have greater clinical value if they are both optimised to account for physiological individuality, as well as if they are harmonised through professional consensus. Clinical decision limits are generally superior to reference intervals as a basis for interpretation because they address the specific clinical concern in any patient. As well as providing quality data and interpretation, the knowledge of laboratory experts can be used to provide targeted procedural knowledge in a patient report. Most profoundly critically abnormal results should to be acted upon to minimise the risk of mortality. The three steps in quality report interpretation, (i) describing the abnormal data, (ii) interpreting the clinical information within that data and (iii) providing knowledge for clinical follow-up, highlight that the quality of all laboratory testing is reflected in its impact on clinical management and improving patient outcomes.

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