Interpreting clinical and laboratory tests: importance and implications of context

Diagnosis ◽  
2019 ◽  
Vol 0 (0) ◽  
Author(s):  
Alan N. Charney ◽  
Jordan T. Dourmashkin
Keyword(s):  
Laboratory Tests ◽  
Physiological Condition ◽  
Clinical Medicine ◽  
Normal Values ◽  
Reference Interval ◽  
Reference Intervals ◽  
Test Results ◽  
Normal Range ◽  
Behavioral Diversity ◽  
Range Test

AbstractClinical and laboratory tests in clinical medicine include a range of measurements that may be categorized as “normal range” tests, positive or negative tests, or contextual tests. Normal range test results are quantitative and are compared to a reference interval or range provided by the laboratory. Positive or negative tests are also quantitative tests and characteristically have a cutoff value that specifies the result. Contextual tests require a context, a physiological condition, to correctly interpret the result. A closer examination of reference intervals suggests that these also are contextual. The fact that there is a range of apparently normal values indicates the presence of cultural, biological, physiological and behavioral diversity in the population sampled to determine normality. As such, the reference interval describes the population from which it was determined and may have utility in this regard.

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.

scholarly journals Personalized Reference Intervals in Laboratory Medicine: A New Model Based on Within-Subject Biological Variation

2020 ◽  
Author(s):  
Abdurrahman Coşkun ◽  
Sverre Sandberg ◽  
Ibrahim Unsal ◽  
Coskun Cavusoglu ◽  
Mustafa Serteser ◽  
...  
Keyword(s):  
Steady State ◽  
Personalized Medicine ◽  
Clinical Chemistry ◽  
Reference Interval ◽  
Reference Intervals ◽  
Biological Variation ◽  
Test Results ◽  
Steady State Condition ◽  
Laboratory Test Results ◽  
Measurement Results

Abstract Background The concept of personalized medicine has received widespread attention in the last decade. However, personalized medicine depends on correct diagnosis and monitoring of patients, for which personalized reference intervals for laboratory tests may be beneficial. In this study, we propose a simple model to generate personalized reference intervals based on historical, previously analyzed results, and data on analytical and within-subject biological variation. Methods A model using estimates of analytical and within-subject biological variation and previous test results was developed. We modeled the effect of adding an increasing number of measurement results on the estimation of the personal reference interval. We then used laboratory test results from 784 adult patients (&gt;18 years) considered to be in a steady-state condition to calculate personalized reference intervals for 27 commonly requested clinical chemistry and hematology measurands. Results Increasing the number of measurements had little impact on the total variation around the true homeostatic set point and using ≥3 previous measurement results delivered robust personalized reference intervals. The personalized reference intervals of the study participants were different from one another and, as expected, located within the common reference interval. However, in general they made up only a small proportion of the population-based reference interval. Conclusions Our study shows that, if using results from patients in steady state, only a few previous test results and reliable estimates of within-subject biological variation are required to calculate personalized reference intervals. This may be highly valuable for diagnosing patients as well as for follow-up and treatment.

scholarly journals Partitioning Reference Intervals by Use of Genetic Information

2011 ◽  
Vol 57 (3) ◽  
pp. 475-481 ◽  
Author(s):  
Brian H Shirts ◽  
Andrew R Wilson ◽  
Brian R Jackson
Keyword(s):  
Genetic Information ◽  
Clinical Information ◽  
Reference Interval ◽  
Reference Intervals ◽  
Genetic Effects ◽  
Test Results ◽  
Simple Method ◽  
Asian Populations ◽  
Gilbert Syndrome ◽  
Recessive Effects

BACKGROUND Reference intervals that incorporate genetic information could reduce the misidentification of unusual test results caused by non–disease-associated genetic variation and increase the detection of results indicating underlying pathology. Subdividing reference groups by genetic effects, however, may lead to increased uncertainty around reference interval endpoints (because of the smaller subgroup sample sizes), thus offsetting any benefits. METHODS We evaluated CLSI guidelines to develop a method appropriate for partitioning reference intervals on the basis of genetic variants with dominant or recessive effects. This method uses information available before reference samples are recruited, thus allowing a preliminary decision regarding partitioning to be made before sampling. We used this method to evaluate the example of Gilbert syndrome. RESULTS The decision point for partitioning occurs when the percentage of total variance attributable to a dominant or recessive genetic polymorphism exceeds 4%. Similarly, partitioning decision curves are presented based on difference in means between 2 subgroups, sample SD, and subgroup or allele frequency. Laboratory-specific partitioned reference intervals for Gilbert syndrome appear to be statistically warranted for white and African-American populations, but not for Asian populations. CONCLUSIONS We present a simple method to evaluate whether partitioning based on dominant or recessive genetic effects is statistically justified. Important limitations remain that, in many situations, will preclude integration of genetic, laboratory, and clinical information. As society moves toward personalized medicine, additional research is needed on how to evaluate patient normality while accounting for additive genetic, multigenic, and other multifactorial effects.

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.

Desirable standards for laboratory tests if they are to fulfill medical needs

1993 ◽  
Vol 39 (7) ◽  
pp. 1447-1455 ◽  
Author(s):  
C G Fraser ◽  
P H Petersen
Keyword(s):  
Laboratory Tests ◽  
Normal Values ◽  
Performance Standards ◽  
Biological Variation ◽  
Test Results ◽  
Medical Needs ◽  
Advantages And Disadvantages ◽  
Clinical Vignettes ◽  
Traditional Approaches ◽  
Test Result

Abstract Many strategies to define desirable standards for laboratory tests to fulfill medical needs have been proposed over the last three decades. Traditional approaches are based on reference (normal) values, opinions of clinicians, the state of the art, views of experts, data on biological variation, and assessment of the effect of error on clinical use. All these approaches have advantages and disadvantages, but the consensus of experts reached over a decade ago that imprecision desirably be less than one-half of the within-subject biological variation still seems to provide the best set of generally applicable performance standards. Desirable bias is less than one-quarter of the group (within-subject plus between-subject) biological variation. Recent proposals are either restatements of traditional recommendations, further empirical suggestions, or models based on assessment of clinical needs, and have not been widely accepted. Both old and new studies on clinical opinions, sought by using structured questionnaires containing clinical vignettes designed to seek views on the magnitude of significant change, are flawed in design, execution, and data analysis. Until clinicians are more aware of test-result variability and clinical chemists gain quantitative knowledge on the interpretation of test results, it will be difficult to set desirable standards that fulfill actual medical needs, except in a few well-defined screening situations.

Evaluation of biological variations in glucose and glycated hemoglobin levels in healthy individuals

2017 ◽  
Vol 43 (5) ◽  
pp. 495-501
Author(s):  
Cihan Coskun ◽  
Berrin Bercik Inal ◽  
Humeyra Ozturk Emre ◽  
Sehide Baz ◽  
Alper Gumus ◽  
...  
Keyword(s):  
International Organizations ◽  
Glycated Hemoglobin ◽  
Reference Interval ◽  
Reference Intervals ◽  
Study Group ◽  
Test Results ◽  
Healthy Individuals ◽  
Reference Change Value ◽  
Performance Specifications ◽  
Index Of Individuality

Abstract Objective: In this study, we firstly aimed to determine components of biological variations (BVCs) in levels of glucose and glycated hemoglobin (HbA1c) in detail based on guidance from relevant organizations and experts. We also investigated whether reference intervals for both analytes were useful for evaluations, particularly consecutive test results. Methods: The study group consisted of 36 healthy volunteers. Samples were collected from each individual 4 times every 2 weeks for 45 days. All samples were assayed in duplicate within a single run. Finally, we estimated BVCs and the analytical performance specifications of both analytes. Results: Our results were fairly compatible with current biological variations (BVs) in both analytes reported in a database. It was calculated as within biological variation (CVI)=4.2% and between-subject variation (CVG)=5.3% for glucose while calculating as CVI=1.7% and CVG=4.5% for HbA1c. According to these results, the index of individuality (II) of glucose was higher than 0.6 while HbA1c’s II was lower than this value. Conclusion: We thought that guidelines from relevant international organizations should be followed to standardize the study design and to appropriately calculate BVCs for any analyte in BV studies. Finally, reference change value should be used to evaluate meaningful differences in HbA1c levels instead of reference interval.

Blood sampling frequency as a proxy for comorbidity indices when identifying patient samples for review of reference intervals

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Simon Lykkeboe ◽  
Stine Linding Andersen ◽  
Claus Gyrup Nielsen ◽  
Peter Vestergaard ◽  
Peter Astrup Christensen
Keyword(s):  
Laboratory Data ◽  
Low Frequency ◽  
Reference Interval ◽  
Reference Intervals ◽  
Sampling Frequency ◽  
Blood Sampling ◽  
Test Results ◽  
Healthy Individuals ◽  
Simple Method ◽  
Blood Samples

Abstract Objectives Indirect data mining methods have been proposed for review of published reference intervals (RIs), but methods for identifying patients with a low likelihood of disease are needed. Many indirect methods extract test results on patients with a low frequency blood sampling history to identify putative healthy individuals. Although it is implied there has been no attempt to validate if patients with a low frequency blood sampling history are healthy and if test results from these patients are suitable for RI review. Methods Danish nationwide health registers were linked with a blood sample database, recording a population of 316,337 adults over a ten-year period. Comorbidity indexes were defined from registrations of hospital diagnoses and redeemed prescriptions of drugs. Test results from patients identified as having a low disease burden were used for review of RIs from the Nordic Reference Interval Project (NORIP). Results Blood sampling frequency correlated with comorbidity Indexes and the proportion of patients without disease conditions were enriched among patients with a low number of blood samples. RIs based on test results from patients with only 1–3 blood samples per decade were for many analytes identical compared to NORIP RIs. Some analytes showed expected incongruences and gave conclusive insights into how well RIs from a more than 10 years old multi-center study (NORIP) performed on current pre-analytical and analytical methods. Conclusions Blood sampling frequency enhance the selection of healthy individuals for reviewing reference intervals, providing a simple method solely based on laboratory data without the addition of clinical information.

Homogeneous, liposome-based assay for total complement activity in serum.

1986 ◽  
Vol 32 (2) ◽  
pp. 275-278 ◽  
Author(s):  
D W Bowden ◽  
M Rising ◽  
G Akots ◽  
A Myles ◽  
R J Broeze
Keyword(s):  
Normal Population ◽  
Test Results ◽  
Normal Range ◽  
Serum Samples ◽  
Complement Components ◽  
Complement Activity ◽  
Standard Curve ◽  
Total Complement ◽  
Speed Accuracy ◽  
Range Test

Abstract This is a rapid, homogeneous, liposome-based assay for total complement activity in human serum. Liposome-encapsulated enzyme is unmasked by the action of complement on liposomes carrying surface-bound immune complexes. The amount of unmasked enzyme, proportional to the concentration of added complement, is quantified by measuring the absorbance of enzymically produced product at 410 nm. Complement activity in serum samples is extrapolated from a standard curve generated from dilutions of a guinea pig serum containing a known activity of complement. Interassay CVs were less than 7.0% and intra-assay CVs less than 2.8% for serum pools with complement activities spanning the normal range. Test results correlate as well with those of the hemolytic complement test (r = 0.80) as the latter correlates with itself (r = 0.82), and also correlate reasonably with measurements of complement components C3 (r = 0.62) and C4 (r = 0.74). Values for a normal population are reported. Advantages of this test include stability of reagents, speed, accuracy, simplicity, and avoidance of radioisotopes.

Current Practices When Reporting Quantitative Human Chorionic Gonadotropin Test Results

2020 ◽  
Vol 5 (5) ◽  
pp. 850-857 ◽  
Author(s):  
David G Grenache
Keyword(s):  
Chorionic Gonadotropin ◽  
Gestational Age ◽  
Human Chorionic Gonadotropin ◽  
Single Point ◽  
Reference Interval ◽  
Reference Intervals ◽  
Chronological Age ◽  
Specific Reference ◽  
Test Results ◽  
Reporting Practices

Abstract Background Quantitative human chorionic gonadotropin (hCG) tests are commonly used to determine a woman’s pregnancy status. Discrete results are evaluated and/or interpreted against a reference interval or cutoff. Reporting practices across laboratories have not been investigated. Methods A voluntary questionnaire was distributed to 6433 laboratories participating in a general chemistry proficiency testing survey. Results Responses were received from 3568 (55%) laboratories. Overall, 31% used a single reference cutoff, with 42% and 14% using values of 5.0 and 25.0 IU/L, respectively. In total, 68% of laboratories provided result interpretations, most frequently “negative” and “positive.” Reference intervals based on chronological age were offered by 9% of laboratories; 60% reported gestational age-based intervals. In addition, 25% provided male-specific reference intervals, with 2.0 IU/L being the most commonly used single-point cutoff. Only 12% of laboratories offered a separate, orderable test for hCG as a tumor marker, with 5.0 IU/L as the most frequently used reference threshold. Nearly half of laboratories used assay product insert data as the reference interval source. Conclusions There is wide variation when reporting quantitative hCG results. Despite a well-established reference limit of &lt;5.0 IU/L for nonpregnant women, fewer than half of laboratories used this cutoff. The reporting of gestational age-based reference intervals is more common than those based on chronological age despite greater clinical utility for the latter. Data-driven guidelines for reporting quantitative hCG test results could deliver more consistent result interpretation.

Vestibular Function and Motion Sickness Susceptibility: Videonystagmographic Evidence From Oculomotor and Caloric Tests

2020 ◽  
Vol 29 (2) ◽  
pp. 188-198
Author(s):  
Cynthia G. Fowler ◽  
Margaret Dallapiazza ◽  
Kathleen Talbot Hadsell
Keyword(s):  
Phase Velocity ◽  
Motion Sickness ◽  
Repeated Measures ◽  
Short Form ◽  
Vestibular Function ◽  
Slow Phase ◽  
Test Results ◽  
Normal Range ◽  
Slow Phase Velocity ◽  
Caloric Tests

Purpose Motion sickness (MS) is a common condition that affects millions of individuals. Although the condition is common and can be debilitating, little research has focused on the vestibular function associated with susceptibility to MS. One causal theory of MS is an asymmetry of vestibular function within or between ears. The purposes of this study, therefore, were (a) to determine if the vestibular system (oculomotor and caloric tests) in videonystagmography (VNG) is associated with susceptibility to MS and (b) to determine if these tests support the theory of an asymmetry between ears associated with MS susceptibility. Method VNG was used to measure oculomotor and caloric responses. Fifty young adults were recruited; 50 completed the oculomotor tests, and 31 completed the four caloric irrigations. MS susceptibility was evaluated with the Motion Sickness Susceptibility Questionnaire–Short Form; in this study, percent susceptibility ranged from 0% to 100% in the participants. Participants were divided into three susceptibility groups (Low, Mid, and High). Repeated-measures analyses of variance and pairwise comparisons determined significance among the groups on the VNG test results. Results Oculomotor test results revealed no significant differences among the MS susceptibility groups. Caloric stimuli elicited responses that were correlated positively with susceptibility to MS. Slow-phase velocity was slowest in the Low MS group compared to the Mid and High groups. There was no significant asymmetry between ears in any of the groups. Conclusions MS susceptibility was significantly and positively correlated with caloric slow-phase velocity. Although asymmetries between ears are purported to be associated with MS, asymmetries were not evident. Susceptibility to MS may contribute to interindividual variability of caloric responses within the normal range.

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