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Related Concept Videos

Sensitivity, Specificity, and Predicted Value01:13

Sensitivity, Specificity, and Predicted Value

In healthcare diagnostics, laboratory tests play a crucial role in identifying and diagnosing a wide range of medical conditions. However, interpreting test results is not always straightforward. An abnormal test result does not always confirm the presence of a disease, just as a normal result does not guarantee its absence. To assess the reliability of these diagnostic tools, healthcare practitioners rely on two key statistical indicators: sensitivity and specificity.
Sensitivity is the...
Multiple Comparison Tests01:13

Multiple Comparison Tests

Multiple comparison test, abbreviated as MCT, is a post hoc analysis generally performed after comparing multiple samples with one or more tests. An MCT will help identify a significantly different sample among multiple samples or a factor among multiple factors.
It would be easy to compare two samples using a significance alpha level of 0.05. In other words, there is only one sample pair to be compared. However, it would be difficult to identify a significantly different sample if the number...
Bioavailability Study Design: Single Versus Multiple Dose Studies01:11

Bioavailability Study Design: Single Versus Multiple Dose Studies

Bioavailability studies are essential for understanding how a drug is absorbed, distributed, metabolized, and excreted in the body. These studies assess the extent and rate at which the active pharmaceutical agent becomes available at the site of action. The design of bioavailability studies can involve single-dose or multiple-dose regimens, each with distinct advantages and limitations.Single-dose studies are the preferred approach due to their simplicity and reduced drug exposure for...
Automated Microbial Diagnostics01:24

Automated Microbial Diagnostics

Automated diagnostic analyzers have transformed clinical microbiology by providing rapid and reliable methods for pathogen identification and antibiotic susceptibility testing. Among these systems, the Vitek 2 is widely used because it automates the traditionally labor-intensive processes of microbial identification (ID) and antibiotic susceptibility testing (AST), delivering standardized and timely results that are essential for effective patient care.Microbial Identification with ID CardsThe...
Quality Control01:05

Quality Control

Quality control is one of the three cyclical quality assurance activities that help keep a system under statistical control. Typical quality control activities include creating quality control charts, conducting proficiency testing, and documenting and archiving results.
Quality control helps track data, visualize trends, and identify variations, making it easier to detect deviations that may affect the accuracy of an analysis. One way to do this is by generating a quality control chart, which...
Bioequivalence Experimental Study Designs: Repeated Measures, Cross-Over, Carry-Over, and Latin Square Designs01:15

Bioequivalence Experimental Study Designs: Repeated Measures, Cross-Over, Carry-Over, and Latin Square Designs

Bioequivalence experimental study designs play a pivotal role in testing the effectiveness of various treatments. Key among these are the repeated measures, cross-over, carry-over, and Latin square designs. In the repeated measures design, each subject receives all treatments, allowing for temporal comparisons. This type of design is useful in reducing variability but requires careful planning to avoid bias.The cross-over design, an economical method, involves sequential administration of...

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Related Experiment Video

Updated: Jun 3, 2026

Evaluation of a Point-of-Care Testing Analyzer for Measuring Peripheral Blood Leukocytes
05:58

Evaluation of a Point-of-Care Testing Analyzer for Measuring Peripheral Blood Leukocytes

Published on: March 22, 2022

Does routine repeat testing of critical values offer any advantage over single testing?

Adam D Toll1, Jennifer M Liu, Gene Gulati

  • 1Department of Pathology, Anatomy, and Cell Biology, Thomas Jefferson University Hospital, Philadelphia,Pennsylvania 19107, USA. Adam.Toll@JeffersonHospital.org

Archives of Pathology & Laboratory Medicine
|April 7, 2011
PubMed
Summary

Routine repeat testing of critical laboratory values, including hemoglobin, white blood cell count, and platelet count, does not improve accuracy or prevent errors compared to a single test run. This finding applies to key hematology tests.

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Observational Study Protocol for Repeated Clinical Examination and Critical Care Ultrasonography Within the Simple Intensive Care Studies
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Observational Study Protocol for Repeated Clinical Examination and Critical Care Ultrasonography Within the Simple Intensive Care Studies

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Last Updated: Jun 3, 2026

Evaluation of a Point-of-Care Testing Analyzer for Measuring Peripheral Blood Leukocytes
05:58

Evaluation of a Point-of-Care Testing Analyzer for Measuring Peripheral Blood Leukocytes

Published on: March 22, 2022

Observational Study Protocol for Repeated Clinical Examination and Critical Care Ultrasonography Within the Simple Intensive Care Studies
10:38

Observational Study Protocol for Repeated Clinical Examination and Critical Care Ultrasonography Within the Simple Intensive Care Studies

Published on: January 16, 2019

Area of Science:

  • Clinical laboratory science
  • Hematology
  • Diagnostic accuracy

Background:

  • Critical laboratory values require verification before communication to caregivers.
  • Repeat testing aims to ensure accuracy and prevent reporting of false or erroneous results.

Purpose of the Study:

  • To evaluate if a second testing run offers benefits over a single run for critical laboratory values.
  • To assess if repeat testing enhances accuracy or reduces reporting errors.

Main Methods:

  • Retrospective collection of over 500 critical values for five hematology tests: hemoglobin, white blood cell count, platelet count, prothrombin time, and activated partial thromboplastin time.
  • Calculation and averaging of absolute value and percentage change between two testing runs for each critical value.
  • Comparison of results against laboratory-defined acceptable tolerance limits for reruns.

Main Results:

  • Mean differences between runs were within acceptable tolerance limits for all tested critical values (e.g., hemoglobin: 0.08 g/dL, 1.4%).
  • The percentage of specimens outside acceptable tolerance limits ranged from 0% to 2.2%.
  • No false or erroneous critical results were identified between the two testing runs across all categories.

Conclusions:

  • Routine repeat testing of critical hemoglobin, platelet, and white blood cell counts, as well as prothrombin time and activated partial thromboplastin time, provides no added advantage over a single testing run.
  • Current practices of repeat testing for these critical values may not be necessary for ensuring accuracy.