Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Quality Control01:05

Quality Control

2.8K
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...
2.8K
Quality Assurance01:19

Quality Assurance

2.5K
Quality assurance is the overarching term used to describe the activities employed to ensure the proper performance of a system. These activities can be classified into three categories: quality control, quality assessment, and internal corrective measures. Typically, these activities work cyclically: quality control is performed before and during the analysis, while quality assessment occurs during and after the investigation. Internal corrective measures are implemented based on the findings...
2.5K
Quality of Water01:19

Quality of Water

574
In concrete preparation, the quality of water is paramount as it affects the strength and durability of the concrete. Potable water is usually preferred; however, it must not have excessive sodium or potassium to prevent compromising the concrete's integrity. Water quality is typically evaluated based on impurities such as dissolved solids, chlorides, and sulfates, and its pH value is ideally between 6 and 8. Even slightly acidic natural water may be acceptable unless it contains harmful...
574
Pulse amplitude and quality01:17

Pulse amplitude and quality

3.2K
Pulse amplitude is a crucial indicator of cardiac health because it provides valuable insights into the strength of left ventricular contractions and the overall uniformity of blood circulation within the vasculature. The strength of the pulse is directly related to the force with which the heart contracts and the volume of blood being pumped.
A weak or absent pulse may indicate reduced cardiac output or poor left ventricular contraction, which can be signs of cardiovascular dysfunction or...
3.2K
Testing Water Quality01:14

Testing Water Quality

394
When the quality of water for concrete preparation is uncertain, its impact on the setting time of cement and compressive strength of mortar is assessed by comparison with de-ionized or distilled water benchmarks. American Society for Testing and Materials (ASTM) C1602 requires the setting times to be within 90 minutes of the control, British Standard (BS) 3146:1980 allows a 30-minute variance in the initial setting, while British Standards European Norm (BS EN) 1008 specifies initial setting...
394
Sampling Methods: Sample Types01:18

Sampling Methods: Sample Types

3.3K
Sampling materials are classified into three main types: solid, liquid, and gas.
Solid samples include a variety of substances, such as sediments from water bodies, soil, metals, and biological tissues. Two standard methods for extracting sediments from water bodies are grab sampling and piston coring. Grab sampling involves using a device to collect a discrete sediment sample from the bottom of a water body with minimal disturbance. Grab samples do not always represent the entire area due to...
3.3K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Propionic acid in multiple sclerosis: a phase 2b, double-blind, randomized placebo-controlled trial.

Brain : a journal of neurology·2026
Same author

Predicting Iron Deficiencies Using Routine Complete Blood Cell Count Parameters: A Machine Learning Approach and Evaluation.

Journal of clinical medicine·2026
Same author

Global epidemiology of atrial fibrillation and atrial flutter: An increasing worldwide burden.

International journal of stroke : official journal of the International Stroke Society·2026
Same author

Toward Precision Cardiac Rehabilitation: Current Limitations and Future Opportunities of Omics and Artificial Intelligence.

Sports medicine (Auckland, N.Z.)·2026
Same author

Correction: Bukvić et al. Effects of High-Intensity Training on Complete Blood Count, Iron Metabolism, Lipid Profile, Liver, and Kidney Function Tests of Professional Water Polo Players. <i>Diagnostics</i> 2024, <i>14</i>, 2014.

Diagnostics (Basel, Switzerland)·2026
Same author

Laboratory Monitoring of Complement Activation in Gene Therapy: Analytical Pitfalls and Clinical Interpretation.

Seminars in thrombosis and hemostasis·2026
Same journal

Intraloop neoangiogenesis in an AI-classified scleroderma pattern: recognizing a morphological clue to suspected dermatomyositis.

Diagnosis (Berlin, Germany)·2026
Same journal

Lessons in clinical reasoning: a case of a boy who continued crying after falling.

Diagnosis (Berlin, Germany)·2026
Same journal

Accuracy of emergency physicians' probability estimates for acute coronary syndrome.

Diagnosis (Berlin, Germany)·2026
Same journal

Interfering factors in the normative diagnostic approach.

Diagnosis (Berlin, Germany)·2026
Same journal

Using generative AI to support clinical reasoning coaching: a theory-informed approach.

Diagnosis (Berlin, Germany)·2026
Same journal

Learning from what went right: a Safety-II application of the SIDER protocol to a case of occult breast cancer.

Diagnosis (Berlin, Germany)·2026
See all related articles

Related Experiment Video

Updated: Feb 10, 2026

Author Spotlight: Developing an Efficient Blood Collection Method in Non-Anesthetized Rats
03:52

Author Spotlight: Developing an Efficient Blood Collection Method in Non-Anesthetized Rats

Published on: November 3, 2023

3.7K

Blood sample quality.

Giuseppe Lippi1, Alexander von Meyer2, Janne Cadamuro3

  • 1Section of Clinical Biochemistry, University Hospital of Verona, Piazzale LA Scuro, 37100 - Verona, Italy.

Diagnosis (Berlin, Germany)
|May 26, 2018
PubMed
Summary
This summary is machine-generated.

Most laboratory errors stem from preanalytical issues, particularly poor blood sample quality. Hemolyzed samples are the leading cause of unsuitable specimens, necessitating strategies to improve sample collection and management.

Keywords:
blood sampleserrorshemolysislaboratory medicinequality

More Related Videos

Non-Terminal Blood Sampling Techniques in Guinea Pigs
07:58

Non-Terminal Blood Sampling Techniques in Guinea Pigs

Published on: October 11, 2014

39.0K
DNA Microarrays: Sample Quality Control, Array Hybridization and Scanning
09:27

DNA Microarrays: Sample Quality Control, Array Hybridization and Scanning

Published on: March 15, 2011

38.6K

Related Experiment Videos

Last Updated: Feb 10, 2026

Author Spotlight: Developing an Efficient Blood Collection Method in Non-Anesthetized Rats
03:52

Author Spotlight: Developing an Efficient Blood Collection Method in Non-Anesthetized Rats

Published on: November 3, 2023

3.7K
Non-Terminal Blood Sampling Techniques in Guinea Pigs
07:58

Non-Terminal Blood Sampling Techniques in Guinea Pigs

Published on: October 11, 2014

39.0K
DNA Microarrays: Sample Quality Control, Array Hybridization and Scanning
09:27

DNA Microarrays: Sample Quality Control, Array Hybridization and Scanning

Published on: March 15, 2011

38.6K

Area of Science:

  • Clinical Laboratory Science
  • Medical Diagnostics
  • Healthcare Quality Improvement

Background:

  • The majority of laboratory medicine errors occur during extra-analytical phases, especially preanalysis.
  • Unsuitable specimen collection (volume or quality) is the primary source of laboratory errors.
  • Improving blood sample quality is crucial for accurate laboratory testing.

Purpose of the Study:

  • To review the most frequent types of unsuitable blood samples encountered in clinical laboratories.
  • To summarize current evidence on preanalytical non-conformities.
  • To provide recommendations for preventing and managing these issues.

Main Methods:

  • Comprehensive review of scientific literature on laboratory errors and specimen quality.
  • Analysis of reported causes of specimen non-conformity.
  • Synthesis of evidence on preanalytical challenges.

Main Results:

  • Hemolyzed samples are the most frequent cause of non-conformity (40-70%).
  • Insufficient/inappropriate sample volume (10-20%) and wrong collection containers (5-15%) are also significant issues.
  • Other causes include clotting, contamination, and improper storage.

Conclusions:

  • Preanalytical errors, particularly those related to blood sample quality, significantly impact laboratory medicine.
  • Addressing issues like hemolysis and inadequate sample volume is essential for reducing laboratory errors.
  • Implementing preventative strategies can improve specimen integrity and diagnostic accuracy.