Laboratory diagnosis of heparin-induced thrombocytopenia

Theodore E Warkentin1,2,3,4

  • 1Department of Medicine, Michael G. DeGroote School of Medicine, McMaster University, Hamilton, Ontario, Canada.

Heparin-induced thrombocytopenia (HIT) is a clinical-pathological disorder; thus, laboratory testing for the pathogenic platelet-activating antiplatelet factor 4 (PF4)/heparin antibodies is central for diagnosis. The "iceberg" model summarizes the inter-relationship between platelet activation assays and PF4-dependent immunoassays, with platelet-activating antibodies comprising a subset of anti-PF4/heparin antibodies. The platelet serotonin-release assay (SRA), performed by reference laboratories, has high sensitivity and specificity for HIT (~95% each), and is especially suited for detecting highly pathogenic HIT sera containing both heparin-dependent and heparin-independent platelet-activating antibodies; this latter subgroup of antibodies explains "autoimmune HIT" disorders (delayed-onset, persisting, spontaneous, heparin "flush," fondaparinux-associated). Recently, SRA-negative HIT has become recognized, in which serum from some HIT patients contains subthreshold levels of platelet-activating antibodies (by SRA) that become detectable using a PF4-enhanced platelet activation assay. Unusual immunologic features of HIT include early antibody detectability (at onset of platelet count fall) and antibody transience (seroreversion). Widely available PF4-dependent enzyme immunoassays (EIAs) have high sensitivity but poor specificity for HIT, although specificity is enhanced with IgG-specific EIAs and strong positive results; unfortunately, EIA results are usually not available in real time. Automated rapid immunoassays, such as the chemiluminescence immunoassay (CLIA) and latex immunoturbidimetric assay (LIA), facilitate real-time laboratory diagnosis. Recently available likelihood ratio (LR) data for positive (LR+) and negative (LR-) test results allow clinicians to adjust their pretest probabilities for HIT, using Bayesian analysis, into real-time posttest probabilities that are dramatically increased (test positive) or decreased (test negative). Moreover, (semi-)quantitative CLIA- and LIA-positive results (weak, moderate, strong positive) can further refine the posttest probability of HIT.

Related Concept Videos

Anticoagulant Drugs: Low-Molecular-Weight Heparins01:30

Anticoagulant Drugs: Low-Molecular-Weight Heparins

Hemostasis is a crucial process that prevents excessive blood loss from damaged blood vessels. It involves various mechanisms such as vasoconstriction, platelet adhesion and activation, and fibrin formation. The importance of each mechanism depends on the type of vessel injury. In contrast, thrombosis is the abnormal formation of a blood clot within the blood vessels, leading to potential complications if the clot obstructs blood flow. Thrombosis can be caused by increased coagulability of the...
1.8K
Nursing Diagnosis01:22

Nursing Diagnosis

Following assessment, a nursing diagnosis is the next step in the nursing process. It begins after the nurse has collected and recorded the patient data. The purpose of diagnosing is to identify how the client responds to actual or potential health processes, identify factors that bestow or that cause health problems, the etiologies, and identify resources or strengths the individual, group, or community can draw on to prevent or resolve problems.
The nursing diagnosis focuses on evidence-based...
3.8K
Documentation of Nursing Diagnosis01:10

Documentation of Nursing Diagnosis

The nurse documents nursing diagnoses and enters them into the patient record. The identified patient's nursing diagnosis is either written out with a plan of care or entered into the electronic health record.
In some settings, data-driven computerized decision support systems are in place, allowing for more accurate nursing diagnoses. The database within one of these systems includes diagnostic labels defining characteristics, activities, and indicators for nursing. A nurse enters...
1.7K
Formulating and Validating Nursing Diagnosis I01:26

Formulating and Validating Nursing Diagnosis I

A nursing diagnosis is written when the nurse recognizes a cluster of essential patient data indicating health problems treated with independent nursing interventions. The standardized terminologies of a nursing diagnosis help nurses identify and treat patients' problems. Every electronic health record that uses nursing diagnosis must employ standard diagnostic terminology. Developing an efficient, individualized care plan begins with accurate nursing diagnoses.
There are thirteen domains...
3.6K
Diabetes: Symptoms, Diagnosis, and Complications01:15

Diabetes: Symptoms, Diagnosis, and Complications

For most patients, experiencing several weeks of polyuria, polydipsia, fatigue, and significant weight loss may indicate the presence of diabetes. Furthermore, adults displaying the phenotypic appearance of type 2 diabetes (particularly those who are obese and not initially insulin-requiring), may have islet cell autoantibodies, suggesting autoimmune-mediated β cell destruction and a diagnosis of latent autoimmune diabetes of adults (LADA). The categorization of glucose homeostasis is...
2.1K
Formulating and Validating Nursing Diagnosis II01:25

Formulating and Validating Nursing Diagnosis II

Nursing diagnoses represent a problem validated by major defining characteristics. There are four categories of nursing diagnoses: problem-focused, risk, health promotion or wellness, and syndrome. The anatomy of a nursing diagnosis includes three components: problem statement or diagnostic label, defining characteristics, and related factors.
Risk nursing diagnoses represent clinical judgments of an individual, family, or community more vulnerable to developing the health problem than others...
3.6K