Evidence map›Paper›PMID 39940813›Full record

ReviewInternational journal of molecular sciences2025

Review of Literature and Recommended Procedures for Management of Unusual Cases of False Positive Troponin Tests.

Michela Salvatici, Carmen Sommese, Massimiliano M Corsi Romanelli, Lorenzo Drago

Abstract readReview
In one paragraph

Review in International journal of molecular sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Michela SalvaticiUOC Laboratory of Clinical Medicine with Specialized Areas, IRCCS MultiMedica Hospital, 20099 Milan, Italy.ORCID 0000-0001-9678-0942
Carmen SommeseMedical Direction, IRCCS MultiMedica, 20099 Milan, Italy.
Massimiliano M Corsi RomanelliDepartment of Biomedical Sciences for Health, University of Milan, 20122 Milan, Italy.ORCID 0000-0001-7928-7697
Lorenzo DragoUOC Laboratory of Clinical Medicine with Specialized Areas, IRCCS MultiMedica Hospital, 20099 Milan, Italy.ORCID 0000-0002-5206-540X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Heterophile antibodies are immunoglobulins produced by the immune system in response to exposure to animal and bacterial antigens, blood transfusions, autoimmune disorders, hematologic malignancies, dialysis, and pregnancy. Recently, these antibodies have garnered significant attention due to their impact on the accuracy of laboratory test results. Heterophile antibodies can bind not only to specific antigens but also to those from different species, including the antibodies used in laboratory tests. This cross-reactivity with foreign proteins is the basis for their interference in immunological assays, such as those measuring cardiospecific troponins (cTn). This manuscript reviews the literature on cases of heterophile antibody interference in troponin testing and proposes an algorithm for identifying such interference when clinical discrepancies arise. Recognizing and addressing heterophile antibody interference is crucial, particularly for tests like those for troponins, which are key biomarkers in the diagnosis and management of emergency and intensive care patients. The literature emphasizes the need for accurate procedures to distinguish true cardiac damage from false positives, thereby preventing unnecessary additional tests and hospitalizations.

Indexed as

Antibodies, HeterophileTroponinBiomarkersFalse Positive ReactionsHumansAntibodies, HeterophileBiomarkersTroponincardiovascular riskfalse positiveheterophile antibodiestroponin

Identifiers

PMID39940813
PMCPMC11817740

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.