Clinical false positives resulting from recent intravenous immunoglobulin therapy: case report
Bibliographic record
Abstract
BACKGROUND: Many clinicians are aware that certain therapies administered to their patients can have downstream consequences in the form of clinical laboratory test interferences. This is particularly true of laboratory tests that depend on, or directly involve the use of, antibody-based methodology. Intravenously-administered immunoglobulin therapy is one such treatment that can in theory directly impact the results of particular tests in the area of viral serology. This study can help serve as a reference for clinicians researching the impact of intravenously-administered immunoglobulin therapy in the context of positive results that do not reflect the clinical background of the patient. CASE PRESENTATION: We describe a case whereby an intravenously-administered immunoglobulin therapy led to a series of clinical false positives in viral serology, inconsistent with the known patient history as well as recent laboratory results. The patient presented to hospital with petechiae-type bleeding rashes and was investigated for thrombocytopenia after initial blood investigations indicated very low platelets. Subsequent testing of the potential causes for low-platelet involved several viral serology investigations, including hepatitis, cytomegalovirus and human immunodeficiency virus. Initial testing indicated patient exhibited negative status for all viral antibodies and antigens (except immunity for hepatitis B surface antigen antibody). As part of the thrombocytopenia treatment, intravenously-administered immunoglobulin therapy was administered, and subsequent viral serology was ordered. These investigations indicated a positive status for several hepatitis antibodies as well as cytomegalovirus. CONCLUSIONS: This case study illustrates the potential for improper diagnosis of previous or ongoing infection status in patients administered IVIg therapy. Caution should be exercised particularly when interpreting results involving cytomegalovirus and hepatitis.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.010 | 0.007 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".