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Towards a Conceptual Framework for Diagnosis of Heparin-Induced Thrombocytopenia (HIT).

2005· article· en· W2573243718 on OpenAlexaff
Gregory Lo, Theodore E. Warkentin

Bibliographic record

VenueBlood · 2005
Typearticle
Languageen
FieldMedicine
TopicHeparin-Induced Thrombocytopenia and Thrombosis
Canadian institutionsMcMaster University
Fundersnot available
KeywordsHeparin-induced thrombocytopeniaPlatelet factor 4HeparinMedicineAntibodyThrombosisClinical significanceConfoundingPlateletImmunologyInternal medicine

Abstract

fetched live from OpenAlex

Abstract HIT can be regarded as a “clinicopathologic” syndrome whereby the diagnosis is based upon a compatible clinical picture and the presence of platelet-activating, anti-platelet factor 4 (PF4)/heparin antibodies of IgG class. However, both components of this conceptual framework are problematic. First, there are many potential non-HIT explanations for thrombocytopenia and/or thrombosis in hospitalized patients receiving heparin (“clinical confounders”); and second, prospective studies show that numerous heparin-treated patients develop non-pathogenic anti-PF4/heparin antibodies of no clinical significance (“antibody confounders”). A third issue is that the most specific laboratory assay for pathogenic HIT antibodies (platelet serotonin release assay [SRA]) is performed in only a few reference centers, whereas less specific commercial anti-PF4/polyanion enzyme-immunoassays (EIAs) are widely available. Recently, a clinical scoring system (“4 T’s”) that classifies patients into low-, intermediate- and high-risk groups (LR, IR, and HR, respectively) has been shown to have predictive value in estimating the likelihood of a patient having clinically-significant HIT antibodies. Applying these various concepts, we sought to estimate the potential for HIT “over-diagnosis” inferred from a comparison of “conservative” and “liberal” conceptual frameworks for HIT. The conservative definition required an IR or HR clinical score, as well as that strict laboratory criteria be met for defining pathogenic antibodies (positive SRA [>50% serotonin release] and positive EIG-IgG [>0.45 units]). In comparison, a liberal definition considered HIT in the setting of any positive commercial anti-PF4/polyanion-EIA result (>0.40 units) in any patient evaluated for possible HIT irrespective of clinical score. Our data base consisted of 100 consecutive patients evaluated for possible clinical HIT over a 16-month period in which the “4 T’s” clinical scoring system was applied prospectively. Patients underwent systematic serologic assessment by SRA, EIA-IgG, and EIA-GTI. We found that 16 patients (HR=8, IR=8) met the clinical and serologic criteria for clinical HIT using the conservative framework. In contrast, using the liberal framework, there were 32 patients who would have been considered to have clinical HIT (HR=8, IR=12, LR=12). Thus, twice as many patients (32 vs 16) would have been “diagnosed” as HIT from the liberal perspective. The EIA-GTI absorbance values (in units) for the 16 patients identified using the conservative framework (median=2.39; IQR=2.09–2.70; range=1.46–2.90) were significantly greater (p<0.001 by Mann-Whitney u test, 2-sided) than in the additional 16 patients identified using the liberal framework (median=0.89; IQR=0.54–1.13; range=0.42–2.13). In summary, there is considerable potential for over-diagnosis of HIT (by approximately 100%) depending upon one’s conceptual framework (and available assay) for defining HIT. However, in a center relying upon the EIA-GTI for diagnosis, the designation of a patient as having clinical HIT by integrating the clinical score (IR or HR status required) with a strong positive result in the EIA-GTI (e.g., >1.20 units in this data set) yields a population of patients that overlaps considerably with that identified using a more conservative approach utilizing a more specific diagnostic assay. Thus, by integrating information from the clinical score together with the magnitude of a positive test result, accurate diagnosis of HIT is achievable even when very different assays are employed.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.030
metaresearch head score (Gemma)0.027
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.030
Threshold uncertainty score0.157

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0300.027
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0100.004
Science and technology studies0.0030.015
Scholarly communication0.0080.010
Open science0.0040.005
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.058
GPT teacher head0.331
Teacher spread0.274 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreMethods

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".

Quick stats

Citations1
Published2005
Admission routes1
Has abstractyes

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