Appropriateness of Thrombophilia Testing in Tertiary Care Centers in Edmonton
Bibliographic record
Abstract
Abstract INTRODUCTION Thrombophilia is associated with an increased risk of venous thromboembolism (VTE). Despite this link, determining the presence or absence of such conditions has no role in VTE management including determining the choice or duration of anticoagulant therapy. Testing can be potentially harmful when results are misinterpreted or impact patient anxiety and insurance eligibility. METHODS We performed a retrospective chart review of adult patients presenting to the emergency department (ED) or were admitted to the University of Alberta Hospital (UAH), Royal Alexandra Hospital (RAH) and Grey Nuns Hospital (GNH) and underwent any number of thrombophilia tests (including factor V Leiden [FVL], prothrombin gene mutation [PT20210], protein C [PC], protein S [PS], antithrombin [AT] and antiphospholipid antibody testing). To assess for appropriateness of testing, categories of data were collected including presence of other strong risk factors obviating the need to look for other causes, indicators for higher yield (age of patient, presence of family history of VTE, idiopathic nature of VTE), presence of factors that confound testing (such as therapeutic anticoagulation) and relevant follow up (appropriate repeat testing when necessary). We also collected basic patient demographics, VTE details and ordering physician/service details to evaluate under what circumstances testing may be ordered more frequently. RESULTS 134 charts of patients tested for thrombophilia were reviewed between 2007-2013 at UAH and RAH Hospitals. A total of 965 thrombophilia tests were done (see analysis table). 13.4% of the testing was ordered by hematologists, 23.1% by neurologists, 52.2% by other internists. Overall, all patients had tests performed inappropriately, lacked appropriate follow up or had uninterpretable results and none had documented counseling prior to thrombophilia testing. CONCLUSIONS Thrombophilia testing is frequently ordered inappropriately and not adequately followed up. Strategies to educate physicians on indications and limitations of testing are warranted. These strategies can help decrease over/under/misinterpretation of thrombophilia testing as well as result in significant savings to the health care system if testing can be reduced. Table 1. Demographics Sample Size Males Females Total 74 (55.22%) 60 (44.78%) 134 (100%) Age at time of testing (Yrs) Range 19-88 Average 48.7 Patients' Test Results Test Times Performed Abnormal Results APCR 134 (100%) 32 (23.8%) FVL genetic test 58 (43%) 21 (39%) PT20210 105 (77%) 4 (3.8%) Protein C 100 (74.1%) 8 (8%) Protein S 99 (73.3%) 16 (16.2%) AT levels 99 (73.3%) 19 (19.2%) Anticardiolipin Ab 117 (86.7%) 4 (3.4%) Lupus Anticoagulant 109 (81.3%) 10 (10.2%) Provoking Factors Patients with One or More Provoking Factors Major 10 7.4% Moderate 74 56% Minor 29 21.8% No Provoking Factors 49 36.8% Family History of VTE 12 8.9% Protein C and Protein S Testing Done During Acute VTE 64 64% Patient was on Warfarin 25 25% Number of Abnormal Test Results 24 16% Number of Repeated Abnormal Tests 0 0% AT Testing Total Tests Performed 99 73.3% Done During Acute VTE 62 63% Patient was on Therap. Heparin or LMWH 62 62.6% Number of Abnormal Test Results 19 19.2% Abnormal Tests Repeated? 7 37% Repeat Tests Showing Normal Results 3 57% APA Testing Tests were Repeated After 12 Weeks for Confirmation 11% Disclosures Wu: Leo Pharma: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Pfizer: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
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".