Single center evaluation on the use of conditionally ordered low molecular weight heparins in malignant hematology patients with venous thromboembolism
Bibliographic record
Abstract
BACKGROUND: Cancer and cancer-related treatments are significant independent risk factors for malignant hematology (MH) patients in developing venous thromboembolism (VTE). Treatment of VTE in MH patients at the Princess Margaret Cancer Centre is predominantly initiated with low molecular weight heparin (LMWH) in accordance with guidelines. While guidelines recommend against LMWH use in patients with thrombocytopenia, prescribers may order LMWH conditionally based on platelet values. Currently, there is a lack of consistent practice with variation in both the use of conditional orders as well as the threshold of platelet values for conditional orders. The objectives of the study were to (a) describe the use of conditionally ordered LMWH based on platelet values; (b) determine its safety by measuring administration concordance with conditional orders and bleeding event rates during inpatient admission; and (c) determine its efficacy by measuring the rate of worsening VTE or recurrence during inpatient admission. METHODS: Electronic records of MH inpatients admitted between January 2017 and December 2019 and who were administered at least one dose of an LMWH for the treatment of VTE were screened. RESULTS: < 0.0001). In this group of patients, 8 patients had either documented bleeding or experienced a drop in hemoglobin >10 g/L within a 72 h time frame. No patients experienced a recurrent VTE during inpatient treatment (for up to 40 days post-admission). CONCLUSIONS: It appears that conditionally ordered LMWH can be concordantly administered and is safe and effective in the treatment of VTE in MH patients experiencing thrombocytopenia. There were no reports of worsening or new VTE in our small sample.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".