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A Retrospective Study of Venous Thromboembolism in Acute Leukemia Patients during Prolonged Hospital Stay. the Princess Margaret Cancer Centre Experience

2016· article· en· W2740491057 on OpenAlexaffabout
Hassan Sibai, Umberto Falcone, Arjun Law, Ali Hosni, Carmen Tan, Naoko Sakurai, Andre C. Schuh, Mark D. Minden, Steven M. Chan, Karen Yee, Vikas Gupta, Aaron D. Schimmer, Jack T Seki

Bibliographic record

VenueBlood · 2016
Typearticle
Languageen
FieldMedicine
TopicVenous Thromboembolism Diagnosis and Management
Canadian institutionsPrincess Margaret Cancer CentreUniversity Health Network
Fundersnot available
KeywordsMedicineIncidence (geometry)Acute leukemiaVenous thromboembolismCancerRetrospective cohort studyCohortInternal medicineSurgeryPediatricsLeukemiaThrombosis

Abstract

fetched live from OpenAlex

Abstract Background The role of thromboprophylaxis in solid organ malignancies is well established. Hematologic malignancies can also be associated with a considerable risk of thromboembolic complications. The incidence of these events is variable and is influenced by multiple factors. Limited data are available regarding the incidence of venous thromboembolism (VTE) in hospitalized acute leukemia (AL) patients. The management of symptomatic VTE in patients with AL can be challenging due to the increased risk of thrombocytopenia-related bleeding. Methods The Discharge summary Database (DAD) was used to extract post-admitted PE and DVT volumes in AL patients admitted to Princess Margaret Cancer Centre from 2007-2016. ICD-10-CA diagnosis codes for acute leukemia, and both PE and DVT events, were used. Only patients diagnosed with VTE at least 48 hours post-admission were included to restrict the cohort to patients that developed VTE during their admission. Results We analyzed a total of 10,041 patients that were admitted to Princess Margaret Cancer Centre during the 2007-2016 period. (Table 1) Of these, 7759 had a solid tumor diagnosis (271 VTE events, 3.4%) and 2282 patients had AL (1675 AML, 464 ALL, 144 APL). The AL patients (AML, ALL, APL) admitted to our Centre for chemotherapy or for the management of complications were further evaluated to determine VTE incidence and to evaluate its management in this setting. As of September 2012, patients with solid tumors treated at our Centre received standard thromboprophylaxis as part of an institutional in-patient (VTE) prophylaxis policy (IPP) that reduced the incidence of VTE from 4.8% (219/4520) to 1.6% (3239/52) before and after the policy was initiated, respectively. AL patients are not given prophylactic anticoagulation. 37 AL patients (22 AML, 10 ALL, and 5 APL; overall incidence 1.6%) developed symptomatic VTE (DVT only 23, PE only 8, DVT + PE 6). VTE was reported as central venous catheter related in 12/37 patients (32.4%). PE was detected in all cases by CT-PE. Median age of VTE patients was 53 years (range 32-77), with a median hospital stay of 35 days (range 2-144). Chemotherapy was given to 26 of the 37 patients that developed VTE, with 20 receiving initial induction chemotherapy. 17/37 (46%) patients had PLT<50.000/mm3 at VTE diagnosis. Full dose low molecular weight heparin with platelet transfusion support was used to treat 35/37 patients with acute VTE during the first month of treatment. 2/37 did not receive anticoagulation due to ongoing active bleeding. None of the treated patients experienced major bleeding. Conclusions In our experience, the incidence of VTE in AL patients during prolonged hospital stay is relatively low, raising questions about the need for routine VTE prophylaxis in this group. The relatively increased risk of VTE in AL patients receiving chemotherapy (particularly, induction chemotherapy), should prompt particular scrutiny in symptomatic patients. Disclosures Schuh: Amgen: Membership on an entity's Board of Directors or advisory committees. Yee:Novartis Canada: Membership on an entity's Board of Directors or advisory committees, Research Funding. Gupta:Incyte Corporation: Consultancy, Research Funding; Novartis: Consultancy, Honoraria, Research Funding. Schimmer:Novartis: Honoraria.

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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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.007
GPT teacher head0.248
Teacher spread0.241 · 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 designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2016
Admission routes2
Has abstractyes

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