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Venous Thromboembolism Prevention Practices Among Health Care Providers Caring for Patients Hospitalized for Hematopoietic Stem Cell Transplantation: A International Web-Based Survey

2012· article· en· W2575664361 on OpenAlexaboutno aff
Amer M. Zeidan, Jessica C. Wellman, Patrick M. Forde, Javier Bolaños‐Meade, Michael B. Streiff

Bibliographic record

VenueBlood · 2012
Typearticle
Languageen
FieldMedicine
TopicVenous Thromboembolism Diagnosis and Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineFamily medicineInstitutional review boardTransplantationHematopoietic stem cell transplantationVenous thromboembolismInternal medicineSurgery

Abstract

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Abstract Abstract 2062 Background: We and others have noted that venous thromboembolism (VTE) is a common complication of hematopoietic stem cell transplant (HSCT). However, bleeding complications are even more common. Consequently, our center takes a cautious approach to VTE prevention. The purpose of this study was to determine VTE prophylaxis practice patterns among providers caring for patients during HSCT. Methods: We generated a 20 question web-based survey to determine institutional VTE prevention practices. The survey was approved by the Johns Hopkins Institutional Review Board and the American Society of Bone Marrow Transplantation (ASBMT). The survey was distributed by email by the ASBMT to its members on 6/27/2012 with 2 reminders sent at 2-week intervals. Results: A total of 114 providers from 18 countries practicing in 95 different institutions completed the survey. The majority of responders were from the United States of America (USA) (69%); but responses were received from Canada (6); Australia (5); Mexico, Spain, Germany (3 each); India, Saudi Arabia, New Zealand (2 each); and Oman, Thailand, China, Turkey, UK, Egypt, Singapore, Chile, and Croatia (1 each). The median age of responders was 47 years (standard deviation 10.3 years), and 72% were males. Ninety-one percent of respondents were board certified in hematology or oncology. One third of responders had ≥21 years of post-fellowship experience of, while 22% were within 5 years of completing fellowship training. Fifty-six percent worked in institutions performing more than 100 HSCT annually. Forty-one percent of responders described themselves as clinicians, 46% as clinical researchers, 6% as clinical educators, and 3% laboratory researchers. The majority practiced in university-affiliated or public institutions (80%).Only 32.5% and 14% of responders worked in institutions that had cancer-specific and transplant-specific VTE prophylaxis order sets, respectively. Provider preferences for VTE prevention for patients undergoing allogeneic and autologous HSCT are displayed in Figure 1. Most respondents (79%) used a platelet count threshold of 50,000/μL for pharmacologic VTE prophylaxis. Fewer respondents used 30,000/μL (19%) or 75,000/μL as a cutoff for pharmacologic VTE prophylaxis. The primary reasons cited for the current approach to VTE prevention in HSCT patients included: 1. a perceived low risk of VTE (30%), 2. a high risk of bleeding (24%), and 3. An absence of data supporting VTE prophylaxis in HSCT patients (24%). Conclusions: The first reported international web-based survey of VTE prophylaxis among health care professionals caring for HSCT patients notes considerable variation in clinical practice. These data underscore the need for further investigation to develop evidence-based recommendations for VTE prophylaxis in this vulnerable population. Disclosures: Streiff: sanofi-aventis: Consultancy, Honoraria; BristolMyersSquibb: Research Funding; Eisai: Consultancy; Janssen Healthcare: Consultancy; Daiichi-Sankyo: Consultancy.

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)0.002
metaresearch head score (Gemma)0.006
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 score0.004
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.029
GPT teacher head0.309
Teacher spread0.280 · 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".

Quick stats

Citations0
Published2012
Admission routes1
Has abstractyes

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