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The influence of anemia on clinical outcomes in venous thromboembolism: Results from GARFIELD-VTE

2021· article· en· W3163089425 on OpenAlexafffund
Shinya Goto, Alexander G.G. Turpie, Alfredo E. Farjat, Jeffrey I. Weitz, Sylvia Haas, Walter Ageno, Samuel Z. Goldhaber, Pantep Angchaisuksiri, Gloria Kayani, Peter MacCallum, Sebastian Schellong, Henri Bounameaux, LG Mantovani, Paolo Prandoni, Ajay K. Kakkar

Bibliographic record

VenueThrombosis Research · 2021
Typearticle
Languageen
FieldMedicine
TopicVenous Thromboembolism Diagnosis and Management
Canadian institutionsThrombosis and Atherosclerosis Research InstituteMcMaster University
FundersJapan Society for the Promotion of SciencePharmaceuticals BayerBristol-Myers SquibbNakatani Foundation for Advancement of Measuring Technologies in Biomedical EngineeringNational Heart, Lung, and Blood InstitutePfizerHeart and Stroke Foundation of CanadaMinistero della SaluteMinistry of Education, Culture, Sports, Science and TechnologyCanadian Institutes of Health ResearchAmerican Heart AssociationSanofiServierDaiichi-SankyoOno Pharmaceutical
KeywordsVenous thromboembolismMedicineAnemiaIntensive care medicineInternal medicineThrombosis

Abstract

fetched live from OpenAlex

INTRODUCTION: Clinical characteristics and outcomes of venous thromboembolism (VTE) patients with concomitant anemia are unclear. This study compares baseline characteristics, treatment patterns, and 24-month outcomes in patients with and without anemia within GARFIELD-VTE. MATERIALS AND METHODS: GARFIELD-VTE (ClinicalTrials.gov: NCT02155491) is a global, prospective, non-interventional registry of real-world treatment practices. Of the 10,679 patients enrolled in GARFIELD-VTE, 7698 were eligible for analysis. Primary outcomes were all-cause mortality, recurrent VTE, and major bleeding in VTE patients with or without concomitant anemia over 24-months after diagnosis. Event rates and 95% confidence intervals were estimated using Poisson regression. Adjusted hazard ratios were calculated using Cox proportional hazard models. RESULTS: Distribution of VTE events in 2771 patients with anemia and 4927 without anemia was similar (deep-vein thrombosis alone: 61·1% vs. 55·9%, pulmonary embolism ± deep vein thrombosis: 38·9% vs. 44·0%, respectively). Patients with anemia were older (62.6 year vs. 58.9 years) than those without. At baseline, VTE risk factors that were more common in patients with anemia included hospitalization (22·0% vs. 6·8%), surgery (19·2% vs. 8·2%), cancer (20·1% vs. 5·6%) and acute medical illness (8·3% vs. 4·2%). Patients with anemia were more likely to receive parenteral anticoagulation therapy alone than those without anemia (26·6% vs. 11·7%) and less likely to receive a direct oral anticoagulant (38·5% vs. 53·5%). During 24-months of follow-up, patients with anemia had a higher risk (adjusted hazard ratio [95% confidence interval]) of all-cause mortality (1·84 [1·56-2·18]), major bleeding (2·83 [2·14-3·75]). Among anemia patients, the risk of all-cause mortality and major bleeding remained higher in patients with severe anemia than in those with mild/moderate anemia, all-cause mortality: HR 1·43 [95% CI: 1·21-1·77]; major bleeding: HR 2·08 [95% CI: 1·52-2·86]). CONCLUSIONS: VTE patients with concomitant anemia have a higher risk of adverse clinical outcomes compared with those without anemia. Further optimization of anticoagulation therapy for VTE patients with anemia is warranted.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation 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 score0.269
Threshold uncertainty score0.721

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.140
GPT teacher head0.457
Teacher spread0.318 · 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 teacher head, 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

Citations19
Published2021
Admission routes2
Has abstractyes

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