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Record W2086721960 · doi:10.1055/s-0034-1390325

Thrombosis: A Major Contributor to Global Disease Burden

2014· review· en· W2086721960 on OpenAlexaff
Pantep Angchaisuksiri, A Blanco, Harry R. Büller, Alexander Gallus, Beverley J. Hunt, Elaine M. Hylek, The Kakkar, Stavros Konstantinides, Micah McCumber, Yukio Ozaki, Aaron M. Wendelboe, Jeffrey I. Weitz, Gary E. Raskob

Bibliographic record

VenueSeminars in Thrombosis and Hemostasis · 2014
Typereview
Languageen
FieldMedicine
TopicVenous Thromboembolism Diagnosis and Management
Canadian institutionsMcMaster UniversityThrombosis and Atherosclerosis Research Institute
Fundersnot available
KeywordsMedicineDisease burdenPopulationStroke (engine)DiseaseIncidence (geometry)Burden of diseaseGlobal healthYears of potential life lostEnvironmental healthCause of deathPublic healthIntensive care medicineLife expectancyInternal medicinePathology

Abstract

fetched live from OpenAlex

Thrombosis is a common pathology underlying ischemic heart disease, ischemic stroke, and venous thromboembolism (VTE). The Global Burden of Disease Study 2010 (GBD 2010) documented that ischemic heart disease and stroke collectively caused one in four deaths worldwide. GBD 2010 did not report data for VTE as a cause of death and disability. We performed a systematic review of the literature on the global disease burden due to VTE in low-, middle-, and high-income countries. Studies from Western Europe, North America, Australia, and Southern Latin America (Argentina) yielded consistent results with annual incidences ranging from 0.75 to 2.69 per 1,000 individuals in the population. The incidence increased to between 2 and 7 per 1,000 among those 70 years of age or more. Although the incidence is lower in individuals of Chinese and Korean ethnicity, their disease burden is not low because of population aging. VTE associated with hospitalization was the leading cause of disability-adjusted-life-years (DALYs) lost in low- and middle-income countries, and second in high-income countries, responsible for more DALYs lost than nosocomial pneumonia, catheter-related blood stream infections, and adverse drug events. VTE causes a major burden of disease across low-, middle-, and high-income countries. More detailed data on the global burden of VTE should be obtained to inform policy and resource allocation in health systems, and to evaluate if improved utilization of preventive measures will reduce the burden.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.885
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0060.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.000
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 head0.047
GPT teacher head0.380
Teacher spread0.333 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations143
Published2014
Admission routes1
Has abstractyes

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