MétaCan
Menu
Back to cohort
Record W1986111003 · doi:10.1177/1076029613481105

Venous Thromboembolism in Elderly High-Risk Medical Patients

2013· article· en· W1986111003 on OpenAlexaffabout
Russell D. Hull, Tazmin Merali, Allan Mills, Abigail Stevenson, Jane Liang

Bibliographic record

VenueClinical and Applied Thrombosis/Hemostasis · 2013
Typearticle
Languageen
FieldMedicine
TopicVenous Thromboembolism Diagnosis and Management
Canadian institutionsTrillium Health CentreUniversity of TorontoUniversity of Calgary
Fundersnot available
KeywordsMedicineVenous thromboembolismMedical recordEmergency medicineIntensive care medicineMedical illnessPopulationPediatricsInternal medicineThrombosisDiabetes mellitus

Abstract

fetched live from OpenAlex

Venous thromboembolism (VTE) causes significant morbidity and mortality in hospitalized medical populations; however, medical patients do not currently receive thromboprophylaxis beyond their hospital stay. We reviewed the real-life occurrence of VTE-related care for 100 days post-hospitalization in Calgary, Canada. Using medical visit records with a unique patient identifier number applied throughout the city's hospitals, 989 high-risk patients were selected for review. Almost three-quarters of the elderly patients received appropriate prophylaxis while in hospital, and only 2% received prophylaxis on discharge. Over the 100-day follow-up, 21% of the patients presented with clinically suspected VTE, of which 3.8% had confirmed VTE. Patients with multiple risk factors (≥ 3) had the highest frequency of confirmed VTE (≥ 6.1%). This study suggests that the actual rate of VTE-related follow-up care in patients post-hospitalization is high in the first 100 days, particularly among those who have multiple risk factors, warranting consideration of extended thromboprophylaxis in this population.

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), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.689
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.022
GPT teacher head0.302
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 teacher head, not a consensus.

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

Citations51
Published2013
Admission routes2
Has abstractyes

Explore more

Same venueClinical and Applied Thrombosis/HemostasisSame topicVenous Thromboembolism Diagnosis and ManagementFrench-language works237,207