International registry on splanchnic vein thrombosis: description of the study population
Bibliographic record
Abstract
Background: Splanchnic vein thrombosis (SVT) is an uncommon, butpotentially life-threatening disease. Aim of this ISTH based registryis to improve the knowledge on SVT by studying a large, international,unselected population.Methods: Consecutive patients with objectively diagnosed SVT areeligible for the registry. Information on clinical presentations, diagnosticapproaches, risk factors, therapeutic approaches, and recurrencesof SVT, bleedings and deaths at a 2 year follow up are enteredon a website database (www.svt.altervista.org). We planned a samplesize of 500 patients, including all sites of thrombosis.Results: As of December 31st, 2010, 429 patients with SVT (85.8%of the planned sample) have been enrolled at 25 centres from sevencountries. The mean age is 52.6 years (range 16-85 years); 62.2% aremales, 67.8% are Caucasians, and 31.2% Asians. SVT occurred inmultiple vein segments in 36.4% of patients, 40.5% of patients hadisolated portal vein thrombosis, 11.9% of patients had mesentericvein thrombosis, 7.5% had supra-hepatic vein thrombosis, and 3.6%had splenic vein thrombosis. Abdominal pain was the most commonsymptom occurring in 56.6% of the patients; 9.5% of patients hadgastrointestinal bleeding at the time of diagnosis; 25.4% of patientswith SVT were asymptomatic. Mean time between onset of symptomsand diagnosis was 7.4 days. Objective diagnosis was obtained withabdominal CT in 79.9% of patients. Most common risk factors atthe time of diagnosis included cancer (24.1%), cirrhosis (23.1%), andhematological disorders (15.4%); in 15.9% of patients SVT was idiopathic.Most patients were treated with anticoagulant drugs: 30.8%with parenteral drugs only, 56.9% with parenteral drugs followed byvitamin K antagonists.Conclusions: SVT is a major challenge for experts in thrombosis andhemostasis. Large collaborative studies are necessary to improve theunderstanding and the management of this heterogeneous disease.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".