Bibliographic record
Abstract
Postthrombotic syndrome (PTS) is a chronic complication of deep venous thrombosis (DVT) that reduces quality of life and has important socioeconomic consequences. More than one-third of patients with DVT will develop PTS, and 5% to 10% of patients will develop severe PTS, which may manifest as venous ulceration. The principal risk factors for PTS are persistent leg symptoms 1 month after the acute episode of DVT, extensive DVT, recurrent ipsilateral DVT, obesity, and older age. Daily use of elastic compression stockings (ECSs) for 2 years after proximal DVT appears to reduce the risk of PTS; however, there is uncertainty about optimal duration of use and compression strength of ECSs and the magnitude of their effect. The cornerstone of managing PTS is compression therapy, primarily using ECSs. Venoactive medications such as aescin and rutoside may provide short-term relief of PTS symptoms. The likelihood of developing PTS after DVT should be discussed with patients, and symptoms and signs of PTS should be monitored during clinical follow-up. Further studies to elucidate the pathophysiology of PTS, to identify clinical and biologic risk factors, and to test new preventive and therapeutic approaches to PTS are needed to ultimately improve the long-term prognosis of patients with DVT.
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 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.007 |
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".