Bibliographic record
Abstract
The post-thrombotic syndrome (PTS) is an important chronic complication of deep vein thrombosis (DVT). The present review focuses on risk determinants of PTS after DVT and available means to prevent and treat PTS. More than one-third of patients with DVT will develop PTS, and 5% to 10% of patients develop severe PTS, which can manifest as venous ulcers. PTS has an adverse impact on quality of life as well as significant socioeconomic consequences. The main risk factors for PTS are persistent leg symptoms 1 month after acute DVT, anatomically extensive DVT, recurrent ipsilateral DVT, obesity, and older age. Subtherapeutic dosing of initial oral anticoagulation therapy for DVT treatment may also be linked to subsequent PTS. By preventing the initial DVT and DVT recurrence, primary and secondary prophylaxis of DVT will prevent cases of PTS. Daily use of elastic compression stockings for 2 years after proximal DVT appears to reduce the risk of PTS; however, uncertainty remains regarding optimal duration of use, optimal compression strength, and usefulness after distal DVT. The cornerstone of managing PTS is compression therapy, primarily using elastic compression stockings. Venoactive medications such as aescin and rutosides may provide short-term relief of PTS symptoms. Further studies to elucidate the pathophysiology of PTS, to identify clinical and biological risk factors, and to test new preventive and therapeutic approaches to PTS are needed.
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 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".