Deep vein thrombosis (DVT) in advanced cancer patients with lower extremity edema referred for assessment
Bibliographic record
Abstract
Lower extremity edema is a common complication in advanced cancer patients, and deep vein thrombosis (DVT) is one among many causes. Clinical signs and symptoms are known to be unreliable, and radiographic investigations are often required in diagnosing DVT. A retrospective chart review was conducted on 46 advanced cancer patients with lower extremity edema. Researchers analyzed 52 venous duplex scans to determine the radiographic incidence of DVT the reliability of other clinical signs and symptoms in diagnosing DVT, apart from leg edema, and to assess other potential causes of lower extremity edema and their correlation to DVT. Twenty-three (44 percent) of 52 scans were positive for DVT. The most common presentation of edema in the patients with positive scans was bilateral asymmetric edema (11/23, 48 percent). There was limited documentation of other clinical signs and symptoms suggesting DVT. Other variables such as serum albumin (p = 0.46) and creatinine (p = 0.11) were not statistically different in patients who had positive and negative scans. Of other potential causes of lower extremity edema, such as previous surgery, radiotherapy, tumor, or lymph node compression, a number of patients had a coexisting DVT with bilateral asymmetric edema as the most common presentation. The results of this study suggest that advanced cancer patients with bilateral asymmetric lower extremity edema of potentially multifactorial origin have a high incidence of DVT.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".