Incidence and Predictive Factors of Symptomatic Thrombosis Related to Peripherally Inserted Central Catheters In Chemotherapy Patients
Bibliographic record
Abstract
Abstract Abstract 4206 Background: The use of peripherally inserted central catheter (PICC) lines has significantly enhanced the management of chemotherapy patients. While deep vein thrombosis (DVT) of a catheterized vein is a common and potentially serious complication, such thromboses are frequently asymptomatic. Indeed, the true incidence of symptomatic catheter-related DVT in cancer patients remains unclear, and there is a lack of reliable data on the risk factors of catheter-related thrombosis. Moreover, little work has focused on predictive factors of symptomatic events related specifically to PICC lines in chemotherapy patients. Methods: We performed a retrospective cohort study of consecutive cancer patients who received an ultrasound guided PICC line for the administration of chemotherapy at The Ottawa Hospital between September 1, 2009 and December 31, 2009. Relevant demographic, clinical and laboratory characteristics were collected, including factors previously suggested as being predictive of catheter-related DVT. Univariate and multivariate logistic regression analyses were performed for symptomatic PICC-related DVT, defined as a clot in one or more of the deep veins of the catheterized arm leading to and confirmed by Doppler ultrasound. Results: In total, 340 cancer patients obtained PICC lines for the administration of chemotherapy. Of these patients, 19 (5.6%; 95% CI: 3.6–8.6) developed symptomatic PICC-related DVT. In the univariate analysis, demographic factors were not significant predictors of PICC-related DVT, including gender, age, body mass index and smoking status. Interestingly, factors previously suggested as being associated with central venous catheter-related clots in prior studies were not significant determinants in our analysis; in particular, side of line placement (p=0.281), catheter tip location (p=0.539), number of lumens (p=0.911), number of insertion attempts (p=0.964), and catheter repositioning (p=0.731) were not predictive. Importantly, patients with diabetes were three times more likely to develop PICC-related DVT (OR 3.0, p=0.039), while the presence of chronic obstructive pulmonary disease (COPD) or metastatic cancer increased the odds of developing PICC-related DVT (OR 3.3, p=0.078; OR 2.3, p=0.083 respectively). Diabetes remained a significant risk factor after adjustment for effect of metastases and COPD (OR 3.175, p=0.039). Further, the presence of metastases was a significant predictor (OR 3.34, p=0.024) in our multivariate model. Conclusion: Symptomatic PICC-related DVT are frequent in cancer patients receiving chemotherapy. Previously described factors associated with catheter-related thrombosis, such as tip location, lumen size, and side of catheter, were not predictive of PICC-related DVT in our study. In addition, known risk factors for DVT, including gender and obesity, were not predictive, which may suggest an alternate pathophysiologic process in this particular population. Diabetes, advanced disease and COPD appear to increase the risk of developing PICC-related DVT in chemotherapy patients, although the biologic mechanism of this result is not clear. To our knowledge, this is the largest study to date to exclusively examine PICC-associated DVT in cancer patients. Further studies with larger number of patients are required to better characterize risk factors and their relative impact in developing PICC-related DVT. Disclosures: Tay: Ortho-Biotech: Honoraria; Pfizer: Honoraria.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".