Need for tissue plasminogen activator for central venous catheter dysfunction is significantly associated with thrombosis in pediatric cancer patients
Bibliographic record
Abstract
BACKGROUND: Central venous catheter (CVC) dysfunction is a common complication among pediatric cancer patients. Tissue plasminogen activator (tPA) is administered to resolve CVC dysfunction. The present study was designed to determine risk factors associated with requirement of tPA for CVC dysfunction and to assess the clinical impact of CVC dysfunction in terms of CVC loss and venous thrombotic events (VTE). PROCEDURE: Case records of all pediatric patients with cancer from the Maritimes, Canada were reviewed following ethics approval. Data regarding demographics, clinical diagnosis, CVC dysfunction, characteristics of CVCs, and VTE were pooled from multiple data sources. RESULTS: Seven hundred and forty-one patients required ≥1 CVC. 26.3% of patients required tPA for ≥1 episodes of CVC dysfunction. Requirement of one or more doses of tPA for episodes of CVC dysfunction increased the odds of VTE by two times (95% confidence interval, 1.1-3.6). Patients that required ≥1 doses of tPA required significantly more CVCs (2.05 ± 1.29 per individual patient, 55% of the patients needed >1 CVCs) as compared to the remainder (1.52 ± 0.95 per individual patient, 32% needed >1 CVCs) (P = 0.0001). Multivariate analysis revealed age > 10 years, diagnosis of sarcoma, and tunneled line were independently associated with tPA requirement. CONCLUSION: We determined independent risk factors associated with requirement of tPA for CVC dysfunction. Requirement of tPA for CVC dysfunction was associated with significantly increased risk of VTE and requirement of more CVCs. These observations can assist in identification of patients at increased risk of CVC dysfunction and inform approaches to reduce CVC loss and VTE.
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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 | 0.004 |
| 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".