Elucidating the chronological relationship between central venous line dysfunction, infection and thrombosis in children with cancer: A preliminary analysis
Notice bibliographique
Résumé
Abstract Background In children with cancer and central venous lines (CVLs), about 31–50% of children experience CVL-related complications, primarily venous thromboembolism (VTE) and infection, leading to device removal in up to 35% of cases. CVL dysfunction (CVLD), which can range from partial to complete occlusion, is typically either thrombotic or mechanical in nature. The triad of VTE, CVLD, and infection appears to be interrelated; however, the interplay remains poorly understood, underscoring the need for a comprehensive analysis to determine whether either of the events serves as a predictor or a consequence of these complications. This knowledge will help optimize preventive strategies and improve patient outcomes. Objective To evaluate the chronological timeline and interrelationship between VTE, CVLD and infection in a prospective cohort of children with cancer. Methods Patients (age at cancer diagnosis equal or less than 18 years, n=486) newly diagnosed with cancer (excluding central nervous system) were recruited prospectively from all five tertiary care pediatric oncology centres in Ontario, Canada. Patients were followed prospectively from the time of CVL insertion until completion of therapy for the development of CVLD (defined as persistent difficulty in infusion and/or withdrawal), blood culture-positive infections, and symptomatic VTE. We restricted our analysis to the first year from the first CVL insertion to standardized exposure time and minimized non-random censoring due to different treatment lengths for different cancer types. Swimmer’s plots were generated using R Studio (version 2024.09.1+394) for visual illustration of the sequence of events focusing on first occurrences of VTE, infection and CVLD. Inferential statistics, including Mann-Whitney U, Chi-square, log-rank test and logistic regressions, assessed the relationships amongst variables with significance set at p<0.05. The study was approved by each participating institutional ethics board. Results VTE occurred in 56 (11.5%; median age 7.2y [0.01-17.2], 39% males) patients during 1-year follow-up time. The majority (n=37, 66%) were diagnosed with acute lymphoblastic leukemia (ALL); other diagnoses included lymphoma (n=6), sarcoma (n=4), neuroblastoma (n=5), and others (n=4). A swimmer's plot was created to display individual trajectories and timelines of events of these 56 patients. Among these, 24 patients developed at least one prior complication, 16 (29%) had an infection, and 14 (25%) developed CVLD before VTE and 6 (11%) had both infection and CVLD. The median time to VTE was significantly shorter in 32 patients without prior infection or CVLD (27 days) compared to 24 patients with prior complications (106 days; p=0.00043. Patients without prior CVLD (n=42) had an earlier onset of VTE (median 24 days) than those with prior CVLD (n=14; median 78 days; p = 0.015), Likewise patients without prior infection (n=40) developed VTE earlier (median 25 days) compared with those with prior infection (n=16; median 50 days; p=0.033) Amongst patients with ALL one-third (12/37; 32%) experienced VTE within the first four weeks of diagnosis (early-VTE) whereas over half of patients (10/19; 53%) with non-ALL cancers (p=0.0062) revealed early-onset VTE. ConclusionIn our cohort, cancer-associated TE had two distinct presentations; ~60% of patients had early onset TE within the first 4 weeks of cancer diagnosis that had no preceding infection or CVLD, whereas late onset VTE (within ~ 12 weeks since diagnosis) had prior infection and/or CVLD. Further, patients with non-ALL cancers were more likely to have early-onset VTE compared to those with ALL. The swimmer plot visualization offers a useful framework for identifying patterns of complication emergence with a timeline-based analysis. Ongoing analyses will further clarify the causal pathways and interaction between VTE, CVLD and infection. and inform targeted interventions to mitigate VTE and infection risk.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».