Venous Thromboembolism in Children 0-18 Years — a Regional Population-Based Study from Sweden
Notice bibliographique
Résumé
Abstract Introduction: Venous thromboembolism (VTE) is a rare complication in childhood. Pediatric VTE is an important and increasingly frequent clinical challenge likely due to increased detection and advanced medical interventions leading to improved survival of previously fatal conditions. Objective: The principal aim of this population based study was to describe the incidence, age distribution, type/location of VTE, and acquired and genetic pro-thrombotic risk factors of VTE and recurrence of VTE in children 0-18 years. Material and Methods: The Regional Ethical Review Board in Lund approved the study. We conducted a retrospective regional study of all consecutive ICD-10 codes of VTE in children 0-18 years over a 15-year period (January 1, 2000, to December 31, 2015) in a regional catchment area of southern Sweden using an electronic diagnosis registry. Eligible subjects were defined as children under the age of 18 who presented with VTE and had imaging evidence of thrombosis. Of the 174 patients diagnosed with VTEs, 164 fulfilled the study group criteria. Data regarding subject demographics and medical history (central venous catheter, cancer, congenital heart disease, history of VTE, current infection, etc.), location of VTE and imaging method (upper, lower extremities, pulmonary embolism, renal, cardiac, cerebral sinus venous thrombosis (CSVT), etc.), coagulation studies at primary investigation which included in all cases evaluation of at least plasma concentrations of protein C, protein S, antithrombin, resistance to activated protein C and the genotypes FV-G1691A and FII-G20210A. In addition, plasma values for coagulation factors VIII and XI, D-dimer, PK-INR, and cardiolipin antibodies were analyzed. Results: The incidence of VTE in children in the investigated region of Sweden was found to be 0.8 per 10,000 children. Of the study group with confirmed VTE (n=164), 73/164 (45%) were males and 91/164(55%) females, with bimodal age distribution at diagnosis, 25 (15%) < 1 month, 139 (85%) >1 month-18 years. Of the children, 143/164 (87%) had DVT (deep venous thrombosis), 21/164 (13%) had PE (pulmonary embolism) and 5/164 (3%) had both DVT and PE. Of 143 patients with DVT, 50 (30%) had lower extremity DVT, 46 (28%) had upper extremity DVT and 34 (20.7%) CSVT and the remaining 13 various locations. 79/164 (59%) had acquired potential risk factors, 11/164 (11%) had genetic risk factors, 34/164 (21%) had both genetic and acquired risk factors, and 22/164 (13%) had no identified risk factors. The most frequent acquired risk factors in the cohort were the use of hormonal therapy (34%), concomitant malignancy (21%), infection at the time of thrombosis (19%) or a CVL (central venous line) (15%). Genetic thrombophilia risk factors were found in 45/164 (27.5%), the most common were Factor V Leiden (FVL) in heterozygous form in 35 (21%), FII mutation (heterozygous) in 4 (2%) and double heterozygosity for FVL and FII mutation found in 2 (1%). Plasma deficiency of Protein S was found in 5, Protein C deficiency in 6 and Antithrombin deficiency in 1 patient (who had 3 episodes of VTE). Recurrent VTE was documented in 9 (5%), of which 5 had a congenital pro-thrombotic disorder (i.e. FVL mutation (n=3), antithrombin deficiency (n=1) and a protein S deficiency (n=1). Two out of the nine with recurrent VTE had neither a genetic nor an acquired identified risk factor. Six out of a total of 45 (13.3%) with genetic risk factors had a recurrent VTE. No common acquired pro-thrombotic risk factor was found in the group with recurrent VTE. Conclusion: The incidence, age-distribution, locations and underlying disorders agree with published findings in pediatric populations. In our study, 87% of the children with VTE had either an identifiable acquired or genetic risk factor or a combination of both. Of those with a genetic risk factor, 13% had a recurrent VTE during the study period which indicates an even higher cumulative risk during childhood which emphasizes the need to consider prophylaxis in situations with increased risk of VTE. However, of those with recurrent VTE, no frequent acquired risk factor was identified. Disclosures No relevant conflicts of interest to declare.
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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 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 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 | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».