Perioperative outcomes in patients with myeloproliferative neoplasms: a multicentric analysis of 354 surgical procedures
Notice bibliographique
Résumé
Polycythemia vera (PV), essential thrombocythemia (ET), and myelofibrosis (MF) are chronic myeloproliferative neoplasms (MPN) whose clinical course is punctuated by risks of both thrombotic and bleeding complications.Although surgery is an established situational risk factor for thrombosis in the general population, 1 this risk is further increased in patients with MPN. 2 In the perioperative setting, the effects of JAK2V617F mutations, elevated hematocrit (Hct), hyperviscosity, and stasis may be amplified, contributing to higher rates of cardiovascular events.3 In addition, concurrent acquired von Willebrand syndrome and inherent or therapeutic platelet (PLT) dysfunction may increase the risk of hemorrhage.One of the most comprehensive studies on this subject to date corroborated high rates of both perioperative thrombosis (7%) and hemorrhage (10.5%) in patients with PV/ET, despite most (74%) having optimally controlled blood counts.2 Importantly, there is currently no consensus or guidelines for perioperative management of MPN, and expert recommendations are based on limited data.4,5 Correspondingly, practices are heterogeneous and potentially inappropriate, as demonstrated by a recent pan-Canadian study.6 Moreover, there are particularly scarce data on MF cohorts and the impact of JAK (Janus kinase) inhibitors, now widespread in this population.This study sought to comparatively assess 90-day perioperative complication rates, risk variables impacting outcomes, and management strategies and their ramifications in a large MPN population, with the goal of informing clinical practice and improving patient outcomes.This study was approved by institutional review boards and written informed patient consent was obtained.Patients diagnosed with PV, ET, and MF according to World Health Organization criteria 7 between August 1981 and October 2021, and enrolled in the Quebec MPN Research Group registry (6 academic and community centers) were included.Consecutive cases where the patient had undergone at least 1 surgical procedure since diagnosis, with available pre-and postoperative data, were analyzed.Data were abstracted on demographics, cardiovascular risk factors, thrombosis/ hemorrhage history, laboratory values at diagnosis and pre-and postsurgery, type of surgery, therapy, and perioperative modifications.End points included surgical (per procedure) and 90-day postsurgery hemorrhage, arterial and venous thrombosis, and mortality.Major thrombotic and hemorrhagic events were defined per convention.8,9 Standard surgical definitions were used to categorize interventions as major (general, orthopedic, cardiovascular, and neurosurgery) 10,11 ; all others were defined as minor.Conventional statistical methods were used (JMP Pro 14.1.0software; SAS Institute, Cary, NC), with P <.05 considered significant.A total of 354 procedures were performed in 184 patients: PV, n = 87 (47%); ET, n = 66 (36%); and MF, n = 31 (17%).Demographic and clinical variables at diagnosis are presented in Table 1.The median age at diagnosis was 64 years (range, 19-89 years); 48% male; 82% JAK2V617F mutated
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
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 | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 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 ».