Clinical Characteristics, Outcomes and Prognostic Factors for Patients with Acute Myeloid Leukemia Admitted to Intensive Care Settings
Notice bibliographique
Résumé
Abstract Abstract 4320 Introduction Acute myeloid leukemia (AML) is a life-threatening, hematological malignancy that is characterized by a rapid clonal proliferation of myeloblasts. Patients with AML often present with compromised bone marrow function, increasing their risk for treatment-related morbidity and mortality, which may be complicated by patient-related factors such as age and co-morbid medical conditions. The objectives of our study were to determine the clinical characteristics, outcomes and prognostic factors of patients with acute myeloid leukemia (AML) admitted to intensive care settings (intensive care unit ICU or coronary care unit CCU). Methods We conducted a retrospective chart analysis of patients diagnosed and treated for AML at Hamilton Health Sciences (in Hamilton, Ontario, Canada) between January 2004-December 2011. Inpatients admitted to hospital were included in the analysis. We included patients with de novo, secondary and relapsed AML. Treatment for AML included: induction or consolidation chemotherapy, palliative and supportive measures. All patients admitted to intensive care settings were age (within three years) and gender matched to a control group of 24 patients with AML who did not require admission to an intensive care setting. We also looked at the number of co-morbid medical conditions between the two groups. Results A total of 115 patient charts were analyzed retrospectively. 24 patients (20.8%) required ICU/CCU admission during their treatment for AML. 11 patients (46%) were male. The most common reason for admission to an intensive care setting was respiratory distress (79.1%). The majority of patients requiring admission had de novo AML (66.7%) with intermediate risk cytogenetics (63.6%). Of the 24 patients requiring admission to an intensive care setting, 9 patients (37.5%) did not survive to be discharged from hospital. All of the remaining 15 patients survived at least 30 days post discharge from hospital. Using univariate analysis, white blood cell count (WBC) at diagnosis (p=0.01), type of AML (p=0.002), AML treatment (p=0.001) and admission to an intensive care setting (p=0.032) affected overall survival for the entire cohort. Using multivariate analysis, WBC at diagnosis (hazard ratio 1.007; 95% CI 1.002 to 1.012) and type of AML (hazard ratio for the comparison of denovo AML vs other categories is 0.059; 95% CI 0.009 to 0.367) affected overall survival. Using univariate analysis, denovo AML vs other types of AML (p=0.04) and percentage of peripheral blood blasts at diagnosis (borderline p=0.06) predicted admission to an intensive care setting. The number of co-morbid medical conditions did not predict admission to an intensive care setting. Conclusions The majority of AML patients do not require admission to an intensive care setting, however, the mortality rate of AML patients admitted to an intensive care setting is high. In this small retrospective dataset admission to an intensive care setting was associated with a significant difference in overall survival, but despite admission, long term survival is possible (overall survival for entire cohort 75%). Also, although a number of factors were significant on univariate analysis, (WBC at diagnosis, intensive care setting admission, type and treatment of AML), on multivariate analysis the only factors affecting overall survival were WBC at diagnosis and the type of AML. Type of AML predicted admission to an intensive care setting, there was no significant effect of the number of co-morbid medical conditions on admission to an intensive care setting. Disclosures: No relevant conflicts of interest to declare.
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 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».