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Enregistrement W3214923683 · doi:10.1182/blood-2021-153569

Myelodysplastic Syndromes: Have You Seen Your Patient Beyond His Hemoglobin?

2021· article· en· W3214923683 sur OpenAlexaboutno aff
Raíssa Pires Camargo Ebert, Mariana Munari Magnus, Cristina Bueno Terzi, Antônio Luís Eiras Falcão, Fernando Ferreira Costa, Sara T.O. Saad, Paula de Melo Campos

Notice bibliographique

RevueBlood · 2021
Typearticle
Langueen
DomaineMedicine
ThématiqueAcute Myeloid Leukemia Research
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésMedicineMyelodysplastic syndromesPopulationQuality of life (healthcare)Palliative careDiseasePsychosocialDeliriumHematologic diseasePediatricsAsymptomaticAdvance care planningIntensive care medicineInternal medicinePsychiatryBone marrow

Résumé

récupéré en direct d'OpenAlex

Abstract Background: Palliative care (PC) is a patient-centered care model that aims to relief suffering by establishing a plan of care that integrates physical, psychosocial, cultural, familial and spiritual issues during the course of disease's evolution. Thus, PC applies not only to patients who face a diagnosis beyond the possibility of cure, but to all those who experience significant symptoms throughout the course of the disease. Myelodysplastic syndromes (MDS) are a heterogeneous group of myeloid neoplasms characterized by cytopenias and an elevated risk of developing acute leukemia. As MDS display a wide genetic heterogeneity, patients have a variable clinical presentation, ranging from asymptomatic patients to individuals with severe cytopenias and high-risk disease. MDS are more prevalent in the elderly population, which usually experience several morbidities; thus, MDS frequently lead to notable symptoms and deterioration of quality-of-life, making most of them eligible to PC in addition to standard hematologic care. In spite of that, previous studies demonstrated that patients with hematologic malignancies appear to have restricted access to PC services and receive more aggressive therapies at the end of life. Aims: To evaluate eligibility criteria for PC in a cohort of MDS patients and correlate with clinical and laboratory data. Methods: Clinical and demographic data of MDS patients were collected through interviews using a standardized questionnaire: time from diagnosis, number of morbidities, need for seeking the emergency during the last 12mo, delirium events, wounds, dysphagia, recurrent falls, adverse events to medication, quality of communication with the medical team, fears regarding the disease and its complications, religious support, age, gender, monthly household income and level of schooling. Specific PC scores were also applied: Edmonton Symptom Assessment Scale (ESAS) and Palliative Performance Scale (PPS). Clinical and laboratory data were collected: hemoglobin (Hb), platelet and neutrophil counts, Revised International Prognostic Scoring System (IPSS-R) and transfusion burden. Statistical univariate and multivariate analysis were performed. P value <.05 was considered statistically significant. This research was approved by the Institutional and National Review Board; written informed consent was obtained from all subjects. Results:Thirty-six patients were evaluated: median age 68y (21-90), sex 16F/20M. According to ESAS, tiredness and anxiety were the most relevant symptoms in MDS patients [median (min-max)]: pain 0 (0-10), tiredness 4.5 (0-10), drowsiness 1.5 (0-10), nausea 0 (0-7), lack of appetite 0 (0-10), shortness of breath 0 (0-10), depression 0 (0-10), anxiety 3.5 (0-10), best wellbeing 2.5 (0-8). Younger patients (<60y, n=10) had a worse ESAS for best wellbeing (5 (2-8)) when compared to older individuals (≥60y, n=26): (2 (0-7)), p=.007, and tended to have worse ESAS scores for tiredness: 8.5 (0-10) vs 3.5 (0-10), p=.56. Importantly, ESAS for tiredness was not correlated to Hb levels, the number of red blood cell transfusions nor with IPSS-R (all p>.05). ESAS for drowsiness was significantly higher in patients with two (5 (0-10)) and ≥three morbidities (3 (0-8) vs those with only one morbidity (0 (0-10)): p=.01 and p=.03, respectively. ESAS for best wellbeing was better in individuals with higher household income 0 (0-0) vs patients with lower financial resources 3 (0-7), p=.04). PPS median was 90% (60-100%) and negatively correlated with transfusion burden (r=0.407, p=.01) and with the need for seeking the emergency in the past 12mo (r=-0.332, p=.04). Finally, despite facing a potential life-threatening disease, 94.4% of the patients reported that their doctors had never talked to them about aspects related to end-of-life care. Conversely, 75% of them reported fears and doubts regarding this phase. Conclusions: In our casuistic of MDS patients, tiredness was the most important symptom observed. Surprisingly, it was not correlated with Hb levels and transfusion burden, suggesting that Hb levels alone should not be used to justify symptoms. The number of morbidities and lower household income also impacted ESAS scores. Finally, a great part of the patients revealed miscommunication with their hematologists regarding end-of-life planning. Our data indicate that MDS patients might benefit from a PC multidisciplinary team approach. Disclosures Costa: Novartis: Consultancy.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,001
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Commentaire · Signal consensuel: aucune
Score de désaccord entre enseignants0,002
Score d'incertitude au seuil0,007

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0010,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0020,000

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.

Tête enseignante Opus0,021
Tête enseignante GPT0,275
Écart entre enseignants0,254 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreCommentaire

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2021
Routes d'admission1
Résumé présentoui

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