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Enregistrement W3096202787 · doi:10.1182/blood-2020-142002

Sickle Cell Cerebrovascular Reactivity to a CO2 Stimulus Is Both Too Little and Too Slow

2020· article· en· W3096202787 sur OpenAlexaffabout
Stéphanie Forté, Olivia Sobczyk, Julien Poublanc, James Duffin, Joe Fisher, David J. Mikulis, Kevin H.M. Kuo

Notice bibliographique

RevueBlood · 2020
Typearticle
Langueen
DomaineMedicine
ThématiqueHemoglobinopathies and Related Disorders
Établissements canadiensThornhill Medical (Canada)University of TorontoCentre Hospitalier de l’Université de MontréalUniversity Health Network
Organismes subventionnairesnon disponible
Mots-clésCerebral blood flowMedicineVasodilationCardiologySickle cell anemiaInternal medicineStroke (engine)AnesthesiaDisease

Résumé

récupéré en direct d'OpenAlex

Background: By age 30, over 50% of sickle cell disease (SCD) patients have suffered a cerebral infarct. In response to anemia and the reduction in oxygen-carrying capacity, cerebral blood flow (CBF) increases to match metabolic demand. Increased velocity of CBF in major cerebral arteries is a strong risk factor for stroke in SCD children and adolescents. Despite generally increased CBF, silent cerebral infarcts (SCI) can still occur in patients receiving optimal transfusions. This suggests that the increased CBF does not meet metabolic demand and that vasodilatory response is compromised. Hypothesis: In adult patients with SCD, cerebrovascular reactivity (slope of the vasodilatory response to CO2 (CVR) and the steady-state CVR (amplitude) and speed of the vasodilatory response (tau) to a standardized vasodilatory stimulus CO2), are reduced compared to normal subjects. We also explored for possible associations with clinical characteristics. Methods: Functional brain imaging performed as part of routine care in adult (≥18) SCD patients (any phenotype) at the University Health Network Comprehensive Sickle Cell Center (Toronto, Canada) between 2017 and 2018 were reviewed. Patients with known cerebral vasculopathy were excluded. CVR was calculated as the change in CBF measured as the blood oxygenation level dependent (BOLD)-MRI signal, in response to a standard vasoactive stimulus of CO2 (delivered by RespirActTM). To calculate the dynamic (tau) and steady-state CVR (amplitude) components of the BOLD signal response, the PET CO2 waveform was convolved with an exponential decay function. The tau corresponding to the best fit between the convolved CO2 and BOLD signal was defined as the speed of vascular response. The slope of the regression between the convolved CO2 and BOLD signal was defined as amplitude. CVR, amplitude and tau were normalized voxel-wise relative to the mean and standard deviation of the same metric in the corresponding voxels of a previously generated atlas of 42 healthy controls (Z scores). These Z scores were averaged over the vascular territories of the brain for both grey (GM) and white matter (WM). Fisher exact and Pearson correlations were performed to identify possible associations between CVR metrics and SCD comorbid conditions, laboratory parameters, and use of disease-modifying therapy. Associations with univariate P <0.20 were included in the multiple linear regression model. Multi-collinearity was assessed. Results: Fifteen patients were included in the study. The median age was 27 [IQR22-35]. 5/15 (33.3%) were male. 9/15 (60%) were SS or S/b0 and 5/15 (33.3%) were SC. 4/15 (26.7%) were on transfusion. MRI/MRA uncovered Moya moya in 1 patient. SCI were present in 3/15 (21.4%). Compared to the reference atlas of normal subjects, CVR and amplitude were reduced both in GM and WM (mean Z-score for CVR -0.52 [-1.8 - 0.28] and -0.63 [-2.31 - 0.66]; amplitude -0.26 [-2.61 - 0.66] and -0.28 [-2.70 - 0.60] respectively). Tau was lengthened in GM and WM (mean tau Z-score +0.90 [-0.49 - 3.32] and +0.76 [-0.66 - 2.78] respectively). These abnormal metrics were observed with varying severities in all 3 main vascular territories (Figure). CVR decreased linearly with decreasing hematocrit (Hct) (r=0.59, p=0.03). There was also a trend towards lower CVR in SS or S/b0 patients (t=-1.41, p=0.18, d=0.76) and was highly collinear with Hct. Hematocrit was the only significant independent predictor of CVR metrics on multivariable regression. Conclusions: All three measures of cerebrovascular health (CVR, amplitude and tau) in SCD patients were abnormal compared to normal controls. Hematocrit appears to be the strongest independent predictor of these measures. The protocol we applied for measuring CVR provides a standardized reproducible vasodilatory stimulus, enabling comparison against a population of healthy individuals for more accurate assessment of CVR in individual subjects. Furthermore, the stimulus protocol produces rapid changes in arterial CO2 levels within one breath that can be used to measure the speed of response of the vasculature representing a novel metric of vascular performance postulated to represent vessel compliance and functional endothelial integrity. These findings show that CVR methodology represents a promising tool to assess disease state, stroke risk, and therapeutic efficacy in sickle cell patients and merits further investigation. Figure 1 Disclosures Forté: Canadian Hematology Society: Research Funding; Pfizer - Global Medical Grants: Research Funding. Sobczyk:Thornhill Research Inc.: Current Employment. Duffin:Thornhill Research Inc.: Current Employment. Fisher:Thornhill Research Inc.: Current equity holder in private company. Mikulis:Thornhill Research Inc.: Current equity holder in private company. Kuo:Bioverativ: Membership on an entity's Board of Directors or advisory committees; Novartis: Consultancy, Honoraria; Bluebird Bio: Consultancy; Agios: Consultancy, Membership on an entity's Board of Directors or advisory committees; Alexion: Consultancy, Honoraria; Pfizer: Consultancy, Research Funding; Apellis: Consultancy; Celgene: 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: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,004
Score d'incertitude au seuil0,009

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
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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 Opus0,009
Tête enseignante GPT0,215
Écart entre enseignants0,206 · 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'étudeObservationnel
Domainenon disponible
GenreEmpirique

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

En bref

Citations2
Publié2020
Routes d'admission2
Résumé présentoui

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