Systematic Transcranial Doppler Examination in Adults with Sickle Cell Disease : A Cross-Sectional Single Center Study
Notice bibliographique
Résumé
Background Individuals with sickle cell disease (SCD) are at a high risk of stroke throughout their lifespan. Regular transcranial doppler (TCD) screening is widely adopted for children with SCD to identify those in need of treatment intensification. However, TCD screening is not routinely performed beyond ages 16-18. Data on TCD feasibility and standard velocities in adults with SCD are limited. Since 2021, all adults with SCD followed at the Centre Hospitalier de l'Université de Montréal (CHUM) Comprehensive SCD Centre are referred for TCD examination as part of routine neurovascular surveillance, regardless of their genotype, age, comorbidities, or neurologic status. ObjectivesThe primary aim of this study is to determine the feasibility of TCD in unselected adults with SCD. The secondary aim is to report the distribution of Doppler velocities in this population. We also aimed to explore associations between these measures and biological and clinical patient characteristics. Methods In this retrospective study, clinical data of all patients seen at the SCD Center between September 2021 and June 2024 were reviewed and extracted.Patients with routine TCD examination were included in the study sample. Mean flow velocity (MFV) measurements were attempted in all patients for the anterior cerebral artery (ACA), the middle cerebral artery (MCA), the posterior cerebral artery (PCA), and the basilar artery (BasA). Feasibility was assessed using the following definitions: “standard TCD” with successful insonation of both MCA, and “complete TCD” for successful insonation of bilateral MCA, ACA, PCA and BasA. Chi-squared test was used to compare feasibility across predetermined groups (age, sex, genotype and body mass index (BMI)). Distribution of MFV was calculated as mean ± standard deviation (SD). A priori determined covariates tested for univariate linear association with MFV were age, sex, genotype, BMI, hemoglobin (Hb) and hematocrit (Hct). The project was approved by the local ethics committee.Results A total of 249 SCD patients with a documented TCD examination were analyzed (mean age 35 [range 18 to 79 years], 141 (57%) were women). Overall, 115 (46%) patients had a SS/Sβ0 and 134 (54%) a SC/Sβ+ genotype. A prior diagnosis of cognitive disorder was present in 4 (2%), and of stroke in 19 (8%) cases. A majority of 156 patients (63%) were on hydroxyurea (HU) treatment alone, while 65 (26%) were on transfusions, and 18 (7%) on both treatments. A “standard” TCD examination was feasible in 229 (92%) patients, while a “complete” TCD was successfully documented in 190 (76%). There was no statistically significant effect of sex, age, genotype and BMI on TCD feasibility. Documented MFV (±SD) for cerebral arteries were as follows: MCAleft 67 (±19) cm/s; right 67 (±19) cm/s;ACAleft 53 (±16) cm/s; right 52 (±15) cm/s;PCAleft 37 (±12) cm/s; right 38 (±12) cm/s;BasA43 (±14) cm/s Linear regression showed increasing age was inversely associated with MFV in all arteries (p≤0.002). For each additional 10 years, a decrease of MFV (±SD) in the respective brain arteries was as follows: MCAleft -4.8 (±1.0); right -3.6 (±1.0) cm/s;ACAleft -3.1 (±1.0); right -2.9 (±0.9) cm/s;PCAleft -2.6 (±0.7); right -2.2 (±0.7) cm/s;BasA-3.3 (±0.7) cm/s. Female sex was associated with higher MFV in the left ACM and both PCA (p<0.05). MFV were negatively correlated with Hb and Hct for all arteries (p<0.005 for all). MFV were higher in the HbSS/Sβ0, compared to the HbSC/Sβ+ group (p<0.05). Conclusion : Our study showed that TCD can be implemented in routine follow-up of adult patients with SCD with a high (92%) success rate for standard MCA evaluation. Overall, measured intracranial velocities were in line with previously established patterns showing an inverse association with age throughout adulthood. Longitudinal TCD follow-up may help to further determine the role of intracranial flow parameters in the neurovascular risk assessment of adults with SCD.
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 | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| 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 ».