Utility of Transient Elastography (Fibroscan) in Estimating Hepatic Iron Concentration in Comparison to MRI in Patients with Transfusion Dependent Hemoglobinopathies
Notice bibliographique
Résumé
Abstract Background Patients with severe hereditary anemias (e.g. β-Thalassemia Major) are transfusion-dependent for survival. Current guidelines suggest monitoring serum ferritin every three months and annual MRI to assess hepatic and cardiac iron load1. However, MRI, particularly the R2 sequence (FerriScan) which has high specificity and sensitivity in estimating the liver iron concentration, is expensive and not always readily available. Transient elastography (FibroScan) measures liver's stiffness and predicts fibrosis. Previous studies have suggested its utility in other conditions that increase liver stiffness, such as amyloidosis2and perhaps iron overload. Aim To determine if FibroScan value correlates with hepatic iron concentration estimated using R2 MRI (FerriScan), and/or serum ferritin level. Methods A prospective cross-sectional study was conducted at a university-affiliated tertiary care center (St. Paul’s Hospital, Vancouver, BC) in 2013 and 2014. Inclusion criteria: Age ≥ 19 years with transfusion-dependent hereditary anemias. Exclusion criteria: liver cirrhosis, primary liver disease (e.g. Wilson’s disease, hereditary hemochromatosis), and chronic viral hepatitis (e.g. Hepatitis B, C and HIV). In addition to having annual MRI and ferritin levels monitored every three months, subjects underwent FibroScan within six months of MRI in 2013. In 2014, participants were invited to undergo repeat FibroScan within three months of the annual MRI. Linear regression analysis was used to determine if there is any correlation/linear fit between FibroScan result, MRI result, and ferritin levels. This study was approved by the University of British Columbia Research Ethics Board. Results 20 subjects have been recruited as of August 1, 2014, with 35 and 33 complete FibroScan and MRI results, respectively. 14 (70%) were female. Mean age was 30.7±9.8 years. Most common primary diagnosis was transfusion-dependent beta-thalassemia (Major and intermedia) (n=17). Linear regression analysis showed a weakly positive correlation between hepatic iron concentrations estimated with R2 MRI (FerriScan) and ferritin levels (R2=0.29; p=0.004), when they are performed within four weeks apart. The correlation remained statistically significant when all subjects were included regardless of time lapse between the two investigations (R2=0.30; p=0.001). However, FibroScan values did not appear to correlate with MRI, regardless of whether the scans are performed within six months (R2=0.011; p=0.58) or three months apart (R2=0.035; p=0.44). Similarly, there was no correlation between FibroScan and Ferritin (R2=0.022; p=0.49) when the investigations were performed within 4 weeks part. Conclusion Interim analysis did not demonstrate any correlation between FibroScan result and MRI-estimated hepatic iron concentration. A final analysis will be performed upon complete formal evaluation of the remaining MRI and FibroScan data. References Remacha A, Sanz C, Contreras E, et al. Guidelines on haemovigilance of post-transfusional iron overload. Blood Transfus. 2013; 11(1): 128-139Loustaud-Ratti V, Cypierre A, Rousseau A, et al. Non-invasive detection of hepatic amyloidosis: Fibroscan, a new tool. Amyloid 2013; 18(1): 19-24 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 | 0,002 | 0,008 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 ».