Editorial: Measuring progression in Multiple Sclerosis: Progressing beyond the ordinary
Notice bibliographique
Résumé
When considering predictors of progression, not only the quantity of lesion burden but the location of lesions is known to be important. In a systematic review, Yang et al. showed brainstem and cerebellar clinically isolated syndrome have a higher risk of early conversion to a clinically definite MS; while infratentorial lesions in RRMS are not as reliable in predicting progression to SPMS. Their review summarized that while some studies have reported brainstem and cerebellar lesions may be associated with rapid progression to SPMS or even treatment failure in the second year; others have concluded that these lesions carry no significance in the timing of conversion to SPMS. These inconsistencies need further investigation, as infratentorial lesions are well known to contribute to poor overall prognosis and higher disability rate. Along the same lines, two other Research Topic contributions put their focus on critical white matter tracts, showing that lesions in these areas tend to impact disability progression in a clinically measurable way. Yoon et al. used a combination of white matter tractography and a multi-b shells diffusion weighted MRI to indirectly quantify axonal injury in the transcallosal and corticospinal white matter tracts. They found that lesion and non lesional related injury in transcallosal white matter tracts was more predictive of motor disability, than similar injury in corticospinal tracts. Similarly, Oladosu et al. reported the importance of pathology located in the corpus callosum, another strategic transcallosal tract, along with the optic radiations. Further, they found that in normal appearing white matter, higher density white matter bundles with small diameter and low dispersion were more susceptible to damage in people with SPMS. These studies highlight the importance of disease localization. They uphold an understanding that the differences detected in lesional and non lesional specific white matter areas are likely to give insight into the microstructural changes that precede severe and irreversible injury, and thus possibly the transition from RRMS to SPMS.Imaging metrics are important but ultimately progression remains intimately connected with the clinical manifestations of the disease, e.g., frequency and severity of clinical relapses and symptoms outside overt relapses. Early detection and initiation of treatment can prevent costly relapses. To this end, the remaining three Research Topic contributions focused their work on patients in the early stages of MS, with attention to how non motor symptoms can often be challenging to quantify and contextualize in the landscape of progressive disease. It is known that MS disrupts functional networks in the brain, and in doing so causes hyperconnectivity in other networks to compensate. These compensatory mechanisms are thought to be most active in the mild stages of RRMS, often delaying clinical manifestation of disease. As an example, fatigue is one common non-motor symptom that is reported in up to 80% of people with MS. Previous studies have captured structural and functional correlates of MS, but primarily in patients with moderate to severe disability. The review by Sobczak et al. looked at fatigue in patients with mild stages of RRMS and found that elevated levels of fatigue were associated with a higher functional connectivity in the posterior salience network -a region known to play an important role in information processing. To expand on this concept, de Aratanha et al. looked at how patients in the early stages of MS activated the dorsolateral prefrontal cortex and supplementary motor area when performing a motor activity at the same time as a cognitive task, to reflect activities of daily life. They found that in easier tasks, people with MS had higher measures of unilateral cortical activity than healthy controls and in difficult tasks, showed a bilateral increase in cortical activity compared to healthy controls. This suggests that despite compensatory mechanisms in early stages of MS, it is possible to detect significant differences in cortical demand -even when these differences are not captured on the Expanded Disability Status Scale or Fatigue Severity Score.The final contribution to this Research Topic focused on people with MS with optic neuritis, a very common first symptom. In this retrospective study, Park et al. addressed the need for improved sensitivity in testing with visual evoked potentials (VEP) and aimed to investigate whether low contrast VEP could improve sensitivity to optic neuritis with the goal of identifying optic neuritis in patients with mild or unremarkable visual impairment. This study revealed that in subclinical optic neuritis detection, VEP with low contrast stimuli detected abnormalities 53.1% of abnormalities while conventional VEP with high contrast detected 9.9% of abnormalities -making it reasonable to conclude low contrast VEP is more sensitive that the conventional high contrast VEP.In conclusion, this Research Topic provided a comprehensive overview on the measurement of progression in MS. Using novel imaging techniques, expansion of well-established diagnostic tools, and innovative approaches to studying non-motor symptoms -these articles have highlighted how measuring progression in MS is quickly expanding beyond our ordinary tools.
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 | 0,009 | 0,044 |
| Méta-épidémiologie (sens strict) | 0,005 | 0,002 |
| Méta-épidémiologie (sens large) | 0,008 | 0,005 |
| Bibliométrie | 0,005 | 0,003 |
| Études des sciences et des technologies | 0,003 | 0,003 |
| Communication savante | 0,007 | 0,007 |
| Science ouverte | 0,007 | 0,002 |
| Intégrité de la recherche | 0,018 | 0,021 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,020 | 0,013 |
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 ».