Notice bibliographique
Résumé
The authors 1 report having performed a secondary analysis on the data in Honey et al. 2 Based on these data, the authors concluded that there is a specific access problem to deep brain stimulation (DBS) in rural areas of the Atlantic provinces.They were interested how centralization of DBS services may impact people living in rural areas.This letter echoes some interesting and valuable thoughts that might help to improve an equal access to complex neuromodulation procedures such as DBS or even magnetic resonance-guided focused ultrasound surgery (MRGFUS).Even though I agree it is crucial to address access issues in remote and rural areas, the conclusions of this letter are not necessarily substantiated due to data that are actually missing in the primary data source.First of all, the primary article does not include the site where the surgery was performed.The method section states "No data were provided on gender, diagnosis, wait time for surgery, implantation hospital or surgeon, electrode target or clinical outcome" as the data were retrieved from the industry and not from the implanting sites.Furthermore, the authors claim significant access issues but do not provide any information on which statistical test was used to prove significance.This is in contrast to the original article that had already analyzed the access between rural areas and the entire provincial populations: "Within each province, the percentage of patients receiving DBS who lived in a rural area was calculated and compared with the percentage of all people living in a rural area within that province.There was no significant difference between the percentage of patients receiving DBS from rural areas".The authors of the letter do not explain why their secondary analysis came to a different conclusion.The graphical analysis shows the data in cases per million, which is difficult when talking about rural communities in the Atlantic provinces, that comprise a population between several 10,000 to a maximum of 300,000 or 400,000.Therefore, small changes in small population lead to large differences when scaling them up to a million.This makes these numbers seem significant, which they are not according to Honey et al.In this context, it is of interest that there was a specific access problem for the Atlantic provinces during the study period of 2015-2016.This was a period with a longer hiatus of DBS surgeries in Halifax, which is the main DBS center for this largely rural region.The two neurosurgeons performing DBS had moved out of province or out of country, just before and during the study period.A regular DBS practice in Halifax was restarted by November 2016.In the meantime, surgeries, including the Nova Scotia cases had to be referred to other centers (e.g. in Ontario and Quebec) or had to wait until the program was restarted.This could be an explanation for a certain disparity between the Atlantic and other provinces during the study period.
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 | 0,005 | 0,050 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,003 | 0,002 |
| Communication savante | 0,004 | 0,004 |
| Science ouverte | 0,003 | 0,002 |
| Intégrité de la recherche | 0,043 | 0,032 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,014 | 0,016 |
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 ».