MétaCan
Menu
Retour à la cohorte
Enregistrement W3107037440 · doi:10.1097/aln.0000000000003631

Burst-suppression and Postoperative Delirium: Comment

2020· letter· en· W3107037440 sur OpenAlexaboutno aff
Hilary P. Grocott

Notice bibliographique

RevueAnesthesiology · 2020
Typeletter
Langueen
DomaineMedicine
ThématiqueIntensive Care Unit Cognitive Disorders
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésDexmedetomidineMedicineDeliriumBurst suppressionIntensive care medicineElectroencephalographyRandomized controlled trialPostoperative cognitive dysfunctionCognitionAnesthesiaPsychiatrySedationInternal medicine

Résumé

récupéré en direct d'OpenAlex

The recent report by Pedemonte et al.1 of their substudy of the Minimizing ICU Neurologic Dysfunction with Dexmedetomidine-induced Sleep (MINDDS) study2 emphasized the relationship between electroencephalogram (EEG) burst-suppression during cardiopulmonary bypass and delirium in elderly patients undergoing cardiac surgery. It raises several important points regarding the potential for cerebral monitoring to identify patients who may be at risk for significant postoperative neurologic complications, including delirium and postoperative cognitive dysfunction. However, interpreting these complex relationships requires certain safeguards to minimize the risk of potential false discovery, and thus maximize the confidence in a study’s conclusions. These safeguards include, but are not limited to, clear adherence to the prespecified substudy aims and a priori hypotheses, the development of a data statistical analytic plan before accessing the data, and consideration to the potential moderating effects in the substudy from the intervention of the parent trial. In this case, for example, the data from the substudy were derived from an ongoing randomized controlled trial investigating the potential effects of dexmedetomidine on postoperative delirium. It would seem reasonable then for any analysis in the substudy to be adjusted for the use of dexmedetomidine. Clarification as to whether and how this was done would be useful.Several other aspects of their study might also benefit from additional clarity. For example, adherence of reporting to the ordered prestated hypotheses seems to have been modified. For example, the primary hypothesis stated in their introduction was that “preexisting cognitive impairment accounts for electroencephalogram burst-suppression during CPB.”1 It is curious, then, that the article’s title, and the subsequent analysis and reporting of the study, principally focuses on postoperative delirium as opposed to preexisting cognitive impairment. This is particularly notable because their power analysis states that the “primary objective of the study was to detect the difference in mean preoperative cognitive scores between the burst-suppression and no burst-suppression groups.”1 The current delirium analysis, as they state, was likely underpowered.Although there is a potentially important relationship between preexisting cognitive impairment and delirium, and one that could be plausibly mediated via EEG burst-suppression, the primary analysis reported should have been the relationship between baseline cognition and EEG burst suppression, with the delirium-related analyses being secondary, and/or exploratory, and fully adjusted for multiple comparisons. Indeed, although some mention is made of adjustments to reduce false discovery, it is not clear where and how these were done. Furthermore, as the authors stated that the “data and statistical analyses plans were defined and written after the data were accessed,”1 it is not clear how much data and analyses mining might have been undertaken before these complex analyses were settled on and which results were chosen to be reported. The study’s actual primary objective found that the relationship between preexisting cognition (assessed using the abbreviated Montreal cognitive assessment) and EEG burst-suppression was not statistically significant (P = 0.965 in their table 1).These limitations should not dissuade the reader from considering the potentially important relationships that the authors have described, because they may in fact be quite meaningful. However, without adequate adjustment for the unit of randomization, consideration for the analytical plan being developed after the data was accessed, and the subsequent organization of the results around a hypothesis that was not the primary one, it does raise the question as to whether undue emphasis is being placed on the “positive” results surrounding delirium, as opposed to the “negative” results related to baseline cognition.The author declares no competing interests.

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)0,047
score de la tête « metaresearch » (Gemma)0,182
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Commentaire · Signal consensuel: Commentaire
Score de désaccord entre enseignants0,047
Score d'incertitude au seuil0,248

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0470,182
Méta-épidémiologie (sens strict)0,0020,001
Méta-épidémiologie (sens large)0,0030,006
Bibliométrie0,0020,002
Études des sciences et des technologies0,0030,006
Communication savante0,0040,011
Science ouverte0,0130,003
Intégrité de la recherche0,0350,052
Charge utile insuffisante (le modèle a refusé de juger)0,0100,009

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 Opus0,022
Tête enseignante GPT0,272
Écart entre enseignants0,250 · 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'étudeSans objet
Domainenon disponible
GenreCommentaire

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'admission1
Résumé présentoui

Explorer davantage

Même revueAnesthesiologyMême sujetIntensive Care Unit Cognitive DisordersTravaux en français237 207