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Enregistrement W2054185554 · doi:10.1111/acps.12300

Observations on <scp>DSM</scp>‐5 Mild Neurocognitive Disorder vs. its predecessor, Mild Cognitive Impairment

2014· letter· en· W2054185554 sur OpenAlexafffund
John C.S. Breitner

Notice bibliographique

RevueActa Psychiatrica Scandinavica · 2014
Typeletter
Langueen
DomaineMedicine
ThématiqueDementia and Cognitive Impairment Research
Établissements canadiensDouglas Mental Health University InstituteDouglas College
Organismes subventionnairesMcGill University
Mots-clésDementiaMemory impairmentCognitive impairmentPsychologyProdromeNeurocognitiveCognitionConstruct (python library)Memory clinicPopulationPsychiatryClinical psychologyGerontologyMedicineDiseasePathology

Résumé

récupéré en direct d'OpenAlex

This issue of Acta Psychiatrica Scandinavica contains an important paper from the Zaragosa (Spain) ‘Zarademp’ population studies group 1. The new work compares the well-known category of Mild Cognitive Impairment, or MCI, as first proposed by R. Petersen and colleagues, with a new construct proposed by the American Psychiatric Association (APA)'s fifth edition of its Diagnostic and Statistical Manual (DSM-5). Petersen and collaborators introduced the MCI concept in 1997 to describe a category of patients with subjective memory loss verifiable by psychometric testing, but with no gross impairment in other aspects of cognition and no impairment in their usual activities of daily living (hence, no dementia) 2. Importantly, from its inception, the MCI construct was meant to denote a degree of cognitive impairment not expected in the course of normal aging [but see, e.g. 3]. Although patients with MCI do not (by definition) have dementia, the syndrome drew interest as a possible prodrome among individuals destined soon to develop dementia, and therefore to be potentially suitable for treatment. The original Petersen paper noted that ‘approximately 10–15%’ of patients meeting this description went on to develop dementia in each of the coming several years, and that individuals with one or more ε4 alleles at the polymorphic APOE locus were especially predisposed to ‘convert’ to dementia in this way 2. The MCI construct was refined over the succeeding years, as it was recognized that some patients had mild impairment that was not memory-predominant and others had defects in several different domains of cognitive activity, even though they retained sufficient independence in daily life to avoid a diagnosis of dementia 4. Thus, a broadly accepted consensus document proposed categorization of cases according to their predominant cognitive feature(s) (memory vs. other) and the number of cognitive domains affected (single- vs. multiple-domain) 5. That document continued to emphasize the presence of a subjective memory or other cognitive complaint [although the role for this criterion has recently been challenged – see, e.g., 6]. By contrast, the document does not evaluate the predictive capacity of genetic risk factors such as APOE ε4 or AD biomarkers such as CSF concentrations of Aβ42 and tau. Nonetheless, later work has repeatedly demonstrated the prognostic significance of these markers 7, particularly for identification of individuals whose condition represents an early stage of Alzheimer's disease 8. With these and other minor improvements, therefore, the MCI construct has stood the test of time as a useful clinical entity. an opportunity for early detection and treatment of cognitive decline before patients’ deficits become more pronounced and progress to Major Neurocognitive Disorder (dementia) or other debilitating conditions. Its inclusion in the manual will help clinicians develop effective treatment plans as well as encourage researchers to evaluate diagnostic criteria and potential therapies. 9 a level of cognitive decline that requires compensatory strategies and accommodations to help maintain independence and perform activities of daily living. To be diagnosed with this disorder there must be changes that impact cognitive functioning (emphasis added.) 9 Intuitively, one might expect this more exacting definition to predict the development of dementia with greater accuracy, as the cases would likely include a lower proportion of ‘false-positive’ individuals who do not progress to dementia. However, predictive performance depends not only on a category's tendency toward identification of false-positives (usually calculated as specificity, which is 1 minus the proportion of false-positives) but also on its sensitivity (proportion detected among those who will in fact progress to dementia). Here, the Zaragosa group's comparison of the two sets of criteria is worrisome because their observed prevalence of Mild Neurocognitive Disorder was only half that of classic MCI in the same population. What about the other half? These cannot all be ‘false-positives’, as we know that as many as half of all carefully diagnosed MCI cases will progress to dementia within three years (and a higher proportion within 5–7 years) 10, 11. To address this issue, the Zaragosa group compared the two disorders’ comorbid neuropsychiatric features, seeking characteristics more typical of ‘true’ prodromal dementia or AD in the group diagnosed using DSM-5. However, they were unable to convince themselves that the features associated with the DSM-5 disorder were more indicative of subsequent progression to dementia, even though they did find that cases of Mild Neurocognitive Disorder had more associated ‘negative-type’ neuropsychiatric symptoms that would probably have more serious implications for function. This writer finds it disappointing that the development of the DSM-5 criteria (in a continuation of the approach used to delineate the classic MCI criteria) adopted the approach of seeking ever more specific clinical features to refine crude observations of cognitive dysfunction. A different approach could have relied more on correlative (and better validated) Alzheimer disease biomarkers or risk genes as predictors of incipient decline 10. There is substantial clinical need to recognize individuals who need care for cognitive issues that go beyond normal aging. The impact of these problems is noticeable, but clinicians have lacked a reliable diagnosis by which to assess symptoms or understand the most appropriate treatment or services. Recent studies suggest that identifying mild neurocognitive disorder as early as possible may allow interventions to be more effective. Early intervention efforts may enable the use of treatments that are not effective at more severe levels of impairment and may prevent or slow progression. (emphasis added) 9 It is not clear what reliable studies, recent or otherwise, demonstrate that early identification of cognitive disorders leads to more effective interventions 12. But even if this were so, what should we make of the fact that DSM-5 Mild Neurocognitive Disorder appears to have reduced sensitivity for early diagnosis, presumably because its defining criteria demand more severe impairment in function? And what about the finding that the comorbid neuropsychiatric features of the DSM-5 entity typically include more disabling (and less readily treated) ‘negative-type’ symptoms such as apathy or slowed mentation? From a financial perspective, there is little doubt that the APA's revised DSM has been a huge success. As a clinical tool, however, its success is less certain. The findings from Zaragosa seem to run counter to the APA's intent of ‘identifying Mild Neurocognitive Disorder as early as possible (to) allow interventions to be more effective’ or to ‘enable the use of treatments that are not effective at more severe levels of impairment and may prevent or slow progression.’ Has the APA's preferred method of relying on consensus opinion in fact produced a perverse result? Should the experts instead have relied on studies such as those of the Zaragosa group in formulating their diagnostic terminology? Are there not lessons to be learned here? Thanks to Drs. Bernard Carroll and Pierre Etienne who provided helpful comments.

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Intégrité de la recherche, Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesMéta-épidémiologie (sens strict), Intégrité de la recherche
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 enseignants0,221
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,001
Méta-épidémiologie (sens strict)0,0020,001
Méta-épidémiologie (sens large)0,0020,001
Bibliométrie0,0020,002
Études des sciences et des technologies0,0010,000
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0010,005
Charge utile insuffisante (le modèle a refusé de juger)0,0010,001

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 Opus0,036
Tête enseignante GPT0,315
Écart entre enseignants0,280 · 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; les deux têtes enseignantes s’accordent sur ce qui est montré ici.

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

Citations11
Publié2014
Routes d'admission2
Résumé présentoui

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