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Record 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 on OpenAlexafffund
John C.S. Breitner

Bibliographic record

VenueActa Psychiatrica Scandinavica · 2014
Typeletter
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsDouglas Mental Health University InstituteDouglas College
FundersMcGill University
KeywordsDementiaMemory impairmentCognitive impairmentPsychologyProdromeNeurocognitiveCognitionConstruct (python library)Memory clinicPopulationPsychiatryClinical psychologyGerontologyMedicineDiseasePathology

Abstract

fetched live from 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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.221
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.005
Insufficient payload (model declined to judge)0.0010.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.036
GPT teacher head0.315
Teacher spread0.280 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreCommentary

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations11
Published2014
Admission routes2
Has abstractyes

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Same venueActa Psychiatrica ScandinavicaSame topicDementia and Cognitive Impairment ResearchFrench-language works237,207