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Record W3118644131 · doi:10.1007/s00401-020-02255-2

Neuropathological consensus criteria for the evaluation of Lewy pathology in post-mortem brains: a multi-centre study

2021· article· en· W3118644131 on OpenAlexaff
Johannes Attems, Jon B. Toledo, Lauren Walker, Ellen Gelpí, Steve Gentleman, Glenda M. Halliday, Tibor Hortobágyi, K. A. Jellinger, Gábor G. Kovács, Edward B. Lee, Seth Love, Kirsty E. McAleese, Peter T. Nelson, Manuela Neumann, Laura Parkkinen, Tuomo Polvikoski, Beata Sikorska, Colin Smith, Lea T. Grinberg, Dietmar Rudolf Thal, John Q. Trojanowski, Ian G. McKeith

Bibliographic record

VenueActa Neuropathologica · 2021
Typearticle
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsUniversity of TorontoUniversity Health Network
FundersNational Institute on AgingNational Institutes of HealthAlzheimer’s Research UKNational Institute of Neurological Disorders and StrokeMedical Research CouncilParkinson's UK
KeywordsLewy bodyLewy body diseasePathologyNeocortexPsychologyDementia with Lewy bodiesMedicineNeuroscienceDementiaDisease

Abstract

fetched live from OpenAlex

Currently, the neuropathological diagnosis of Lewy body disease (LBD) may be stated according to several staging systems, which include the Braak Lewy body stages (Braak), the consensus criteria by McKeith and colleagues (McKeith), the modified McKeith system by Leverenz and colleagues (Leverenz), and the Unified Staging System by Beach and colleagues (Beach). All of these systems use semi-quantitative scoring (4- or 5-tier scales) of Lewy pathology (LP; i.e., Lewy bodies and Lewy neurites) in defined cortical and subcortical areas. While these systems are widely used, some suffer from low inter-rater reliability and/or an inability to unequivocally classify all cases with LP. To address these limitations, we devised a new system, the LP consensus criteria (LPC), which is based on the McKeith system, but applies a dichotomous approach for the scoring of LP (i.e., "absent" vs. "present") and includes amygdala-predominant and olfactory-only stages. α-Synuclein-stained slides from brainstem, limbic system, neocortex, and olfactory bulb from a total of 34 cases with LP provided by the Newcastle Brain Tissue Resource (NBTR) and the University of Pennsylvania brain bank (UPBB) were scanned and assessed by 16 raters, who provided diagnostic categories for each case according to Braak, McKeith, Leverenz, Beach, and LPC systems. In addition, using LP scores available from neuropathological reports of LP cases from UPBB (n = 202) and NBTR (n = 134), JT (UPBB) and JA (NBTR) assigned categories according to all staging systems to these cases. McKeith, Leverenz, and LPC systems reached good (Krippendorff's α ≈ 0.6), while both Braak and Beach systems had lower (Krippendorff's α ≈ 0.4) inter-rater reliability, respectively. Using the LPC system, all cases could be unequivocally classified by the majority of raters, which was also seen for 97.1% when the Beach system was used. However, a considerable proportion of cases could not be classified when using Leverenz (11.8%), McKeith (26.5%), or Braak (29.4%) systems. The category of neocortical LP according to the LPC system was associated with a 5.9 OR (p < 0.0001) of dementia in the 134 NBTR cases and a 3.14 OR (p = 0.0001) in the 202 UPBB cases. We established that the LPC system has good reproducibility and allows classification of all cases into distinct categories. We expect that it will be reliable and useful in routine diagnostic practice and, therefore, suggest that it should be the standard future approach for the basic post-mortem evaluation of LP.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.032
metaresearch head score (Gemma)0.041
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.032
Threshold uncertainty score0.167

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0320.041
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0080.004
Science and technology studies0.0020.001
Scholarly communication0.0010.002
Open science0.0030.004
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.128
GPT teacher head0.381
Teacher spread0.253 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations276
Published2021
Admission routes1
Has abstractyes

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