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Record W2133054322 · doi:10.1093/brain/awp191

Updated clinical diagnostic criteria for sporadic Creutzfeldt-Jakob disease

2009· article· en· W2133054322 on OpenAlexaff
Inga Zerr, Kai Kallenberg, David Summers, Carlos Romero, A.L. Taratuto, Uta Heinemann, Maren Breithaupt, Daniela Varges, Bettina Meißner, Anna Ladogana, Maaike Schuur, Stéphane Haı̈k, Steven Collins, Gerard H. Jansen, Gorazd B. Stokin, José Pimentel, Ekkehard Hewer, Donald A. Collie, P. Smith, Hannah Roberts, J.P. Brandel, Cornelia M. van Duijn, Maurizio Pocchiari, Christián Begué, Patrick Cras, Robert Will, Pascual Sánchez‐Juan

Bibliographic record

VenueBrain · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPrion Diseases and Protein Misfolding
Canadian institutionsPublic Health Agency of Canada
FundersRobert Koch InstitutFleniBundesministerium für GesundheitMinisterio de Ciencia, Tecnología e Innovación ProductivaMinisterio de Salud de la NaciónEuropean Centre for Disease Prevention and ControlBundesamt für GesundheitEuropean CommissionBundesministerium für Bildung und ForschungNational Institute for Health and Care Research
KeywordsMagnetic resonance imagingDifferential diagnosisPutamenMedicinePathologyDiseaseCerebrospinal fluidDementiaCreutzfeldt-Jakob SyndromeBasal gangliaThalamusDegenerative diseaseNeuroimagingCaudate nucleusRadiologyCentral nervous systemInternal medicinePrion proteinPsychiatry

Abstract

fetched live from OpenAlex

Several molecular subtypes of sporadic Creutzfeldt-Jakob disease have been identified and electroencephalogram and cerebrospinal fluid biomarkers have been reported to support clinical diagnosis but with variable utility according to subtype. In recent years, a series of publications have demonstrated a potentially important role for magnetic resonance imaging in the pre-mortem diagnosis of sporadic Creutzfeldt-Jakob disease. Magnetic resonance imaging signal alterations correlate with distinct sporadic Creutzfeldt-Jakob disease molecular subtypes and thus might contribute to the earlier identification of the whole spectrum of sporadic Creutzfeldt-Jakob disease cases. This multi-centre international study aimed to provide a rationale for the amendment of the clinical diagnostic criteria for sporadic Creutzfeldt-Jakob disease. Patients with sporadic Creutzfeldt-Jakob disease and fluid attenuated inversion recovery or diffusion-weight imaging were recruited from 12 countries. Patients referred as 'suspected sporadic Creutzfeldt-Jakob disease' but with an alternative diagnosis after thorough follow up, were analysed as controls. All magnetic resonance imaging scans were assessed for signal changes according to a standard protocol encompassing seven cortical regions, basal ganglia, thalamus and cerebellum. Magnetic resonance imaging scans were evaluated in 436 sporadic Creutzfeldt-Jakob disease patients and 141 controls. The pattern of high signal intensity with the best sensitivity and specificity in the differential diagnosis of sporadic Creutzfeldt-Jakob disease was identified. The optimum diagnostic accuracy in the differential diagnosis of rapid progressive dementia was obtained when either at least two cortical regions (temporal, parietal or occipital) or both caudate nucleus and putamen displayed a high signal in fluid attenuated inversion recovery or diffusion-weight imaging magnetic resonance imaging. Based on our analyses, magnetic resonance imaging was positive in 83% of cases. In all definite cases, the amended criteria would cover the vast majority of suspected cases, being positive in 98%. Cerebral cortical signal increase and high signal in caudate nucleus and putamen on fluid attenuated inversion recovery or diffusion-weight imaging magnetic resonance imaging are useful in the diagnosis of sporadic Creutzfeldt-Jakob disease. We propose an amendment to the clinical diagnostic criteria for sporadic Creutzfeldt-Jakob disease to include findings from magnetic resonance imaging scans.

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)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.026
GPT teacher head0.365
Teacher spread0.339 · 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 designNot applicable
Domainnot available
GenreMethods

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

Citations920
Published2009
Admission routes1
Has abstractyes

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