Clinical performance of the fully automated Lumipulse plasma p‐tau217 assay in mild cognitive impairment and mild dementia
Bibliographic record
Abstract
Introduction: Plasma phosphorylated tau (p-tau)217 is a leading blood-biomarker for the detection of amyloid beta (Aβ) pathology. We assessed the performance of a fully automated plasma p-tau217 immunoassay to detect Aβ pathology in mild cognitive impairment (MCI)/mild dementia. Methods: Paired plasma and cerebrospinal fluid (CSF) samples were obtained at time of diagnostic lumbar puncture (LP) in a specialist memory service. Plasma p-tau217 was measured using the Lumipulse immunoassay platform and ability to detect CSF-defined Aβ positivity assessed. Results: Of 148 participants (69.4 ± 6.5 years; 54.1% female), 101 had MCI and 47 mild dementia. Median plasma p-tau217 was > 4-fold higher in Aβ+ vs Aβ- individuals with an area under the curve of 0.92 (0.87-0.97). Application of 90%, 95%, and 97.5% sensitivity/specificity thresholds for plasma p-tau217 may have obviated the need for more than half of LPs. Discussion: Our real-world data support the clinical use of fully automated plasma p-tau217 immunoassays, although further studies in more diverse cohorts are required. HIGHLIGHTS: Plasma phosphorylated tau (p-tau)217 was measured using a fully automated immunoassay (Lumipulse).P-tau217 was > 4-fold higher in amyloid beta (Aβ)+ versus Aβ- individuals.Plasma p-tau217 had an area under the curve of 0.92 for detection of Aβ status.Using a previously proposed two-threshold approach may avoid more than half of lumbar punctures.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".