Optimal ATN biomarkers and their role in predicting cognitive progress of mild cognitive impairment
Bibliographic record
Abstract
Abstract Background It is of great significance to investigate the optimal cerebrospinal fluid (CSF) and magnetic resonance image biomarkers of ATN system and clarify their predictive value in cognitive progression of mild cognitive impairment individuals (MCI). Methods 147 healthy control (HC), 197 patients with MCI, and 128 patients with Alzheimer’ Disease (AD) were included from the ADNI database. All MCI patients were followed up from 6 to 60 months. The amyloid (A) was assessed by CSF Aβ42 or Aβ42/Aβ40. The tau pathology (T) was assessed by CSF p-tau. The neurodegeneration (N) was assessed by radiomics of the whole brain MRI or by CSF t-tau. Biomarkers with larger area under the receiver operating characteristic curve (AUC) in the discrimination of AD and HC were considered to be the optimal biomarkers. The conversion rates of different ATN profiles in MCI subjects during follow-up were analyzed using Kaplan-Meier estimates and compared using the Log-rank test. Results The CSF Aβ 42 and the radiomics signature (AUC 0.822 and 0.998, respectively) were identified as the optimal A and N biomarkers, respectively. For MCI patients of the Alzheimer continuum, there was no significant difference in the progression rate of A + T − N− and A − T−N − profiles (p > 0.05). The A + T + N−, A + T − N + profiles had a significant higher progression rate than that of the A + T − N− patients (all p < 0.05). For MCI of the suspected non-AD pathophysiology (SNAP), patients with the A − T−N + profile (p < 0.05) showed significant higher progression rate than A − T−N − profile. There was no significant difference in the progression rate of A − T + N − and A − T−N − profiles (p > 0.05). Discussion We proposed a new radiomics method to assess N accurately and ascertained the optimal A/T/N biomarkers for the discrimination of HC and AD. For MCI patients of the Alzheimer continuum, isolated A + was indicator of cognitive stability, while the abnormality of T and N, respectively or simultaneously, indicated the high risk of progression. For MCI patients of SNAP, isolated T + indicated the cognitive stability, while the appearance of N + indicated the high risk of progression.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".