bioMIND‐A Novel Approach to Integrating Biomarkers in the Diagnostic Workup for Alzheimer's Disease
Bibliographic record
Abstract
BACKGROUND: Biomarkers for amyloid and tau pathology have revolutionized Alzheimer's Disease (AD) management, enabling pathological confirmation and therapeutic targets. Currently, there are no standardized care pathways for biomarker testing in Canada and most eligible patients are offered biomarker testing late, if ever, in the diagnostic pathway. The objective of this study was to investigate the feasibility of a "biomarker first" approach in the diagnostic pathway of AD in a real-world cohort of patients. METHOD: This prospective, observational study enrolled patients with subjective cognitive decline, amnestic mild cognitive impairment (aMCI), or mild dementia awaiting assessment at a tertiary memory clinic. Standardized inclusion criteria were based on disease modifying therapy eligibility from referral information provided by a primary care physician. Participants underwent cognitive and functional testing, lumbar puncture for cerebrospinal fluid (CSF) collection, and amyloid PET scans prior to being evaluated by a specialist. Participants then underwent specialist clinical assessment with the results of their biomarker testing. A standard of care group (biomarker second) was included for comparison. RESULT: 276 participants were screened with 47 (17.02%) eligible. Exclusions were due to age (10%), low MoCA scores (16%), medical comorbidities (15%), inability to complete study procedures (14%), insufficient referral information (16%), MRI contraindications (5%), other neurodegenerative diseases (5%), psychiatric disease (2%). 28% of eligible participants were reluctant to undergo lumbar puncture. Demographics and cognitive profiles were comparable between the two groups, with mean MMSE scores of 26.28 ±2.50 in the biomarker first group and 26.15 ±2.94 in the biomarker second group (p = 0.719). CSF biomarkers consistent with AD were detected in 78.5% of biomarker first group compared to 63.15% of biomarker second group. CSF results predicted positive amyloid PET scans in all patients. CONCLUSION: This study demonstrates that 17% of "real-world" patients referred to a tertiary memory clinic would be eligible for biomarker testing based solely on screening information provided by primary care. The biomarker-first approach is feasible and accurate, enabling earlier diagnostic clarification and personalized treatment opportunities for AD. This pathway could help shift care from late-stage symptom management to early intervention targeting disease pathology, improving outcomes and optimizing healthcare delivery.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".