Examining a telecognitive assessment‐derived Preclinical Alzheimer’s Cognitive Composite, the tPACC, for cognitive migration over one year in community‐dwelling older adults
Bibliographic record
Abstract
Abstract Background ADRD clinical trials often target preclinical disease, where hope of averting the pathologic cascade and eventual cognitive decline remains highest. The preclinical Alzheimer’s cognitive composite (PACC5) was developed for in‐person administration to capture subtle cognitive decline. Early cognitive fluctuations may inform multidirectional disease progression, defined as cognitive migration. It is desirable to have a harmonized composite measurement derived from in‐person and remote assessments for detecting cognitive migration. Method We examined in‐person data from 417 adults (70.6±8.0y) from the Wake Forest ADRC Clinical Core, who received MRI, clinical evaluation and cognitive testing. The primary outcome was cognitive migration status determined by global CDR (0 and 0.5) increase/decrease between baseline (BL) and follow‐up (mean difference = 13.9 months): CDR‐0 Stable (51% maintained CDR‐0), CDR‐0.5 Stable (27% maintained CDR‐0.5), Reverter+ (13% migrated from CDR‐0.5 to CDR‐0) and Migrant− (9% migrated from CDR‐0 to CDR‐0.5). In‐person PACC5 was calculated (RAVLT Delayed Recall, Digit Symbol Coding [DSC], semantic fluency, Craft Story Delayed Verbatim, total MMSE) using BL participants with global CDR = 0 as reference. tPACC used measurements available at both in‐person and remote visits with minor modifications from PACC5: Montreal Cognitive Assessment (MoCA) replaced MMSE and DSC not included. We performed intraclass correlation coefficient (ICC) analysis and generated Bland‐Altman plots for BL tPACC and PACC5. We also evaluated associations between tPACC and neuroimaging. Result Participant characteristics and group differences in MRI markers are in Table 1. Bland‐Altman plots show differences and mean of tPACC and PACC5 (dashed line: ±1.96 SD, solid line: mean difference/bias). 92% of values lie within limit of agreement, indicating good agreement (overall ICC = .960, 95%CI = [.952, .967]), between tPACC and PACC5 in each group (Figure 1). At BL, there was a significant absolute agreement between in‐person tPACC and PACC5 in all groups (Figure 1). tPACC showed significant associations (Table 2) with Temporal Meta ROI thickness, hippocampal volume as % head size (ICV) and white matter hyperintensities (logWMH controlled for ICV) overall and in some cognitive migration groups. Conclusion There is generally good agreement between BL tPACC and PACC5 across cognitive migration groups. BL tPACC may predict BL neuroimaging based on cognitive migration status. Longitudinal tPACC examination is warranted.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".