Longitudinal characterization of mild cognitive impairment and dementia in World Trade Center responders at midlife
Bibliographic record
Abstract
Abstract Background Though the Montreal Cognitive Assessment (MoCA) is validated for cross‐sectional assessment, there is limited guidance as to methods for reliably identifying incident cases of Mild Cognitive Impairment (MCI) and dementia. The goal of this study was to examine characteristics of individuals identified as having MCI and dementia using different diagnostic routines. Methods World Trade Center (WTC) responders are a unique population, not only because of the historic significance of the traumatic exposures many endured while onsite following the terrorist attacks in New York City on 9/11/2001 but also given responders participation in a long‐term monitoring program established by the Centers for Disease Control (CDC) in 2002 to monitor the long‐term effects of WTC exposures on health outcomes. Since 2014, we have administered the MoCA to responders over at least three assessments (n=2,370). The MoCA was administered by trained research staff; alternate versions were used to account for learning. Seven diagnostic routines were examined that variably examined adjusting for learning, objective evidence of functional limitations, and cognitive decline to identify one with the least variability in outcome. Stability of diagnostic outcome was the primary outcome. Follow‐up studies in subsets of the population included a detailed computer‐assisted neuropsychological examination, measures of physical functional limitations, a cross‐sectional sample of plasma based biomarkers measured using Simoa (e.g., b‐Amyloid1‐40, b‐Amyloid1‐42, Total‐Tau, Glial Fibrillary Acidic Protein, and Neurofilament‐Light), a cross‐sectional assessment of cortical thickness, and a self‐reported version of the Mild Behavioral Checklist. Results 8.0% of responders were male, 4.3% were Black, and 7.7% were Hispanic. The mean age at initial MoCA assessment was 52.6 years old (SD=8.1). There was enormous variability in longitudinal stability in MCI and dementia diagnostic outcomes between different longitudinal diagnostic routines (Spearman’s r=0.22‐0.86). Though domain‐specific sub‐scales with high internal consistency (a=0.92‐0.97) were available, the most stable definition relied on MoCA scores adjusted for learning and expected within‐person test‐retest score distributions. MCI and dementia identified using all diagnostic routines were variably associated poorer cognitive functioning and with biomarkers. Conclusion This study gives guidance about differences between methods relying on the MoCA to longitudinally screen WTC responders for MCI and dementia at midlife.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".