Physician Practice Patterns Associated with Diagnostic Evaluation of Patients with Suspected Mild Cognitive Impairment and Alzheimer’s Disease
Bibliographic record
Abstract
The diagnostic process for patients presenting with cognitive decline and suspected dementia is complex. Physicians face challenges distinguishing between normal aging, mild cognitive impairment, Alzheimer's disease, and other dementias. Although there is some evidence for improving attitudes towards the importance of prompt diagnosis, there is limited information describing how physicians approach this diagnostic challenge in practice. This was explored in the present study. Across-sectional survey of primary care and specialist physicians, in 5 European countries, Canada, and the United States, was conducted. Participants were asked about their use of cognitive screening tools and diagnostic technologies, as well as the rationales and barriers for use. In total, 1365 physicians participated in the survey, 63% of whom were specialists. Most physicians stated they use objective cognitive tools to aid the early detection of suspected mild cognitive impairment or Alzheimer's disease in patients. The Mini-Mental State Examination was the most common tool used for initial screening; respondents cited speed and ease of use but noted its lack of specificity. Cerebrospinal fluid biomarker and amyloid positron emission tomography tests, respectively, had been used by only 26% and 32% of physicians in the preceding 6 months, although patterns of use varied across countries. The most commonly cited reasons for not ordering such tests were invasiveness (for cerebrospinal fluid biomarker testing) and cost (for amyloid positron emission tomography imaging). Data reported by physicians reveal differences in the approaches to the diagnostics process in Alzheimer's. A higher proportion of primary care physicians in the United States are routinely incorporating cognitive assessment tools into annual visits, but this is due to country differences in clinical practice. The value of screening tools and regular use could be discussed further with physicians; however, lack of specificity associated with cognitive tools and the investment required from patients and the healthcare system are limiting factors.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".