[P3–279]: MILD COGNITIVE IMPAIRMENT TREATMENT: PROVIDER PATTERNS ACROSS MEDICAL SPECIALTIES
Bibliographic record
Abstract
Individuals with mild cognitive impairment (MCI), specifically the amnestic subtype (MCIa), tend to progress to probable Alzheimer's disease (AD) at a rate of approximately 10%-15% per year. Individuals often first consult with general practitioners (GPs) when they start to experience a decline in memory. However, symptoms of MCI can be subtle and providers without specialized training may attribute MCI symptoms to normal aging, resulting in possible under-diagnosing of MCI and missed opportunities to slow the disease progression. This research examined treatment provider trends for patients diagnosed with MCI and AD. Data were obtained from the TreatmentAnswers™ database, which includes data from 3,219 US-based physicians. One day each month, participating physicians complete a survey about patient activity during that day, including visit information, patient/physician demographics, diagnostic information, and intended drug therapy. Data collected are projected to the wider US population using a standardized projection factor. This investigation included a review of the 2015 data for patients with ICD-9 diagnoses of either MCI or AD. Data were summarized by provider (Neurologists, Psychiatrists, Generalists and all others) then stratified by gender and age. Neurologists treated the majority of patients diagnosed with MCI (79.4%). Non-neurologists treated fewer MCI patients than patients with AD. 100% of MCI patients seen by GPs were over the age of 81. Neurologists saw the majority of patients diagnosed with MCI across all age groups, whereas GPs only saw patients with MCI who were over the age of 81. These results may indicate that GPs are either referring MCI cases to neurologists or they might not be making MCI diagnoses as frequently as warranted. Early identification of individuals with MCI is crucial in providing treatment as early as possible in the course of the illness. With an aging population, it is imperative that non-neurologists be equipped with the tools to screen and diagnose AD and other dementias.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| 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) | 0.020 | 0.003 |
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".