Health Economic Evaluations for Alzheimer’s Disease: Pathophysiology, Diagnosis and Pharmacological Approaches
Bibliographic record
Abstract
Alzheimer's disease (AD) was first described by Alois Alzheimer in 1907 as a slowly progressing form of dementia that affects cognition, behavior, and functional status. It may be identified by the extracellular amyloid b (Ab) plaques as well as neurofibrillary tangle (NFT) deposits that are seen inside the neurons. Early-onset Alzheimer's disease (EOAD) and late-onset Alzheimer's disease (LOAD) are the two main categories that form the base of AD presentation. EOAD is a condition that develops before the age of 65 and is linked to Mendelian inheritance, which results in a mutation in the genes APP, PSEN1, or PSEN2. So it is familial AD. While LOAD occur after age 65 years of age and, it is not related to a genetic cause. So it is sporadic AD. To assess and monitor the rate and pattern of cognitive loss, screening measures like the MMSE and the Montreal Cognitive Examination are utilized. Clinical biomarker testing is now available to assist physicians in determining the the presence and severity of AD pathologic alterations, as well as their lasting effects. Fibrillar (plaque) amyloid is detectable on PET. Despite the fact that AD is a public health issue, only two pharmaceutical classes—antagonists of N-methyl d-aspartate (NMDA) and inhibitors of the cholinesterase enzyme (naturally occurring, synthetic, and hybrid variants)—are allowed to be practiced to treat AD. AD is brought on by a decrease in the synthesis of acetylcholine (Ach) Increasing acetylcholine levels by decreasing acetylcholinesterase is one of the therapeutic interventions that enhances neuronal cells and cognitive function. Tacrine was the first cholinesterase inhibitor drug authorized by the FDA to be used for the treatment of AD.
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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 | 0.039 | 0.123 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".