Deconstructing normal pressure hydrocephalus: Ventriculomegaly as early sign of neurodegeneration
Bibliographic record
Abstract
Idiopathic normal pressure hydrocephalus (NPH) remains both oversuspected on clinical grounds and underconfirmed when based on immediate and sustained response to cerebrospinal fluid diversion. Poor long-term postshunt benefits and findings of neurodegenerative pathology in most patients with adequate follow-up suggest that hydrocephalic disorders appearing in late adulthood may often result from initially unapparent parenchymal abnormalities. We critically review the NPH literature, highlighting the near universal lack of blinding and controls, absence of specific clinical, imaging, or pathological features, and ongoing dependence for diagnostic confirmation on variable cutoffs of gait response to bedside fluid-drainage testing. We also summarize our long-term institutional experience, in which postshunt benefits in patients with initial diagnosis of idiopathic NPH persist in only 32% of patients at 36 months, with known revised diagnosis in over 25% (Alzheimer's disease, dementia with Lewy bodies, and progressive supranuclear palsy). We postulate that previously reported NPH cases with "dual" pathology (ie, developing a "second" disorder) more likely represent ventriculomegalic presentations of selected neurodegenerative disorders in which benefits from shunting may be short-lived, with a consequently unfavorable risk-benefit ratio. Ann Neurol 2017;82:503-513.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".