A proposed scheme for comprehensive and systematic evaluation of normal pressure hydrocephalus
Bibliographic record
Abstract
Abstract Background As ageing population continues to rise across the globe, age‐related conditions such as normal pressure hydrocephalus (NPH) are expected to become a prevalent health problem effecting gait and cognition in the elderly. Alas, the vague definition of NPH, coupled with the absence of standardized assessment protocols, can potentially result in unnecessary surgical interventions and complications. We aim to demonstrate the feasibility of our proposed objective scheme for a comprehensive and systematic evaluation of NPH, which we anticipate will be beneficial in guiding future management of this enigmatic disorder. Method Participants suspected of idiopathic NPH (iNPH) selected to undergo a trial of fluid diversion (i.e. large volume spinal tap) were enrolled to receive structured assessment with various biomarkers. This assessment includes pre‐fluid diversion evaluation of the following: iNPH grading scale (Kubo et al., 2008), voxel based morphometry analysis of the MRI, tablet‐based digitalized Montreal Cognitive Assessment, International Consultation on Incontinence Questionnaires, urodynamic studies. Tests that were conducted both pre‐ and post‐fluid diversion test included actigraphy, video gait analysis using Kinovea®, in‐house tablet‐based go/no‐go test and conjunction search test. During the fluid diversion trial, participants underwent an infusion test for objective quantification of cerebrospinal fluid dynamics. Cerebrospinal fluid was collected and analyzed for levels of Alzheimer’s disease biomarkers, specifically Aβ and tau species, using ELISA, as well as an α‐synuclein seeding assay. The decision to operate was made according to subjective improvement, which is the current standard of care, and subsequent assessments were repeated at 4‐month intervals for 1, 2, and 3 years postoperatively Result Between May 2022 and November 2022, six participants were recruited. Each test was completed by at least three out of the six participants. The participant who completed the most tests completed all but one of the tests. It is important to note that none of the participants recruited underwent shunt surgery. Conclusion The proposed scheme for the assessment of NPH demonstrates feasibility, however, certain optimizations are necessary. Further research should be conducted to determine the correlation between these parameters and their performance in predicting long‐term responsiveness to shunt surgery.
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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 | 0.023 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".