Gait Analysis in Idiopathic Normal Pressure Hydrocephalus: A <scp>Meta‐Analysis</scp>
Why this work is in the frame
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Bibliographic record
Abstract
Background: Gait analysis objectively quantifies gait impairment in idiopathic normal pressure hydrocephalus (iNPH), may improve diagnosis and evaluation for surgical candidacy. Objectives: This meta-analysis aims to understand which objective gait parameters improve after tap-test (TT) and CSF shunt surgery (CSS), also comparing responders (R) with non-responders (NR) and to assess if gait restores within the range of healthy controls after procedures. Methods: Studies enrolling iNPH with at least one instrumented gait measure were selected. Three time points of gait assessment were defined: PRE, POST-TT, and POST-CSS. Gait velocity, cadence, step length, stride length, and double limb support time were evaluated. Patients were categorized based on responsiveness to CSF diversion procedures. Results: Seventeen studies including 527 patients were selected. iNPH improved significantly in almost all gait parameters POST-TT, and to a greater extent POST-CSS. Gait parameters consistently discriminated iNPH from healthy controls. Despite the aforementioned improvements, iNPH's gait did not completely normalize after CSF diversion procedures. Meta-regression analysis also revealed that TT's effect on gait velocity plateaus after 24-48 hr and returns to baseline in 90-100 hr. Conclusions: Gait analysis is a reliable quantitative instrument to assess gait impairment in iNPH, demarking a net differentiation from healthy controls, according to the notion that the iNPH CSF dynamic alteration also leads to an irreversible damage. Specific gait parameters improve among TT-R, providing an opportunity to select patients that will respond to CSS. Future studies validating a standardized reporting method including criteria of responsiveness, specific gait parameters, and timeframe of assessment are needed.
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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 | 0.008 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.012 |
| Bibliometrics | 0.003 | 0.017 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it