Freezing of gait in idiopathic normal pressure hydrocephalus
Bibliographic record
Abstract
BACKGROUND: Reports of freezing of gait (FoG) in idiopathic normal pressure hydrocephalus (iNPH) are few and results are variable. This study's objective was to evaluate the frequency of FoG in a large cohort of iNPH patients, identify FoG-associated factors, and assess FoG's responsiveness to shunt surgery. METHODS: Videotaped standardized gait protocols with iNPH patients pre- and post-shunt surgery (n = 139; median age 75 (71-79) years; 48 women) were evaluated for FoG episodes by two observers (Cohens kappa = 0.9, p < 0.001). FoG episodes were categorized. Mini-mental state examination (MMSE) and MRI white matter hyperintensities (WMH) assessment using the Fazekas scale were performed. CSF was analyzed for Beta-amyloid, Tau, and Phospho-tau. Patients with and without FoG were compared. RESULTS: Twenty-two patients (16%) displayed FoG at baseline, decreasing to seven (8%) after CSF shunt surgery (p = 0.039). The symptom was most frequently exhibited during turning (n = 16, 73%). Patients displaying FoG were older (77.5 vs. 74.6 years; p = 0.029), had a slower walking speed (0.59 vs. 0.89 m/s; p < 0.001), a lower Tinetti POMA score (6.8 vs. 10.8; p < 0.001), lower MMSE score (21.3 vs. 24.0; p = 0.031), and longer disease duration (4.2 vs. 2.3 years; p < 0.001) compared to patients not displaying FoG. WMH or CSF biomarkers did not differ between the groups. CONCLUSIONS: FoG is occurring frequently in iNPH patients and may be considered a typical feature of iNPH. FoG in iNPH was associated with higher age, longer disease duration, worse cognitive function, and a more unstable gait. Shunt surgery seems to improve the symptom.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".