CSF Tap Test Parameters and Short-Term Outcomes in operated and non-operated patients with idiopathic Normal Pressure Hydrocephalus: A Cohort Study
Bibliographic record
Abstract
Abstract Background Normal Pressure hydrocephalus (NPH) is treated by ventriculoperitoneal shunting. The cerebrospinal fluid tap test (CSF-TT) is widely used to identify candidates for shunt surgery in idiopathic NPH (iNPH). This study aimed to compare the CSF tap test responses and 24-week functional outcomes between patients with probable iNPH who underwent surgery and those who did not. Methods This Ambispective cohort study included 40 patients with probable iNPH, as defined by the 2019 Japanese guidelines, from 2019 to 2024. All patients underwent a large-volume CSF-TT, and they were offered surgery based on the clinico-radiologic profile. Results Twenty-four patients underwent ventriculoperitoneal shunt surgery, and 16 did not for various reasons. No significant differences were found in the baseline or 24-hour post-CSF tap test parameters between the groups. However, at 24 weeks, 62.5% of the operated patients showed at least a 1-point improvement in mRS. In contrast, only 14.3% in the non-operated group did, indicating the beneficial role of VP shunting in NPH. Those who were operated had a 10 times higher odds (95% CI 1.6-105) of achieving at least one point improvement in mRS at 24 weeks. Interestingly, 46.7% of patients whose mRS did not improve after CSF-TT but who underwent surgery still benefited from shunting. Conclusion Shunt surgery leads to a favorable short-term functional outcome in patients with probable iNPH. However, the CSF-TT alone lacks sufficient discriminatory power to guide surgical decisions in a cohort of patients with clinico-radiological probable iNPH. A negative tap test should not preclude surgery in patients with supportive clinical and imaging features.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".