Diagnostic accuracy of CSF tap-test parameters in predicting shunt responsiveness in normal pressure hydrocephalus: a cohort study
Year: 2026
Type: article
Study design: Observational Study
Abstract: Background The cerebrospinal fluid tap test (CSF-TT) is widely used as an ancillary test to select patients with idiopathic Normal Pressure Hydrocephalus (iNPH) for surgical management; however, its diagnostic utility remains unclear. We evaluate the diagnostic utility of CSF-TT in predicting outcomes following shunt surgery. Methods Patients with possible or probable iNPH underwent assessments of gait, urinary, and cognitive function using Boon’s gait scale, iNPH grading scale, TUG score, MoCA, and modified Rankin Scale (mRS) at baseline and 24 hours after CSF-TT. They were offered VP shunt surgery based on clinico-radiological profile, regardless of CSF-TT outcome. Post-operative outcomes were evaluated at 24 weeks, and those who showed a ≥1-point improvement in the mRS were classified shunt responders. The diagnostic performance of various scales was assessed using receiver operating characteristic curves. Results Out of 24 patients who underwent shunting 15 (62.5%) were classified as shunt responders. A one-point reduction in the modified Rankin scale at 24 hours post-CSF-TT had a sensitivity of 53.3% (95% CI: 26.6-78.7) and specificity of 66.7% (95% CI: 29.9-92.5) in predicting shunt responsiveness. Changes in the iNPH score, TUG test score, percentage change in TUG score, Boon’s gait score, and percentage change in Boon’s gait score were not valid predictors since the confidence intervals of the AUROCs crossed 0.5. Conclusion CSF-TT parameters show limited accuracy in predicting shunt responsiveness in patients with iNPH. Our results suggest that about one-third of positive tap tests were false positives, and the test’s sensitivity was only slightly better than random chance in predicting post-operative shunt outcomes.
Source: BMC Neurology
Authors: Sagar Poudel, Deepa Dash, Alfonso Fasano, Aparna Wagle Shukla, Ajay Garg, Ashish Datt Upadhyay, Naveet Wig, Roopa Rajan, Animesh Das, Divya M Radhakrishnan, Manjari Tripathi, Achal K. Srivastava, SS Kale, P Sarat Chandra, Ashish Suri, Pramod K Pal, Hrishikesh Kumar, Sakoon Saggu, Deepti Vibha, Rajesh Kumar Singh, Jasmine Parihar, Ranveer Singh Jadon, Ved Prakash Meena, Bindu Prakash, Arunmozhimaran Elavarasi
Language: English
Subfield: Cellular and Molecular Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $3,090
OpenAlex ID: W4413850989