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Can Cerebrospinal Fluid Pressure Detect Catheter Complications in Patients Who Experience Loss of Effectiveness With Intrathecal Baclofen Therapy?

2016; Elsevier BV; Volume: 20; Issue: 2 Linguagem: Inglês

10.1111/ner.12471

1525-1403

Michael Saulino, Michael S. Turner, Keith Miesel, Felicia R. Cochran, Katherine Stromberg, Elizabeth Fehrmann, M. Louise Markert, Robert J. Spencer,

Cerebral Palsy and Movement Disorders

Objective The catheter status of patients who presented with loss of intrathecal baclofen (ITB) therapy effectiveness was investigated using measurements of cerebrospinal fluid (CSF) pressure transmitted through the catheter fluid path to the pump. The aim of the study was to estimate the appropriate threshold separating catheter complications from “normal” catheter function, and to compare catheter status based on CSF pressure with the clinical diagnosis. Methods This was a prospective, masked nonsignificant risk, research study. Patients (N = 47) received ITB for the treatment of severe spasticity and presented with symptoms of catheter malfunction. CSF pressure data were recorded using an external sensor connected to a needle inserted into the catheter access port. An algorithm calculated the energy of the variations in CSF pressure caused by respiration and heartbeat within the intrathecal space. These data were evaluated against a threshold that separated normal from abnormal catheter function. Catheter status based on the algorithm was compared with the clinical diagnosis. Results Complete data were available for 37 patients. Mean CSF pressure energy was significantly higher (p = 0.025; student t-test) for patients diagnosed with normal catheter function vs. catheters with complications. The CSF pressure algorithm matched the clinical diagnosis in 16 of 18 patients with catheter complications (sensitivity = 89%), and 13 of 19 patients with normal catheter function (specificity = 68%). Conclusion In-clinic CSF pressure data acquisition is technically feasible. Overall, catheter status based on the algorithm demonstrated concordance with the clinical diagnosis in 29 of 37 patients (78.4%).