Brain Tumor Clinical Trial
— SmartSurgeryOfficial title:
Linking Day-to-day Digital Behaviour Captured on the Smartphone With Brain Function in Patients Undergoing Brain Surgery - the "Smart Surgery" Study
This study will thus examine daily behaviour based on smartphone use and link it to the
neurological and neuropsychological status as well as to neuroradiological studies that are
part of the clinical routine. The study will examine behaviour changes before and after
surgery, and how this change in measured behaviour with the smartphone relates to today's
"gold standard", namely professional neuropsychological examination and quantification of
brain damage on imaging studies (MRI).
This study is a proof-of-principle study that intends to build the basis for larger future
observational studies on patients with focal or diffuse brain pathologies.
Status | Recruiting |
Enrollment | 100 |
Est. completion date | December 2020 |
Est. primary completion date | April 2020 |
Accepts healthy volunteers | No |
Gender | All |
Age group | 18 Years and older |
Eligibility |
Inclusion Criteria: - Consent of the patient - Age: =18 - Fluent language skills in German - Patient is scheduled for either maximum safe resection of a brain tumour/AVM via craniotomy or VP-shunting for hydrocephalus - Patient is capable to use a smartphone (based on the Google Android system) and uses a smartphone since at least 3 months - Preoperative smartphone-assessed day-to-day behaviour can be recorded for at least 1 week (7 days) Exclusion Criteria: - Presence of known neurologic or psychiatric disease other than brain tumour/AVM or hydrocephalus that can potentially influence the performance of a patient while using the smartphone (e.g. dementia, multiple sclerosis, bipolar disorder) - Foreseeable difficulties in follow-up due to geographic reasons (e.g. patients living abroad) - Patients enrolled in a different clinical trial according to KlinV (participation in another research project according to HFV is allowed, if this is not a burden to the patient) |
Country | Name | City | State |
---|---|---|---|
Switzerland | University Hospital Zurich | Zurich |
Lead Sponsor | Collaborator |
---|---|
University of Zurich |
Switzerland,
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Other | General remarks | For each individual patient, the secondary endpoints before and after surgery will be compared (in-subject differences) and related to the patterns of smartphone-assessed day-to-day behaviour. In general, patients with brain tumours and patients with hydrocephalus are analysed separately. As this study is a proof-of-concept study, no formal sample size calculation is performed. |
One week before surgery until the follow-up three months after surgery | |
Primary | Change in pattern of smartphone-assessed day-to-day behaviour | For the primary endpoint, the patterns of smartphone-assessed day-to-day behaviour in the time period before the operation (day -7 until day 0) will be graphically illustrated and compared for obvious differences to the behaviour in the first postoperative week (+7 days) and in the week before the postoperative consultation at three months after the operation. Towards this we shall employ exhaustive statistical and numerical methods that are typical of complex systems research. This includes comparing the patterns in defined parameter space, clustering of patterns dependent on the diseased state and defining new parameter spaces where the data conforms to the working hypothesis. | One week before surgery until the follow-up three months after surgery | |
Secondary | KPS | For the secondary endpoints, several scores have to be correlated to the complex data generated. Towards this we shall deploy large-scale multivariate approaches that span various time scales - from ms to hours, and that are conducted using sweeping windows across the entire period recording. By using statistical clustering methods, we shall correct for multiple comparison when inferring our data. | One week before surgery until the follow-up three months after surgery | |
Secondary | NIHSS | For the secondary endpoints, several scores have to be correlated to the complex data generated. Towards this we shall deploy large-scale multivariate approaches that span various time scales - from ms to hours, and that are conducted using sweeping windows across the entire period recording. By using statistical clustering methods, we shall correct for multiple comparison when inferring our data. | One week before surgery until the follow-up three months after surgery | |
Secondary | MoCA score | For the secondary endpoints, several scores have to be correlated to the complex data generated. Towards this we shall deploy large-scale multivariate approaches that span various time scales - from ms to hours, and that are conducted using sweeping windows across the entire period recording. By using statistical clustering methods, we shall correct for multiple comparison when inferring our data. | One week before surgery until the follow-up three months after surgery | |
Secondary | Domain-specific z-scores of neuropsychological functioning, age-, sex- and education-adjusted | For the secondary endpoints, several scores have to be correlated to the complex data generated. Towards this we shall deploy large-scale multivariate approaches that span various time scales - from ms to hours, and that are conducted using sweeping windows across the entire period recording. By using statistical clustering methods, we shall correct for multiple comparison when inferring our data. | One week before surgery until the follow-up three months after surgery | |
Secondary | For patients with a brain tumour, location of the lesion, as determined on MRI imaging | For the secondary endpoints, several scores have to be correlated to the complex data generated. Towards this we shall deploy large-scale multivariate approaches that span various time scales - from ms to hours, and that are conducted using sweeping windows across the entire period recording. By using statistical clustering methods, we shall correct for multiple comparison when inferring our data. | One week before surgery until the follow-up three months after surgery | |
Secondary | For patients with a brain tumour, the size of the lesion | For the secondary endpoints, several scores have to be correlated to the complex data generated. Towards this we shall deploy large-scale multivariate approaches that span various time scales - from ms to hours, and that are conducted using sweeping windows across the entire period recording. By using statistical clustering methods, we shall correct for multiple comparison when inferring our data. | One week before surgery until the follow-up three months after surgery | |
Secondary | For patients with a brain tumour, the degree of affected brain tissue as seen on early (within 5 days) or late postoperative MRI (3 months) | For the secondary endpoints, several scores have to be correlated to the complex data generated. Towards this we shall deploy large-scale multivariate approaches that span various time scales - from ms to hours, and that are conducted using sweeping windows across the entire period recording. By using statistical clustering methods, we shall correct for multiple comparison when inferring our data. | One week before surgery until the follow-up three months after surgery | |
Secondary | For patients with hydrocephalus, ventricular enlargement, as determined on MRI imaging, according to the Evans index (=A/E); Third ventricle index (= C/E); Cella media index (=D/F); Ventricular score (=(A+B+C+D)/E x 100) | For the secondary endpoints, several scores have to be correlated to the complex data generated. Towards this we shall deploy large-scale multivariate approaches that span various time scales - from ms to hours, and that are conducted using sweeping windows across the entire period recording. By using statistical clustering methods, we shall correct for multiple comparison when inferring our data. | One week before surgery until the follow-up three months after surgery |
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