Risk Factors for Postoperative Delirium Severity After Deep Brain Stimulation Surgery in Parkinson's Disease.

Background: Postoperative delirium (POD) is a serious complication following deep brain stimulation (DBS) but only received little attention. Its main risk factors are higher age and preoperative cognitive deficits. These are also main risk factors for long-term cognitive decline after DBS in Parkinson's disease (PD). Objective: To identify risk factors for POD severity after DBS surgery in PD. Methods: 57 patients underwent DBS (21 female; age 60.2±8.2; disease duration 10.5±5.9 years). Preoperatively, general, PD- and surgery-specific predictors were recorded. Montreal Cognitive Assessment and the neuropsychological test battery CANTAB ConnectTM were used to test domain-specific cognition. Volumes of the cholinergic basal forebrain were calculated with voxel-based morphometry. POD severity was recorded with the delirium scales Confusion Assessment Method for Intensive Care Unit (CAM-ICU) and Nursing Delirium Scale (NU-DESC). Spearman correlations were calculated for univariate analysis of predictors and POD severity and linear regression with elastic net regularization and leave-one-out cross-validation was performed to fit a multivariable model. Results: 21 patients (36.8%) showed mainly mild courses of POD following DBS. Correlation between predicted and true POD severity was significant (spearman rho = 0.365, p = 0.001). Influential predictors were age (p < 0.001), deficits in attention and motor speed (p = 0.002), visual learning (p = 0.036) as well as working memory (p < 0.001), Nucleus basalis of Meynert volumes (p = 0.003) and burst suppression (p = 0.005). Conclusions: General but also PD- and surgery-specific factors were predictive of POD severity. These findings underline the multifaceted etiology of POD after DBS in PD. Valid predictive models must therefore consider general, PD- and surgery-specific factors.

The Role of Levodopa Challenge in Predicting the Outcome of Subthalamic Deep Brain Stimulation.

Background: Deep brain stimulation of the subthalamic nucleus (STN-DBS) is an effective and evidence-based treatment for idiopathic Parkinson's disease (iPD). A minority of patients does not sufficiently benefit from STN-DBS. Objective: The predictive validity of the levodopa challenge for individual patients is analyzed. Methods: Data from patients assessed with a preoperative Levodopa-test and a follow-up examination (mean ± standard deviation: 9.15 months ±3.39) from Kiel (n = 253), Berlin (n = 78) and Toronto (n = 98) were studied. Insufficient DBS outcome was defined as an overall UPDRS-III reduction <33% compared to UPDRS-III in med-off at baseline or alternatively if the minimal clinically important improvement of 5 points was not reached. Single UPDRS-items and sub-scores were dichotomized. Following exploratory analysis, we trained supervised regression- and classification models for outcome prediction. Results: Data analysis confirmed significant correlation between the absolute UPDRS-III reduction during Levodopa challenge and after stimulation. But individual improvement was inaccurately predicted with a large range of up to 30 UPDRS III points. Further analysis identified preoperative UPDRS-III/med-off-scores and preoperative Levodopa-improvement as most influential factors. The models for UPDRS-III and sub-scores improvement achieved comparably low accuracy. Conclusions: With large prediction intervals, the Levodopa challenge use for patient counseling is limited, though remains important for excluding non-responders to Levodopa. Despite these deficiencies, the current practice of patient selection is highly successful and builds not only on the Levodopa challenge. However, more specific motor tasks and further paraclinical tools for prediction need to be developed.

Optimization of sensitivity and specificity of a biomarker-based blood test (LVOCheck-Opti): A protocol for a multicenter prospective observational study of patients suspected of having a stroke.

Introduction: Acute ischemic stroke (AIS) is a time-critical medical emergency. For patients with large-vessel occlusions (LVO), mechanical thrombectomy (MT) is the gold-standard treatment. Mobile Stroke Units (MSUs) provide on-site diagnostic capabilities via computed tomography (CT) and have been shown to improve functional outcomes in stroke patients, but are cost-efficient only in urban areas. Blood biomarkers have recently emerged as possible alternative to cerebral imaging for LVO diagnosis. Prehospital LVO diagnosis offers the potential to transport patients directly to centers that have MT treatment available. In this study, we assess the accuracy of combining two biomarkers, HFABP and NT-proBNP, with clinical indicators to detect LVO using ultra-early prehospital blood samples. The study was registered in the German Clinical Trials Register (DRKS-ID: DRKS00030399). Methods and analysis: We plan a multicenter prospective observational study with 800 patients with suspected stroke enrolled within 24 h of symptom onset. Study participants will be recruited at three sites (MSUs) in Berlin, Germany. Blood-samples will be taken pre-hospitally at the scene and tested for HFABP and NT-proBNP levels. Additional clinical data and information on final diagnosis will be collected and documented in an electronic case report form (eCRF). Sensitivity and specificity of the combination will be calculated through iterative permutation-response calculations. Discussion: This study aims to evaluate the diagnostic capabilities of a combination of the biomarkers HFABP and NT-proBNP in LVO prediction. In contrast to most other biomarker studies to date, by employing MSUs as study centers, ultra-early levels of biomarkers can be analyzed. Point-of-care LVO detection in suspected stroke could lead to faster treatment in both urban and rural settings and thus improve functional outcomes on a broader scale. Clinical trial registration: Deutsches Register klinischer Studien https://drks.de/search/de/trial/DRKS00030399, DRKS00030399.