Efficacy of Electrical Stimulation for Spinal Fusion: A Systematic Review and Meta-Analysis of Randomized Controlled Trials.

Spinal fusion is one of the most common procedures performed in spine surgery. As rates of spinal fusion continue to increase, rates of complications such as nonunions continue to increase as well. Current evidence supporting the use of electrical stimulation to promote fusion is inconclusive. This review aimed to determine if postoperative electrical stimulation is more efficacious than no stimulation or placebo in promoting radiographic fusion in patients undergoing spinal fusion. We searched the Cochrane Central Register of Controlled Trials (CENTRAL), EMBASE, CINAHL and MEDLINE from date of inception to current. Ongoing clinical trials were also identified and reference lists of included studies were manually searched for relevant articles. Two reviewers independently screened studies, extracted data, and assessed risk of bias. Data were pooled using the Mantel-Haenszel method. Trialists were contacted for any missing or incomplete data. Of 1184 articles screened, 7 studies were eligible for final inclusion (n = 941). A total of 487 patients received postoperative electrical stimulation and 454 patients received control or sham stimulation. All evidence was of moderate quality. Electrical stimulation (pulsed electromagnetic fields, direct current, and capacitive coupling) increased the odds of a successful fusion by 2.5-fold relative to control (OR = 2.53, 95% CI 1.86 to 3.43, p < 0.00001). A test for subgroup interaction by stimulation type, smoking status, and number of levels fused was not significant (p = 0.93, p = 0.82 and p = 0.65, respectively). This systematic review and meta-analysis found moderate-quality evidence supporting the use of postoperative electrical stimulation as an adjunct to spinal fusion surgery. Patients treated with electrical stimulation have significantly greater rates of successful fusion. The level of evidence for this study is therapeutic level I.

Efficacy of Electrical Stimulators for Bone Healing: A Meta-Analysis of Randomized Sham-Controlled Trials.

Electrical stimulation is a common adjunct used to promote bone healing; its efficacy, however, remains uncertain. We conducted a meta-analysis of randomized sham-controlled trials to establish the efficacy of electrical stimulation for bone healing. We identified all trials randomizing patients to electrical or sham stimulation for bone healing. Outcomes were pain relief, functional improvement, and radiographic nonunion. Two reviewers assessed eligibility and risk of bias, performed data extraction, and rated the quality of the evidence. Fifteen trials met our inclusion criteria. Moderate quality evidence from 4 trials found that stimulation produced a significant improvement in pain (mean difference (MD) on 100-millimeter visual analogue scale = -7.7 mm; 95% CI -13.92 to -1.43; p = 0.02). Two trials found no difference in functional outcome (MD = -0.88; 95% CI -6.63 to 4.87; p = 0.76). Moderate quality evidence from 15 trials found that stimulation reduced radiographic nonunion rates by 35% (95% CI 19% to 47%; number needed to treat = 7; p < 0.01). Patients treated with electrical stimulation as an adjunct for bone healing have less pain and are at reduced risk for radiographic nonunion; functional outcome data are limited and requires increased focus in future trials.

Towards a hemodynamic BCI using transcranial Doppler without user-specific training data.

UNLABELLED: Transcranial Doppler (TCD) was recently introduced as a new brain-computer interface (BCI) modality for detecting task-induced hemispheric lateralization. To date, single-trial discrimination between a lateralized mental activity and a rest state has been demonstrated with long (45 s) activation time periods. However, the possibility of detecting successive activations in a user-independent framework (i.e. without training data from the user) remains an open question. OBJECTIVE: The objective of this research was to assess TCD-based detection of lateralized mental activity with a user-independent classifier. In so doing, we also investigated the accuracy of detecting successive lateralizations. Approach. TCD data from 18 participants were collected during verbal fluency, mental rotation tasks and baseline counting tasks. Linear discriminant analysis and a set of four time-domain features were used to classify successive left and right brain activations. MAIN RESULTS: In a user-independent framework, accuracies up to 74.6 ± 12.6% were achieved using training data from a single participant, and lateralization task durations of 18 s. SIGNIFICANCE: Subject-independent, algorithmic classification of TCD signals corresponding to successive brain lateralization may be a feasible paradigm for TCD-BCI design.

Clinical decision analysis: Incorporating the evidence with patient preferences.

Decision analysis has become an increasingly popular decision-making tool with a multitude of clinical applications. Incorporating patient and expert preferences with available literature, it allows users to apply evidence-based medicine to make informed decisions when confronted with difficult clinical scenarios. A decision tree depicts potential alternatives and outcomes involved with a given decision. Probabilities and utilities are used to quantify the various options and help determine the best course of action. Sensitivity analysis allows users to explore the uncertainty of data on expected clinical outcomes. The decision maker can thereafter establish a preferred method of treatment and explore variables which influence the final clinical outcome. The present paper reviews the technique of decision analysis with particular focus on its application to clinical decision making.