Board Certification: Vascular Neurology, American Board of Psychiatry and Neurology (2018)
Board Certification: Neurocritical Care, United Council for Neurologic Subspecialties (2017)
Fellowship:Stanford University Vascular Neurology Fellowship (2017) CA
Fellowship:Stanford University Neurocritical Care and Stroke Fellowship (2017) CA
Board Certification: Neurology, American Board of Psychiatry and Neurology (2015)
Residency:University of Kentucky GME Office Verifications (2015) KY
Medical Education:PSG Institute of Medical Sciences and Research (2007) India
Rapid Bedside Evaluation of Seizures in the ICU by Listening to the Sound of Brainwaves: A Prospective Observational Clinical Trial of Ceribell's Brain Stethoscope Function.
BACKGROUND: Patients suffering from non-convulsive seizures experience delays in diagnosis and treatment due to limitations in acquiring and interpreting electroencephalography (EEG) data. The Ceribell EEG System offers rapid EEG acquisition and conversion of EEG signals to sound (sonification) using a proprietary algorithm. This study was designed to test the performance of this EEG system in an intensive care unit (ICU) setting and measure its impact on clinician treatment decision.METHODS: Encephalopathic ICU patients at Stanford University Hospital were enrolled if clinical suspicion for seizures warranted EEG monitoring. Treating physicians rated suspicion for seizure and decided if the patient needed antiepileptic drug (AED) treatment at the time of bedside evaluation. After listening to 30s of EEG from each hemisphere in each patient, they reevaluated their suspicion for seizure and decision for additional treatment. The EEG waveforms recorded with Ceribell EEG were subsequently analyzed by three blinded epileptologists to assess the presence or absence of seizures within and outside the sonification window. Study outcomes were EEG set up time, ease of use of the device, change in clinician seizure suspicion, and change in decision to treat with AED before and after sonification.RESULTS: Thirty-five cases of EEG sonification were performed. Mean EEG setup time was 6±3min, and time to obtain sonified EEG was significantly faster than conventional EEG (p<0.001). One patient had non-convulsive seizure during sonification and another had rhythmic activity that was followed by seizure shortly after sonification. Change in treatment decision after sonification occurred in approximately 40% of patients and resulted in a significant net reduction in unnecessary additional treatments (p=0.01). Ceribell EEG System was consistently rated easy to use.CONCLUSION: The Ceribell EEG System enabled rapid acquisition of EEG in patients at risk for non-convulsive seizures and aided clinicians in their evaluation of encephalopathic ICU patients. The ease of use and speed of EEG acquisition and interpretation by EEG-untrained individuals has the potential to improve emergent clinical decision making by quickly detecting non-convulsive seizures in the ICU.
View details for PubMedID 29923167
Quantitative EEG Metrics Differ Between Outcome Groups and Change Over the First 72 h in Comatose Cardiac Arrest Patients
2018; 28 (1): 51–59
Forty to sixty-six percent of patients resuscitated from cardiac arrest remain comatose, and historic outcome predictors are unreliable. Quantitative spectral analysis of continuous electroencephalography (cEEG) may differ between patients with good and poor outcomes.Consecutive patients with post-cardiac arrest hypoxic-ischemic coma undergoing cEEG were enrolled. Spectral analysis was conducted on artifact-free contiguous 5-min cEEG epochs from each hour. Whole band (1-30 Hz), delta (δ, 1-4 Hz), theta (θ, 4-8 Hz), alpha (α, 8-13 Hz), beta (β, 13-30 Hz), α/δ power ratio, percent suppression, and variability were calculated and correlated with outcome. Graphical patterns of quantitative EEG (qEEG) were described and categorized as correlating with outcome. Clinical outcome was dichotomized, with good neurologic outcome being consciousness recovery.Ten subjects with a mean age = 50 yrs (range = 18-65) were analyzed. There were significant differences in total power (3.50 [3.30-4.06] vs. 0.68 [0.52-1.02], p = 0.01), alpha power (1.39 [0.66-1.79] vs 0.27 [0.17-0.48], p < 0.05), delta power (2.78 [2.21-3.01] vs 0.55 [0.38-0.83], p = 0.01), percent suppression (0.66 [0.02-2.42] vs 73.4 [48.0-97.5], p = 0.01), and multiple measures of variability between good and poor outcome patients (all values median [IQR], good vs. poor). qEEG patterns with high or increasing power or large power variability were associated with good outcome (n = 6). Patterns with consistently low or decreasing power or minimal power variability were associated with poor outcome (n = 4).These preliminary results suggest qEEG metrics correlate with outcome. In some patients, qEEG patterns change over the first three days post-arrest.
View details for PubMedID 28646267
Innovation in Stroke Care Quality: NIH Stroke Scale Change and Shewhart Charts
QUALITY MANAGEMENT IN HEALTH CARE
2015; 24 (3): 135-139
Stroke care, admission through discharge, is a process that should lead to symptomatic improvement. Improvement or decline in conditions of patients with acute stroke during hospitalization can be measured by the National Institutes of Health Stroke Scale (NIH Stroke Scale or NIHSS) at both admission and discharge and may indicate the overall quality of acute stroke care for a patient and the stability of care in the system. Shewhart control charts were analyzed for 98 patients with stroke admissions in a random sample at a tertiary care stroke center to determine the feasibility of examining the NIHSS score change to detect statistical control or identify excess variance in outcomes. The study sample showed a mean improvement of 1.33 points from admission to discharge on the NIHSS. Three statistical outliers were found. Excess statistical variation clustered within a specific stroke team's tenure suggested a need for targeted education and examination for process redesign. Using the NIHSS and the Shewhart control charts identified a systematic process flaw that could be targeted to improve stroke outcomes and move the delivery system toward statistical control.
View details for DOI 10.1097/QMH.0000000000000064
View details for Web of Science ID 000357941400005
View details for PubMedID 26115061
Spinal Epidural Abscess
CURRENT INFECTIOUS DISEASE REPORTS
2014; 16 (11)
Spinal epidural abscess (SEA) remains a relatively infrequent diagnosis. Staphylococcus aureus is the most common organism identified, and the infectious source in SEA emanates from skin and soft tissue infections in about 20 % of instances. The thoracic spine is most often involved followed by the lumbar spine. The classic triad of fever, spinal pain, and neurological deficit is present in but a minority of patients. The appearance of neurological deficits with SEA has a significant impact on the prognosis; therefore, early diagnosis is imperative. Magnetic resonance imaging has permitted earlier diagnosis, although significant delays in diagnosis are common due to the nonspecific symptoms that frequently attend the disorder. Due to the rarity of this condition, there have been few randomized controlled trials to evaluate new treatment strategies, and most recommendations regarding treatment are based on case series studies often derived from the experiences at a single center.
View details for DOI 10.1007/s11908-014-0436-7
View details for Web of Science ID 000343958700004
View details for PubMedID 25230605
Community-acquired Methicillin-resistant Staphylococcus aureus Prostatic Abscesses
AMERICAN JOURNAL OF THE MEDICAL SCIENCES
2013; 346 (4): 341-344
We describe 2 men with prostatic abscesses due to community-acquired methicillin-resistant Staphylococcus aureus. Neither of them had diabetes mellitus, prior prostate disease, recent health care exposure or urinary instrumentation and had no evidence of bloodstream infection at the time of presentation. Both were treated with surgical drainage and prolonged antibiotics.
View details for DOI 10.1097/MAJ.0b013e318294f53a
View details for Web of Science ID 000326041000019
View details for PubMedID 23689049