13 research outputs found
A Reinforcement Learning Based Control Approach for Propofol-Induced Burst Suppression
High-dose propofol is being investigated for its potential antidepressant effect. Propofol is titrated to induce burst suppression, a specific EEG pattern. However, propofol is difficult to dose due to uncertainty in each patient’s pharmacokinetics (PK) and pharmacodynamics (PD), and the lack of a commercially available monitor of propofol concentration. Clinicians currently infer the proper drug dose after observing the EEG response to the given dose. In this report we share our development of an automated controller to optimally administer propofol-induced burst suppression. We designed a deep deterministic policy gradient (DDPG) algorithm, which includes two deep neural networks and relates a 2-dimensional action space with a 3-dimensional state space. Our DDPG prototype did not satisfy our minimum training criteria. However, we share our diagnosis of current limitations in training a DDPG-based RL agent to administer propofol to PK-PD-simulated in silico patients. We also discuss potential solutions to improve RL agent training and performance
Model-Based Propofol Dosing to Improve Control of Patient EEG Dynamics
Propofol is a common anesthetic, which is being investigated as an antidepressant alternative to electroconvulsive therapy (ECT). Propofol can induce similar EEG effects to that of ECT, and has also demonstrated similar improvements in depression scores. However, propofol dosing is challenging because patients differ in their required drug doses. A model of the relationship between administered propofol and monitored EEG can be used to improve the accuracy and reliability of this treatment. Our objective is ultimately to automate processes in propofol’s dose determination. A summary of patient-system modeling in anesthesia will be discussed, along with preliminary results from recent open-label trials
Genetics and Gene Expression Involving Stress and Distress Pathways in Fibromyalgia with and without Comorbid Chronic Fatigue Syndrome
In complex multisymptom disorders like fibromyalgia syndrome (FMS) and chronic fatigue syndrome (CFS) that are defined primarily by subjective symptoms, genetic and gene expression profiles can provide very useful objective information. This paper summarizes research on genes that may be linked to increased susceptibility in developing and maintaining these disorders, and research on resting and stressor-evoked changes in leukocyte gene expression, highlighting physiological pathways linked to stress and distress. These include the adrenergic nervous system, the hypothalamic-pituitary-adrenal axis and serotonergic pathways, and exercise responsive metabolite-detecting ion channels. The findings to date provide some support for both inherited susceptibility and/or physiological dysregulation in all three systems, particularly for catechol-O-methyl transferase (COMT) genes, the glucocorticoid and the related mineralocorticoid receptors (NR3C1, NR3C2), and the purinergic 2X4 (P2X4) ion channel involved as a sensory receptor for muscle pain and fatigue and also in upregulation of spinal microglia in chronic pain models. Methodological concerns for future research, including potential influences of comorbid clinical depression and antidepressants and other medications, on gene expression are also addressed
Dysregulation of leukocyte gene expression in women with medication-refractory depression versus healthy non-depressed controls
Correction: Antidepressant and Neurocognitive Effects of Isoflurane Anesthesia versus Electroconvulsive Therapy in Refractory Depression.
[This corrects the article DOI: 10.1371/journal.pone.0069809.]
Antidepressant and neurocognitive effects of isoflurane anesthesia versus electroconvulsive therapy in refractory depression.
BACKGROUND:Many patients have serious depression that is nonresponsive to medications, but refuse electroconvulsive therapy (ECT). Early research suggested that isoflurane anesthesia may be an effective alternative to ECT. Subsequent studies altered drug, dose or number of treatments, and failed to replicate this success, halting research on isoflurane's antidepressant effects for a decade. Our aim was to re-examine whether isoflurane has antidepressant effects comparable to ECT, with less adverse effects on cognition. METHOD:Patients with medication-refractory depression received an average of 10 treatments of bifrontal ECT (n = 20) or isoflurane (n = 8) over 3 weeks. Depression severity (Hamilton Rating Scale for Depression-24) and neurocognitive responses (anterograde and retrograde memory, processing speed and verbal fluency) were assessed at Pretreatment, Post all treatments and 4-week Follow-up. RESULTS:Both treatments produced significant reductions in depression scores at Post-treatment and 4-week Follow-up; however, ECT had modestly better antidepressant effect at follow-up in severity-matched patients. Immediately Post-treatment, ECT (but not isoflurane) patients showed declines in memory, fluency, and processing speed. At Follow-up, only autobiographical memory remained below Pretreatment level for ECT patients, but isoflurane patients had greater test-retest neurocognitive score improvement. CONCLUSIONS:Our data reconfirm that isoflurane has an antidepressant effect approaching ECT with less adverse neurocognitive effects, and reinforce the need for a larger clinical trial
Group Demographics, Intellectual Level, Depression Severity, and Pretreatment Medications.
*<p><i>ECT-All vs. ISO, p<0.05; ECT-Matched vs. ISO nonsignificant.</i></p>**<p><i>ECT-Matched vs. ISO, p<0.05; ECT-All vs. ISO non-significant.</i></p>a<p><i>Group differences non-significant.</i></p>b<p><i>Responders are defined as at least 50% reduction in HRSD score.</i></p>c<p><i>Anticonvulsant medications were stopped during treatment sessions in all groups.</i></p
Neurocognitive Means (SEM) at Pretreatment, Post-Treatment and Follow-up, Adjusted for Intellectual Level and Age.
<p><i>All p-values are for mean comparisons versus ISO after adjustment for group differences in age and WTAR score. Post-treatment and Follow-up p-values are also adjusted for group differences in Pretreatment and thus test group differences in performance decline or improvement from Pretreatment levels.</i></p><p><i>Cohen's d effect sizes for significant comparisons were consistently large and ranged from 1.1 to 1.7.</i></p