EEG response of dexmedetomidine during drug induced sleep endoscopy.

Introduction: Dexmedetomidine is one of the anesthetics of choice for drug induced sleep endoscopy (DISE), with advantages including limited respiratory depression, analgesia, and decreased incidence of emergence delirium. However, challenges with determining sedation levels and prolonged recovery have limited its usage. An improved understanding of the effect of dexmedetomidine on the level of sedation and the corresponding electroencephalographic (EEG) changes could help overcome these barriers. Methods: Fifty-one patients received dexmedetomidine sedation with Richmond Agitation-Sedation Scale (RASS) score assessment and continuous EEG monitoring via SedLine for DISE. We constructed a pharmacokinetic model to determine continuous dexmedetomidine blood concentration. From the SedLine, we extracted the patient state index (PSI), and from the EEG we calculated the spectral edge frequency 95% (SEF95) and the correlation dimension (CD), a type of fractal dimension used to assess the complexity of a system. These metrics were subsequently compared against one another and with the dexmedetomidine concentration. Results: Our pharmacokinetic model yielded a two-compartment model with volumes of 51.8 L and 106.2 L, with clearances of 69.5 and 168.9 L/h, respectively, and a time to effect of 9 min, similar to prior studies. Based on this model, decreasing RASS score, SEF95, CD, and PSI were all significantly associated with increasing dexmedetomidine concentration (p < 0.001, p = 0.006, p < 0.001 respectively). The CD, SEF95, and PSI better captured the effects of increasing dexmedetomidine concentration as compared to the RASS score. Simulating dexmedetomidine concentration based on titration to target levels derived from CD and PSI confirmed commonly used dexmedetomidine infusion dosages. Conclusion: Dexmedetomidine use for DISE confirmed previous pharmacokinetic models seen with dexmedetomidine. Complex EEG metrics such as PSI and CD, as compared to RASS score and SEF95, better captured changes in brain state from dexmedetomidine and have potential to improve the monitoring of dexmedetomidine sedation.

Evaluation of patient state index, bispectral index, and entropy during drug induced sleep endoscopy with dexmedetomidine.

Multiple electroencephalographic (EEG) monitors and their associated EEG markers have been developed to aid in assessing the level of sedation in the operating room. While many studies have assessed the response of these markers to propofol sedation and anesthetic gases, few studies have compared these markers when using dexmedetomidine, an alpha-2 agonist. Fifty-one patients underwent drug induced sleep endoscopy with dexmedetomidine sedation. Continuous EEG was captured using SedLine (Masimo, Inc), and a playback system was used to extract the bispectral index (BIS) (Medtronic Inc), the patient state index (PSI) (Masimo, Inc), the state and response Entropy (GE Healthcare), and calculate the spectral edge frequency 95% (SEF95). Richmond Agitation-Sedation Scale (RASS) scores were assessed continually throughout the procedure and in recovery. We assessed the correlation between EEG markers and constructed ordinal logistic regression models to predict the RASS score and compare EEG markers. All three commercial EEG metrics were significantly associated with the RASS score (p < 0.001 for all metrics) whereas SEF95 alone was insufficient at characterizing dexmedetomidine sedation. PSI and Entropy achieved higher accuracy at predicing deeper levels of sedation as compared to BIS (PSI: 58.3%, Entropy: 58.3%, BIS: 44.4%). Lightening secondary to RASS score assessment is significantly captured by all three commercial EEG metrics (p < 0.001). Commercial EEG monitors can capture changes in the brain state associated with the RASS score during dexmedetomidine sedation. PSI and Entropy were highly correlated and may be better suited for assessing deeper levels of sedation.

Evaluation of the Stanford Anesthesiology Faculty Teaching Scholars Program Using the Context, Input, Process, and Product Framework.

Background: Faculty development programs are essential to the educational mission of academic medical centers as they promote skill development and career advancement and should be regularly evaluated to determine opportunities for improvement. The context, input, process, and product (CIPP) framework evaluates all phases of a program and focuses on improvement and outcomes. The aim of this study was to use the CIPP framework to evaluate the Stanford Anesthesiology Faculty Teaching Scholars Program. Methods: Using the CIPP framework, a survey was developed for alumni (2007 to 2018) of the program, followed by structured interviews, and each interview was deductively coded to identify themes. Results: Twenty-six of the 54 (48% response rate) participants in the program completed the survey, with 23 completing their projects and 17 of those projects still part of the anesthesiology training program. Seventeen survey responders went on to educational leadership roles. Twenty-five of the 26 survey responders would recommend this program to their colleagues. Fifteen structured interviews were conducted. Using the CIPP framework, themes were identified for context (reason for participation, previous experience in medical education, and resident education impact), input (benefits/negatives of the lecture series, availability of resources, and adequacy of nonclinical time), process (resident participation, mentorship, and barriers to implementation), and product (project completion, education sustainability, positive/negative outcomes of the program, and suggestions for improvement). Conclusions: The CIPP framework was successfully used to evaluate the Teaching Scholars Program. Areas of improvement were identified, including changing the program for input (add education lectures customized to faculty interests) and process (formally designate an experienced mentor to faculty).

The significance of widely split P waves: a case report.

BACKGROUND: P wave morphology on electrocardiogram is often overlooked but indicates abnormal cardiac conduction from various etiologies. Split P waves on electrocardiogram have been reported previously but not in a perioperative setting. CASE PRESENTATION: A 69-year-old Caucasian male patient with widely split P waves on his preoperative electrocardiogram was scheduled for a reimplantation right total hip replacement under a combined spinal-general anesthetic technique. The patient was evaluated prior to surgery by a cardiologist and the preoperative anesthesia clinic without any comment on the abnormal P wave morphology on electrocardiogram. The patient was cleared to proceed with anesthesia and surgery. Following induction of general anesthesia, his cardiac rhythm changed to a Mobitz type II pattern. The surgical procedure was cancelled, and a permanent cardiac pacemaker was inserted. CONCLUSIONS: Anesthesiologists should be aware that the presence of widely split P waves on electrocardiogram indicates the presence of atrial conduction abnormalities, likely from an ischemic or infiltrative process that can lead to more serious cardiac arrhythmias. P wave morphology should be observed and noted during the perioperative period for all patients.