Kimmo Uutela

Comparison of the Surgical Pleth Index™ with haemodynamic variables to assess nociception–anti-nociception balance during general anaesthesia

BACKGROUND The Surgical Pleth Index (SPI) is proposed as a means to assess the balance between noxious stimulation and the anti-nociceptive effects of anaesthesia. In this study, we compared SPI, mean arterial pressure (MAP), and heart rate (HR) as a means of assessing this balance. METHODS We studied a standard stimulus [head-holder insertion (HHI)] and varying remifentanil concentrations (CeREMI) in a group of patients undergoing neurosurgery. Patients receiving target-controlled infusions were randomly assigned to one of the three CeREMI (2, 4, or 6 ng m⁻¹), whereas propofol target was fixed at 3 µg ml⁻¹. Steady state for both targets was achieved before HHI. Intravascular volume status (IVS) was evaluated using respiratory variations in arterial pressure. Prediction probability (Pk) and ordinal regression were used to assess SPI, MAP, and HR performance at indicating CeREMI, and the influence of IVS and chronic treatment for high arterial pressure, as possible confounding factors. RESULTS The maximum SPI, MAP, or HR observed after HHI correctly indicated CeREMI in one of the two patients [accurate prediction rate (APR)=0.5]. When IVS and chronic treatment for high arterial pressure were taken into account, the APR was 0.6 for each individual variable and 0.8 when all of them predicted the same CeREMI. That increase in APR paralleled an increase in Pk from 0.63 to 0.89. CONCLUSIONS SPI, HR, and MAP are of comparable value at gauging noxious stimulation-CeREMI balance. Their interpretation is improved by taking account of IVS, treatment for chronic high arterial pressure, and concordance between their predictions.

Effect of a fluid challenge on the Surgical Pleth Index during stable propofol-remifentanil anaesthesia.

The Surgical Pleth Index (SPI), derived from pulse amplitude and heartbeat interval, is proposed to monitor anti‐nociception during anaesthesia. Its response to noxious stimulation can be affected by the intravascular volume status. This study investigated the effect of a fluid challenge (FC) on SPI during steady‐state conditions.

Algorithm for Quantifying Frontal EMG Responsiveness for Sedation Monitoring.

INTRODUCTION To study stimulation-related facial electromyographic (FEMG) activity in intensive care unit (ICU) patients, develop an algorithm for quantifying the FEMG activity, and to optimize the algorithm for monitoring the sedation state of ICU patients. METHODS First, the characteristics of FEMG response patterns related to vocal stimulation of 17 ICU patients were studied. Second, we collected continuous FEMG data from 30 ICU patients. Based on these data, we developed the Responsiveness Index (RI) algorithm that quantifies FEMG responses. Third, we compared the RI values with clinical sedation level assessments and adjusted algorithm parameters for best performance. RESULTS In patients who produced a clinically observed response to the vocal stimulus, the poststimulus FEMG power was 0.33 µV higher than the prestimulus power. In nonresponding patients, there was no difference. The sensitivity and specificity of the developed RI for detecting deep sedation in the subgroup with low probability of encephalopathy were 0.90 and 0.79, respectively. CONCLUSION Consistent FEMG patterns were found related to standard stimulation of ICU patients. A simple and robust algorithm was developed and good correlation with clinical sedation scores achieved in the development data.

A randomized controlled proof-of-concept trial of early sedation management using Responsiveness Index monitoring in mechanically ventilated critically ill patients.

IntroductionDeep sedation is associated with adverse patient outcomes. We recently described a novel sedation-monitoring technology, the Responsiveness Index (RI), which quantifies patient arousal using processed frontal facial EMG data. We explored the potential effectiveness and safety of continuous RI monitoring during early intensive care unit (ICU) care as a nurse decision-support tool.MethodsIn a parallel-group controlled single centre proof of concept trial, patients requiring mechanical ventilation and sedation were randomized via sequential sealed envelopes following ICU admission. Control group patients received hourly clinical sedation assessment and daily sedation holds; the RI monitor was connected but data were concealed from clinical staff. The intervention group received control group care, but RI monitoring was visible and nurses were asked to adjust sedation to maintain patients with an RI>20 whenever possible. Traffic-light colour coding (RI<20, Red; 20–40, Amber; >40, Green) simplified decision-making. The intervention lasted up to 48 hours. Sixteen nurses were interviewed to explore their views of the novel technology.ResultsWe analysed 74 patients treated per protocol (36 intervention; 38 control). The proportion of patients with RI<20 was identical at the start of monitoring (54 % both groups). Overall, the proportion of time with RI<20 trended to lower values for the intervention group (median 16 % (1–3rd quartile 8–30 %) versus 33 % (10–54 %); P = 0.08); sedation and analgesic use was similar. A post hoc analysis restricted to patients with RI<20 when monitoring started, found intervention patients spent less time with low RI value (16 % (11–45 %) versus 51 % (33–72 %); P = 0.02), cumulative propofol use trended to lower values (median 1090 mg versus 2390 mg; P = 0.14), and cumulative alfentanil use was lower (21.2 mg versus 32.3 mg; P = 0.01). RASS scores were similar for both groups. Sedation related adverse event rates were similar (7/36 versus 5/38). Similar proportions of patients had sedation holds (83 % versus 87 %) and were extubated (47 % versus 44 %) during the intervention period. Nurses valued the objective visible data trends and simple colour prompts, and found RI monitoring a useful adjunct to existing practice.ConclusionsRI monitoring was safe and acceptable. Data suggested potential to modify sedation decision-making. Larger trials are justified to explore effects on patient-centred outcomes.Trial registrationNCT01361230 (registered April 19, 2010)

An evaluation of the validity and potential utility of facial electromyelogram Responsiveness Index for sedation monitoring in critically ill patients.

PURPOSE The purpose of this study is to explore the validity of a novel sedation monitoring technology based on facial electromyelography (EMG) in sedated critically ill patients. MATERIALS AND METHODS The Responsiveness Index (RI) integrates the preceding 60 minutes of facial EMG data. An existing data set was used to derive traffic light cut-offs for low (red), intermediate (amber), and higher (green) states of patient arousal. The validity of these was prospectively evaluated in 30 sedated critically ill patients against hourly Richmond Agitation Sedation Scale (RASS) assessments with concealment of RI data from clinical staff. RESULTS With derivation data, an RI less than or equal to 35 had best discrimination for a Ramsay score of 5/6 (sensitivity, 90%; specificity, 79%). For traffic lights, we chose RI less than or equal to 20 as red, 20 to 40 as amber, and more than 40 as green. In the prospective study, RI values were red/amber for 76% of RASS -5/-4 assessments, but RI varied dynamically over time in many patients, and discordance with RASS may have resulted from the use of 1 hour of data for RI calculations. We also noted that red/amber values resulted from sleep, encephalopathy, and low levels of stimulation. CONCLUSIONS Responsiveness Index is not directly comparable with clinical sedation scores but is a potential continuous alert to possible deep sedation in critically ill patients.