Novel insights on association and reactivity of Bispectral Index, frontal electromyogram, and autonomic responses in nociception-sedation monitoring of critical care patients.

BACKGROUND: Assessing nociception and sedation in mechanically ventilated patients in the ICU is challenging, with few reliable methods available for continuous monitoring. Measurable cardiovascular and neurophysiological signals, such as frontal EEG, frontal EMG, heart rate, and blood pressure, have potential in sedation and nociception monitoring. The hypothesis of this explorative study is that derived variables from the aforementioned signals predict the level of sedation, as described by the Richmond Agitation-Sedation score (RASS), and respond to painful stimuli during critical care. METHODS: Thirty adult postoperative ICU patients on mechanical ventilation and receiving intravenous sedation, excluding patients with primary neurological disorders, head injury, or need for continuous neuromuscular blockage. Bispectral Index (BIS), EMG power (EMG), EMG-derived Responsiveness Index (RI), and averaged blood pressure variability (ARV) were tested against RASS measurements. The aforementioned variables together with blood pressure and Surgical Pleth Index (SPI) were explored before and after painful stimuli (for example bronchoscopy, or pleural puncture) at varying RASS levels, to test variable responsiveness. RESULTS: BIS, EMG, and RI predicted RASS levels with a prediction probability (PK) of 0.776 for BIS, 0.761 for EMG, and 0.763 for RI. In addition, BIS, EMG, and ARV demonstrated responsiveness to painful stimuli during deep sedation (RASS score ≤ -3). CONCLUSION: Variables derived from EEG and EMG are associated with sedation levels, as described by the RASS score. Furthermore, these variables, along with ARV, react with consistency to painful stimuli during deep sedation (RASS -5 to -3), offering novel tools for nociception-sedation monitoring of mechanically ventilated ICU patients requiring deep sedation.

Postoperative pain as a risk factor for stiff knee following total knee arthroplasty and excellent patientreported outcomes after manipulation under anesthesia.

BACKGROUND AND PURPOSE: Manipulation under anesthesia (MUA) is the first-choice treatment for stiffness following total knee arthroplasty (TKA) unresponsive to pain management and physiotherapy. Some of the predisposing factors and patient-reported outcome measures (PROMs) following MUA remain poorly studied. We retrospectively investigated the etiological risk factors and the outcomes of MUA. PATIENTS AND METHODS: 391 TKA patients from a randomized trial comparing the use of a tourniquet and anesthesia (spinal or general) were analyzed, and patients needing MUA were identified (MUA group). We evaluated in-hospital opioid consumption, Oxford Knee Score (OKS), range of motion (ROM), and pain assessed by the Brief Pain Inventory-short form with a 1-year follow-up. RESULTS: 39 (10%) MUA patients were identified. The MUA patients were younger (60 years vs. 64 years, difference -4, 95% CI -6 to -1) and had higher postoperative oxycodone consumption (66 mg vs. 51 mg, median difference 11, CI 1-22) than the no-MUA patients. The proportion of MUA patients who contacted the emergency department within 3 months because of pain was larger than that of non-MUA patients (41% vs. 12%, OR 5, CI 3-10). At the 1-year follow-up, the ROM was improved by 39° following MUA, but the total ROM was worse in the MUA group (115° vs. 124°, p < 0.001). No difference was found in the OKS between the MUA and no-MUA patients. INTERPRETATION: Higher postoperative pain seems to predict MUA risk. MUA performed 3 months postoperatively offers substantial ROM improvement and comparable PROMs to no-MUA patients 1 year after TKA.

Anesthesia Method, Tourniquet Use, and Persistent Postsurgical Pain after Total Knee Arthroplasty: A Prespecified Secondary Analysis of a Randomized Trial.

BACKGROUND: Persistent postsurgical pain after total knee arthroplasty is a common problem and a major reason for patient dissatisfaction. This secondary analysis aimed to investigate the effects of anesthesia (spinal vs. general) and tourniquet use on persistent pain after total knee arthroplasty. METHODS: In this secondary analysis of a previously presented parallel, single-center, randomized trial, 404 patients scheduled for total knee arthroplasty were randomized to spinal versus general anesthesia and no-tourniquet versus tourniquet groups. Patients assessed pain using the Brief Pain Inventory-short form preoperatively and 3 and 12 months postoperatively. The prespecified main outcome was the change in "average pain" measured with numerical 0 to 10 rating scale 1 yr postoperatively. The threshold for clinical importance between groups was set to 1.0. RESULTS: The change in average pain scores 1 yr postoperatively did not differ between the spinal and general anesthesia groups (-2.6 [SD 2.5] vs. -2.3 [SD 2.5], respectively; mean difference, -0.4; 95% CI, -0.9 to 0.1; P = 0.150). The no-tourniquet group reported a smaller decrease in the average pain scores than the tourniquet group (-2.1 [SD 2.7] vs. -2.8 [SD 2.3]; mean difference, 0.6; 95% CI, 0.1 to 1.1; P = 0.012). After 1 yr, the scores concerning the mean of four pain severity variables (numerical rating scale) decreased more in the spinal than in the general anesthesia group (-2.3 [SD 2.2] vs. -1.8 [SD 2.1]; mean difference, -0.5; 95% CI, -0.9 to -0.05; P = 0.029) and less in the no-tourniquet than in the tourniquet group (-1.7 [SD 2.3] vs. -2.3 [SD 2.0]; mean difference, 0.6; 95% CI, 0.2 to 1.0; P = 0.005). None of the differences in pain scores reached the threshold for clinical importance. CONCLUSIONS: The type of anesthesia (spinal vs. general) or tourniquet use has no clinically important effect on persistent postsurgical pain after total knee arthroplasty.

Hypothermia-treated cardiac arrest patients with good neurological outcome differ early in quantitative variables of EEG suppression and epileptiform activity.

OBJECTIVE: To evaluate electroencephalogram-derived quantitative variables after out-of-hospital cardiac arrest. DESIGN: Prospective study. SETTING: University hospital intensive care unit. PATIENTS: Thirty comatose adult patients resuscitated from a witnessed out-of-hospital ventricular fibrillation cardiac arrest and treated with induced hypothermia (33 degrees C) for 24 hrs. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Electroencephalography was registered from the arrival at the intensive care unit until the patient was extubated or transferred to the ward, or 5 days had elapsed from cardiac arrest. Burst-suppression ratio, response entropy, state entropy, and wavelet subband entropy were derived. Serum neuron-specific enolase and protein 100B were measured. The Pulsatility Index of Transcranial Doppler Ultrasonography was used to estimate cerebral blood flow velocity. The Glasgow-Pittsburgh Cerebral Performance Categories was used to assess the neurologic outcome during 6 mos after cardiac arrest. Twenty patients had Cerebral Performance Categories of 1 to 2, one patient had a Cerebral Performance Categories of 3, and nine patients had died (Cerebral Performance Categories of 5). Burst-suppression ratio, response entropy, and state entropy already differed between good (Cerebral Performance Categories 1-2) and poor (Cerebral Performance Categories 3-5) outcome groups (p = .011, p = .011, p = .008) during the first 24 hrs after cardiac arrest. Wavelet subband entropy was higher in the good outcome group between 24 and 48 hrs after cardiac arrest (p = .050). All patients with status epilepticus died, and their wavelet subband entropy values were lower (p = .022). Protein 100B was lower in the good outcome group on arrival at ICU (p = .010). After hypothermia treatment, neuron-specific enolase and protein 100B values were lower (p = .002 for both) in the good outcome group. The Pulsatility Index was also lower in the good outcome group (p = .004). CONCLUSIONS: Quantitative electroencephalographic variables may be used to differentiate patients with good neurologic outcomes from those with poor outcomes after out-of-hospital cardiac arrest. The predictive values need to be determined in a larger, separate group of patients.

Quantification of epileptiform electroencephalographic activity during sevoflurane mask induction.

BACKGROUND: Sevoflurane may induce epileptiform electroencephalographic activity leading to unstable Bispectral Index numbers, underestimating the hypnotic depth of anesthesia. The authors developed a method for the quantification of epileptiform electroencephalographic activity during sevoflurane anesthesia. METHODS: Electroencephalographic data from 60 patients under sevoflurane mask induction were used in the analysis. Electroencephalographic data were visually classified. A novel electroencephalogram-derived quantity, wavelet subband entropy (WSE), was developed. WSE variables were calculated from different frequency bands. Performance of the WSE in detection and quantification of epileptiform electroencephalographic activity and the ability of the WSE to recognize misleading Bispectral Index readings caused by epileptiform activity were evaluated. RESULTS: Two WSE variables were found to be sufficient for the quantification of epileptiform activity: WSE from the frequency bands 4-16 and 16-32 Hz. The lower frequency band was used for monophasic pattern monitoring, and the higher frequency band was used for spike activity monitoring. WSE values of the lower and higher bands followed the time evolution of epileptiform activity with prediction probabilities of 0.809 (SE, 0.007) and 0.804 (SE, 0.007), respectively. In deep anesthesia with epileptiform activity, WSE detected electroencephalographic patterns causing Bispectral Index readings greater than 60, with event sensitivity of 97.1%. CONCLUSIONS: The developed method proved useful in detection and quantification of epileptiform electroencephalographic activity during sevoflurane anesthesia. In the future, it may improve the understanding of electroencephalogram-derived information by assisting in recognizing misleading readings of depth-of-anesthesia monitors. The method also may assist in minimizing the occurrence of epileptiform activity and seizures during sevoflurane anesthesia.

A rapid increase in the inspired concentration of desflurane is not associated with epileptiform encephalogram.

UNLABELLED: The large inspired concentration of sevoflurane (S) during mask induction of anesthesia can induce epileptiform electroencephalogram (EEG) associated with tachycardia. Tachycardia is also seen when the concentration of desflurane (D) is abruptly increased. It is not known whether this is associated with epileptiform EEG similar to S. We studied EEG and heart rate (HR) during rapidly increased concentrations of S or D in 31 females during the postintubation period of anesthesia. Anesthesia was induced with propofol and remifentanil, and the tracheas were intubated. Patients were randomized to receive either S or D in nitrous oxide-oxygen mixture after intubation, at a small dose first. After 10 min, S or D vaporizer was advanced to the highest reading of the vaporizer (7% for S, 18% for D) for 5 min. HR and EEG were recorded. Epileptiform EEG activity was recorded in eight of 15 patients in group S and in none in group D (P < 0.05). HR increased in both groups. In group S, HR increased gradually and the highest HR value was 84 bpm at 5 min after the increase in sevoflurane concentration. In group D, HR increased to 93 bpm 2 min after the increase in desflurane concentration (no significant difference, S versus D). A rapid increase in the concentration of S frequently induces epileptiform EEG during normoventilation. Tachycardia during increasing concentrations of D is not associated with epileptiform EEG. IMPLICATIONS: A rapid increase in the concentration of sevoflurane induces epileptiform encephalogram (EEG) with tachycardia. A rapid increase in the concentration of desflurane also induces tachycardia but is not associated with epileptiform EEG.