Alpha rhythm collapse predicts iso-electric suppressions during anesthesia.

Could an overly deep sedation be anticipated from ElectroEncephaloGram (EEG) patterns? We report here motifs hidden in the EEG signal that predict the appearance of Iso-Electric Suppressions (IES), observed during epileptic encephalopathies, drug intoxications, comatose, brain death or during anesthetic over-dosage that are considered to be detrimental. To show that IES occurrences can be predicted from EEG traces dynamics, we focus on transient suppression of the alpha rhythm (8-14 Hz) recorded for 80 patients, that had a Propofol target controlled infusion of 5 μg/ml during a general anesthesia. We found that the first time of appearance as well as changes in duration of these Alpha-Suppressions (αS) are two parameters that anticipate the appearance of IES. Using machine learning, we predicted IES appearance from the first 10 min of EEG (AUC of 0.93). To conclude, transient motifs in the alpha rhythm predict IES during anesthesia and can be used to identify patients, with higher risks of post-operative complications

Cerebral autoregulation and cerebral blood flow response to mean arterial pressure challenge following induction of general anaesthesia for neuroradiology procedure

IntroductionIntraoperative hypotension is common following general anaesthesia induction with propofol, but its impact on cerebral autoregulation (CA) remains unclear. We investigate the incidence and risk factors of impaired CApost-propofol induction and its recovery after a mean arterial pressure (mAP) challenge.MethodsWe included 40 non-emergency neuroradiology surgery patients [58 (47, 58)years old., 57% women]. We recorded mAP, mean blood flow velocity in the mean cerebral artery (MCAvmean), and regional cerebral oxygen saturation (rSO2). We computed the mean flow index (Mxa) pre and post mAP challenge. Mxa > 0.3 defined poor CA.ResultsAfter anaesthesia induction, 21 (53%) had impaired CBF autoregulation (CA−, Mxa > 0.3). The average mAP was 66 ± 9 mmHg, average MCAv was 39 ± 12 cm.s−1, and rSO2 was 63 ± 7%. We found no significant difference in age, norepinephrine infusion rate, and cardiovascular risks factors were similar between CA− and CA+ (Mxa ≤ 0.3) patients. Among the 22 patients (CA−: n = 14; CA+: n = 8) undergoing mAP challenge, there was a significant Mxa improvement and MCAv increase among CA− patients, (CA−: 0.63 ± 0.18 vs. 0.28 ± 0.20, p < 0.001), and [absolute variation: 1 (0.7–1.5) vs. 7 (3–9) cm.sec−1], respectively.ConclusionAfter induction of general anaesthesia for neuroradiology procedure, 53% of the patients had an impaired CA, regardless of age or medical history. Importantly, a mAP challenge effectively restored CA and improved CBF.Clinical Trial Registrationidentifier, NCT0428886

Quality of reporting of studies using artificial intelligence in intensive care and anesthesiology: a systematic review

Data science as a whole has become a major part in all science fields. Artificial intelligence enables quick answer to huge data streams, and some newly available algorithms are already validated in routine care by medical organization worldwide. Intensive care and anesthesiology are at the forefront of this evolution thanks to a vast amount of computerized data along with a constant need for patient deterioration prediction (e.g. mortality, organ failure). Along with this growing interest, we observe a major increase in medical publications on this field of search, often without real knowledge of the most inherent and specific bias on this area

Cerebral autoregulation and cerebral blood flow response to mean arterial pressure challenge following induction of general anaesthesia for neuroradiology procedure

International audienceIntroduction Intraoperative hypotension is common following general anaesthesia induction with propofol, but its impact on cerebral autoregulation (CA) remains unclear. We investigate the incidence and risk factors of impaired CApost-propofol induction and its recovery after a mean arterial pressure (mAP) challenge. Methods We included 40 non-emergency neuroradiology surgery patients [58 (47, 58)years old., 57% women]. We recorded mAP, mean blood flow velocity in the mean cerebral artery (MCAv$_{ mean}$ ), and regional cerebral oxygen saturation (rSO2). We computed the mean flow index (Mxa) pre and post mAP challenge. Mxa > 0.3 defined poor CA. Results After anaesthesia induction, 21 (53%) had impaired CBF autoregulation (CA−, Mxa < 0.3). The average mAP was 66 ± 9 mmHg, average MCAv was 39 ± 12 cm.s$^{−1}$ , and rSO 2 was 63 ± 7%. We found no significant difference in age, norepinephrine infusion rate, and cardiovascular risks factors were similar between CA− and CA+ (Mxa ≤ 0.3) patients. Among the 22 patients (CA−: n = 14; CA+: n = 8) undergoing mAP challenge, there was a significant Mxa improvement and MCAv increase among CA− patients, (CA−: 0.63 ± 0.18 vs. 0.28 ± 0.20, p < 0.001), and [absolute variation: 1 (0.7–1.5) vs. 7 (3–9) cm.sec$^{−1}$ ], respectively. Conclusion After induction of general anaesthesia for neuroradiology procedure, 53% of the patients had an impaired CA, regardless of age or medical history. Importantly, a mAP challenge effectively restored CA and improved CBF. Clinical Trial Registration identifier, NCT0428886

The ICEBERG: A score and visual representation to track the severity of traumatic brain injury: Design principles and preliminary results

International audienceBACKGROUND Establishing neurological prognoses in traumatic brain injury (TBI) patients remains challenging. To help physicians in the early management of severe TBI, we have designed a visual score (ICEBERG score) including multimodal monitoring and treatment-related criteria. We evaluated the ICEBERG scores among patients with severe TBI to predict the 28-day mortality and long-term disability (Extended Glasgow Outcome Scale score at 3 years). In addition, we made a preliminary assessment of the nurses and doctors on the uptake and reception to the use of the ICEBERG visual tool. METHODS This study was part of a larger prospective cohort study of 207 patients with severe TBI in the Parisian region (PariS-TBI study). The ICEBERG score included six variables from multimodal monitoring and treatment-related criteria: cerebral perfusion pressure, intracranial pressure, body temperature, sedation depth, arterial partial pressure of CO2, and blood osmolarity. The primary outcome measures included the ICEBERG score and its relationship with hospital mortality and Extended Glasgow Outcome Score. RESULTS The hospital mortality was 21% (45/207). The ICEBERG score baseline value and changes during the 72nd first hours were more strongly associated with TBI prognosis than the ICEBERG parameters measured individually. Interestingly, when the clinical and computed tomography parameters at admission were combined with the ICEBERG score at 48 hours using a multimodal approach, the predictive value was significantly increased (area under the curve = 0.92). Furthermore, comparing the ICEBERG visual representation with the traditional numerical readout revealed that changes in patient vitals were more promptly detected using ICEBERG representation (p < 0.05). CONCLUSION The ICEBERG score could represent a simple and effective method to describe severity in TBI patients, where a high score is associated with increased mortality and disability. In addition, ICEBERG representation could enhance the recognition of unmet therapeutic goals and dynamic evolution of the patient's condition. These preliminary results must be confirmed in a prospective manner. LEVEL OF EVIDENCE Diagnostic Tests or Criteria; Level III

Repurposing EEG monitoring of general anaesthesia for building biomarkers of brain ageing: An exploratory study

Background: EEG is a common tool for monitoring anaesthetic depth but is rarely reused at large for biomedical research. This study sets out to explore repurposing of EEG during anaesthesia to learn biomarkers of brain ageing. Methods: We focused on brain age estimation as an example. Using machine learning, we reanalysed 4-electrodes EEG of 323 patients under propofol and sevoflurane. We included spatio-spectral features from stable anaesthesia for EEG-based age prediction applying recently published reference methods. Anaesthesia was considered stable when 95% of the total power was below a frequency between 8Hz and 13Hz. Results: We considered moderate-risk patients (ASA <= 2) with propofol anaesthesia to explore predictive EEG signatures. Average alpha-band power (8-13Hz) was informative about age. Yet, state-of-the-art prediction performance was achieved by analysing the entire power spectrum from all electrodes (MAE = 8.2y, R2 = 0.65). Clinical exploration revealed that brain age was systematically linked with intra-operative burst suppression-commonly associated with agerelated postoperative cognitive issues. Surprisingly, the brain age was negatively correlated with burst suppression in high-risk patients (ASA = 3), pointing at unknown confounding effects. Secondary analyses revealed that brain-age EEG signatures were specific to propofol anaesthesia, reflected by limited prediction performance under sevoflurane and poor cross-drug generalisation. Conclusions: EEG from general anaesthesia may enable state-of-the-art brain age prediction. Yet, differences between anaesthetic drugs can impact the effectiveness of repurposing EEG from anaesthesia. To unleash the dormant potential of repurposing EEG-monitoring for clinical and health research, collecting larger datasets with precisely documented drug dosage will be key enabling factors

Repurposing electroencephalogram monitoring of general anaesthesia for building biomarkers of brain ageing: an exploratory study

Background: Electroencephalography (EEG) is increasingly used for monitoring the depth of general anaesthesia, but EEG data from general anaesthesia monitoring are rarely reused for research. Here, we explored repurposing EEG monitoring from general anaesthesia for brain-age modelling using machine learning. We hypothesised that brain age estimated from EEG during general anaesthesia is associated with perioperative risk. Methods: We reanalysed four-electrode EEGs of 323 patients under stable propofol or sevoflurane anaesthesia to study four EEG signatures (95% of EEG power <8–13 Hz) for age prediction: total power, alpha-band power (8–13 Hz), power spectrum, and spatial patterns in frequency bands. We constructed age-prediction models from EEGs of a healthy reference group (ASA 1 or 2) during propofol anaesthesia. Although all signatures were informative, state-of-the-art age-prediction performance was unlocked by parsing spatial patterns across electrodes along the entire power spectrum (mean absolute error=8.2 yr; R2=0.65). Results: Clinical exploration in ASA 1 or 2 patients revealed that brain age was positively correlated with intraoperative burst suppression, a risk factor for general anaesthesia complications. Surprisingly, brain age was negatively correlated with burst suppression in patients with higher ASA scores, suggesting hidden confounders. Secondary analyses revealed that age-related EEG signatures were specific to propofol anaesthesia, reflected by limited model generalisation to anaesthesia maintained with sevoflurane. Conclusions: Although EEG from general anaesthesia may enable state-of-the-art age prediction, differences between anaesthetic drugs can impact the effectiveness and validity of brain-age models. To unleash the dormant potential of EEG monitoring for clinical research, larger datasets from heterogeneous populations with precisely documented drug dosage will be essential

Impact of impaired cerebral blood flow autoregulation on electroencephalogram signals in adults undergoing propofol anaesthesia: a pilot study

International audienceBackground: Cerebral autoregulation actively maintains cerebral blood flow over a range of MAPs. During general anaesthesia, this mechanism may not compensate for reductions in MAP leading to brain hypoperfusion. Cerebral autoregulation can be assessed using the mean flow index derived from Doppler measurements of average blood velocity in the middle cerebral artery, but this is impractical for routine monitoring within the operating room. Here, we investigate the possibility of using the EEG as a proxy measure for a loss of cerebral autoregulation, determined by the mean flow index. Methods: Thirty-six patients (57.5 [44.25; 66.5] yr; 38.9% women, non-emergency neuroradiology surgery) anaesthetised using propofol were prospectively studied. Continuous recordings of MAP, average blood velocity in the middle cerebral artery, EEG, and regional cerebral oxygen saturation were made. Poor cerebral autoregulation was defined as a mean flow index greater than 0.3. Results: Eighteen patients had preserved cerebral autoregulation, and 18 had altered cerebral autoregulation. The two groups had similar ages, MAPs, and average blood velocities in the middle cerebral artery. Patients with altered cerebral autoregulation exhibited a significantly slower alpha peak frequency (9