Diffuse optical tomography for mapping cerebral hemodynamics and functional connectivity in delirium.

INTRODUCTION: Delirium is associated with mortality and new onset dementia, yet the underlying pathophysiology remains poorly understood. Development of imaging biomarkers has been difficult given the challenging nature of imaging delirious patients. Diffuse optical tomography (DOT) offers a promising approach for investigating delirium given its portability and three-dimensional capabilities. METHODS: Twenty-five delirious and matched non-delirious patients (n = 50) were examined using DOT, comparing cerebral oxygenation and functional connectivity in the prefrontal cortex during and after an episode of delirium. RESULTS: Total hemoglobin values were significantly decreased in the delirium group, even after delirium resolution. Functional connectivity between the dorsolateral prefrontal cortex and dorsomedial prefrontal cortex was strengthened post-resolution compared to during an episode; however, this relationship was still significantly weaker compared to controls. DISCUSSION: These findings highlight DOT's potential as an imaging biomarker to measure impaired cerebral oxygenation and functional dysconnectivity during and after delirium. Future studies should focus on the role of cerebral oxygenation in delirium pathogenesis and exploring the etiological link between delirium and dementias. HIGHLIGHTS: We developed a portable diffuse optical tomography (DOT) system for bedside three-dimensional functional neuroimaging to study delirium in the hospital. We implemented a novel DOT task-focused seed-based correlation analysis. DOT revealed decreased cerebral oxygenation and functional connectivity strength in the delirium group, even after resolution of delirium.

The role of heart rate variability in predicting delirium: A systematic review and meta-analysis.

Brain and heart interact through multiple ways. Heart rate variability, a non-invasive measurement is studied extensively as a predicting model for various health conditions including subarachnoid hemorrhage, cancer, and diabetes. There is limited evidence to predict delirium, an acute fluctuating disorder of brain dysfunction, as it poses a significant challenge in the intensive care unit (ICU) and post-operative setting. In this systematic review of 9 articles, heart rate variability indices were used to investigate the occurrence of post-operative and ICU delirium. This systematic review and meta-analysis reveal evidence of a strong predilection between postoperative and intensive care unit delirium and alterations in the heart rate variability, measured by mean differences for standard deviation of NN-intervals. Other heart rate variability indices [root mean squares of successive differences, low-frequency (LF), high-frequency (HF), and LF:HF ratio] showed lack of or very weak association. A non-invasive tool of brain and heart interaction may refine diagnostic predictions for acute brain dysfunctions like delirium in such population and would be an important step in delirium research.

Prevalence of clinical electroencephalography findings in stroke patients with delirium.

OBJECTIVE: Delirium is an acute cognitive disorder associated with multiple electroencephalographic (EEG) abnormalities in non-neurological patients, though specific EEG characteristics in patients with stroke remain unclear. We aimed to compare the prevalence of EEG abnormalities in stroke patients during delirium episodes with periods that did not correspond to delirium. METHODS: We retrospectively analyzed clinical EEG reports for stroke patients who received daily delirium assessments as part of a prospective study. We compared the prevalence of EEG features corresponding to patient-days with vs. without delirium, including focal and generalized slowing, and focal and generalized epileptiform abnormalities (EAs). RESULTS: Among 58 patients who received EEGs, there were 192 days of both EEG and delirium monitoring (88% [n = 169] corresponding to delirium). Generalized slowing was significantly more prevalent on days with vs. without delirium (96% vs. 57%, p = 0.03), as were bilateral or generalized EAs (38% vs. 13%, p = 0.03). In contrast, focal slowing (53% vs. 74%, p = 0.11) and focal EAs were less prevalent on days with delirium (38% vs. 48%, p = 0.37), though these differences were not statistically significant. CONCLUSIONS: We found a higher prevalence of generalized but not focal EEG abnormalities in stroke patients with delirium. SIGNIFICANCE: These findings may reinforce the diffuse nature of delirium-associated encephalopathy, even in patients with discrete structural lesions.

Single-channel qEEG characteristics distinguish delirium from no delirium, but not postoperative from non-postoperative delirium.

OBJECTIVE: This exploratory study examined quantitative electroencephalography (qEEG) changes in delirium and the use of qEEG features to distinguish postoperative from non-postoperative delirium. METHODS: This project was part of the DeltaStudy, a cross-sectional,multicenterstudy in Intensive Care Units (ICUs) and non-ICU wards. Single-channel (Fp2-Pz) four-minutes resting-state EEG was analyzed in 456 patients. After calculating 98 qEEG features per epoch, random forest (RF) classification was used to analyze qEEG changes in delirium and to test whether postoperative and non-postoperative delirium could be distinguished. RESULTS: An area under the receiver operatingcharacteristic curve (AUC) of 0.76 (95% Confidence Interval (CI) 0.71-0.80) was found when classifying delirium with a sensitivity of 0.77 and a specificity of 0.63 at the optimal operating point. The classification of postoperative versus non-postoperative delirium resulted in an AUC of 0.50 (95%CI 0.38-0.61). CONCLUSIONS: RF classification was able to discriminate delirium from no delirium with reasonable accuracy, while also identifying new delirium qEEG markers like autocorrelation and theta peak frequency. RF classification could not distinguish postoperative from non-postoperative delirium. SIGNIFICANCE: Single-channel EEG differentiates between delirium and no delirium with reasonable accuracy. We found no distinct EEG profile for postoperative delirium, which may suggest that delirium is one entity, whether it develops postoperatively or not.

Post-sepsis psychiatric disorder: Pathophysiology, prevention, and treatment.

Post-sepsis psychiatric disorder, encompassing anxiety, depression, post-traumatic stress disorder and delirium, is a highly prevalent complication secondary to sepsis, resulting in a marked increase in long-term mortality among affected patients. Regrettably, psychiatric impairment associated with sepsis is frequently disregarded by clinicians. This review aims to summarize recent advancements in the understanding of the pathophysiology, prevention, and treatment of post-sepsis mental disorder, including coronavirus disease 2019-related psychiatric impairment. The pathophysiology of post-sepsis psychiatric disorder is complex and is known to involve blood-brain barrier disruption, overactivation of the hypothalamic-pituitary-adrenal axis, neuroinflammation, oxidative stress, neurotransmitter dysfunction, programmed cell death, and impaired neuroplasticity. No unified diagnostic criteria for this disorder are currently available; however, screening scales are often applied in its assessment. Modifiable risk factors for psychiatric impairment post-sepsis include the number of experienced traumatic memories, the length of ICU stay, level of albumin, the use of vasopressors or inotropes, daily activity function after sepsis, and the cumulative dose of dobutamine. To contribute to the prevention of post-sepsis psychiatric disorder, it may be beneficial to implement targeted interventions for these modifiable risk factors. Specific therapies for this condition remain scarce. Nevertheless, non-pharmacological approaches, such as comprehensive nursing care, may provide a promising avenue for treating psychiatric disorder following sepsis. In addition, although several therapeutic drugs have shown preliminary efficacy in animal models, further confirmation of their potential is required through follow-up clinical studies.

Effect of Atypical Sleep EEG Patterns on Weaning From Prolonged Mechanical Ventilation.

BACKGROUND: Approximately one-third of acute ICU patients display atypical sleep patterns that cannot be interpreted by using standard EEG criteria for sleep. Atypical sleep patterns have been associated with poor weaning outcomes in acute ICUs. RESEARCH QUESTION: Do patients being weaned from prolonged mechanical ventilation experience atypical sleep EEG patterns, and are these patterns linked with weaning outcomes? STUDY DESIGN AND METHODS: EEG power spectral analysis during wakefulness and overnight polysomnogram were performed on alert, nondelirious patients at a long-term acute care facility. RESULTS: Forty-four patients had been ventilated for a median duration of 38 days at the time of the polysomnogram study. Eleven patients (25%) exhibited atypical sleep EEG. During wakefulness, relative EEG power spectral analysis revealed higher relative delta power in patients with atypical sleep than in patients with usual sleep (53% vs 41%; P < .001) and a higher slow-to-fast power ratio during wakefulness: 4.39 vs 2.17 (P < .001). Patients with atypical sleep displayed more subsyndromal delirium (36% vs 6%; P = .027) and less rapid eye movement sleep (4% vs 11% total sleep time; P < .02). Weaning failure was more common in the atypical sleep group than in the usual sleep group: 91% vs 45% (P = .013). INTERPRETATION: This study provides the first evidence that patients in a long-term acute care facility being weaned from prolonged ventilation exhibit atypical sleep EEG patterns that are associated with weaning failure. Patients with atypical sleep EEG patterns had higher rates of subsyndromal delirium and slowing of the wakeful EEG, suggesting that these two findings represent a biological signal for brain dysfunction.

Oxidative stress and soluble receptor for advanced glycation end-products play a role in the pathophysiology of delirium after cardiac surgery.

Coronary-artery bypass graft (CABG) surgery is known to improve cardiac function and decrease mortality, albeit, this method of treatment is also associated with a neuropsychiatric complications including postoperative delirium. The pathophysiology of delirium after cardiac surgery remains poorly understood. Thus, the purpose of this study was to investigate whether oxidative stress reflected by decreased preoperative and postoperative plasma antioxidant activity is independently associated with delirium after cardiac surgery. The second aim was to assess whether decreased antioxidant activity is stress-related or mediated by other pathologies such as major depressive disorder (MDD), anxiety disorders, and cognitive impairment. Furthermore, the putative relationship between pre- and postoperative soluble receptor for advanced glycation end-products (sRAGE) overexpression and plasma antioxidant capacity was evaluated. The patients cognitive status was assessed 1 day preoperatively with the use of the Mini-Mental State Examination Test and the Clock Drawing Test. A diagnosis of MDD and anxiety disorders was established on the basis of DSM-5 criteria. Blood samples for antioxidant capacity and sRAGE levels were collected both preoperatively and postoperatively. The Confusion Assessment Method for the Intensive Care Unit was used within the first 5 days postoperatively to screen for a diagnosis of delirium. Postoperative delirium was diagnosed in 34% (61 of 177) of individuals. Multivariate logistic regression analysis revealed that low baseline antioxidant capacity was independently associated with postoperative delirium development. Moreover, increased risk of delirium was observed among patients with a preoperative diagnosis of MDD associated with antioxidant capacity decreased postoperatively. According to receiver operating characteristic analysis, the most optimal cutoff values of the preoperative and postoperative antioxidant capacity that predict the development of delirium were 1.72 mM and 1.89 mM, respectively. Pre- and postoperative antioxidant capacity levels were negatively correlated with postoperative sRAGE concentration (Spearman's Rank Correlation - 0.198 and - 0.158, p < 0.05, respectively). Patients with decreased preoperative antioxidant activity and those with depressive episodes complicated with lower postoperative antioxidant activity are at significantly higher risk of delirium after cardiac surgery development. sRAGE overexpression may be considered as protective mechanism against increased oxidative stress and subsequent cell damage.

ICU delirium burden predicts functional neurologic outcomes.

BACKGROUND: We investigated the effect of delirium burden in mechanically ventilated patients, beginning in the ICU and continuing throughout hospitalization, on functional neurologic outcomes up to 2.5 years following critical illness. METHODS: Prospective cohort study of enrolling 178 consecutive mechanically ventilated adult medical and surgical ICU patients between October 2013 and May 2016. Altogether, patients were assessed daily for delirium 2941days using the Confusion Assessment Method for the ICU (CAM-ICU). Hospitalization delirium burden (DB) was quantified as number of hospital days with delirium divided by total days at risk. Survival status up to 2.5 years and neurologic outcomes using the Glasgow Outcome Scale were recorded at discharge 3, 6, and 12 months post-discharge. RESULTS: Of 178 patients, 19 (10.7%) were excluded from outcome analyses due to persistent coma. Among the remaining 159, 123 (77.4%) experienced delirium. DB was independently associated with >4-fold increased mortality at 2.5 years following ICU admission (adjusted hazard ratio [aHR], 4.77; 95% CI, 2.10-10.83; P < .001), and worse neurologic outcome at discharge (adjusted odds ratio [aOR], 0.02; 0.01-0.09; P < .001), 3 (aOR, 0.11; 0.04-0.31; P < .001), 6 (aOR, 0.10; 0.04-0.29; P < .001), and 12 months (aOR, 0.19; 0.07-0.52; P = .001). DB in the ICU alone was not associated with mortality (HR, 1.79; 0.93-3.44; P = .082) and predicted neurologic outcome less strongly than entire hospital stay DB. Similarly, the number of delirium days in the ICU and for whole hospitalization were not associated with mortality (HR, 1.00; 0.93-1.08; P = .917 and HR, 0.98; 0.94-1.03, P = .535) nor with neurological outcomes, except for the association between ICU delirium days and neurological outcome at discharge (OR, 0.90; 0.81-0.99, P = .038). CONCLUSIONS: Delirium burden throughout hospitalization independently predicts long term neurologic outcomes and death up to 2.5 years after critical illness, and is more predictive than delirium burden in the ICU alone and number of delirium days.

Perioperative Electroencephalogram Spectral Dynamics Related to Postoperative Delirium in Older Patients.

BACKGROUND: Intraoperative electroencephalography (EEG) signatures related to the development of postoperative delirium (POD) in older patients are frequently studied. However, a broad analysis of the EEG dynamics including preoperative, postinduction, intraoperative and postoperative scenarios and its correlation to POD development is still lacking. We explored the relationship between perioperative EEG spectra-derived parameters and POD development, aiming to ascertain the diagnostic utility of these parameters to detect patients developing POD. METHODS: Patients aged ≥65 years undergoing elective surgeries that were expected to last more than 60 minutes were included in this prospective, observational single center study (Biomarker Development for Postoperative Cognitive Impairment [BioCog] study). Frontal EEGs were recorded, starting before induction of anesthesia and lasting until recovery of consciousness. EEG data were analyzed based on raw EEG files and downloaded excel data files. We performed multitaper spectral analyses of relevant EEG epochs and further used multitaper spectral estimate to calculate a corresponding spectral parameter. POD assessments were performed twice daily up to the seventh postoperative day. Our primary aim was to analyze the relation between the perioperative spectral edge frequency (SEF) and the development of POD. RESULTS: Of the 237 included patients, 41 (17%) patients developed POD. The preoperative EEG in POD patients was associated with lower values in both SEF (POD 13.1 ± 4.6 Hz versus no postoperative delirium [NoPOD] 17.4 ± 6.9 Hz; P = .002) and corresponding γ-band power (POD -24.33 ± 2.8 dB versus NoPOD -17.9 ± 4.81 dB), as well as reduced postinduction absolute α-band power (POD -7.37 ± 4.52 dB versus NoPOD -5 ± 5.03 dB). The ratio of SEF from the preoperative to postinduction state (SEF ratio) was ~1 in POD patients, whereas NoPOD patients showed a SEF ratio >1, thus indicating a slowing of EEG with loss of unconscious. Preoperative SEF, preoperative γ-band power, and SEF ratio were independently associated with POD (P = .025; odds ratio [OR] = 0.892, 95% confidence interval [CI], 0.808-0.986; P = .029; OR = 0.568, 95% CI, 0.342-0.944; and P = .009; OR = 0.108, 95% CI, 0.021-0.568, respectively). CONCLUSIONS: Lower preoperative SEF, absence of slowing in EEG while transitioning from preoperative state to unconscious state, and lower EEG power in relevant frequency bands in both these states are related to POD development. These findings may suggest an underlying pathophysiology and might be used as EEG-based marker for early identification of patients at risk to develop POD.

Automatic continuous EEG signal analysis for diagnosis of delirium in patients with sepsis.

OBJECTIVE: In critical care, continuous EEG (cEEG) monitoring is useful for delirium diagnosis. Although visual cEEG analysis is most commonly used, automatic cEEG analysis has shown promising results in small samples. Here we aimed to compare visual versus automatic cEEG analysis for delirium diagnosis in septic patients. METHODS: We obtained cEEG recordings from 102 septic patients who were scored for delirium six times daily. A total of 1252 cEEG blocks were visually analyzed, of which 805 blocks were also automatically analyzed. RESULTS: Automatic cEEG analyses revealed that delirium was associated with 1) high mean global field power (p < 0.005), mainly driven by delta activity; 2) low average coherence across all electrode pairs and all frequencies (p < 0.01); 3) lack of intrahemispheric (fronto-temporal and temporo-occipital regions) and interhemispheric coherence (p < 0.05); and 4) lack of cEEG reactivity (p < 0.005). Classification accuracy was assessed by receiver operating characteristic (ROC) curve analysis, revealing a slightly higher area under the curve for visual analysis (0.88) than automatic analysis (0.74) (p < 0.05). CONCLUSIONS: Automatic cEEG analysis is a useful supplement to visual analysis, and provides additional cEEG diagnostic classifiers. SIGNIFICANCE: Automatic cEEG analysis provides useful information in septic patients.

Increased Emergency Department Hallway Length of Stay is Associated with Development of Delirium.

INTRODUCTION: Our study aimed to determine 1) the association between time spent in the emergency department (ED) hallway and the development of delirium and 2) the hospital location of delirium development. METHODS: This single-center, retrospective chart review included patients 18+ years old admitted to the hospital after presenting, without baseline cognitive impairment, to the ED in 2018. We identified the Delirium group by the following: key words describing delirium; orders for psychotropics, special observation, and restraints; or documented positive Confusion Assessment Method (CAM) screen. The Control group included patients not meeting delirium criteria. We used a multivariable logistic regression model, while adjusting for confounders, to assess the odds of delirium development associated with percentage of ED LOS spent in the hallway. RESULTS: A total of 25,156 patients met inclusion criteria with 1920 (7.6%) meeting delirium criteria. Delirium group vs. Control group patients spent a greater percentage of time in the ED hallway (median 50.5% vs 10.8%, P<0.001); had longer ED LOS (median 11.94 vs 8.12 hours, P<0.001); had more ED room transfers (median 5 vs 4, P<0.001); and had longer hospital LOS (median 5.0 vs 4.6 days, P<0.001). Patients more frequently developed delirium in the ED (77.5%) than on inpatient units (22.5%). The relative odds of a patient developing delirium increased by 3.31 times for each percent increase in ED hallway time (95% confidence interval, 2.85, 3.83). CONCLUSION: Patients with delirium had more ED hallway exposure, longer ED LOS, and more ED room transfers. Understanding delirium in the ED has substantial implications for improving patient safety.

Factors affecting hallucinations in patients with delirium.

Delirium develops through a multifactorial process and include multiple subtypes with different pathological factors. To refine the treatment and care for delirium, a more detailed examination of these subtypes is needed. Therefore, this study aimed to explore the factors affecting delirium in cases in which hallucinations are conspicuous. In total, 602 delirium cases referred to the psychiatry department at a general hospital between May 2015 and August 2020 were enrolled. The Delirium Rating Scale-revised-98 was used to assess perceptual disturbances and hallucinations in patients with delirium. Multiple regression analysis was applied to determine whether individual factors were associated with the hallucinations. A total of 156 patients with delirium (25.9%) experienced hallucinations, with visual hallucinations being the most common subtype. Alcohol drinking (p < 0.0005), benzodiazepine withdrawal (p = 0.004), and the use of angiotensin II receptor blockers (p = 0.007) or dopamine receptor agonists (p = 0.014) were found to be significantly associated with hallucinations in patients with delirium. The four factors detected in this study could all be reversible contributing factors derived from the use of or withdrawal from exogenous substances.

Postoperative Delirium is Not Associated with Long-Term Decline in Activities of Daily Living or Mortality After Laryngectomy.

PURPOSE: To determine the relationships between postoperative delirium (POD) and postoperative activities of daily living (ADL) and mortality in patients undergoing laryngectomy. We hypothesized that POD would reduce postoperative ADL and increase postoperative mortality. PATIENTS AND METHODS: The prospective study included older participants (age ≥65 y) undergoing total laryngectomy, partial laryngectomy, total laryngectomy plus neck dissection, or partial laryngectomy plus neck dissection under general anesthesia. The diagnosis of delirium was based on the Confusion Assessment Method algorithm, which was administered on postoperative days 1 through 6. ADL were evaluated using the Chinese version of the Index of ADL scale. Follow-up assessments of ADL and mortality were conducted 24 months after surgery. RESULTS: Of 127 participants (aged 70.3 ± 4.1 y), 19 (15.0%) developed POD. POD was not associated with a decrease in ADL after laryngectomy (p=0.599) nor with an increase in postoperative mortality [3/19 (15.8%) vs 12/108 (11.1%), p=0.560, Log rank test]. However, longer surgery duration was significantly associated with worse overall survival (OR, 3.262; 95% CI, 1.261-9.169, p=0.025). CONCLUSION: POD was not associated with long-term ADL or mortality after laryngectomy. Prolonged surgery was the only factor associated with a higher postoperative mortality rate.

Noninvasive neuromonitoring in the operating room and its role in the prevention of delirium.

Delirium is a frequent and serious complication after surgery. It has a variable incidence between 20% and 40% with the highest incidence in elderly people undergoing major or cardiac surgery. The development of postoperative delirium (POD) is associated with increased hospital stay lengths, morbidity, the need for home care, and mortality. Studies have appeared in the last decade that evaluate the use of noninvasive monitoring to prevent its development. The evaluation of the depth of anesthesia with processed EEG allows to avoid awareness and burst suppression events. The cessation of brain activity is associated with the development of delirium. Another noninvasive monitoring technique is NIRS for cerebral tissue hypoxia detection by measuring regional oxygen saturation. The reduction of this parameter does not seem to be associated with the development of POD but with postoperative cognitive dysfunction. There are few studies in the literature and with conflicting results on the use of the pupillometer and transcranial Doppler in predicting the development of postoperative delirium.

Association of Delirium during Critical Illness With Mortality: Multicenter Prospective Cohort Study.

BACKGROUND: The temporal association of delirium during critical illness with mortality is unclear, along with the associations of hypoactive and hyperactive motoric subtypes of delirium with mortality. We aimed to evaluate the relationship of delirium during critical illness, including hypoactive and hyperactive motoric subtypes, with mortality in the hospital and after discharge up to 1 year. METHODS: We analyzed a prospective cohort study of adults with respiratory failure and/or shock admitted to university, community, and Veterans Affairs hospitals. We assessed patients using the Richmond Agitation-Sedation Scale and the Confusion Assessment Method for the intensive care unit (ICU) and defined the motoric subtype according to the corresponding Richmond Agitation-Sedation Scale if delirium was present. We used Cox proportional hazard models, adjusted for baseline characteristics, coma, and daily hospital events, to determine whether delirium on a given day predicted mortality the following day in patients in the hospital and also to determine whether delirium presence and duration predicted mortality after discharge up to 1 year in patients who survived to hospital discharge. We performed similar analyses for hypoactive and hyperactive subtypes of delirium. RESULTS: Among 1040 critically ill patients, 214 (21%) died in the hospital and 204 (20%) died out-of-hospital by 1 year. Delirium was common, occurring in 740 (71%) patients for a median (interquartile range [IQR]) of 4 (2-7) days. Hypoactive delirium occurred in 733 (70%) patients, and hyperactive occurred in 185 (18%) patients, with a median (IQR) of 3 (2-7) days and 1 (1-2) days, respectively. Delirium on a given day (hazard ratio [HR], 2.87; 95% confidence interval [CI], 1.32-6.21; P = .008), in particular the hypoactive subtype (HR, 3.35; 95% CI, 1.51-7.46; P = .003), was independently associated with an increased risk of death the following day in the hospital. Hyperactive delirium was not associated with an increased risk of death in the hospital (HR, 4.00; 95% CI, 0.49-32.51; P = .19). Among hospital survivors, neither delirium presence (HR, 1.01; 95% CI, 0.82-1.24; P = .95) nor duration (HR, 0.99; 95% CI, 0.97-1.01; P = .56), regardless of motoric subtype, was associated with mortality after hospital discharge up to 1 year. CONCLUSIONS: Delirium during critical illness is associated with nearly a 3-fold increased risk of death the following day for patients in the hospital but is not associated with mortality after hospital discharge. This finding appears primarily driven by the hypoactive motoric subtype. The independent relationship between delirium and mortality occurs early during critical illness but does not persist after hospital discharge.

Is the Frontal Lobe the Primary Target of SARS-CoV-2?

Acute delirium and other neuropsychiatric symptoms have frequently been reported in COVID-19 patients and are variably referred to as acute encephalopathy, COVID-19 encephalopathy, SARS-CoV-2 encephalitis, or steroid-responsive encephalitis. COVID-19 specific biomarkers of cognitive impairment are currently lacking, but there is some evidence that SARS-CoV-2 could preferentially and directly target the frontal lobes, as suggested by behavioral and dysexecutive symptoms, fronto-temporal hypoperfusion on MRI, EEG slowing in frontal regions, and frontal hypometabolism on 18F-FDG-PET imaging. We suggest that an inflammatory parainfectious process targeting preferentially the frontal lobes (and/or frontal networks) could be the underlying cause of these shared clinical, neurophysiological, and imaging findings in COVID-19 patients. We explore the biological mechanisms and the clinical biomarkers that might underlie such disruption of frontal circuits and highlight the need of standardized diagnostic procedures to be applied when investigating patients with these clinical findings. We also suggest the use of a unique label, to increase comparability across studies.

Association Between Cerebral Desaturation and Postoperative Delirium in Thoracotomy With One-Lung Ventilation: A Prospective Cohort Study.

BACKGROUND: The association between cerebral desaturation and postoperative delirium in thoracotomy with one-lung ventilation (OLV) has not been specifically studied. METHODS: A prospective observational study performed in thoracic surgical patients. Cerebral tissue oxygen saturation (Scto2) was monitored on the left and right foreheads using a near-infrared spectroscopy oximeter. Baseline Scto2 was measured with patients awake and breathing room air. The minimum Scto2 was the lowest measurement at any time during surgery. Cerebral desaturation and hypersaturation were an episode of Scto2 below and above a given threshold for ≥15 seconds during surgery, respectively. The thresholds based on relative changes by referring to the baseline measurement were <80%, <85%, <90%, <95%, and <100% baseline for desaturation and >105%, >110%, >115%, and >120% baseline for hypersaturation. The thresholds based on absolute values were <50%, <55%, <60%, <65%, and <70% for desaturation and >75%, >80%, >85%, and >90% for hypersaturation. The given area under the threshold (AUT)/area above the threshold (AAT) was analyzed. Delirium was assessed until postoperative day 5. The primary analysis was the association between the minimum Scto2 and delirium using multivariable logistic regression controlled for confounders (age, OLV time, use of midazolam, occurrence of hypotension, and severity of pain). The secondary analysis was the association between cerebral desaturation/hypersaturation and delirium, and between the AUT/AAT and delirium using multivariable logistic regression controlled for the same confounders. Multiple testing was corrected using the Holm-Bonferroni method. We additionally monitored somatic tissue oxygen saturation on the forearm and upper thigh. RESULTS: Delirium occurred in 35 (20%) of 175 patients (65 ± 6 years old). The minimum left or right Scto2 was not associated with delirium. Cerebral desaturation defined by <90% baseline for left Scto2 (odds ratio [OR], 5.82; 95% confidence interval [CI], 2.12-19.2; corrected P =.008) and <85% baseline for right Scto2 (OR, 4.27; 95% CI, 1.77-11.0; corrected P =.01) was associated with an increased risk of delirium. Cerebral desaturation defined by other thresholds, cerebral hypersaturation, the AUT/AAT, and somatic desaturation and hypersaturation were all not associated with delirium. CONCLUSIONS: Cerebral desaturation defined by <90% baseline for left Scto2 and <85% baseline for right Scto2, but not the minimum Scto2, may be associated with an increased risk of postthoracotomy delirium. The validity of these thresholds needs to be tested by randomized controlled trials.

Electrophysiological signatures of acute systemic lipopolysaccharide-induced inflammation: potential implications for delirium science.

BACKGROUND: Novel preventive therapies are needed for postoperative delirium, which especially affects older patients. A mouse model is presented that captures inflammation-associated cortical slow wave activity (SWA) observed in patients, allowing exploration of the mechanistic role of prostaglandin-adenosine signalling. METHODS: EEG and cortical cytokine measurements (interleukin 6, monocyte chemoattractant protein-1) were obtained from adult and aged mice. Behaviour, SWA, and functional connectivity were assayed before and after systemic administration of lipopolysaccharide (LPS)+piroxicam (cyclooxygenase inhibitor) or LPS+caffeine (adenosine receptor antagonist). To avoid the confounder of inflammation-driven changes in movement which alter SWA and connectivity, electrophysiological recordings were classified as occurring during quiescence or movement, and propensity score matching was used to match distributions of movement magnitude between baseline and post-LPS administration. RESULTS: LPS produces increases in cortical cytokines and behavioural quiescence. In movement-matched data, LPS produces increases in SWA (likelihood-ratio test: χ2(4)=21.51, P<0.001), but not connectivity (χ2(4)=6.39, P=0.17). Increases in SWA associate with interleukin 6 (P<0.001) and monocyte chemoattractant protein-1 (P=0.001) and are suppressed by piroxicam (P<0.001) and caffeine (P=0.046). Aged animals compared with adult animals show similar LPS-induced SWA during movement, but exaggerated cytokine response and increased SWA during quiescence. CONCLUSIONS: Cytokine-SWA correlations during wakefulness are consistent with observations in patients with delirium. Absence of connectivity effects after accounting for movement changes suggests decreased connectivity in patients is a biomarker of hypoactivity. Exaggerated effects in quiescent aged animals are consistent with increased hypoactive delirium in older patients. Prostaglandin-adenosine signalling may link inflammation to neural changes and hence delirium.

Motoric Subtypes of Delirium and Long-Term Functional and Mental Health Outcomes in Adults After Critical Illness.

OBJECTIVES: Adult ICU survivors that experience delirium are at high risk for developing new functional disabilities and mental health disorders. We sought to determine if individual motoric subtypes of delirium are associated with worse disability, depression, and/or post-traumatic stress disorder in ICU survivors. DESIGN: Secondary analysis of a prospective multicenter cohort study. SETTING: Academic, community, and Veteran Affairs hospitals. PATIENTS: Adult ICU survivors of respiratory failure and/or shock. INTERVENTIONS: We assessed delirium and level of consciousness using the Confusion Assessment Method-ICU and Richmond Agitation and Sedation Scale daily during hospitalization. We classified delirium as hypoactive (Richmond Agitation and Sedation Scale ≤ 0) or hyperactive (Richmond Agitation and Sedation Scale > 0). At 3- and 12-month postdischarge, we assessed for dependence in activities of daily living and instrumental activities of daily living, symptoms of depression, and symptoms of post-traumatic stress disorder. Adjusting for baseline and inhospital covariates, multivariable regression examined the association of exposure to delirium motoric subtype and long-term outcomes. MEASUREMENTS AND MAIN RESULTS: In our cohort of 556 adults with a median age of 62 years, hypoactive delirium was more common than hyperactive (68.9% vs 16.8%). Dependence on the activities of daily living was present in 37% at 3 months and 31% at 12 months, whereas dependence on instrumental activities of daily living was present in 63% at 3 months and 56% at 12 months. At both time points, depression and post-traumatic stress disorder rates were constant at 36% and 5%, respectively. Each additional day of hypoactive delirium was associated with higher instrumental activities of daily living dependence at 3 months only (0.24 points [95% CI, 0.07-0.41; p = 0.006]). There were no associations between the motoric delirium subtype and activities of daily living dependence, depression, or post-traumatic stress disorder. CONCLUSIONS: Longer duration of hypoactive delirium, but not hyperactive, was associated with a minimal increase in early instrumental activities of daily living dependence scores in adult survivors of critical illness. Motoric delirium subtype was neither associated with early or late activities of daily living functional dependence or mental health outcomes, nor late instrumental activities of daily living functional dependence.