The Association of Plasma Leptin, Soluble Leptin Receptor and Total and High-Molecular Weight Adiponectin With the Risk of Perioperative Neurocognitive Disorders.

BACKGROUND: Perioperative neurocognitive disorders (NCD) are poorly characterized in terms of their risk factor profiles. Leptin and adiponectin are adipose-tissue-derived hormones with a role in inflammation and atherosclerosis whose function in perioperative NCD is unclear. Here, we used a cohort of older adults to examine the association of preoperative plasma concentrations of these biomarkers with the risk of perioperative NCD. METHODS: Prospective analysis of 768 participants aged ≥ 65 years of the BioCog study. Blood was collected before surgery for measurement of plasma total and high-molecular-weight (hmw) adiponectin, leptin, and soluble leptin receptor (sOB-R). The free leptin index (FLI, leptin:sOB-R) was calculated. Postoperative delirium (POD) was assessed twice daily until postoperative day 7/discharge. Five hundred twenty-six patients (68.5%) returned for 3-month follow-up and provided data on postoperative cognitive dysfunction (POCD). POCD was defined as a decline on six neuropsychological tests that exceeded that of a nonsurgical control group. Logistic regression analyses examined the associations of each exposure with POD and POCD risk, in separate models adjusted for age, sex, fasting, surgery type, and body mass index (BMI). RESULTS: Of 768 patients, 152 (19.8%) developed POD. Of 526 attendants of the follow-up, 54 (10.3%) had developed POCD. Leptin, sOB-R, and total and hmw adiponectin were each not associated with POD. For POCD, we observed reduced risk in patients in FLI quartile 4 compared with quartile 1 (odds ratio, 0.26; 95% CI 0.08, 0.89). Sensitivity analyses for the outcome POD revealed statistically significant interaction terms of sOB-R and total adiponectin with obesity (BMI≥30kg/m2 versus BMI<30kg/m2). For the outcome POCD, a higher sOB-R was associated with an increased risk in the obese subgroup (odds ratio, 4.00; 95% CI 1.01, 15.86). CONCLUSIONS: We did not find consistent evidence for the role of leptin, its receptor, and total and hmw adiponectin in POD and POCD risk. Future research should be used to support or refute our findings and to fully characterize any differences in the associations of these hormones with POD/POCD between obese and nonobese individuals.

DeltaScan for the Assessment of Acute Encephalopathy and Delirium in ICU and non-ICU Patients, a Prospective Cross-Sectional Multicenter Validation Study.

OBJECTIVES: To measure the diagnostic accuracy of DeltaScan: a portable real-time brain state monitor for identifying delirium, a manifestation of acute encephalopathy (AE) detectable by polymorphic delta activity (PDA) in single-channel electroencephalograms (EEGs). DESIGN: Prospective cross-sectional study. SETTING: Six Intensive Care Units (ICU's) and 17 non-ICU departments, including a psychiatric department across 10 Dutch hospitals. PARTICIPANTS: 494 patients, median age 75 (IQR:64-87), 53% male, 46% in ICUs, 29% delirious. MEASUREMENTS: DeltaScan recorded 4-minute EEGs, using an algorithm to select the first 96 seconds of artifact-free data for PDA detection. This algorithm was trained and calibrated on two independent datasets. METHODS: Initial validation of the algorithm for AE involved comparing its output with an expert EEG panel's visual inspection. The primary objective was to assess DeltaScan's accuracy in identifying delirium against a delirium expert panel's consensus. RESULTS: DeltaScan had a 99% success rate, rejecting 6 of the 494 EEG's due to artifacts. Performance showed and an Area Under the Receiver Operating Characteristic Curve (AUC) of 0.86 (95% CI: 0.83-0.90) for AE (sensitivity: 0.75, 95%CI=0.68-0.81, specificity: 0.87 95%CI=0.83-0.91. The AUC was 0.71 for delirium (95%CI=0.66-0.75, sensitivity: 0.61 95%CI=0.52-0.69, specificity: 72, 95%CI=0.67-0.77). Our validation aim was an NPV for delirium above 0.80 which proved to be 0.82 (95%CI: 0.77-0.86). Among 84 non-delirious psychiatric patients, DeltaScan differentiated delirium from other disorders with a 94% (95%CI: 87-98%) specificity. CONCLUSIONS: DeltaScan can diagnose AE at bedside and shows a clear relationship with clinical delirium. Further research is required to explore its role in predicting delirium-related outcomes.

The risk of delirium after sedation with propofol or midazolam in intensive care unit patients.

AIM: Knowledge of risk factors may provide strategies to reduce the high burden of delirium in intensive care unit (ICU) patients. We aimed to compare the risk of delirium after deep sedation with propofol versus midazolam in ICU patients. METHODS: In this prospective cohort study, ICU patients who were in an unarousable state for ≥24 h due to continuous sedation with propofol and/or midazolam were included. Patients admitted ≤24 h, those with an acute neurological disorder and those receiving palliative sedation were excluded. ICU patients were assessed daily for delirium during the 7 days following an unarousable state due to continuous sedation. RESULTS: Among 950 included patients, 605 (64%) subjects were delirious during the 7 days after awaking. The proportion of subsequent delirium was higher after midazolam sedation (152/207 [73%] patients) and after both propofol and midazolam sedation (257/377 [68%] patients), compared to propofol sedation only (196/366 [54%] patients). Midazolam sedation (adjusted cause-specific hazard ratio [adj. cause-specific HR] 1.32, 95% confidence interval [CI] 1.05-1.66) and propofol and midazolam sedation (adj. cause-specific HR 1.29, 95% CI 1.06-1.56) were associated with a higher risk of subsequent delirium compared to propofol sedation only. CONCLUSION: This study among sedated ICU patients suggests that, compared to propofol sedation, midazolam sedation is associated with a higher risk of subsequent delirium. This risk seems more apparent in patients with high cumulative midazolam intravenous doses. Our findings underpin the recommendations of the Society of Critical Care Medicine Pain, Agitation/sedation, Delirium, Immobility (rehabilitation/mobilization), and Sleep (disruption) guidelines to use propofol over benzodiazepines for sedation in ICU patients.

How to manage catatonia, Parkinson and dementia in ICU.

PURPOSE OF REVIEW: The rising prevalence of neurodegenerative and mental disorders, combined with the challenges posed by their frailty, has presented intensivists with complex issues in the intensive care unit (ICU). This review article explores specific aspects of care for patients with catatonia, Parkinson's disease (PD), and dementia within the context of the ICU, shedding light on recent developments in these fields. RECENT FINDINGS: Catatonia, a neuropsychiatric syndrome with potentially life-threatening forms, remains underdiagnosed, and its etiologies are diverse. PD patients in the ICU present unique challenges related to admission criteria, dopaminergic treatment, and respiratory care. Dementia increases the risk of delirium. Delirium is associated with long-term cognitive impairment and dementia. SUMMARY: While evidence is lacking, further research is needed to guide treatment for ICU patients with these comorbidities.

Changes in quality of life 1 year after intensive care: a multicenter prospective cohort of ICU survivors.

BACKGROUND: With survival rates of critical illness increasing, quality of life measures are becoming an important outcome of ICU treatment. Therefore, to study the impact of critical illness on quality of life, we explored quality of life before and 1 year after ICU admission in different subgroups of ICU survivors. METHODS: Data from an ongoing prospective multicenter cohort study, the MONITOR-IC, were used. Patients admitted to the ICU in one of eleven participating hospitals between July 2016 and June 2021 were included. Outcome was defined as change in quality of life, measured using the EuroQol five-dimensional (EQ-5D-5L) questionnaire, and calculated by subtracting the EQ-5D-5L score 1 day before hospital admission from the EQ-5D-5L score 1 year post-ICU. Based on the minimal clinically important difference, a change in quality of life was defined as a change in EQ-5D-5L score of ≥ 0.08. Subgroups of patients were based on admission diagnosis. RESULTS: A total of 3913 (50.6%) included patients completed both baseline and follow-up questionnaires. 1 year post-ICU, patients admitted after a cerebrovascular accident, intracerebral hemorrhage, or (neuro)trauma, on average experienced a significant decrease in quality of life. Conversely, 11 other subgroups of ICU survivors reported improvements in quality of life. The largest average increase in quality of life was seen in patients admitted due to respiratory disease (mean 0.17, SD 0.38), whereas the largest average decrease was observed in trauma patients (mean -0.13, SD 0.28). However, in each of the studied 22 subgroups there were survivors who reported a significant increase in QoL and survivors who reported a significant decrease in QoL. CONCLUSIONS:  This large prospective multicenter cohort study demonstrated the diversity in long-term quality of life between, and even within, subgroups of ICU survivors. These findings emphasize the need for personalized information and post-ICU care. TRIAL REGISTRATION: The MONITOR-IC study was registered at ClinicalTrials.gov: NCT03246334 on August 2nd 2017.

A Biopsychosocial Approach to Persistent Post-COVID-19 Fatigue and Cognitive Complaints: Results of the Prospective Multicenter NeNeSCo Study.

OBJECTIVE: To evaluate whether psychological and social factors complement biomedical factors in understanding post-COVID-19 fatigue and cognitive complaints. Additionally, to incorporate objective (neuro-cognitive) and subjective (patient-reported) variables in identifying factors related to post-COVID-19 fatigue and cognitive complaints. DESIGN: Prospective, multicenter cohort study. SETTING: Six Dutch hospitals. PARTICIPANTS: 205 initially hospitalized (March-June 2020), confirmed patients with SARS-CoV-2, aged ≥18 years, physically able to visit the hospital, without prior cognitive deficit, magnetic resonance imaging (MRI) contraindication, or severe neurologic damage post-hospital discharge (N=205). INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Nine months post-hospital discharge, a 3T MRI scan and cognitive testing were performed and patients completed questionnaires. Medical data were retrieved from medical dossiers. Hierarchical regression analyses were performed on fatigue severity (Fatigue Severity Scale; FSS) and cognitive complaints (Cognitive Consequences after Intensive Care Admission; CLC-IC; dichotomized into CLC-high/low). Variable blocks: (1) Demographic and premorbid factors (sex, age, education, comorbidities), (2) Illness severity (ICU/general ward, PROMIS physical functioning [PROMIS-PF]), (3) Neuro-cognitive factors (self-reported neurological symptoms, MRI abnormalities, cognitive performance), (4) Psychological and social factors (Hospital Anxiety and Depression Scale [HADS], Utrecht Coping List, Social Support List), and (5) Fatigue or cognitive complaints. RESULTS: The final models explained 60% (FSS) and 48% (CLC-IC) variance, with most blocks (except neuro-cognitive factors for FSS) significantly contributing. Psychological and social factors accounted for 5% (FSS) and 11% (CLC-IC) unique variance. Higher FSS scores were associated with younger age (P=.01), lower PROMIS-PF (P<.001), higher HADS-Depression (P=.03), and CLC-high (P=.04). Greater odds of CLC-high were observed in individuals perceiving more social support (OR=1.07, P<.05). CONCLUSIONS: Results show that psychological and social factors add to biomedical factors in explaining persistent post-COVID-19 fatigue and cognitive complaints. Objective neuro-cognitive factors were not associated with symptoms. Findings highlight the importance of multidomain treatment, including psychosocial care, which may not target biologically-rooted symptoms directly but may reduce associated distress.

Structural disconnectivity in postoperative delirium: A perioperative two-center cohort study in older patients.

BACKGROUND: Structural disconnectivity was found to precede dementia. Global white matter abnormalities might also be associated with postoperative delirium (POD). METHODS: We recruited older patients (≥65 years) without dementia that were scheduled for major surgery. Diffusion kurtosis imaging metrics were obtained preoperatively, after 3 and 12 months postoperatively. We calculated fractional anisotropy (FA), mean diffusivity (MD), mean kurtosis (MK), and free water (FW). A structured and validated delirium assessment was performed twice daily. RESULTS: Of 325 patients, 53 patients developed POD (16.3%). Preoperative global MD (standardized beta 0.27 [95% confidence interval [CI] 0.21-0.32] p < 0.001) was higher in patients with POD. Preoperative global MK (-0.07 [95% CI -0.11 to (-0.04)] p < 0.001) and FA (0.07 [95% CI -0.10 to (-0.04)] p < 0.001) were lower. When correcting for baseline diffusion, postoperative MD was lower after 3 months (0.05 [95% CI -0.08 to (-0.03)] p < 0.001; n = 183) and higher after 12 months (0.28 [95% CI 0.20-0.35] p < 0.001; n = 45) among patients with POD. DISCUSSION: Preoperative structural disconnectivity was associated with POD. POD might lead to white matter depletion 3 and 12 months after surgery.

Perioperative Levels of IL8 and IL18, but not IL6, are Associated with Nucleus Basalis Magnocellularis Atrophy Three Months after Surgery.

Past studies have observed that brain atrophy may accelerate after surgical procedures. Furthermore, an association of systemic inflammation with neurodegeneration has been described. We hypothesize that postoperative interleukin (IL) levels in circulation as well as the perioperative change in interleukin levels are associated with increased postoperative atrophy in the Nucleus basalis magnocellularis (of Meynert, NBM) which is the major source of cortical acetylcholine. We analyzed data from the BioCog cohort which included patients ≥ 65 years presenting for elective major surgery (≥ 60min). Blood samples were taken before surgery and on the first postoperative day. Magnetic resonance imaging of the brain and neuropsychological assessments were conducted before surgery and after three months follow-up. We used linear regression analysis to determine the association of three interleukins (IL6, IL8 and IL18) with NBM atrophy (in % volume change from baseline before surgery to follow-up), as well as to examine the associations of NBM atrophy and volume with postoperative cognitive ability and perioperative cognitive change. Receiver-operating curves were used to determine the prognostic value of preoperative interleukin levels. For IL8 (N = 97) and IL18 (N = 217), but not IL6 (N = 240), we observed significant associations of higher postoperative IL levels at the first postoperative day with higher NBM atrophy at three months after surgery. Subsequent analyses suggested that in both IL8 and IL18, this association was driven by a more general association of chronically elevated IL levels and NBM atrophy, reflected by preoperative IL concentrations, rather than IL response to surgery, measured as the difference between pre- and postoperative IL concentrations. At follow-up, NBM volume was positively associated with the level of cognitive performance, but NBM atrophy was not significantly related to perioperative cognitive change. Prognostic value of preoperative IL concentrations for NBM atrophy was low. Our results suggest that an association of postoperative interleukin levels with NBM atrophy is driven by preoperatively elevated interleukins due to pre-existing inflammation, rather than perioperative change in interleukin levels in response to surgery and anesthesia. The BioCog study has been registered at clinicaltrials.gov on Oct 15, 2014 (NCT02265263).

Prevalence and trajectories of neuropsychological post-COVID-19 symptoms in initially hospitalized patients.

OBJECTIVE: To investigate the prevalence and trajectories of post-COVID-19 neuropsychological symptoms. DESIGN: Prospective longitudinal multicentre cohort study. SUBJECTS: A total of 205 patients initially hospitalized with SARS-CoV-2 (COVID-19). METHODS: Validated questionnaires were administered at 9 months (T1) and 15 months (T2) post-hospital discharge to assess fatigue, cognitive complaints, insomnia, anxiety, depression, and post-traumatic stress symptoms. RESULTS: Analyses included 184 out of 205 patients. Approximately 50% experienced high cognitive complaints at T1 and T2, while severe fatigue affected 52.5% at T1 and 55.6% at T2. Clinically relevant insomnia scores were observed in 25% of patients at both time-points. Clinically relevant anxiety scores were present in 18.3% at T1 and 16.7% at T2, depression in 15.0% at T1 and 18.9% at T2, and PTSD in 12.4% at T1 and 11.8% at T2. Most symptoms remained stable, with 59.2% of patients experiencing at least 1 persistent symptom. In addition, 31.5% of patients developed delayed-onset symptoms. CONCLUSION: Post-COVID-19 cognitive complaints and fatigue are highly prevalent and often persist. A subgroup develops delayed symptoms. Emotional distress is limited. Screening can help identify most patients experiencing long-term problems. Future research should determine risk factors for persistent and delayed onset symptoms.

Whole blood thiamine, intravenous thiamine supplementation and delirium occurrence in the intensive care unit: retrospective cohort analyses.

BACKGROUND: Thiamine di-phosphate is an essential cofactor in glucose metabolism, glutamate transformation and acetylcholinesterase activity, pathways associated with delirium occurrence. We hypothesised that a deficiency in whole blood thiamine and intravenous thiamine supplementation could impact delirium occurrence. AIM: To establish whether a deficiency in whole blood thiamine and/or intravenous thiamine supplementation within 72 h of intensive care admission is associated with delirium occurrence. METHOD: The first dataset was secondary analysis of a previous study in an intensive care unit in the Netherlands, reported in 2017. The second dataset contained consecutive intensive care admissions 2 years before (period 1: October 2014 to October 2016) and after (period 2: April 2017 to April 2019) routine thiamine supplementation was introduced within 72 h of admission. Delirium was defined as a positive Confusion Assessment Method-Intensive Care Unit score(s) in 24 h. RESULTS: Analysis of the first dataset (n = 57) using logistic regression showed no relationship between delirium and sepsis or whole blood thiamine, but a significant association with age (p = 0.014). In the second dataset (n = 3074), 15.1% received IV thiamine in period 1 and 62.6% during period 2. Hierarchical regression analysis reported reduction in delirium occurrence in the second period; this did not reach statistical significance, OR = 0.81 (95% CI 0.652-1.002); p = 0.052. CONCLUSION: No relationship was detected between whole blood thiamine and delirium occurrence on admission, at 24 and 48 h. It remains unclear whether routine intravenous thiamine supplementation during intensive care admission impacts delirium occurrence. Further prospective randomised clinical trials are needed.

International Delirium Pathophysiology & Electrophysiology Network for Data sharing (iDEPEND).

In an era of 'big data', we propose that a collaborative network approach will drive a better understanding of the mechanisms of delirium, and more rapid development of therapies. We have formed the International Delirium Pathophysiology & Electrophysiology Network for Data sharing (iDEPEND) group with a key aim to 'facilitate the study of delirium pathogenesis with electrophysiology, imaging, and biomarkers including data acquisition, analysis, and interpretation'. Our initial focus is on studies of electrophysiology as we anticipate this methodology has great potential to enhance our understanding of delirium. Our article describes this principle and is used to highlight the endeavour to the wider community as we establish key stakeholders and partnerships.

One-year outcomes in COVID-19 and non-COVID-19 intensive care unit survivors.

PURPOSE: To determine differences in one-year multi-domain health outcomes in COVID-19 and non-COVID-19 intensive care unit (ICU) survivors. MATERIALS AND METHODS: Adult ICU survivors treated for COVID-19 were compared to a control group consisting of survivors admitted for respiratory distress due to other causes, i.e. non-COVID-19 ARDS or pneumonia. Occurrence of physical (frailty, fatigue, physical symptoms), mental (anxiety, depression, post-traumatic stress) and cognitive symptoms, and quality of life (QoL) scores were measured, using validated questionnaires, before and one year after ICU treatment. RESULTS: In total, 506 COVID-19 survivors could be compared to 228 non-COVID-19 survivors. At one-year follow-up, COVID-19 ICU survivors had less physical (76.2% vs. 86.9%, p = 0.001) and mental symptoms (32.0% vs. 47.1%, p < 0.001) than the control group. Cognitive symptoms were comparable (22.5% vs. 17.2%, p = 0.12). However, compared to pre-ICU health symptoms and scores, COVID-19 survivors experienced an increase in symptom occurrence rates in all domains and a decrease in QoL, whereas the control group only experienced an increase in mental and cognitive symptoms, with a similar QoL at one-year follow-up. CONCLUSIONS: COVID-19 ICU survivors experience equal or less health problems but a greater decline in QoL one year after ICU admission compared to non-COVID-19 ARDS or pneumonia survivors.

The sensitivity of the Mini-Mental State Examination to detect objective cognitive side-effects induced by electroconvulsive therapy, results from the Dutch ECT Consortium.

BACKGROUND: Monitoring cognitive side-effects following electroconvulsive therapy (ECT) is crucial for balancing side-effects and clinical effectiveness. Unfortunately, evidence-based guidelines on cognitive testing following ECT are lacking. A frequently used test in global ECT practice is the Mini Mental State Examination (MMSE). We examined the change of the MMSE and its performance in identifying a decline in predefined neuropsychological measures sensitive to ECT-induced cognitive changes: verbal recall and verbal fluency. METHODS: The mean MMSE scores pre- and one week post-ECT were compared using a Wilcoxon signed-rank test. The Reliable Change Index was calculated for all cognitive measures to indicate whether an individual's change score from pre- to post-ECT is considered statistically significant. The sensitivity and specificity of the MMSE were calculated. RESULTS: 426 patients with depression from five sites were included from the Dutch ECT Consortium. The mean MMSE increased significantly from 26.2 (SD=3.9) pre-ECT to 26.8 (SD=3.8) post-ECT (p=0.002). 36 patients (8.5%) showed a significant decline in MMSE score post-ECT. The sensitivity of the MMSE in identifying patients who experienced a significant decline in verbal recall or verbal fluency ranged from 3.6% to 11.1%. The specificity of the MMSE in identifying patients who did not experience a significant decline in verbal recall or verbal fluency ranged from 95.6% to 96.6%. CONCLUSIONS: Given the very low sensitivity of the MMSE, we propose reconsidering the prominence of the MMSE in ECT practice and cognitive monitoring guidelines, advocating for a more comprehensive approach to assess ECT-induced cognitive changes.

The Delphi Delirium Management Algorithms. A practical tool for clinicians, the result of a modified Delphi expert consensus approach.

Delirium is common in hospitalised patients, and there is currently no specific treatment. Identifying and treating underlying somatic causes of delirium is the first priority once delirium is diagnosed. Several international guidelines provide clinicians with an evidence-based approach to screening, diagnosis and symptomatic treatment. However, current guidelines do not offer a structured approach to identification of underlying causes. A panel of 37 internationally recognised delirium experts from diverse medical backgrounds worked together in a modified Delphi approach via an online platform. Consensus was reached after five voting rounds. The final product of this project is a set of three delirium management algorithms (the Delirium Delphi Algorithms), one for ward patients, one for patients after cardiac surgery and one for patients in the intensive care unit.