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.

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.

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.

Predicting 30-day mortality in intensive care unit patients with ischaemic stroke or intracerebral haemorrhage.

BACKGROUND: Stroke patients admitted to an intensive care unit (ICU) follow a particular survival pattern with a high short-term mortality, but if they survive the first 30 days, a relatively favourable subsequent survival is observed. OBJECTIVES: The development and validation of two prognostic models predicting 30-day mortality for ICU patients with ischaemic stroke and for ICU patients with intracerebral haemorrhage (ICH), analysed separately, based on parameters readily available within 24 h after ICU admission, and with comparison with the existing Acute Physiology and Chronic Health Evaluation IV (APACHE-IV) model. DESIGN: Observational cohort study. SETTING: All 85 ICUs participating in the Dutch National Intensive Care Evaluation database. PATIENTS: All adult patients with ischaemic stroke or ICH admitted to these ICUs between 2010 and 2019. MAIN OUTCOME MEASURES: Models were developed using logistic regressions and compared with the existing APACHE-IV model. Predictive performance was assessed using ROC curves, calibration plots and Brier scores. RESULTS: We enrolled 14 303 patients with stroke admitted to ICU: 8422 with ischaemic stroke and 5881 with ICH. Thirty-day mortality was 27% in patients with ischaemic stroke and 41% in patients with ICH. Important factors predicting 30-day mortality in both ischaemic stroke and ICH were age, lowest Glasgow Coma Scale (GCS) score in the first 24 h, acute physiological disturbance (measured using the Acute Physiology Score) and the application of mechanical ventilation. Both prognostic models showed high discrimination with an AUC 0.85 [95% confidence interval (CI), 0.84 to 0.87] for patients with ischaemic stroke and 0.85 (0.83 to 0.86) in ICH. Calibration plots and Brier scores indicated an overall good fit and good predictive performance. The APACHE-IV model predicting 30-day mortality showed similar performance with an AUC of 0.86 (95% CI, 0.85 to 0.87) in ischaemic stroke and 0.87 (0.86 to 0.89) in ICH. CONCLUSION: We developed and validated two prognostic models for patients with ischaemic stroke and ICH separately with a high discrimination and good calibration to predict 30-day mortality within 24 h after ICU admission. TRIAL REGISTRATION: Trial registration: Dutch Trial Registry ( https://www.trialregister.nl/ ); identifier: NTR7438.

Update of the European Society of Anaesthesiology and Intensive Care Medicine evidence-based and consensus-based guideline on postoperative delirium in adult patients.

Postoperative delirium (POD) remains a common, dangerous and resource-consuming adverse event but is often preventable. The whole peri-operative team can play a key role in its management. This update to the 2017 ESAIC Guideline on the prevention of POD is evidence-based and consensus-based and considers the literature between 01 April 2015, and 28 February 2022. The search terms of the broad literature search were identical to those used in the first version of the guideline published in 2017. POD was defined in accordance with the DSM-5 criteria. POD had to be measured with a validated POD screening tool, at least once per day for at least 3 days starting in the recovery room or postanaesthesia care unit on the day of surgery or, at latest, on postoperative day 1. Recent literature confirmed the pathogenic role of surgery-induced inflammation, and this concept reinforces the positive role of multicomponent strategies aimed to reduce the surgical stress response. Although some putative precipitating risk factors are not modifiable (length of surgery, surgical site), others (such as depth of anaesthesia, appropriate analgesia and haemodynamic stability) are under the control of the anaesthesiologists. Multicomponent preoperative, intra-operative and postoperative preventive measures showed potential to reduce the incidence and duration of POD, confirming the pivotal role of a comprehensive and team-based approach to improve patients' clinical and functional status.

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.

Advancing specificity in delirium: The delirium subtyping initiative.

BACKGROUND: Delirium, a common syndrome with heterogeneous etiologies and clinical presentations, is associated with poor long-term outcomes. Recording and analyzing all delirium equally could be hindering the field's understanding of pathophysiology and identification of targeted treatments. Current delirium subtyping methods reflect clinically evident features but likely do not account for underlying biology. METHODS: The Delirium Subtyping Initiative (DSI) held three sessions with an international panel of 25 experts. RESULTS: Meeting participants suggest further characterization of delirium features to complement the existing Diagnostic and Statistical Manual of Mental Disorders Fifth Edition Text Revision diagnostic criteria. These should span the range of delirium-spectrum syndromes and be measured consistently across studies. Clinical features should be recorded in conjunction with biospecimen collection, where feasible, in a standardized way, to determine temporal associations of biology coincident with clinical fluctuations. DISCUSSION: The DSI made recommendations spanning the breadth of delirium research including clinical features, study planning, data collection, and data analysis for characterization of candidate delirium subtypes. HIGHLIGHTS: Delirium features must be clearly defined, standardized, and operationalized. Large datasets incorporating both clinical and biomarker variables should be analyzed together. Delirium screening should incorporate communication and reasoning.

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.

Neurological and (neuro)psychological sequelae in intensive care and general ward COVID-19 survivors.

BACKGROUND AND PURPOSE: Coronavirus disease 2019 (COVID-19) affects the brain, leading to long-term complaints. Studies combining brain abnormalities with objective and subjective consequences are lacking. Long-term structural brain abnormalities, neurological and (neuro)psychological consequences in COVID-19 patients admitted to the intensive care unit (ICU) or general ward were investigated. The aim was to create a multidisciplinary view on the impact of severe COVID-19 on functioning and to compare long-term consequences between ICU and general ward patients. METHODS: This multicentre prospective cohort study assessed brain abnormalities (3 T magnetic resonance imaging), cognitive dysfunction (neuropsychological test battery), neurological symptoms, cognitive complaints, emotional distress and wellbeing (self-report questionnaires) in ICU and general ward (non-ICU) survivors. RESULTS: In al, 101 ICU and 104 non-ICU patients participated 8-10 months post-hospital discharge. Significantly more ICU patients exhibited cerebral microbleeds (61% vs. 32%, p < 0.001) and had higher numbers of microbleeds (p < 0.001). No group differences were found in cognitive dysfunction, neurological symptoms, cognitive complaints, emotional distress or wellbeing. The number of microbleeds did not predict cognitive dysfunction. In the complete sample, cognitive screening suggested cognitive dysfunction in 41%, and standard neuropsychological testing showed cognitive dysfunction in 12%; 62% reported ≥3 cognitive complaints. Clinically relevant scores of depression, anxiety and post-traumatic stress were found in 15%, 19% and 12%, respectively; 28% experienced insomnia and 51% severe fatigue. CONCLUSION: Coronavirus disease 2019 ICU survivors had a higher prevalence for microbleeds but not for cognitive dysfunction compared to general ward survivors. Self-reported symptoms exceeded cognitive dysfunction. Cognitive complaints, neurological symptoms and severe fatigue were frequently reported in both groups, fitting the post-COVID-19 syndrome.

Clinical response following hypertension induction for clinical delayed cerebral ischemia following subarachnoid hemorrhage: A retrospective, multicenter, cohort study.

BACKGROUND: Hypertension induction (HTI) is often used for treating delayed cerebral ischemia (DCI) following aneurysmal subarachnoid hemorrhage (aSAH); however, high-quality studies on its efficacy are lacking. We studied immediate and 3-/6-month clinical efficacy of HTI in aSAH patients with clinical DCI. METHODS: A retrospective, multicenter, comparative, observational cohort study in aSAH patients with clinical deterioration due to DCI, admitted to three tertiary referral hospitals in the Netherlands from 2015 to 2019. Two hospitals used a strategy of HTI (HTI group) and one hospital had no such strategy (control group). We calculated adjusted relative risks (aRR) using Poisson regression analyses for the two primary (clinical improvement of DCI symptoms at days 1 and 5 after DCI onset) and secondary outcomes (DCI-related cerebral infarction, in-hospital mortality, and poor clinical outcome [modified Rankin Scale 4-6] assessed at 3 or 6 months), using the intention-to-treat principle. We also performed as-treated and per-protocol analyses. RESULTS: The aRR for clinical improvement on day 1 after DCI in the HTI group was 1.63 (95% CI 1.17-2.27) and at day 5 after DCI 1.04 (95% CI 0.84-1.29). Secondary outcomes were comparable between the groups. The as-treated and per-protocol analyses yielded similar results. CONCLUSIONS: No clinical benefit of HTI is observed 5 days after DCI due to spontaneous reversal of DCI symptoms in patients treated without HTI. The 3-/6-month clinical outcome was similar for both groups. Therefore, these data suggest that one may consider to not apply HTI in aSAH patients with clinical DCI.

Efficacy of haloperidol to decrease the burden of delirium in adult critically ill patients: the EuRIDICE randomized clinical trial.

BACKGROUND: The role of haloperidol as treatment for ICU delirium and related symptoms remains controversial despite two recent large controlled trials evaluating its efficacy and safety. We sought to determine whether haloperidol when compared to placebo in critically ill adults with delirium reduces days with delirium and coma and improves delirium-related sequelae. METHODS: This multi-center double-blind, placebo-controlled randomized trial at eight mixed medical-surgical Dutch ICUs included critically ill adults with delirium (Intensive Care Delirium Screening Checklist ≥ 4 or a positive Confusion Assessment Method for the ICU) admitted between February 2018 and January 2020. Patients were randomized to intravenous haloperidol 2.5 mg or placebo every 8 h, titrated up to 5 mg every 8 h if delirium persisted until ICU discharge or up to 14 days. The primary outcome was ICU delirium- and coma-free days (DCFDs) within 14 days after randomization. Predefined secondary outcomes included the protocolized use of sedatives for agitation and related behaviors, patient-initiated extubation and invasive device removal, adverse drug associated events, mechanical ventilation, ICU length of stay, 28-day mortality, and long-term outcomes up to 1-year after randomization. RESULTS: The trial was terminated prematurely for primary endpoint futility on DSMB advice after enrolment of 132 (65 haloperidol; 67 placebo) patients [mean age 64 (15) years, APACHE IV score 73.1 (33.9), male 68%]. Haloperidol did not increase DCFDs (adjusted RR 0.98 [95% CI 0.73-1.31], p = 0.87). Patients treated with haloperidol (vs. placebo) were less likely to receive benzodiazepines (adjusted OR 0.41 [95% CI 0.18-0.89], p = 0.02). Effect measures of other secondary outcomes related to agitation (use of open label haloperidol [OR 0.43 (95% CI 0.12-1.56)] and other antipsychotics [OR 0.63 (95% CI 0.29-1.32)], self-extubation or invasive device removal [OR 0.70 (95% CI 0.22-2.18)]) appeared consistently more favorable with haloperidol, but the confidence interval also included harm. Adverse drug events were not different. Long-term secondary outcomes (e.g., ICU recall and quality of life) warrant further study. CONCLUSIONS: Haloperidol does not reduce delirium in critically ill delirious adults. However, it may reduce rescue medication requirements and agitation-related events in delirious ICU patients warranting further evaluation. TRIAL REGISTRATION: ClinicalTrials.gov (#NCT03628391), October 9, 2017.

Metabolic syndrome and the risk of postoperative delirium and postoperative cognitive dysfunction: a multi-centre cohort study.

BACKGROUND: Metabolic syndrome and its components are risk factors for cognitive impairment, but their contribution to perioperative neurocognitive disorders is unknown. We examined their associations with the risk of postoperative delirium (POD) and postoperative cognitive dysfunction (POCD) in older patients. METHODS: In 765 male and female participants aged ≥65 years, we measured preoperative metabolic parameters and screened for POD for 7 days or until discharge. POCD was defined through comparison of cognitive change on six neuropsychological tests with non-surgical controls. Multiple logistic regression analyses examined the association of metabolic parameters with risk of POD and POCD with adjustment for age, sex, and surgery type. RESULTS: A total of 149 patients (19.5% of 765) developed POD and 53 (10.1% of 520 attendees) had POCD at 3 months. Patients with metabolic syndrome were at 1.85-fold higher risk of POD (95% confidence interval [CI] 1.26-2.70). Each 1 mM higher high-density lipoprotein cholesterol (HDL-C) was associated with a 0.47-fold lower POD risk (95% CI 0.30-0.74). Each 1 kg m-2 higher body mass index (BMI) was associated with a 1.09-fold higher POCD risk (95% CI 1.02- 1.16). CONCLUSIONS: Older surgical patients with metabolic syndrome were at increased risk of POD. Only reduced HDL-C was significantly associated with POD. For POCD, a higher preoperative BMI was identified as a risk factor. These findings add to mounting evidence of a distinct epidemiology of POD and POCD. Screening programmes taking advantage of HDL-C and BMI measurements and of metabolic interventions in reducing perioperative neurocognitive disorders should be evaluated. CLINICAL TRIAL REGISTRATION: NCT02265263.

Functional brain network and trail making test changes following major surgery and postoperative delirium: a prospective, multicentre, observational cohort study.

BACKGROUND: Delirium is a frequent complication after surgery in older adults and is associated with an increased risk of long-term cognitive impairment and dementia. Disturbances in functional brain networks were previously reported during delirium. We hypothesised that alterations in functional brain networks persist after remission of postoperative delirium and that functional brain network alterations are associated with long-term cognitive impairment. METHODS: In this prospective, multicentre, observational cohort study, we included older patients who underwent clinical assessments (including the Trail Making Test B [TMT-B]) and resting-state functional MRI (rs-fMRI) before and 3 months after elective surgery. Delirium was assessed on the first seven postoperative days. RESULTS: Of the 554 enrolled patients, 246 remained after strict motion correction, of whom 38 (16%) developed postoperative delirium. The rs-fMRI functional connectivity strength increased 3 months after surgery in the total study population (ß=0.006; 95% confidence interval [CI]: 0.001-0.011; P=0.013), but it decreased after postoperative delirium (ß=-0.015; 95% CI: -0.028 to 0.002; P=0.023). No difference in TMT-B scores was found at follow-up between patients with and without postoperative delirium. Patients with decreased functional connectivity strength declined in TMT-B scores compared with those who did not (ß=11.04; 95% CI: 0.85-21.2; P=0.034). CONCLUSIONS: Postoperative delirium was associated with decreased brain functional connectivity strength after 3 months, suggesting that delirium has a long-lasting impact on brain networks. The decreased connectivity strength was associated with significant cognitive deterioration after major surgery. CLINICAL TRIAL REGISTRATION: NCT02265263.

Opioid Use Increases the Risk of Delirium in Critically Ill Adults Independently of Pain.

Rationale: It is unclear whether opioid use increases the risk of ICU delirium. Prior studies have not accounted for confounding, including daily severity of illness, pain, and competing events that may preclude delirium detection.Objectives: To evaluate the association between ICU opioid exposure, opioid dose, and delirium occurrence.Methods: In consecutive adults admitted for more than 24 hours to the ICU, daily mental status was classified as awake without delirium, delirium, or unarousable. A first-order Markov model with multinomial logistic regression analysis considered four possible next-day outcomes (i.e., awake without delirium, delirium, unarousable, and ICU discharge or death) and 11 delirium-related covariables (baseline: admission type, age, sex, Acute Physiology and Chronic Health Evaluation IV score, and Charlson comorbidity score; daily: ICU day, modified Sequential Organ Failure Assessment, ventilation use, benzodiazepine use, and severe pain). This model was used to quantify the association between opioid use, opioid dose, and delirium occurrence the next day.Measurements and Main Results: The 4,075 adults had 26,250 ICU days; an opioid was administered on 57.0% (n = 14,975), severe pain occurred on 7.0% (n = 1,829), and delirium occurred on 23.5% (n = 6,176). Severe pain was inversely associated with a transition to delirium (odds ratio [OR] 0.72; 95% confidence interval [CI], 0.53-0.97). Any opioid administration in awake patients without delirium was associated with an increased risk for delirium the next day [OR, 1.45; 95% CI, 1.24-1.69]. Each daily 10-mg intravenous morphine-equivalent dose was associated with a 2.4% increased risk for delirium the next day.Conclusions: The receipt of an opioid in the ICU increases the odds of transitioning to delirium in a dose-dependent fashion.

Clinical Outcomes Among Patients With 1-Year Survival Following Intensive Care Unit Treatment for COVID-19.

IMPORTANCE: One-year outcomes in patients who have had COVID-19 and who received treatment in the intensive care unit (ICU) are unknown. OBJECTIVE: To assess the occurrence of physical, mental, and cognitive symptoms among patients with COVID-19 at 1 year after ICU treatment. DESIGN, SETTING, AND PARTICIPANTS: An exploratory prospective multicenter cohort study conducted in ICUs of 11 Dutch hospitals. Patients (N = 452) with COVID-19, aged 16 years and older, and alive after hospital discharge following admission to 1 of the 11 ICUs during the first COVID-19 surge (March 1, 2020, until July 1, 2020) were eligible for inclusion. Patients were followed up for 1 year, and the date of final follow-up was June 16, 2021. EXPOSURES: Patients with COVID-19 who received ICU treatment and survived 1 year after ICU admission. MAIN OUTCOMES AND MEASURES: The main outcomes were self-reported occurrence of physical symptoms (frailty [Clinical Frailty Scale score ≥5], fatigue [Checklist Individual Strength-fatigue subscale score ≥27], physical problems), mental symptoms (anxiety [Hospital Anxiety and Depression {HADS} subscale score ≥8], depression [HADS subscale score ≥8], posttraumatic stress disorder [mean Impact of Event Scale score ≥1.75]), and cognitive symptoms (Cognitive Failure Questionnaire-14 score ≥43) 1 year after ICU treatment and measured with validated questionnaires. RESULTS: Of the 452 eligible patients, 301 (66.8%) patients could be included, and 246 (81.5%) patients (mean [SD] age, 61.2 [9.3] years; 176 men [71.5%]; median ICU stay, 18 days [IQR, 11 to 32]) completed the 1-year follow-up questionnaires. At 1 year after ICU treatment for COVID-19, physical symptoms were reported by 182 of 245 patients (74.3% [95% CI, 68.3% to 79.6%]), mental symptoms were reported by 64 of 244 patients (26.2% [95% CI, 20.8% to 32.2%]), and cognitive symptoms were reported by 39 of 241 patients (16.2% [95% CI, 11.8% to 21.5%]). The most frequently reported new physical problems were weakened condition (95/244 patients [38.9%]), joint stiffness (64/243 patients [26.3%]) joint pain (62/243 patients [25.5%]), muscle weakness (60/242 patients [24.8%]) and myalgia (52/244 patients [21.3%]). CONCLUSIONS AND RELEVANCE: In this exploratory study of patients in 11 Dutch hospitals who survived 1 year following ICU treatment for COVID-19, physical, mental, or cognitive symptoms were frequently reported.

Long-Term Mortality Among ICU Patients With Stroke Compared With Other Critically Ill Patients.

OBJECTIVES: Assessment of all-cause mortality of intracerebral hemorrhage and ischemic stroke patients admitted to the ICU and comparison to the mortality of other critically ill ICU patients classified into six other diagnostic subgroups and the general Dutch population. DESIGN: Observational cohort study. SETTING: All ICUs participating in the Dutch National Intensive Care Evaluation database. PATIENTS: All adult patients admitted to these ICUs between 2010 and 2015; patients were followed until February 2017. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Of all 370,386 included ICU patients, 7,046 (1.9%) were stroke patients, 4,072 with ischemic stroke, and 2,974 with intracerebral hemorrhage. Short-term mortality in ICU-admitted stroke patients was high with 30 days mortality of 31% in ischemic stroke and 42% in intracerebral hemorrhage. In the longer term, the survival curve gradient among ischemic stroke and intracerebral hemorrhage patients stabilized. The gradual alteration of mortality risk after ICU admission was assessed using left-truncation with increasing minimum survival period. ICU-admitted stroke patients who survive the first 30 days after suffering from a stroke had a favorable subsequent survival compared with other diseases necessitating ICU admission such as patients admitted due to sepsis or severe community-acquired pneumonia. After having survived the first 3 months after ICU admission, multivariable Cox regression analyses showed that case-mix adjusted hazard ratios during the follow-up period of up to 3 years were lower in ischemic stroke compared with sepsis (adjusted hazard ratio, 1.21; 95% CI, 1.06-1.36) and severe community-acquired pneumonia (adjusted hazard ratio, 1.57; 95% CI, 1.39-1.77) and in intracerebral hemorrhage patients compared with these groups (adjusted hazard ratio, 1.14; 95% CI, 0.98-1.33 and adjusted hazard ratio, 1.49; 95% CI, 1.28-1.73). CONCLUSIONS: Stroke patients who need intensive care treatment have a high short-term mortality risk, but this alters favorably with increasing duration of survival time after ICU admission in patients with both ischemic stroke and intracerebral hemorrhage, especially compared with other populations of critically ill patients such as sepsis or severe community-acquired pneumonia patients.

Occurrence and Risk Factors of Chronic Pain After Critical Illness.

OBJECTIVES: Occurrence, risk factors, and impact on daily life of chronic pain after critical illness have not been systematically studied. DESIGN: Cohort study. SETTING: A tertiary ICU in The Netherlands. PATIENTS: We surveyed patients who had been discharged from our ICU between 2013 and 2016. Three cohorts were defined as follows: 1) ICU survivors; 2) one-year survivors reporting newly-acquired chronic pain; and (3) one-year survivors with pain who lived within 50 km from the study hospital. In cohort 1, we estimated the prevalence of new chronic pain 1 year after ICU discharge and constructed a prediction model for its occurrence incorporating three outcomes: death during follow-up, surviving without new pain, and surviving with newly-acquired pain. In cohort 2, we determined clinical features of pain and its impact on daily life. In cohort 3, we assessed the presence of neuropathic characteristics of pain. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The three cohorts contained 1,842, 160, and 42 patients, respectively. Estimated occurrence of new chronic pain was 17.7% (95% CI, 15.8-19.8%; n = 242) in 1-year survivors (n = 1,368). Median pain intensity on the numeric rating scale was 4 (interquartile range, 2-6) in the week before survey response, with impact being most evident on activities of daily living, social activities, and mobility. Neuropathic pain features were present in 50% (95% CI, 37-68%) of affected subjects. Among nine predictor variables included in a multinomial model, only female gender and days in ICU with hyperinflammation were associated with pain. CONCLUSIONS: Newly-acquired chronic pain is a frequent consequence of critical illness, and its impact on daily life of affected patients is substantial.

Hallucinations after Cardiac Surgery: A Prospective Observational Study.

Background and Objective: Hallucinations after cardiac surgery can be a burden, but their prevalence and phenomenology have not been studied well. Risk factors for postoperative hallucinations, as well as their relation to delirium are unclear. We aimed to study the prevalence and phenomenology of hallucinations after cardiac surgery, and to study the association between hallucinations and delirium in this population. Materials and Methods: We used the Questionnaire for Psychotic Experiences to detect hallucinations in cardiac surgery patients and a control group of cardiology outpatients. We assessed postoperative delirium with validated instruments. Risk factors for postoperative hallucinations and the association between hallucinations and delirium were analysed using logistic regression. Results: We included 201 cardiac surgery patients and 99 cardiology outpatient controls. Forty-four cardiac surgery patients (21.9%) experienced postoperative hallucinations in the first four postoperative days. This was significantly higher compared to cardiology outpatient controls (n = 4, 4.1%, p < 0.001). Visual hallucinations were the most common type of hallucinations in cardiac surgery patients, and less common in outpatient controls. Cardiac surgery patients who experienced hallucinations were more likely to also have delirium (10/44, 22.7%) compared to patients without postoperative hallucinations (16/157, 10.2% p = 0.03). However, the majority of patients with postoperative hallucinations (34/44, 77.3%) did not develop delirium. Conclusion: After cardiac surgery, hallucinations occurred more frequently than in outpatient controls. Hallucinations after cardiac surgery were most often visual in character. Although postoperative hallucinations were associated with delirium, most patients with hallucinations did not develop delirium.

Influence of sedation on delirium recognition in critically ill patients: A multinational cohort study.

BACKGROUND: Guidelines advocate intensive care unit (ICU) patients be regularly assessed for delirium using either the Confusion Assessment Method for the ICU (CAM-ICU) or the Intensive Care Delirium Screening Checklist (ICDSC). Single-centre studies, primarily with the CAM-ICU, suggest level of sedation may influence delirium screening results. OBJECTIVE: The objective of this study was to determine the association between level of sedation and delirium occurrence in critically ill patients assessed with either the CAM-ICU or the ICDSC. METHODS: This was a secondary analysis of a multinational, prospective cohort study performed in nine ICUs from seven countries. Consecutive ICU patients with a Richmond Agitation-Sedation Scale (RASS) of -3 to 0 at the time of delirium assessment where a RASS ≤ 0 was secondary to a sedating medication. Patients were assessed with either the CAM-ICU or the ICDSC. Logistic regression analysis was used to account for factors with the potential to influence level of sedation or delirium occurrence. RESULTS: Among 1660 patients, 1203 patients underwent 5741 CAM-ICU assessments [9.6% were delirium positive; at RASS = 0 (3.3% were delirium positive), RASS = -1 (19.3%), RASS = -2 (35.1%); RASS = -3 (39.0%)]. The other 457 patients underwent 3210 ICDSC assessments [11.6% delirium positive; at RASS = 0 (4.9% were delirium positive), RASS = -1 (15.8%), RASS = -2 (26.6%); RASS = -3 (20.6%)]. A RASS of -3 was associated with more positive delirium evaluations (odds ratio: 2.31; 95% confidence interval: 1.34-3.98) in the CAM-ICU-assessed patients (vs. the ICDSC-assessed patients). At a RASS of 0, assessment with the CAM-ICU (vs. the ICDSC) was associated with fewer positive delirium evaluations (odds ratio: 0.58; 95% confidence interval: 0.43-0.78). At a RASS of -1 or -2, no association was found between the delirium assessment method used (i.e., CAM-ICU or ICDSC) and a positive delirium evaluation. CONCLUSIONS: The influence of level of sedation on a delirium assessment result depends on whether the CAM-ICU or ICDSC is used. Bedside ICU nurses should consider these results when evaluating their sedated patients for delirium. Future research is necessary to compare the CAM-ICU and the ICDSC simultaneously in sedated and nonsedated ICU patients. TRIAL REGISTRATION: ClinicalTrials.gov; NCT02518646.