Postoperative delirium is a geriatric syndrome that manifests as changes in cognition, attention, and levels of consciousness after surgery. It occurs in up to 50% of patients after major surgery and is associated with adverse outcomes, including increased hospital length of stay, higher cost of care, higher rates of institutionalization after discharge, and higher rates of readmission. Furthermore, it is associated with functional decline and cognitive impairments after surgery. As the age and medical complexity of our surgical population increases, practitioners need the skills to identify and prevent delirium in this high-risk population. Because delirium is a common and consequential postoperative complication, there has been an abundance of recent research focused on delirium, conducted by clinicians from a variety of specialties. There have also been several reviews and recommendation statements; however, these have not been based on robust evidence. The Sixth Perioperative Quality Initiative (POQI-6) consensus conference brought together a team of multidisciplinary experts to formally survey and evaluate the literature on postoperative delirium prevention and provide evidence-based recommendations using an iterative Delphi process and Grading of Recommendations Assessment, Development and Evaluation (GRADE) Criteria for evaluating biomedical literature.

PURPOSE To compare pulse wave velocity (PWV) measurements obtained from radially undersampled 4D phase-contrast MRI (PC-MRI) with 2DPC measurements and to evaluate four PWV algorithms. MATERIALS AND METHODS PWV was computed from radially undersampled 3-dimensional, 3-directionally velocity-encoded PC-MRI acquisitions performed on a 3T MR scanner in 18 volunteers. High temporal resolution 2DPC scans serving as a reference standard were available in 14 volunteers. Four PWV algorithms were tested: time-to-upstroke (TTU), time-to-peak (TTP), time-to-foot (TTF), and cross-correlation (XCorr). Bland-Altman analysis was used to determine inter- and intraobserver reproducibility and to compare differences between algorithms. Differences in age and PWV measurements were analyzed with Student’s t-tests. The variability of age-corrected data was assessed with a Brown-Forsythe ANOVA test. RESULTS 2D (4.6–5.3m/s) and 4D (3.8–4.8m/s) PWV results were in agreement with previously reported values in healthy subjects. Of the four PWV algorithms, the TTU, TTF, and XCorr algorithms gave similar and reliable results. Average biases of +0.30m/s and −0.01m/s were determined for intra- and interobserver variability, respectively. The Brown-Forsythe test revealed that no differences in variability could be found between 2D and 4D PWV measurements. CONCLUSION 4D PC-MRI with radial undersampling provides reliable and reproducible measurements of PWV. TTU, TTF, and XCorr were the preferred PWV algorithms.

Background The isolated forearm technique allows assessment of consciousness of the external world (connected consciousness) through a verbal command to move the hand (of a tourniquet-isolated arm) during intended general anesthesia. Previous isolated forearm technique data suggest that the incidence of connected consciousness may approach 37% after a noxious stimulus. The authors conducted an international, multicenter, pragmatic study to establish the incidence of isolated forearm technique responsiveness after intubation in routine practice. Methods Two hundred sixty adult patients were recruited at six sites into a prospective cohort study of the isolated forearm technique after intubation. Demographic, anesthetic, and intubation data, plus postoperative questionnaires, were collected. Univariate statistics, followed by bivariate logistic regression models for age plus variable, were conducted. Results The incidence of isolated forearm technique responsiveness after intubation was 4.6% (12/260); 5 of 12 responders reported pain through a second hand squeeze. Responders were younger than nonresponders (39 ± 17 vs. 51 ± 16 yr old; P = 0.01) with more frequent signs of sympathetic activation (50% vs. 2.4%; P = 0.03). No participant had explicit recall of intraoperative events when questioned after surgery (n = 253). Across groups, depth of anesthesia monitoring values showed a wide range; however, values were higher for responders before (54 ± 20 vs. 42 ± 14; P = 0.02) and after (52 ± 16 vs. 43 ± 16; P = 0.02) intubation. In patients not receiving total intravenous anesthesia, exposure to volatile anesthetics before intubation reduced the odds of responding (odds ratio, 0.2 [0.1 to 0.8]; P = 0.02) after adjustment for age. Conclusions Intraoperative connected consciousness occurred frequently, although the rate is up to 10-times lower than anticipated. This should be considered a conservative estimate of intraoperative connected consciousness.

The confusion assessment method for the intensive care unit (CAM-ICU) and intensive care delirium screening checklist (ICDSC) for the diagnosis of delirium: a systematic review and metaanalysis of clinical studies. Crit Care 2012; 16: R115 21. van Eijk MM, van den Boogaard M, van Marum RJ, et al. Routine use of the confusion assessment method for the intensive care unit: a multicenter study.

BACKGROUND: Pharmacologic agents are frequently utilized for management of intensive care unit (ICU) delirium, yet prescribing patterns and impact of medication choices on patient outcomes are poorly described. We sought to describe prescribing practices for management of ICU delirium and investigate the independent association of medication choice on key in-hospital outcomes including delirium resolution, in-hospital mortality, and days alive and free of the ICU or hospital. METHODS: A retrospective study of delirious adult ICU patients at a tertiary academic medical center. Data were obtained regarding daily mental status (normal, delirious, and comatose), pharmacologic treatment, hospital course, and survival via electronic health record. Daily transition models were constructed to assess the independent association of previous day mental status and medication administration on mental status the following day and in-hospital mortality, after adjusting for prespecified covariates. Linear regression models investigated the association of medication administration on days alive and free of the ICU or the hospital during the first 30 days after ICU admission. RESULTS: We identified 8591 encounters of ICU delirium. Half (45.6%) of patients received pharmacologic treatment for delirium, including 45.4% receiving antipsychotics, 2.2% guanfacine, and 0.84% valproic acid. Median highest Richmond Agitation-Sedation Scale (RASS) score was 1 (0, 1) in patients initiated on medications and 0 (−1, 0) for nonrecipients. Haloperidol, olanzapine, and quetiapine comprised >97% of antipsychotics utilized with 48% receiving 2 or more and 20.6% continued on antipsychotic medications at hospital discharge. Haloperidol and olanzapine were associated with greater odds of continued delirium (odds ratio [OR], 1.48; 95% confidence interval [95% CI], 1.30-1.65; P < .001 and OR, 1.37; 95% CI, 1.20-1.56; P = .003, respectively) and increased hazard of in-hospital mortality (hazard ratio [HR], 1.46; 95% CI, 1.10-1.93; P = .01 and HR, 1.67; 95% CI, 1.14-2.45; P = .01, respectively) while quetiapine showed a decreased hazard of in-hospital mortality (HR, 0.58; 95% CI, 0.40-0.84; P = .01). Haloperidol, olanzapine, and quetiapine were associated with fewer days alive and free of hospitalization (all P < .001). There was no significant association of any antipsychotic medication with days alive and free of the ICU. Neither guanfacine nor valproic acid were associated with in-hospital outcomes examined. CONCLUSIONS: Pharmacologic interventions for management of ICU delirium are common, most often with antipsychotics, and frequently continued at hospital discharge. These medications may not portend benefit, may introduce additional harm, and should be used with caution for delirium management. Continuation of these medications through hospitalization and discharge draws into question their safety and role in patient recovery.

Purpose of review: This review aims to describe the clinical impact and assessment tools capable of identifying delirium in cardiac arrest survivors as well as providing strategies aimed at preventing and treating delirium. Recent findings: Patient factors leading to a cardiac arrest, initial resuscitation efforts, and postresuscitation management all influence the potential for recovery as well as the risk for development of delirium. Data suggests that delirium in cardiac arrest survivors is an independent risk factor for morbidity and mortality. Recognizing delirium in post-cardiac arrest patients can be challenging, however, detection is not only achievable, but important as it may aid in predicting adverse outcomes. Serial neurologic examinations and delirium assessments, targeting light sedation when possible, limiting psychoactive medications, and initiating patient care bundles are important care aspects for not only allowing early identification of primary and secondary brain injury, but in improving patient morbidity and mortality. Summary: Developing delirium after cardiac arrest is associated with increased morbidity and mortality. The importance of addressing modifiable risk factors, recognizing symptoms early, and initiating coordinated treatment strategies can help to improve outcomes within this high risk population.

brain oxygen saturation somewhere else on the body, and then to make the assumption that these uncalibrated, off-label measurements offer more useful information than those derived from the measurement site for which the device was primarily developed. It is acknowledged that-despite the findings of many monocentric studies! 3,4-a recent multicentre study in cardiac surgical patients did not find an association between decreased perioperative cerebral oxygen saturation and poor outcomes. 5 Although NIRS sensors have been applied to various parts of the human body in observational studies with often promising results (for overview, see Bickler and colleagues), 1 many of these studies were performed with devices that have been specifically designed for use at peripheral sites 1 6 and not with cerebral oximeter probes. Before going more deeply into somatic monitoring (using cerebral sensors), it may be wise to focus more thoroughly on use of this technology for the indication for which it was primarily developed, applying the technology appropriately (including baseline values for cerebral oximetry), and taking meticulous care of potential confounders. Sometimes it is hard to walk slowly, but on complex ground this is often the only way ultimately to reach a goal. Declaration of interest M.H. has received honoraria for scientific advice and lectures from Covidien/Medtronic (Boulder, CO, USA), Orion Pharma (Hamburg, Germany) and Amomed Pharma (Vienna, Austria), and scientific support from CAS Medical Systems (Branford, CT, USA). He is a steering board member of the LEVO-CTS trial sponsored by Tenax. H.M. has received a grant from the University of Lü beck for scientific work on the use of cerebral oximetry in patients with stroke and reports honoraria for lectures from CLS Behring (Marburg, Germany).

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.