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BackgroundPostoperative delirium is prevalent in older adults and has been shown to increase the risk of long-term cognitive decline. Plasma biomarkers to identify the risk for postoperative delirium and the risk of Alzheimer's disease and related dementias are needed.MethodsThis biomarker discovery case-control study aimed to identify plasma biomarkers associated with postoperative delirium. Patients aged ≥65 years undergoing major elective noncardiac surgery were recruited. The preoperative plasma proteome was interrogated with SOMAmer-based technology targeting 1433 biomarkers.ResultsIn 40 patients (20 with vs. 20 without postoperative delirium), a preoperative panel of 12 biomarkers discriminated patients with postoperative delirium with an accuracy of 97.5%. The final model of five biomarkers delivered a leave-one-out cross-validation accuracy of 80%. Represented biological pathways included lysosomal and immune response functions.ConclusionIn older patients who have undergone major surgery, plasma SOMAmer proteomics may provide a relatively non-invasive benchmark to identify biomarkers associated with postoperative delirium.

ObjectivesPrior studies reported incidence of hypoactive and hyperactive subtypes of postoperative delirium, but did not consider cognitive symptoms of delirium which are highlighted in the DSM-5 criteria for delirium. This study aims to address this gap in the literature by classifying cases of delirium according to their constellation of cognitive and motoric symptoms of delirium using a statistical technique called Latent Class Analysis (LCA).MethodsData were from five independent study cohorts (N = 1968) of patients who underwent elective spine, knee/hip, or elective gastrointestinal and thoracic procedures, between 2001 and 2017. Assessments of delirium symptoms were conducted using the long form of the Confusion Assessment Method (CAM) pre- and post-surgery. Latent class analyses of CAM data from the first 2 days after surgery were conducted to determine subtypes of delirium based on patterns of cognitive and motoric symptoms of delirium. We also determined perioperative patient characteristics associated with each latent class of delirium and assessed whether the length of delirium for each of the patterns of delirium symptoms identified by the latent class analysis.ResultsThe latent class model from postoperative day 1 revealed three distinct patterns of delirium symptoms. One pattern of symptoms, denoted as the Hyperalert class, included patients whose predominant symptoms were being hyperalert or overly sensitive to environmental stimuli and having a low level of motor activity. Another pattern of symptoms, denoted as the Hypoalert class, included patients whose predominant symptom was being hypoalert (lethargic or drowsy). A third pattern of symptoms, denoted as the Cognitive Changes class, included patients who experienced new onset of disorganized thinking, memory impairment, and disorientation. Among 352 patients who met CAM criteria for delirium on postoperative day 1, 34% had symptoms that fit within the Hyperalert latent class, 39% had symptoms that fit within the Hypoalert latent class, and 27% had symptoms that fit within the Cognitive Changes latent class. Similar findings were found when latent class analysis was applied to those who met CAM criteria for delirium on postoperative day 2. Multinomial regression analyses revealed that ASA class, surgery type, and preoperative cognitive status as measured by the Telephone Interview for Cognitive Status (TICS) scores were associated with class membership. Length of delirium differed between the latent classes with the Cognitive Changes latent class having a longer duration compared to the other two classes.ConclusionsOlder elective surgery patients who did not have acute events or illnesses or a diagnosis of dementia prior to surgery displayed varying symptoms of delirium after surgery. Compared to prior studies that described hypoactive and hyperactive subtypes of delirium, we identified a novel subtype of delirium that reflects cognitive symptoms of delirium. The three subtypes of delirium reveal distinct patterns of delirium symptoms which provide insight into varying risks and care needs of patients with delirium, indicating the necessity of future research on reducing risk for cognitive symptoms of delirium.

BackgroundThe pathophysiology of delirium is incompletely understood, including what molecular pathways are involved in brain vulnerability to delirium. This study examined whether preoperative plasma neurodegeneration markers were elevated in patients who subsequently developed postoperative delirium through a retrospective case-control study.MethodsInclusion criteria were patients of 65 yr of age or older, undergoing elective noncardiac surgery with a hospital stay of 2 days or more. Concentrations of preoperative plasma P-Tau181, neurofilament light chain, amyloid β1-42 (Aβ42), and glial fibrillary acidic protein were measured with a digital immunoassay platform. The primary outcome was postoperative delirium measured by the Confusion Assessment Method. The study included propensity score matching by age and sex with nearest neighbor, such that each patient in the delirium group was matched by age and sex with a patient in the no-delirium group.ResultsThe initial cohort consists of 189 patients with no delirium and 102 patients who developed postoperative delirium. Of 291 patients aged 72.5 ± 5.8 yr, 50.5% were women, and 102 (35%) developed postoperative delirium. The final cohort in the analysis consisted of a no-delirium group (n = 102) and a delirium group (n = 102) matched by age and sex using the propensity score method. Of the four biomarkers assayed, the median value for neurofilament light chain was 32.05 pg/ml for the delirium group versus 23.7 pg/ml in the no-delirium group. The distribution of biomarker values significantly differed between the delirium and no-delirium groups (P = 0.02 by the Kolmogorov-Smirnov test) with the largest cumulative probability difference appearing at the biomarker value of 32.05 pg/ml.ConclusionsThese results suggest that patients who subsequently developed delirium are more likely to be experiencing clinically silent neurodegenerative changes before surgery, reflected by changes in plasma neurofilament light chain biomarker concentrations, which may identify individuals with a preoperative vulnerability to subsequent cognitive decline.Editor’s perspective

BackgroundAccurate, pragmatic risk stratification for postoperative delirium (POD) is necessary to target preventative resources toward high-risk patients. Machine learning (ML) offers a novel approach to leveraging electronic health record (EHR) data for POD prediction. We sought to develop and internally validate a ML-derived POD risk prediction model using preoperative risk features, and to compare its performance to models developed with traditional logistic regression.MethodsThis was a retrospective analysis of preoperative EHR data from 24,885 adults undergoing a procedure requiring anesthesia care, recovering in the main post-anesthesia care unit, and staying in the hospital at least overnight between December 2016 and December 2019 at either of two hospitals in a tertiary care health system. One hundred fifteen preoperative risk features including demographics, comorbidities, nursing assessments, surgery type, and other preoperative EHR data were used to predict postoperative delirium (POD), defined as any instance of Nursing Delirium Screening Scale ≥2 or positive Confusion Assessment Method for the Intensive Care Unit within the first 7 postoperative days. Two ML models (Neural Network and XGBoost), two traditional logistic regression models ("clinician-guided" and "ML hybrid"), and a previously described delirium risk stratification tool (AWOL-S) were evaluated using the area under the receiver operating characteristic curve (AUC-ROC), sensitivity, specificity, positive likelihood ratio, and positive predictive value. Model calibration was assessed with a calibration curve. Patients with no POD assessments charted or at least 20% of input variables missing were excluded.ResultsPOD incidence was 5.3%. The AUC-ROC for Neural Net was 0.841 [95% CI 0. 816-0.863] and for XGBoost was 0.851 [95% CI 0.827-0.874], which was significantly better than the clinician-guided (AUC-ROC 0.763 [0.734-0.793], p

IntroductionPostoperative delirium is a frequent adverse event following elective non-cardiac surgery. The occurrence of delirium increases the risk of functional impairment, placement to facilities other than home after discharge, cognitive impairment at discharge, as well as in-hospital and possibly long-term mortality. Unfortunately, there is a dearth of effective strategies to minimise the risk from modifiable risk factors, including postoperative pain control and the analgesic regimen. Use of potent opioids, currently the backbone of postoperative pain control, alters cognition and has been associated with an increased risk of postoperative delirium. Literature supports the intraoperative use of lidocaine infusions to decrease postoperative opioid requirements, however, whether the use of postoperative lidocaine infusions is associated with lower opioid requirements and subsequently a reduction in postoperative delirium has not been investigated.Methods and analysisThe Lidocaine Infusion for the Management of Postoperative Pain and Delirium trial is a randomised, double-blinded study of a postoperative 48-hour infusion of lidocaine at 1.33 mg/kg/hour versus placebo in older patients undergoing major reconstructive spinal surgery at the University of California, San Francisco. Our primary outcome is incident delirium measured daily by the Confusion Assessment Method in the first three postoperative days. Secondary outcomes include delirium severity, changes in cognition, pain scores, opioid use, incidence of opioid related side effects and functional benefits including time to discharge and improved recovery from surgery. Lidocaine safety will be assessed with daily screening questionnaires and lidocaine plasma levels.Ethics and disseminationThis study protocol has been approved by the ethics board at the University of California, San Francisco. The results of this study will be published in a peer-review journal and presented at national conferences as poster or oral presentations. Participants wishing to know the results of this study will be contacted directly on data publication.Trial registration numberNCT05010148.

Objectives/backgroundSleep disruption is prevalent in older patients. No previous studies have considered the impact of surgery duration or surgery end time of day on postoperative sleep disruption. Accordingly, we examined the duration of surgery and surgery end times for associations with postoperative sleep disruption.MethodsInclusion criteria were patients ≥ 65 years of age undergoing major, non-cardiac surgery. Sleep disruption was measured by wrist actigraphy and defined as wake after sleep onset (WASO) during the night, or inactivity/sleep time during the day. The sleep opportunity window was set from 22:00 to 06:00 which coincided with "lights off and on" in the hospital. WASO during this 8-hour period on the first postoperative day was categorized into one of three groups: ≤ 15%, 15-25%, and > 25%. Daytime sleep (inactivity) during the first postoperative day was categorized as ≤ 20%, 20-40%, and > 40%. Statistical analyses were conducted to test for associations between surgery duration, surgery end time and sleep disruption on the first postoperative day and following night.ResultsFor this sample of 156 patients, surgery duration ≥ 6 hours and surgery end time after 19:00 were not associated with WASO groups (p = 0.17, p = 0.94, respectively). Furthermore, daytime sleep was also not affected by surgery duration or surgery end time (p = 0.07, p = 0.06 respectively).ConclusionOur hypothesis that patients with longer duration or later-ending operations have increased postoperative sleep disruption was not supported. Our results suggest the pathophysiology of postoperative sleep disruption needs further investigation.

BackgroundWhile specific practices for perioperative care of older adults have been recommended, little is known regarding adherence by US physician anesthesiologists to such practices. To address this gap in knowledge, the ASA Committee on Geriatric Anesthesia and the ASA Perioperative Brain Health Initiative undertook a survey of ASA members to characterize current practices related to perioperative care of older adults.MethodsWe administered a web-based questionnaire with items assessing the proportion of practice focused on delivery of care to older adults, adherence to recommended practices for older surgical patients, resource needs to improve care, and practice characteristics.ResultsResponses were collected between May 24, 2018, and June 29, 2018. A total of 25,587 ASA members were invited to participate, and 1737 answered at least one item (6.8%). 96.4% of respondents reported that they had cared for a patient aged 65 or older within the last year. 47.1% of respondents (95% confidence interval, 44.6%, 49.7%) reported using multimodal analgesia among patients aged 65 and older at least 90% of the time, and 25.5% (95% CI, 23.3%, 27.7%) provided preoperative information regarding postoperative cognitive changes at least 90% of the time. Over 80% of respondents reported that preoperative screening for frailty or dementia, postoperative screening for delirium, and preoperative geriatric consultation occurred in fewer than 10% of cases. Development of practice guidelines for geriatric anesthesia care and expansion of web-based resources were most frequently prioritized by respondents as initiatives to improve care in this domain.DiscussionMost survey respondents reported providing anesthesia care to older adults, but adherence to recommended practices varied across the six items assessed. Reported rates of screening for common geriatric syndromes, such as frailty, delirium, and dementia, were low among survey respondents. Respondents identified multiple opportunities for ASA initiatives to support efforts to improve care for older surgical patients.

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.

BackgroundVolatile Anaesthetics (VAs) may be associated with postoperative delirium (POD). However, to date, the effects of VAs on POD are not completely understood. The objective of this study was to investigate the incidence of POD in different VA groups.MethodsA secondary analysis was conducted using a database created from prospective cohort studies in patients who underwent elective major noncardiac surgery. Patients who received general anaesthesia with desflurane, isoflurane, or sevoflurane were included in the study. POD occurring on either of the first two postoperative days was measured using the Confusion Assessment Method.ResultsFive hundred and thirty-two patients were included in this study, with a mean age of 73.5 ± 6.0 years (range, 65-96 years). The overall incidence of POD on either postoperative day 1 or 2 was 41%. A higher incidence of POD was noted in the desflurane group compared with the isoflurane group (Odds Ratio = 3.35, 95% CI = 1.54-7.28). The incidence of POD between the sevoflurane and isoflurane or desflurane group was not statistically significant.ConclusionEach VA may have different effects on postoperative cognition. Further studies using a prospective randomized approach will be necessary to discern whether anaesthetic type or management affects the occurrence of postoperative delirium.

What we already know about this topicWHAT THIS ARTICLE TELLS US THAT IS NEW: BACKGROUND:: Postoperative delirium complicates approximately 15 to 20% of major operations in patients at least 65 yr old and is associated with adverse outcomes and increased resource utilization. Furthermore, patients with postoperative delirium might also be at risk of developing long-term postoperative cognitive dysfunction. One potentially modifiable variable is use of intraoperative processed electroencephalogram to guide anesthesia. This systematic review and meta-analysis examines the relationship between processed electroencephalogram monitoring and postoperative delirium and cognitive dysfunction.MethodsA systematic search for randomized controlled trials was conducted using Ovid MEDLINE, PubMed, EMBASE, Cochrane Library, and Google search using the keywords processed electroencephalogram, Bispectral Index, postoperative delirium, postoperative cognitive dysfunction. Screening and data extraction were conducted by two independent reviewers, and risk of bias was assessed. Postoperative delirium combined-effect estimates calculated with a fixed-effects model were expressed as odds ratios with 95% CIs.ResultsThirteen of 369 search results met inclusion criteria. Postoperative cognitive dysfunction data were excluded in meta-analysis because of heterogeneity of outcome measurements; results were discussed descriptively. Five studies were included in the quantitative postoperative delirium analysis, with data pooled from 2,654 patients. The risk of bias was low in three studies and unclear for the other two. The use of processed electroencephalogram-guided anesthesia was associated with a 38% reduction in odds for developing postoperative delirium (odds ratio = 0.62; P < 0.001; 95% CI, 0.51 to 0.76).ConclusionsProcessed electroencephalogram-guided anesthesia was associated with a decrease in postoperative delirium. The mechanism explaining this association, however, is yet to be determined. The data are insufficient to assess the relationship between processed electroencephalogram monitoring and postoperative cognitive dysfunction.

BackgroundPostoperative pain and opioid use are associated with postoperative delirium. We designed a single-center, randomized, placebo-controlled, parallel-arm, double-blinded trial to determine whether perioperative administration of gabapentin reduced postoperative delirium after noncardiac surgery.MethodsPatients were randomly assigned to receive placebo (N = 347) or gabapentin 900 mg (N = 350) administered preoperatively and for the first 3 postoperative days. The primary outcome was postoperative delirium as measured by the Confusion Assessment Method. Secondary outcomes were postoperative pain, opioid use, and length of hospital stay.ResultsData for 697 patients were included, with a mean ± SD age of 72 ± 6 yr. The overall incidence of postoperative delirium in any of the first 3 days was 22.4% (24.0% in the gabapentin and 20.8% in the placebo groups; the difference was 3.20%; 95% CI, 3.22% to 9.72%; P = 0.30). The incidence of delirium did not differ between the two groups when stratified by surgery type, anesthesia type, or preoperative risk status. Gabapentin was shown to be opioid sparing, with lower doses for the intervention group versus the control group. For example, the morphine equivalents for the gabapentin-treated group, median 6.7 mg (25th, 75th quartiles: 1.3, 20.0 mg), versus control group, median 6.7 mg (25th, 75th quartiles: 2.7, 24.8 mg), differed on the first postoperative day (P = 0.04).ConclusionsAlthough postoperative opioid use was reduced, perioperative administration of gabapentin did not result in a reduction of postoperative delirium or hospital length of stay.

A diverse group of RNA viruses have the ability to gain access to the central nervous system (CNS) and cause severe neurological disease. Current treatment for people with this type of infection is generally limited to supportive care. To address the need for reliable antivirals, we utilized a strategy of lethal mutagenesis to limit virus replication. We evaluated ribavirin (RBV), favipiravir (FAV) and N4-hydroxycytidine (NHC) against La Crosse virus (LACV), which is one of the most common causes of pediatric arboviral encephalitis cases in North America and serves as a model for viral CNS invasion during acute infection. NHC was approximately 3 to 170 times more potent than RBV or FAV in neuronal cells. Oral administration of molnupiravir (MOV), the prodrug of NHC, decreased neurological disease development (assessed as limb paralysis, ataxia and weakness, repeated seizures, or death) by 31% (4 mice survived out of 13) when treatment was started on the day of infection. MOV also reduced disease by 23% when virus was administered intranasally (IN). NHC and MOV produced less fit viruses by incorporating predominantly G to A or C to U mutations. Furthermore, NHC also inhibited virus production of two other orthobunyaviruses, Jamestown Canyon virus and Cache Valley virus. Collectively, these studies indicate that NHC/MOV has therapeutic potential to inhibit viral replication and subsequent neurological disease caused by orthobunyaviruses and potentially as a generalizable strategy for treating acute viral encephalitis. Author summary: Mutagenic ribonucleosides can be viewed as broadly acting antivirals against RNA viruses. These viruses have small genomes of essential genes and thus are susceptible to enhanced mutation rates as an antiviral strategy. Here we show that the mutagenic ribonucleoside N4-hydroxycytidine (NHC) and its prodrug molnupiravir are active against the negative strand bunyavirus La Crosse Virus. Loss of viral infectivity was proportional to the density of mutations induced by NHC. Using a mouse model, we showed that oral administration of molnupiravir attenuated encephalitis caused by La Crosse virus and resulted in reduced virus titers and less fit virus in the brain. This treatment approach should be widely applicable to acute RNA virus diseases, especially those with high morbidity and an absence of other treatment options. [ABSTRACT FROM AUTHOR]

BackgroundPostoperative delirium is prevalent in older patients and associated with worse outcomes. Recent data in animal studies demonstrate increases in inflammatory markers in plasma and cerebrospinal fluid (CSF) even after aseptic surgery, suggesting that inflammation of the central nervous system may be part of the pathogenesis of postoperative cognitive changes. We investigated the hypothesis that neuroinflammation was an important cause for postoperative delirium and cognitive dysfunction after major non-cardiac surgery.MethodsAfter Institutional Review Board approval and informed consent, we recruited patients undergoing major knee surgery who received spinal anesthesia and femoral nerve block with intravenous sedation. All patients had an indwelling spinal catheter placed at the time of spinal anesthesia that was left in place for up to 24 h. Plasma and CSF samples were collected preoperatively and at 3, 6, and 18 h postoperatively. Cytokine levels were measured using ELISA and Luminex. Postoperative delirium was determined using the confusion assessment method, and cognitive dysfunction was measured using validated cognitive tests (word list, verbal fluency test, digit symbol test).ResultsTen patients with complete datasets were included. One patient developed postoperative delirium, and six patients developed postoperative cognitive dysfunction. Postoperatively, at different time points, statistically significant changes compared to baseline were present in IL-5, IL-6, I-8, IL-10, monocyte chemotactic protein (MCP)-1, macrophage inflammatory protein (MIP)-1α, IL-6/IL-10, and receptor for advanced glycation end products in plasma and in IFN-γ, IL-6, IL-8, IL-10, MCP-1, MIP-1α, MIP-1β, IL-8/IL-10, and TNF-α in CSF.ConclusionsSubstantial pro- and anti-inflammatory activity in the central neural system after surgery was found. If confirmed by larger studies, persistent changes in cytokine levels may serve as biomarkers for novel clinical trials.

BackgroundSleep disruption in critically ill adults can result in acute decrements in cognitive function, including delirium, but it is underdiagnosed in the setting of the intensive care unit (ICU). Although sleep stages can be assessed by polysomnography (PSG), acquisition and interpretation of PSG is costly, is labor intensive, is difficult to do over an extended period of time with critically ill patients (multiple days of continuous recording), and may interfere with patient care. In this pilot study, we investigated the feasibility and utility of monitoring sleep in the ICU setting using a portable electroencephalography (EEG) monitor, the SedLine brain monitor.MethodsWe first performed a baseline comparison study of the SedLine brain monitor by comparing its recordings to PSG recorded in a sleep laboratory (n = 3). In a separate patient cohort, we enrolled patients in the ICU who were monitored continuously with the SedLine monitor for sleep disruption (n = 23). In all enrolled patients, we continuously monitored their EEG. The raw EEG was retrieved and sleep stages and arousals were analyzed by a board-certified technologist. Delirium was measured by a trained research nurse using the Confusion Assessment Method developed for the ICU.ResultsFor all enrolled patients, we continuously monitored their EEGs and were able to retrieve the raw EEGs for analysis of sleep stages. Overall, the SedLine brain monitor was able to differentiate sleep stages, as well as capture arousals and transitions between sleep stages compared with the PSG performed in the sleep laboratory. The percentage agreement was 67% for the wake stage, 77% for the non-rapid eye movement (REM) stage (N1 = 29%, N2 = 88%, and N3 = 6%), and 89% for the REM stage. The overall agreement was measured with the use of weighted kappa, which was 0.61, 95% confidence interval, 0.58 to 0.64. In the ICU study, the mean recording time for the 23 enrolled patients was 19.10 hours. There were several signs indicative of poor-quality sleep, where sleep was distributed throughout the day, with reduced time spent in REM (1.38% ± 2.74% of total sleep time), and stage N3 (2.17% ± 5.53% of total sleep time) coupled with a high arousal index (34.63 ± 19.04 arousals per hour). The occurrence of ICU delirium was not significantly different between patients with and without sleep disruption.ConclusionsOur results suggest the utility of a portable EEG monitor to measure different sleep stages, transitions, and arousals; however, the accuracy in measuring different sleep stages by the SedLine monitor varies compared with PSG. Our results also support previous findings that sleep is fragmented in critically ill patients. Further research is necessary to develop portable EEG monitors that have higher agreement with PSG.

BackgroundWhether postoperative subsyndromal delirium (SSD) is a separate syndrome from delirium and has clinical relevance is not well understood.ObjectivesWe sought to investigate SSD in older surgical patients and to determine its prognostic significance.MethodsWe performed a prospective cohort study of patients who were 65 years or older and were scheduled for noncardiac surgery. Postoperative delirium was determined using the Confusion Assessment Method. SSD was defined as the presence of at least one of the possible 10 symptoms of delirium, as defined by the Confusion Assessment Method, but not meeting the criteria for delirium.ResultsThe number of features of SSD on the first postoperative day was associated with the subsequent development of delirium on the next day, after controlling for other risk factors. When compared with a patient with no SSD features, a patient with 1 SSD feature was 1.07 times more likely to have delirium on the next day (95% CI: 0.42-2.53), with 2 features was 3.32 times more likely to have it (95% CI: 1.42-7.57), and with ≥ 2 features was 8.37 times more likely to have it (95% CI: 4.98-14.53). Furthermore, there was a significant relationship between the number of features of SSD and increased length of hospital stay and worsened functional status at 1 month after surgery.ConclusionsSSD is prevalent in at-risk surgical patients and has prognostic significance. Only a single symptom of SSD was sufficient to cause a significant increase in hospital length of stay and further decline in functional status. These results suggest that monitoring for SSD is indicated in at-risk patients.

Study objectivesTo describe preoperative and postoperative sleep disruption and its relationship to postoperative delirium.DesignProspective cohort study with 6 time points (3 nights pre-hospitalization and 3 nights post-surgery).SettingUniversity medical center.PatientsThe sample consisted of 50 English-speaking patients ≥ 40 years of age scheduled for major non-cardiac surgery, with an anticipated hospital stay ≥ 3 days.InterventionsNone.Measurements and resultsSleep was measured before and after surgery for a total of 6 days using a wrist actigraph to quantify movement in a continuous fashion. Postoperative delirium was measured by a structured interview using the Confusion Assessment Method. Sleep variables for patients with (n = 7) and without (n = 43) postoperative delirium were compared using the unpaired Student t-tests or χ(2) tests. Repeated measures analysis of variance for the 6 days was used to examine within-subject changes over time and between group differences. The mean age of the patients was 66 ± 11 years (range 43-91 years), and it was not associated with sleep variables or postoperative delirium. The incidence of postoperative delirium observed during any of the 3 postoperative days was 14%. For the 7 patients who subsequently developed postoperative delirium, wake after sleep onset (WASO) as a percentage of total sleep time was significantly higher (44% ± 22%) during the night before surgery compared to the patients who did not subsequently developed delirium (21% ± 20%, p = 0.012). This sleep disruption continued postoperatively, and to a greater extent, for the first 2 nights after surgery. Patients with WASO < 10% did not experience postoperative delirium. Self-reported sleep disturbance did not differ between patients with vs. without postoperative delirium.ConclusionsIn this pilot study of adults over 40 years of age, sleep disruption was more severe before surgery in the patients who experienced postoperative delirium. A future larger study is necessary to confirm our results and determine if poor sleep is associated with delirium in larger samples and what specific sleep problems best predict postoperative delirium in older surgical patients.

BackgroundPreoperative cognitive impairment is a major risk factor for postoperative delirium. We therefore investigated the prognostic significance and feasibility of administering a brief cognitive screen before surgery.MethodsPatients > 65 yr of age undergoing hip, knee, or spine surgery were enrolled. A 60-sec cognitive screen, the animal fluency test (AFT), was administered preoperatively. Postoperative delirium was measured using a chart-based tool previously validated using criteria from the Confusion Assessment Method.ResultsOf the 362 patients satisfying the inclusion/exclusion criteria, 199 (55%) underwent the AFT. Among them, 57 patients (29%) had an AFT score

ObjectivesTo investigate whether preoperative risk for delirium moderates the effect of postoperative pain and opioids on the development of postoperative delirium.DesignProspective cohort study.SettingUniversity medical center.ParticipantsPatients 65 years of age or older scheduled for major noncardiac surgery.MeasurementsA structured interview was conducted preoperatively and postoperatively to determine the presence of delirium, defined using the Confusion Assessment Method. We first developed a prediction model to determine which patients were at high versus low risk for the development of delirium based on preoperative patient data. We then computed a logistic regression model to determine whether preoperative risk for delirium moderates the effect of postoperative pain and opioids on incident delirium.ResultsOf 581 patients, 40% developed delirium on days 1 or 2 after surgery. Independent preoperative predictors of postoperative delirium included lower cognitive status, a history of central nervous system disease, high surgical risk, and major spine and joint arthroplasty surgery. Compared with the patients at low preoperative risk for developing delirium, the relative risk for postoperative delirium for those in the high preoperative risk group was 2.38 (95% confidence interval: 1.67-3.40). A significant three-way interaction indicates that preoperative risk for delirium significantly moderated the effect of postoperative pain and opioid use on the development of delirium. Among patients at high preoperative risk for development of delirium who also had high postoperative pain and received high opioid doses, the incidence of delirium was 72%, compared with 20% among patients with low preoperative risk, low postoperative pain, and those who received low opioid doses.ConclusionsHigh levels of postoperative pain and using high opioid doses increased risk for postoperative delirium for all patients. The highest incidence of delirium was among patients who had high preoperative risk for delirium and also had high postoperative pain and used high opioid doses.

BackgroundThere are a variety of techniques to handle missing data, such as removing observations with missing data from the analyses or estimating the missing values using various imputation algorithms. Dropping subjects from standard regression models and analyzing only completers, however, may bias results from the true value of reality. Likewise, 'last-observation-carried-forward' may not be an appropriate technique for studies measuring a particular variable over time.MethodsThis dataset was part of a larger prospective cohort study that examined postoperative cognitive decline (POCD) after surgery in older adults. Data collectors had provided the reasons for data being missing using adjectives including 'confused', 'incapable', 'stuporous', 'comatose', and 'intubated'. Data having these qualitative notations were re-coded as 'incapable' and trial scores of zero were recorded. This value of '0' indicated that the patient was cognitively incapable of performing the neuropsychological test.ResultsMissing data varied by cognitive test and postoperative day. Re-coding word list scores from missing to zero when a patient was too cognitively impaired to complete the tests improved sample size by 13.5% of postoperative day (POD) 1 and 12.8% on POD 2. Recoding missing data to zero for the digit symbol test resulted in 29.3% larger sample size on POD 1 and 22.7% on POD 2. Verbal fluency gained 15.7% sample size with re-coding for POD 1 and 13.7% for POD 2. Re-coding of each cognitive test reduced missing data sample size to 20-32% in all cognitive tests for each day.DiscussionOur data suggest that using a scoring system that enters a value of '0' when patients are unable to perform cognitive testing did significantly increase the number of patients that met the diagnosis of postoperative cognitive decline using the criteria that were determined a priori and may lessen chances of type II error (failure to detect a difference).

PurposePreoperative cognitive impairment is associated with the development of postoperative delirium, a common and consequential complication of major surgery in older patients. Screening for cognitive impairment should become a routine part of the preoperative evaluation of older patients; however, its implementation is hampered by limited clinical time and resources. The objective of this review was to identify cognitive screening tools that could be easily incorporated into the evaluation of older patients before major surgery.Search strategyUsing strict inclusion and exclusion criteria, we searched PubMed over a 15-year period for short and simple cognitive screening tools. In addition, we reviewed studies that examined these cognitive screening tools in a perioperative environment. SEARCH RESULTS: We identified six cognitive screening tools that could each be administered in 2.5 min or less. Among the tools, sensitivity for cognitive impairment ranged from 79-99%, while specificity ranged from 70-98%. Only one (Mini-Cog) of the six tools we identified had been tested in a perioperative environment.ConclusionsIncorporating a cognitive screening assessment into the preoperative evaluation of older patients is feasible. More research is needed to validate cognitive screening tools in the perioperative setting.

Abstract Background The effect of peripheral nerve blocks on postoperative delirium in older patients has not been studied. Peripheral nerve blocks may reduce the incidence of postoperative opioid use and its side effects such as delirium via opioid-sparing effect. Methods A prospective cohort study was conducted in patients who underwent total knee replacement. Baseline cognitive function was assessed using the Telephone Interview for Cognitive Status. Postoperative delirium was measured using the Confusion Assessment Method postoperatively. Incidence of postoperative delirium was compared in two postoperative management groups: femoral nerve block ± patient-controlled analgesia and patient-controlled analgesia only. In addition, pain levels (using numeric rating scales) and opioid use were compared in two groups. Results 85 patients were studied. The overall incidence of postoperative delirium either on postoperative day one or day two was 48.1%. Incidence of postoperative delirium in the femoral nerve block group was lower than patient controlled analgesia only group (25% vs. 61%, P = 0.002). However, there was no significant difference between the groups with respect to postoperative pain level or the amount of intravenous opioid use. Conclusions Femoral nerve block reduces the incidence of postoperative delirium. These results suggest that a larger randomized control trial is necessary to confirm these preliminary findings.

BackgroundInfection with dengue viruses (DENV) leads to a spectrum of disease outcomes. The pathophysiology of severe versus non-severe manifestations of DENV infection may be driven by host responses, which could be reflected in the transcriptional profiles of peripheral blood immune cells.Methodology/principal findingsWe conducted genome-wide microarray analysis of whole blood RNA from 34 DENV-infected children in Nicaragua collected on days 3-6 of illness, with different disease manifestations. Gene expression analysis identified genes that are differentially regulated between clinical subgroups. The most striking transcriptional differences were observed between dengue patients with and without shock, especially in the expression of mitochondrial ribosomal proteins associated with protein biosynthesis. In the dengue hemorrhagic fever patients, one subset of differentially expressed genes encode neutrophil-derived anti-microbial peptides associated with innate immunity. By performing a meta-analysis of our dataset in conjunction with previously published datasets, we confirmed that DENV infection in vivo is associated with large changes to protein and nucleic acid metabolism. Additionally, whereas in vitro infection leads to an increased interferon signature, this was not consistently observed from in vivo patient samples, suggesting that the interferon response in vivo is relatively transient and was no longer observed by days 3-6 of illness.Conclusions/significanceThese data highlight important differences between different manifestations of severity during DENV infection as well as identify some commonalities. Compilation of larger datasets in the future across multiple studies, as we have initiated in this report, may well lead to better prediction of disease manifestation via a systems biology approach.