Preoperative Sleep Disruption and Postoperative Delirium

Role of Wearable Accelerometer Devices in Delirium Studies: A Systematic Review

We sought to determine the feasibility of using wearable accelerometer devices for determining delirium effects on patients' physical activity patterns and detecting delirium and delirium subtype.

DATA SOURCES

PubMed, Embase, and Web of Science.

STUDY SELECTION

Screening was performed using predefined search terms to identify original research studies using accelerometer devices for studying physical activity in relation to delirium.

DATA EXTRACTION

Key data were extracted from the selected articles.

DATA SYNTHESIS

Among the 14 studies identified, there were a total of 315 patients who wore accelerometer devices to record movements related to delirium. Eight studies (57.1%) used accelerometer devices to compare the activity of delirious and nondelirious patients. Delirious patients had lower activity levels, lower restlessness index, higher number of daytime immobility minutes, lower mean activity levels during the day, and higher mean activity levels at night. Delirious patients also had lower actual sleep time, lower sleep efficiency, fewer nighttime minutes resting, fewer minutes resting over 24 hours, and smaller change in activity from day to night. Six studies (42.9%) evaluated the feasibility of using accelerometer devices for detection of delirium and its subtype. Variables including number of postural changes during daytime, frequency of ultrashort, short, and continuous movements were significantly different among the nondelirium and the three delirium subtypes.

CONCLUSIONS

The results from the studies using accelerometer devices in studying delirium demonstrate that accelerometer devices can potentially detect the differences between delirious and nondelirious patients, detect delirium, and determine delirium subtype. We suggest the following directions as the next steps for future studies using accelerometer devices for predicting delirium: benchmark studies with longer data collection, larger and more diverse population size, incorporating related factors (e.g., medications), and evaluating delirium subtype and severity.

Separability of calcium slow waves and functional connectivity during wake, sleep, and anesthesia

Modulation of brain state, e.g., by anesthesia, alters the correlation structure of spontaneous activity, especially in the delta band. This effect has largely been attributed to the ∼ 1    Hz slow oscillation that is characteristic of anesthesia and nonrapid eye movement (NREM) sleep. However, the effect of the slow oscillation on correlation structures and the spectral content of spontaneous activity across brain states (including NREM) has not been comprehensively examined. Further, discrepancies between activity dynamics observed with hemoglobin versus calcium (GCaMP6) imaging have not been reconciled. Lastly, whether the slow oscillation replaces functional connectivity (FC) patterns typical of the alert state, or superimposes on them, remains unclear. Here, we use wide-field calcium imaging to study spontaneous cortical activity in awake, anesthetized, and naturally sleeping mice. We find modest brain state-dependent changes in infraslow correlations but larger changes in GCaMP6 delta correlations. Principal component analysis of GCaMP6 sleep/anesthesia data in the delta band revealed that the slow oscillation is largely confined to the first three components. Removal of these components revealed a correlation structure strikingly similar to that observed during wake. These results indicate that, during NREM sleep/anesthesia, the slow oscillation superimposes onto a canonical FC architecture.

Sleeping pattern before thoracic surgery: A comparison of baseline and night before surgery

Background

Sleep deprivation is considered a stress factor in the perioperative period. There are several studies on sleep disturbance after surgery but very limited literature available on preoperative sleep patterns, predictors of sleep disturbance and its effect on surgical outcome.

Methodology

Patients scheduled for thoracic surgery were asked to fill out a written Pittsburgh Sleep Quality Index (PSQI) questionnaire. The primary investigator explained this form to all the patients. This was filled out before premedication for subjective assessment of sleeping pattern at two different time point. Only those patients included who spent the previous night at home. Participants were asked to respond to the questions regarding their baseline sleeping pattern and compare it with last night.

Results

Total eighty-three patients with a mean age of 47.83 ± 17.88 were included in the study. Overall mean PSQI scores were significantly higher (p-value < 0.01) during the night before surgery (6.94 ± 2.115) when compared with baseline (3.88 ± 1.877). Sleep latency was also significantly affected when last night-1 (the night before admission) was compared with usual sleep latency. Twenty patients were unable to sleep more than 5 hrs at night before admission which was significant when compared with their last month status (20 vs 3). Logistic regression model demonstrated the age and Timing of surgery as a strong predictors of poor sleep (defined as PSQI ≥ 5).

Conclusion

Quality of sleep was profoundly affected at night before thoracic surgery, mainly due to a significant change in sleep latency and sleep duration. Although age and Timing of surgery were strong predictors of poor sleep we were unable to find any association between quality of sleep and type of surgery.

Early Postoperative Actigraphy Poorly Predicts Hypoactive Delirium

STUDY OBJECTIVES

Delirium is a postoperative complication accompanied by disturbances in attention, cognition, arousal, and psychomotor activity. Wrist actigraphy has been advocated to study inactivity and inferred sleep patterns during delirium. We hypothesized that altered patterns of motor activity or immobility, reflective of disordered sleep and wakefulness patterns, would serve as predictive markers of hypoactive postoperative delirium.

METHODS

Eighty-four elderly surgical patients were classified into three groups based on the timing of hypoactive delirium following surgery: intact with no delirium throughout postoperative days (POD) 0-5 (n = 51), delirium during POD 0-1 (n = 24), and delirium during POD 2-5 (n = 13). Delirium was detected on daily Confusion Assessment Method evaluations and chart review. Actigraphy measures were calculated from accelerometry signals acquired on the first postoperative day (POD 0, 16:00-23:00) and night (POD 0, 23:00-POD 1, 06:00).

RESULTS

Actigraphy metrics showed substantial interpatient variability. Among the three patient groups, only those without delirium showed greater movement during the day compared to night and also fewer minutes of night immobility (P = .03 and P = .02, Wilcoxon rank-sum tests). These patients were poorly discriminated from those with delirium during either POD 0-1 or POD 2-5, using differences in day and night activity (C-statistic, 95% confidence interval [CI]: 0.66 [0.53-0.79] and C-statistic, 95% CI: 0.71 [0.55-0.87], respectively). Inclusion of low-frequency signals improved performance of immobility measures without affecting those based on activity. Cognitively intact patients during POD 0-5 were distinguished from those with delirium during POD 0-1, based on differences in the number of day and night immobile minutes (C-statistic 0.65, 95% CI: [0.53-0.78]). Actigraphy metrics with the strongest association to delirium incidence were not reliably correlated with an increased risk during POD 0-5, when accounting for patient age, sex, intensive care unit admission, and Charlson Comorbidity Index (adjusted odds ratio of 1.7, 95% CI: [1.0-3.0], P = .09, likelihood ratio test).

CONCLUSIONS

Early postoperative wrist actigraphy metrics that serve as markers of sleep and wakefulness offer limited capacity as sole predictors or markers of hypoactive delirium.

CLINICAL TRIAL REGISTRATION

Registry: ClinicalTrials.gov; Title: Electroencephalography Guidance of Anesthesia to Alleviate Geriatric Syndromes (ENGAGES) Study; Identifier: NCT02241655; URL: https://clinicaltrials.gov/ct2/show/NCT02241655.

The Incidence of Recorded Delirium Episodes Before and After Dementia Diagnosis: Differences Between Dementia With Lewy Bodies and Alzheimer's Disease

OBJECTIVES

To describe the incidence of delirium recording before and after a diagnosis of dementia is established in patients with dementia with Lewy bodies (DLB) and compare findings to a matched cohort of patients with Alzheimer's disease (AD).

DESIGN

Retrospective cohort study.

SETTING AND PARTICIPANTS

A cohort of patients with dementia from a large mental health and dementia care database in South London, linked to hospitalization and mortality data. We identified 194 patients with DLB and 1:4 matched these with 776 patients diagnosed with AD on age, gender, and cognitive status.

MEASURES

We identified delirium episodes recorded in mental health and hospital records from 1 year before to 1 year after dementia diagnosis. Using dementia diagnosis as an index date we additionally followed patients until first episode of delirium, death or a censoring point without restricting the observation period.

RESULTS

Patients with DLB had significantly more episodes of delirium recorded in the year before dementia diagnosis than patients with AD (incidence rate 17.6 vs 3.2 per 100 person-years; P < .001). Whereas the incidence of recording of delirium episodes reduced substantially in patients with DLB after dementia diagnosis, it remained significantly higher than in patients with AD (incidence rate 6.2 vs 2.3 per 100 person-years; P = .032). Cox regression models indicate that patients with DLB remain at a higher risk of delirium than patients with AD after a dementia diagnosis.

CONCLUSIONS/RELEVANCE

Establishing a diagnosis of dementia reduces episodes classified as delirium in patients with DLB and might lead to fewer potentially harmful interventions such as hospitalization or use of antipsychotic medication.

Improve postoperative sleep: what can we do?

Purpose of review

We reviewed evidences regarding occurrence, risk factors, harmful effects, prevention, and management of sleep disturbances in patients after surgery.

Recent findings

Normal sleep is important to maintain physical and mental health. Sleep disturbances frequently occur in patients after surgery. Factors associated with the development of postoperative sleep disturbances include old age, preoperative comorbidity, type of anesthesia, severity of surgical trauma, postoperative pain, environment stress, as well as other factors leading to discomfort of patients. Development of sleep disturbances produces harmful effects on postoperative patients, that is, leading to higher risk of delirium, increased sensitivity to pain, more cardiovascular events, and poorer recovery. Both nonpharmacological and pharmacological measures (such as zolpidem, melatonin, and dexmedetomidine) can be used to improve postoperative sleep. Recent evidences show that sleep promotion may improve patients’ outcome, but requires further evidences.

Summary

Sleep disturbances are common in patients after surgery and produce harmful effects on postoperative recovery. Sleep-promotion therapy may be helpful to improve postoperative recovery, but long-term effects deserve further study.

NeurimmiRs and Postoperative Delirium in Elderly Patients Undergoing Total Hip/Knee Replacement: A Pilot Study

Objective: Postoperative delirium (POD) is a frequent complication after surgery and its occurrence is associated with poor outcomes. The pathophysiology of this complication is not clear, but identification of risk factors is important for positive postoperative outcomes. The purpose of this study was to investigate the associations between the preoperative expression levels of microRNA (miR)-146a, miR-125b, and miR-181c in cerebrospinal fluid (CSF) and serum and the development and severity of POD.

Methods: Forty elderly patients aged 65 years old and older admitted for elective total hip/knee replacement under spinal anesthesia. Preoperatively, baseline cognitive function was assessed using the Mini-Mental State Examination. Each patient was interviewed daily on the first and second postoperative days. Delirium was diagnosed using the Confusion Assessment Method, and delirium severity was measured using the Memorial Delirium Assessment Scale (MDAS). Preoperative serum and CSF miR levels were determined by quantitative real-time PCR (qRT-PCR).

Results: POD was detected in 27.5% (11/40) of patients. Up-regulation of miR-146a and miR-181c in CSF and down-regulation of miR-146a in serum were observed preoperatively in patients who developed POD, while patients with and without POD did not differ in serum or CSF levels of miR-125b. Delirious patients had higher CSF/serum ratios of miR-146a and miR-181c levels than non-delirious patients. The lower CSF miR-146a and CSF/serum miR-146a ratios were significantly associated with milder POD severity, represented by a lower MDAS score.

Conclusion: The dysregulation of preoperative miR-146a and miR-181c in CSF and serum was associated with the development and severity of POD. These NeurimmiRs might participate in the neuropathogenesis of POD, pending further investigations.

Clinical trial registration: this study was registered at ClinicalTrials.gov (NCT02817386).

Sleep Disruption at Home As an Independent Risk Factor for Postoperative Delirium

OBJECTIVES

To determine whether sleep disruption at home or in hospital is an independent risk factor for postoperative delirium in older adults undergoing elective surgery.

DESIGN

Prospective cohort study.

SETTING

German teaching hospital.

PARTICIPANTS

Individuals aged 65 and older undergoing elective arthroplasty (N = 101).

MEASUREMENTS

Preoperative questionnaires were used to assess sleep disruption at home (Pittsburgh Sleep Quality Index). Actigraphy was used to objectively measure sleep disruption in the hospital before and after surgery. Delirium was assessed daily after surgery using the Confusion Assessment Method and, if there was uncertainty, validated according to International Classification of Diseases, Tenth Revision (ICD-10), criteria.

RESULTS

Twenty-seven participants developed postoperative delirium. Those with sleep disruption at home were 3.26 times as likely to develop postoperative delirium as those without (95% confidence interval (CI) = 1.34-7.92, P = .009). Participants with sleep disruption in hospital were 1.21 times as likely to develop postoperative delirium as those without (95% CI = 1.03-1.41, P = .02). When adjusting for other variables, risk remained significant for sleep disruption at home (risk ratio (RR) = 3.90, 95% CI = 2.14-7.11, P < .001) but not in the hospital (RR = 1.19, 95% CI = 0.69-2.07). Jointly modeling sleep disruption at home and in the hospital, adjusted for covariates, resulted in significant contributions of both (home: RR = 3.10, 95% CI = 1.34-7.17, P = .008; hospital: RR = 1.38 95% CI = 1.13-1.68, P = .002).

CONCLUSIONS

Older people with sleep disruption at home are at significantly higher risk of developing postoperative delirium than those without. Sleep disruption in the hospital may further heighten this risk.