Infrared pupillometry helps to detect and predict delirium in the post-anesthesia care unit

Dynamically Normalized Pupillometry for Detecting Delayed Cerebral Ischemia After Aneurysmal Subarachnoid Hemorrhage

OBJECTIVES

Delayed cerebral ischemia (DCI) is a major driver of morbidity after aneurysmal subarachnoid hemorrhage (aSAH). Quantitative pupillometry has been shown to be of prognostic value after acute neurological injury. However, the evidence for the use of pupillometric features for the detection of DCI has been conflicting. The aim of this study was to investigate the prognostic value of frequent pupillometric monitoring for DCI detection.

DESIGN

Observational cohort study from a prospective aSAH registry.

SETTING

Tertiary referral center.

PATIENTS

Adult patients with confirmed aSAH admitted to the ICU between March 2019 and December 2023.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

One hundred fourteen patients were included, of which 31 (27.2%) suffered from DCI. All patients underwent frequent pupillometry (every 3 hr). We determined the absolute value of the neurological pupil index (NPi) and constriction velocity (CV), and their value normalized to the maximal recorded value between the admission and the pupillometry measure to account for personalized baselines. The association between pupillometry values and the occurrence of DCI within 6-24 hours was investigated. Normalized CV had the best discriminative performance to identify DCI within 8 hours, with an area under the receiver operating characteristic curve of 0.82 (95% CI, 0.69-0.91). NPi, as well as non-normalized metrics, were not significantly associated with DCI.

CONCLUSIONS

Normalized CV has a clinically and statistically significant association with the occurrence of DCI after aSAH. Frequent quantitative pupillometry could improve the multimodal monitoring of patients after aSAH with the goal of improving the identification of patients likely to benefit from therapeutic interventions.

Association Between Pupil Light Reflex and Delirium in Adults With Traumatic Brain Injury: Preliminary Findings

ABSTRACT

BACKGROUND: Delirium is a common neurological complication in patients admitted to the intensive care unit (ICU) after moderate to severe traumatic brain injury (TBI). Although current clinical guidelines prioritize delirium prevention, no specific tool is tailored to detect early signs of delirium in TBI patients. This preliminary 2-phase observational study investigated the correlation between the pupillary light reflex (PLR), measured with a pupillometer during mechanical ventilation, and the development of postextubation delirium in TBI patients. METHODS: A convenience sample of 26 adults with moderate to severe TBI under mechanical ventilation was recruited during their ICU stay. In phase I, PLR measurements were performed in the first 3 days of ICU admission using automated infrared pupillometry. In phase II, 2 raters independently extracted delirium data in the 72 hours post extubation period from medical records. Delirium was confirmed with a documented medical diagnosis. Point-biserial correlations ( rpb ) were used to examine the association between PLR scores and the presence of postextubation delirium. Student t tests were also performed to compare mean PLR scores between patients with and without delirium. RESULTS: Ten TBI patients (38%) were diagnosed with postextubation delirium, whereas 16 (62%) were not. Significant correlations between delirium and 2 PLR variables were found: pupil constriction percentage ( rpb (24) = -0.526, P = .006) and constriction velocity ( rpb (24) = -0.485, P = .012). The t test also revealed a significant difference in constriction percentage and velocity scores between TBI patients with and without delirium ( P ≤ .01). CONCLUSION: Our findings suggest that the use of pupillometry in the first 3 days of mechanical ventilation during an ICU stay may help identify TBI patients at risk for delirium after extubation. Although further research is necessary to support its validity, this technological tool may enable ICU nurses to better screen TBI patients for delirium and prevent its development.

Correlation of preoperative inflammatory factors and emotional disorders with postoperative delirium in patients with craniocerebral trauma

BACKGROUND

Traumatic brain injury (TBI) imposes a substantial societal and familial burden due to its high disability and fatality rates, rendering it a serious public health problem. Some patients with TBI have poor treatment outcomes and are prone to postoperative delirium (POD), which affects their quality of life. Anxiety has been linked to increased POD incidence in some studies, while others have found no correlation.

AIM

To investigate the correlation of POD risk factors, preoperative inflammatory factors, and mood disorders in patients with TBI.

METHODS

We retrospectively collected data on the treatment of 80 patients with TBI from November 2021 to September 2023. Patients were grouped as POD and non-POD, according to their POD status, and the general data of the two groups were compared. Inflammatory factor levels were detected preoperatively, and the Hamilton Depression Scale (HAMD) and Hamilton Anxiety Scale (HAMA) were used to investigate the risk factors associated with POD in these patients. Logistic regression was used to identify the independent risk factors.

RESULTS

Twenty-one patients (26.25%) developed POD, including 7, 10, and 4 cases of the excitatory, inhibitory, and mixed types, respectively. There were 59 cases (73.75%) in the non-POD group. Compared with the non-POD group, the POD group had a significantly higher proportion of patients with low Glasgow Coma Scale (GCS) scores before admission, unilateral mydriasis, preoperative hemorrhagic shock, intraventricular hemorrhage (IVH), and postoperative hyperglycemic hyperosmolar disease (P < 0.05). In the POD group, interleukin-6 (IL-6), human tumor necrosis factor-α (TNF-α), myeloperoxidase levels, HAMA, and HAMD scores were higher than those in the non-POD group (all P < 0.05). Logistic multivariate analysis showed that GCS score at admission, IVH, IL-6, TNF-α, HAMA, and HAMD were independent risk factors for POD in patients with TBI (P < 0.05).

CONCLUSION

Low GCS score at admission, IVH, elevated IL-6 and TNF-α, other inflammatory indicators, anxiety, and depression, can increase the risk of POD in patients with TBI after surgery.

Intraoperative neurological pupil index and postoperative delirium and neurologic adverse events after cardiac surgery: an observational study

Neurological pupil index (NPi) calculated by automated pupillometry predicts clinical outcomes in critically ill patients. However, there are few data on intraoperative NPi and postoperative outcome after cardiac surgery. We evaluated the relationships between intraoperative NPi and clinical outcomes, such as delirium, in cardiac surgery patients. NPi was measured at baseline, after anesthesia induction, at 30 min intervals after initiation of cardiopulmonary bypass or anastomosis of coronary artery bypass graft, and at skin closure. Abnormal NPi was defined as one or more measurements of NPi < 3.0 during surgery. The worst intraoperative NPi was recorded, then multivariate logistic regression analysis was performed to evaluate the relationship between abnormal NPi and postoperative delirium following cardiac surgery. Among 123 included patients, postoperative delirium developed in 19.5% (24/123) of patients. Intraoperative abnormal NPi was significantly associated with postoperative delirium (odds ratio 6.078; 95% confidence interval 1.845-20.025; P = 0.003) after adjustment for Society of Thoracic Surgeons Predicted Risk of Mortality score, coronary artery disease, and use of calcium channel blockers. In conclusion, abnormal intraoperative NPi independently predicted postoperative delirium following cardiac surgery. Intraoperative application of pupillometry may have prognostic value for development of postoperative delirium, thereby enabling close surveillance and early intervention in high-risk patients.Registry number: ClinicalTrials.gov (NCT04136210).

Heart rate response and recovery during exercise predict future delirium risk-A prospective cohort study in middle- to older-aged adults

BACKGROUND

Delirium is a neurocognitive disorder characterized by an abrupt decline in attention, awareness, and cognition after surgical/illness-induced stressors on the brain. There is now an increasing focus on how cardiovascular health interacts with neurocognitive disorders given their overlapping risk factors and links to subsequent dementia and mortality. One common indicator for cardiovascular health is the heart rate response/recovery (HRR) to exercise, but how this relates to future delirium is unknown.

METHODS

Electrocardiogram data were examined in 38,740 middle- to older-aged UK Biobank participants (mean age = 58.1 years, range: 40-72 years; 47.3% males) who completed a standardized submaximal exercise stress test (15-s baseline, 6-min exercise, and 1-min recovery) and required hospitalization during follow-up. An HRR index was derived as the product of the heart rate (HR) responses during exercise (peak/resting HRs) and recovery (peak/recovery HRs) and categorized into low/average/high groups as the bottom quartile/middle 2 quartiles/top quartile, respectively. Associations between 3 HRR groups and new-onset delirium were investigated using Cox proportional hazards models and a 2-year landmark analysis to minimize reverse causation. Sociodemographic factors, lifestyle factors/physical activity, cardiovascular risk, comorbidities, cognition, and maximal workload achieved were included as covariates.

RESULTS

During a median follow-up period of 11 years, 348 participants (9/1000) newly developed delirium. Compared with the high HRR group (16/1000), the risk for delirium was almost doubled in those with low HRR (hazard ratio = 1.90, 95% confidence interval (95%CI): 1.30-2.79, p = 0.001) and average HRR (hazard ratio = 1.54, 95%CI: 1.07-2.22, p = 0.020)). Low HRR was equivalent to being 6 years older, a current smoker, or ≥3 additional cardiovascular disease risks. Results were robust in sensitivity analysis, but the risk appeared larger in those with better cognition and when only postoperative delirium was considered (n = 147; hazard ratio = 2.66, 95%CI: 1.46-4.85, p = 0.001).

CONCLUSION

HRR during submaximal exercise is associated with future risk for delirium. Given that HRR is potentially modifiable, it may prove useful for neurological risk stratification alongside traditional cardiovascular risk factors.

Associations of an eye-tracking task and pupillary metrics with age and ASA physical status score in a preoperative cohort

Advanced age, American Society of Anesthesiologists physical status (ASA) classification and the presence of cognitive impairment are associated with an elevated risk of postoperative morbidity and mortality. The visual paired comparison (VPC) task, which relies on recognition of novel images, examines declarative memory. VPC scores have demonstrated the ability to detect mild cognitive impairment and track progression of neurodegenerative disease. Quantitative pupillometry may have similar value. We evaluate for associations between these variables of interest and the feasibility of performing these tests in the preoperative clinic. Prospective data from 199 patients seen in the preoperative clinic at a tertiary academic center were analyzed. A 5 min VPC task (Neurotrack Technologies, Inc, Redwood City, CA) was administered during their scheduled preoperative clinic visit. Pupillary light reflexes were measured at the same visit (PLR-3000™, Neuroptics Corp, Irvine, California).Thirty-four percent of patients were categorized as ASA 2 and 58% as ASA 3. Median age was 57 (IQR: 44-69). Associations were demonstrated between age and ASA physical status (Mann-Whitney U Test, p < 0.0001), maximum pupil size (Spearman Rank Correlation, r = - 0.40, p < 0.0001), and maximum constriction velocity (Spearman Rank Correlation, r = - 0.39, p < 0.0001). Our data also revealed an association between VPC score and age (Spearman Rank Correlation, p = 0.0016, r = - 0.21) but not ASA score (Kruskal-Wallis Test, p = 0.14). When compared to a nonsurgical cohort with no history of memory impairment, our population scored worse on the VPC task (Mann-Whitney U Test, p = 0.0002). A preoperative 5 min VPC task and pupillometry are feasible tests in the preoperative setting and may provide a valuable window into an individual's cognition prior to elective surgery.

Instruments to Identify Delirium in Patients Recovering From Anesthesia: A Scoping Review

PURPOSE

To identify the validated instruments used for screening and detecting postoperative delirium (POD) during Post Anesthesia Recovery (PAR) period, and the incidence and associated risk factors with POD.

DESIGN

A scoping review.

METHODS

The study search occurred in May 2021 in the PubMed, Embase, Scopus, CINAHL, Web of Science and LILACS databases. Primary studies that used validated instruments for screening and detecting POD in the PAR period were included.

FINDINGS

A total of 38 articles were included. The most used instruments were CAM-ICU, Nu-DESC, and RASS. The instruments that screened and detected delirium earliest were the Nu-DESC and CAM-ICU. POD incidence was up to 20% in more than half of the included studies. Cardiovascular comorbidities, chronic kidney disease, low functional reserve, chronic obstructive pulmonary disease and postoperative pain were among the primary risk factors.

CONCLUSION

The instrumentsshowing the greatest accuracy for screening and detecting POD in the PAR period were the Nu-DESC and CAM-ICU.

Use of Automated Infrared Pupillometry to Predict Delirium in the Intensive Care Unit: A Prospective Observational Study

Introduction

Delirium is an acute state of brain dysfunction prevalent among critically ill patients. Disturbances in the sympathetic neurons, including cholinergic neurons, have been reported to cause delirium by upsetting the balance of neurotransmitter synthesis, release, and inactivation. The cholinergic system mediates pupillary constriction as a response to light stimulation, and this reflex can be measured using automated infrared pupillometry (AIP). The relationship between delirium and AIP parameters has been examined. The Confusion Assessment Method for the Intensive Care Unit (CAM ICU) and the Intensive Care Unit Delirium Screening Checklist (ICDSC) are used for assessing delirium. However, that between the ICDSC score and AIP parameters remains unclear.

Objective

To examine the relationship between AIP parameters and the various categories of delirium as defined by the ICDSC score (delirium, subsyndromal delirium, no delirium).

Methods

This prospective observational study included patients aged ≥18 years admitted to the intensive care unit (ICU) from May 2018 to September 2018. ICU patients were classified into delirium, subsyndromal delirium, and no delirium groups according to the ICDSC score during ICU stay. The pupillary light reflex was assessed in both eyes immediately after admission using AIP with a portable infrared pupillometer. Logistic regression analyses were used to estimate the odds ratio to examine the relationship between the severity of delirium as assessed by the ICDSC score and the AIP parameters.

Results

In total 133 patients were included in the study. Based on the ICDSC scores, 41.4% of patients had no delirium, 40.6% had subsyndromal delirium, and 18% had delirium. Dilation velocity (DV) measured by AIP was significantly different among the delirium, subsyndromal delirium, and no delirium groups. Post-hoc comparisons showed that DV was significantly slower in the delirium group than in the no delirium group but was not significantly different between the subsyndromal delirium and no delirium groups. After adjusting for patients’ sex and age at enrollment, DV was shown to be independently associated with delirium.

Conclusion

This study suggests that the use of AIP at ICU admission may improve the identification of patients at a high risk of developing delirium.

The association between perioperative pupillary parameters and postoperative acute pain: A pilot cross-sectional study

OBJECTIVE

We aim to explore the capacity of perioperative pupillary variables to predict acute pain in the post-anesthesia care unit (PACU).

METHODS

Patients scheduled to undergo thoracic or abdominal surgery under general anesthesia between April 2021 and June 2021 were enrolled. We measured the pupil diameter, pupillary light reflex (PLR), and pupillary reflex dilatation 5 min before anesthesia induction (T1), 5 min after intubation (T2), at the end of anesthesia (T3), immediately before extubation (T4), and 5 min after extubation (T5). We assessed the early postoperative pain intensity in the PACU using Numeric Rating Scales (NRS) at recovery, 5 min after recovery, and 10 min after recovery. Logistic regression models were used to evaluate the association between perioperative pupillary variables and postoperative pain intensity.

RESULTS

Fifty-one patients were enrolled, 50 of whom were included in the final analysis. A total of 13 patients (26%) needed remedial analgesia in the PACU. Pupil parameters at T1, T2, T3, and T5 were not associated with NRS in the PACU. Multiple logistic regression models and receiver operating characteristic (ROC) curves indicated that only latency of PLR at T4 can predict postoperative acute pain. The ROC analysis showed that the cutoff value for latency of PLR at T4 was 0.29 s to discriminate between no pain and pain, and the area under the curve was 0.778 (95% CI 0.634-0.922, p = 0.002) with sensitivity 50.0% and specificity 91.7%.

CONCLUSION

The latency of PLR immediately before extubation may be a useful predictor for postoperative acute pain in the PACU.

Research status and prospect of peri-extubation delirium

Peri-extubation delirium is a clinical syndrome caused by multiple factors, and it is not a simple disease. It occurs within a period of time after extubation when the effect of general anesthesia is reduced. And the incidence is different in disparate populations, and it is more common in elderly patients. Current studies have shown that iatrogenic factors and patients' own factors are the main risk factors for the syndrome. Early identification of risk factors can help clinicians make early diagnosis. The earlier the diagnosis and treatment begin, the more significantly the prognosis of patients can be improved. At present, the treatment of perioperative delirium is based on non-drug therapy, supplemented by drug therapy. This review will introduce in detail the risk factors, population status and prevention measures of delirium during peri-extubation, and look forward to the new research direction in the future.

Automated Pupillometry for Assessment of Treatment Success in Nonconvulsive Status Epilepticus

BACKGROUND

Altered pupillary function may reflect nonconvulsive status epilepticus (NCSE). Neurological pupil index (NPi) assessed by automated pupillometry is a surrogate marker of global pupillary function. We aimed to assess NPi changes in relation to NCSE treatment response.

METHODS

In this prospective observational study, serial automated pupillometry was performed in 68 NCSE episodes. In accordance with local standards, patients were treated with clonazepam (1-2 mg), levetiracetam (40 mg/kg), and lacosamide (5 mg/kg) in a stepwise approach under continuous electroencephalography monitoring until NCSE was terminated. Patients with refractory NCSE received individualized regimens. NPi was assessed bilaterally before and after each treatment step. For statistical analysis, the lower NPi of both sides (minNPi) was used. Nonparametric testing for matched samples and Cohen's d to estimate effect size were performed. Principal component analysis was applied to assess the contribution of baseline minNPi, age, sex, and NCSE duration to treatment outcome.

RESULTS

In 97.1% of 68 episodes, NCSE could be terminated; in 16.2%, NCSE was refractory. In 85.3% of episodes, an abnormal baseline minNPi ≤ 4.0 was obtained. After NCSE termination, minNPi increased significantly (p < 0.001). Cohen's d showed a strong effect size of 1.24 (95% confidence interval 0.88-1.61). Baseline minNPi was higher in clonazepam nonresponders vs. responders (p = 0.008), minNPi increased in responders (p < 0.001) but not in nonresponders. NCSE refractivity was associated with normal baseline minNPi (principal component analysis, component 1, 32.6% of variance, r = 0.78), male sex, and longer NCSE duration (component 2, 27.1% of variance, r = 0.62 and r = 0.78, respectively).

CONCLUSIONS

Automated pupillometry may be a helpful noninvasive neuromonitoring tool for the assessment of patients with NCSE and response to treatment.

Changes in autonomic tone during delirium in acute stroke patients assessed by pupillometry and skin conductance

Delirium is a common complication in acute ischemic stroke, possibly caused by alterations in the regulation of the sympathetic autonomic nervous system. We investigated whether such an association could be demonstrated with two easy-to-use measurement techniques: Measurement of palmar skin conductance level (SCL) and pupillometry measuring the dilation velocity in the pupillary light reflex (PLR_dil.vel.). The cohort study included 64 patients admitted with acute ischemic stroke. During the study period (median 4.1 days, interquartile range 2.1 days) patients were assessed for delirium once daily as well as with measurements of SCL and PLR_dil.vel up to twice daily. SCL and PLR_dil.vel. during delirium were lower than without delirium present. For SCL the unadjusted difference was -40.8% (95% CI (-55.1 to -22.0), P value <.001) and for PLR_dil.vel the unadjusted difference was -0.22 mm/s (95% CI (-0.42 to -0.01), P value = .041). The results demonstrate changes in sympathetic autonomic nervous system regulation during delirium in acute stroke patients.

Quantitative assessments of pupillary light reflexes in hospital-onset unresponsiveness

BACKGROUND

Patients who develop hospital-onset unresponsiveness should be promptly managed in order to avoid clinical deterioration. Pupillary examination through pupillary light reflex is the gold standard method in the initial evaluation of unresponsive patients. However, the current method of shining light and subjective description often shows poor reliability. The objective of this study is to explore whether a quantitative measurement of pupillary light reflexes is useful in detecting brain herniation syndrome and predicting neurological outcomes in patients who developed hospital-onset unresponsiveness after admission for non-neurological reasons.

METHODS

This was a registry-based observational study on patients who activated the neurological rapid response team at Asan Medical Center (Seoul, Korea). Hospital-onset unresponsiveness was defined as a newly developed unresponsive state as assessed by the ACDU (Alert, Confused, Drowsy, and Unresponsive) scale during the hospital stay. Demographics, comorbidities, pupillometry parameters including Neurological Pupil index, brain herniation syndrome, in-hospital mortality, and modified Rankin Scale at 3-months were analyzed.

RESULTS

In 214 consecutive patients with hospital-onset unresponsiveness, 37 (17%) had brain herniation syndrome. The optimal cut-off value of Neurological Pupil index for detecting brain herniation syndrome was < 1.6 (specificity, 91% [95% confidence interval (CI) = 86-95]; sensitivity, 49% [95% CI = 32-66]). The in-hospital mortality rate was 28% (59/214); the Neurological Pupil index was negatively associated with in-hospital mortality after adjustments for the presence of brain herniation syndrome (adjusted odds ratio = 0.77, 95% CI = 0.62-0.96). Poor neurological outcomes (modified Rankin Scale ≥4) at 3 months was observed in 76% (152/201) of the patients; the Neurological Pupil index was negatively associated with poor neurological outcomes after adjustments for clinical variables (adjusted odds ratio = 0.67, 95% CI = 0.49-0.90).

CONCLUSIONS

Quantitative measurements of pupillary light reflexes may be useful for early detection of potentially life-threatening neurological conditions in patients with hospital-onset unresponsiveness.

Pupillary light reflex as a diagnostic aid from computational viewpoint: A systematic literature review

This work presents a detailed and complete review of publications on pupillary light reflex (PLR) used to aid diagnoses. These are computational techniques used in the evaluation of pupillometry, as well as their application in computer-aided diagnoses (CAD) of pathologies or physiological conditions that can be studied by observing the movements of miosis and mydriasis of the human pupil. A careful survey was carried out of all studies published over the last 10 years which investigated, electronic devices, recording protocols, image treatment, computational algorithms and the pathologies related to PLR. We present the frontier of existing knowledge regarding methods and techniques used in this field of knowledge, which has been expanding due to the possibility of performing diagnoses with high precision, at a low cost and with a non-invasive method.

Quantitative Infrared Pupillometry in Nonconvulsive Status Epilepticus

BACKGROUND

Nonconvulsive status epilepticus (NCSE) is a frequent disorder in neurocritical care and diagnosing it can be challenging. NCSE patients often show altered pupil function, but nature and extent may vary. Infrared pupillometry allows detection of subtle changes of pupil function. The neurological pupil index (NPi) is considered a surrogate marker of global pupil function which is supposed to be independent of absolute parameters such as the pupil diameter.

OBJECTIVE

Cross-sectional observational study to assess whether NPi is altered in NCSE.

METHODS

128 consecutive adult emergency patients who had experienced a suspected seizure, have not reached their prior functional level regarding level of consciousness, mental status or focal deficits, had no obvious clinical signs of status epilepticus and had an EEG indication as determined by the treating clinician for exclusion of NCSE were examined by routine EEG and pupillometry. Exclusion criteria were ocular comorbidity (n = 21) and poor EEG quality (n = 4). Pupillometry was performed once directly before the beginning of EEG recording. NCSE diagnosis (no NCSE, possible NCSE and confirmed NCSE) was established according to Salzburg consensus criteria blinded to pupillometry results. Group comparison was performed for right NPi, left NPi, lowest NPi of both sides (minNPi) and the absolute difference of both sides (diffNPi) applying non-parametric testing. In post-hoc analysis, receiver operating characteristics (ROC) of NCSE diagnosis (combined confirmed NCSE and possible NCSE) were performed for minNPi and diffNPi.

RESULTS

From 103 patients included in the final analysis, 5 (4.9%) had confirmed NCSE, 7 (6.8%) had possible NCSE. Right NPi (p = 0.002), left NPi (p < 0.001) and minNPi (p < 0.001) were significantly lower in "confirmed NCSE" and "possible NCSE" compared to "no NCSE"; diffNPi was significantly higher in "confirmed NCSE" and "possible NCSE" compared to "no NCSE" (p < 0.001). There was no significant difference of minNPi and diffNPi between "confirmed NCSE" and "possible NCSE". ROC analysis showed an optimal cut-off of minNPi for NCSE diagnosis of 4.0 (AUC = 0.93, 95% CI 0.86-0.99). Optimal ROC analysis cut-off of diffNPi for NCSE diagnosis was 0.2 (AUC = 0.89, 95% CI 0.80-0.99).

CONCLUSIONS

NPi was significantly reduced and the difference between left and right NPi was significantly higher in confirmed NCSE. An NPi < 4.0 on either side as well as an NPi difference of both sides > 0.2 may be potential indicators of NCSE. Infrared pupillometry may be a helpful diagnostic tool in the assessment of NCSE and should be studied further in larger populations.

Noninvasive neuromonitoring in the operating room and its role in the prevention of delirium

Delirium is a frequent and serious complication after surgery. It has a variable incidence between 20% and 40% with the highest incidence in elderly people undergoing major or cardiac surgery. The development of postoperative delirium (POD) is associated with increased hospital stay lengths, morbidity, the need for home care, and mortality. Studies have appeared in the last decade that evaluate the use of noninvasive monitoring to prevent its development. The evaluation of the depth of anesthesia with processed EEG allows to avoid awareness and burst suppression events. The cessation of brain activity is associated with the development of delirium. Another noninvasive monitoring technique is NIRS for cerebral tissue hypoxia detection by measuring regional oxygen saturation. The reduction of this parameter does not seem to be associated with the development of POD but with postoperative cognitive dysfunction. There are few studies in the literature and with conflicting results on the use of the pupillometer and transcranial Doppler in predicting the development of postoperative delirium.

Implementation of strategies to prevent and treat postoperative delirium in the post-anesthesia caring unit : A German survey of current practice

Postoperative delirium is associated with worse outcome. The aim of this study was to understand present strategies for delirium screening and therapy in German Post-Anesthesia-Caring-Units (PACU). We designed a German-wide web-based questionnaire which was sent to 922 chairmen of anesthesiologic departments and to 726 anesthetists working in ambulatory surgery. The response rate was 30% for hospital anesthesiologists. 10% (95%-confidence interval: 8–12) of the anesthesiologists applied a standardised screening for delirium. Even though not on a regular basis, in 44% (41–47) of the hospitals, a recommended and validated screening was used, the Nursing Delirium Screening Scale (NuDesc) or the Confusion Assessment Method for the Intensive Care Unit (CAM-ICU). If delirium was likely to occur, 46% (43–50) of the patients were examined using a delirium tool. 20% (17–23) of the patients were screened in intensive care units. For the treatment of delirium, alpha-2-agonists (83%, 80–85) were used most frequently for vegetative symptoms, benzodiazepines for anxiety in 71% (68–74), typical neuroleptics in 77% (71–82%) of patients with psychotic symptoms and in 20% (15–25) in patients with hypoactive delirium. 45% (39–51) of the respondents suggested no therapy for this entity. Monitoring of delirium is not established as a standard procedure in German PACUs. However, symptom-oriented therapy for postoperative delirium corresponds with current guidelines.