Postoperative cognitive impairment is among the most common medical complications associated with surgical interventions - particularly in elderly patients. In our aging society, it is an urgent medical need to determine preoperative individual risk prediction to allow more accurate cost-benefit decisions prior to elective surgeries. So far, risk prediction is mainly based on clinical parameters. However, these parameters only give a rough estimate of the individual risk. At present, there are no molecular or neuroimaging biomarkers available to improve risk prediction and little is known about the etiology and pathophysiology of this clinical condition. In this short review, we summarize the current state of knowledge and briefly present the recently started BioCog project (Biomarker Development for Postoperative Cognitive Impairment in the Elderly), which is funded by the European Union. It is the goal of this research and development (R&D) project, which involves academic and industry partners throughout Europe, to deliver a multivariate algorithm based on clinical assessments as well as molecular and neuroimaging biomarkers to overcome the currently unsatisfying situation.

Background: Postoperative cognitive dysfunction (POCD) is an adverse outcome that impacts patients' quality of life. Its diagnosis relies on formal cognitive testing performed before and after surgery. The substantial heterogeneity in methodology limits comparability and meta-analysis of studies. This systematic review critically appraises the methodology of studies on POCD published since the 1995 Consensus Statement and aims to provide guidance to future authors by providing recommendations that may improve comparability between future studies. Methods: This systematic review of literature published between 1995 and 2019 included studies that used baseline cognitive testing and a structured cognitive test battery, and had a minimal follow-up of 1 month. For cohorts with multiple publications, data from the primary publication were supplemented with available data from later follow-up studies. Results: A total of 274 unique studies were included in the analysis. In the included studies, 259 different cognitive tests were used. Studies varied considerably in timing of assessment, follow-up duration, definition of POCD, and use of control groups. Of the 274 included studies, 70 reported POCD as a dichotomous outcome at 1 to <3 months, with a pooled incidence of 2998/10 335 patients (29.0%). Conclusions: We found an overwhelming heterogeneity in methodology used to study POCD since the publication of the 1995 Consensus Statement. Future authors could improve study quality and comparability through optimal timing of assessment, the use of commonly used cognitive tests including the Consensus Statement 'core battery', application of appropriate cut-offs and diagnostic rules, and detailed reporting of the methods used. PROSPERO registry number: CRD42016039293.

BACKGROUND: Intraoperative electroencephalography (EEG) signatures related to the development of postoperative delirium (POD) in older patients are frequently studied. However, a broad analysis of the EEG dynamics including preoperative, postinduction, intraoperative and postoperative scenarios and its correlation to POD development is still lacking. We explored the relationship between perioperative EEG spectra-derived parameters and POD development, aiming to ascertain the diagnostic utility of these parameters to detect patients developing POD. METHODS: Patients aged ≥65 years undergoing elective surgeries that were expected to last more than 60 minutes were included in this prospective, observational single center study (Biomarker Development for Postoperative Cognitive Impairment [BioCog] study). Frontal EEGs were recorded, starting before induction of anesthesia and lasting until recovery of consciousness. EEG data were analyzed based on raw EEG files and downloaded excel data files. We performed multitaper spectral analyses of relevant EEG epochs and further used multitaper spectral estimate to calculate a corresponding spectral parameter. POD assessments were performed twice daily up to the seventh postoperative day. Our primary aim was to analyze the relation between the perioperative spectral edge frequency (SEF) and the development of POD. RESULTS: Of the 237 included patients, 41 (17%) patients developed POD. The preoperative EEG in POD patients was associated with lower values in both SEF (POD 13.1 ± 4.6 Hz versus no postoperative delirium [NoPOD] 17.4 ± 6.9 Hz; P = .002) and corresponding γ-band power (POD −24.33 ± 2.8 dB versus NoPOD −17.9 ± 4.81 dB), as well as reduced postinduction absolute α-band power (POD −7.37 ± 4.52 dB versus NoPOD −5 ± 5.03 dB). The ratio of SEF from the preoperative to postinduction state (SEF ratio) was ~1 in POD patients, whereas NoPOD patients showed a SEF ratio >1, thus indicating a slowing of EEG with loss of unconscious. Preoperative SEF, preoperative γ-band power, and SEF ratio were independently associated with POD (P = .025; odds ratio [OR] = 0.892, 95% confidence interval [CI], 0.808-0.986; P = .029; OR = 0.568, 95% CI, 0.342-0.944; and P = .009; OR = 0.108, 95% CI, 0.021-0.568, respectively). CONCLUSIONS: Lower preoperative SEF, absence of slowing in EEG while transitioning from preoperative state to unconscious state, and lower EEG power in relevant frequency bands in both these states are related to POD development. These findings may suggest an underlying pathophysiology and might be used as EEG-based marker for early identification of patients at risk to develop POD. (Anesth Analg XXX;XXX:00-00) KEY POINTS• Question: Are characteristic perioperative electroencephalography (EEG) patterns related to the development of postoperative delirium (POD) in older patients? • Findings: Lower preoperative spectral edge frequency (SEF) based on reduced γ-band power and absence of change in SEF with loss of consciousness (LOC) and lower intraoperative αband power are rela...

ZusammenfassungEin postoperatives Delir (POD) geht mit einem hohen Leidensdruck für die betroffenen Patienten und ihre Angehörigen und einem großen Mehraufwand für das klinische Personal einher. Darüber hinaus belasten die entstehenden Kosten erheblich das Gesundheitssystem. Der Beitrag beleuchtet die Optionen der Risikoreduktion in der postoperativen Versorgung, um ein POD und eine postoperative neurokognitive Störung zu vermeiden.

Objective Studies have suggested that inflammation contributes to the pathogenesis of postoperative delirium, but previous results on the proinflammatory cytokine IL-8 in plasma are contradictory. Additionally, a significant fraction of IL-8 is bound to erythrocytes, but the relevance of whole blood IL-8 in delirium has not been studied. In this work, we analyzed the association of postoperative delirium with levels of unbound IL-8 in plasma and levels of IL-8 in whole blood in patients from two studies which were conducted in our department and have not been presented previously. We assessed the prognostic value of whole blood IL-8. Methods Plasma/whole blood IL-8 was measured at least once in N ​= ​504 patients preoperatively, on day one (d1) and/or three months after surgery in the BioCog observational study. Whole blood IL-8 was measured in N ​= ​64 patients from the PHYDELIO trial preoperatively, on d1 and d7 after surgery. For the determination of whole blood IL-8, EDTA-preserved blood samples underwent lysis by adding Triton-X100 surfactant. Plasma and whole blood IL-8 levels were assessed with two different immunoassay kits. Delirium was appraised systematically for seven postoperative days according to DSM criteria using two comparable protocols consisting of validated screening tools. Results Delirium occurred in 25% of BioCog and 14% of PHYDELIO patients. In BioCog, IL-8 was elevated on d1 and in delirious patients. A steeper postoperative increase in delirium was confounded by surgery-related factors. A crescendo-decrescendo pattern of whole blood IL-8 levels was observed in non-delirious patients with a peak on d1. This pattern was more distinct in delirious BioCog patients, but inverted in delirious PHYDELIO patients. Preoperative whole blood IL-8>318.4 ​pg/mL (reference <150 ​pg/mL) had adequate sensitivity (0.79/0.78) and specificity (0.53/0.67) for delirium in both samples. Conclusion Our results contribute to an inflammatory hypothesis of postoperative delirium.

Delirium is associated with long-term cognitive dysfunction and with increased brain atrophy. However, it is unclear whether these problems result from or predispose to delirium. We aimed to investigate preoperative to postoperative brain changes, as well as the role of delirium in these changes over time. We investigated the effects of surgery and postoperative delirium with brain MRIs made before and three months after major elective surgery in 299 elderly patients, and an MRI with a three months follow-up MRI in 48 non-surgical control participants. To study the effects of surgery and delirium, we compared brain volumes, white matter hyperintensities, and brain infarcts between baseline and follow-up MRIs, using multiple regression analyses adjusting for possible confounders. Within the patients group, 37 persons (12%) developed postoperative delirium. Surgical patients showed a greater decrease in grey matter volume than non-surgical control participants (linear regression: B (95% Confidence Interval) = -0.65% of intracranial volume (-1.01 to -0.29, p &lt; 0.005). Within the surgery group, delirium was associated with a greater decrease in grey matter volume (B (95% Confidence Interval): -0.44% of intracranial volume (-0.82 to -0.06, p = 0.02). Furthermore, within the patients, delirium was associated with a non-significantly increased risk of a new postoperative brain infarct (logistic regression: odds ratio (95% Confidence Interval): 2.8 (0.7 to 11.1), p = 0.14). Our study was the first to investigate the association between delirium and preoperative to postoperative brain volume changes, suggesting that delirium is associated with increased progression of grey matter volume loss.

IntroductionPostoperative delirium (POD) is seen in approximately 15% of elderly patients and is related to poorer outcomes. In 2017, the Federal Joint Committee (Gemeinsamer Bundesausschuss) introduced a ‘quality contract’ (QC) as a new instrument to improve healthcare in Germany. One of the four areas for improvement of in-patient care is the ‘Prevention of POD in the care of elderly patients’ (QC-POD), as a means to reduce the risk of developing POD and its complications.The Institute for Quality Assurance and Transparency in Health Care identified gaps in the in-patient care of elderly patients related to the prevention, screening and treatment of POD, as required by consensus-based and evidence-based delirium guidelines. This paper introduces the QC-POD protocol, which aims to implement these guidelines into the clinical routine. There is an urgent need for well-structured, standardised and interdisciplinary pathways that enable the reliable screening and treatment of POD. Along with effective preventive measures, these concepts have a considerable potential to improve the care of elderly patients.Methods and analysisThe QC-POD study is a non-randomised, pre–post, monocentric, prospective trial with an interventional concept following a baseline control period. The QC-POD trial was initiated on 1 April 2020 between Charité-Universitätsmedizin Berlin and the German health insurance company BARMER and will end on 30 June 2023. Inclusion criteria: patients 70 years of age or older that are scheduled for a surgical procedure requiring anaesthesia and insurance with the QC partner (BARMER). Exclusion criteria included patients with a language barrier, moribund patients and those unwilling or unable to provide informed consent. The QC-POD protocol provides perioperative intervention at least two times per day, with delirium screening and non-pharmacological preventive measures.Ethics and disseminationThis protocol was approved by the ethics committee of the Charité-Universitätsmedizin, Berlin, Germany (EA1/054/20). The results will be published in a peer-reviewed scientific journal and presented at national and international conferences.Trial registration numberNCT04355195.

A growing body of literature suggests the important role of the thalamus in cognition and neurodegenerative diseases. This study aims to elucidate whether the preoperative thalamic volume is associated with preoperative cognitive impairment (preCI) and whether it is predictive for postoperative cognitive dysfunction at 3 months (POCD). We enrolled 301 patients aged 65 or older and without signs of dementia who were undergoing elective surgery. Magnetic resonance imaging was conducted prior to surgery. Freesurfer (version 5.3.) was used to automatically segment the thalamus volume. A neuropsychological test battery was administered before surgery and at a 3 month follow-up. It included the computerized tests Paired Associate Learning (PAL), Verbal Recognition Memory (VRM), Spatial Span Length (SSP), Simple Reaction Time (SRT), the pen-and-paper Trail-Making-Test (TMT) and the manual Grooved Pegboard Test (GPT). Using a reliable change index, preCI and POCD were defined as total Z-score > 1.96 (sum score over all tests) and/or Z-scores > 1.96 in ≥ 2 individual cognitive test parameters. For statistical analyses, multivariable logistic regression models were applied. Age, sex and intracranial volume were covariates in the models. Of 301 patients who received a presurgical neuropsychological testing and MRI, 34 (11.3%) had preCI. 89 patients (29.5%) were lost to follow-up. The remaining 212 patients received a follow-up cognitive test after 3 months, of whom 25 (8.3%) presented with POCD. Independently of age, sex and intracranial volume, neither preCI (OR per cm3 increment 0.81 [95% CI 0.60–1.07] p = 0.14) nor POCD (OR 1.02 per cm3 increment [95% CI 0.75–1.40] p = 0.87) were statistically significantly associated with patients’ preoperative thalamus volume. In this cohort we could not show an association of presurgical thalamus volume with preCI or POCD.Clinical Trial Number: NCT02265263 (https://clinicaltrials.gov/ct2/show/results/NCT02265263).