While delirium is associated with cognitive decline and dementia, there is limited evidence to support causality for this relationship. Clarification of how delirium may cause cognitive decline, perhaps through evidence of contemporaneous neuronal injury, would enhance plausibility for a causal relationship. Dose-dependence of neuronal injury with delirium severity would further enhance the biological plausibility for this relationship. We tested whether delirium is associated with neuronal injury in 114 surgical patients recruited to a prospective biomarker cohort study. Patients underwent perioperative testing for changes in neurofilament light, a neuronal injury biomarker, as well as a panel of 10 cytokines, with contemporaneous assessment of delirium severity and incidence. A subset of patients underwent preoperative MRI. Initially we confirmed prior reports that neurofilament light levels correlated with markers of neurodegeneration [hippocampal volume (ΔR2 = 0.129, P = 0.015)] and white matter changes including fractional anisotropy of white matter (ΔR2 = 0.417, P < 0.001) with similar effects on mean, axial and radial diffusivity) in our cohort and that surgery was associated with increasing neurofilament light from preoperative levels [mean difference (95% confidence interval, CI) = 0.240 (0.178, 0.301) log10 (pg/ml), P < 0.001], suggesting putative neuronal injury. Next, we tested the relationship with delirium. Neurofilament light rose more sharply in participants with delirium compared to non-sufferers [mean difference (95% CI) = 0.251 (0.136, 0.367) log10 (pg/ml), P < 0.001]. This relationship showed dose-dependence, such that neurofilament light rose proportionately to delirium severity (ΔR2 = 0.199, P < 0.001). Given that inflammation is considered an important driver of postoperative delirium, next we tested whether neurofilament light, as a potential marker of neurotoxicity, may contribute to the pathogenesis of delirium independent of inflammation. From a panel of 10 cytokines, the pro-inflammatory cytokine IL-8 exhibited a strong correlation with delirium severity (ΔR2 = 0.208, P < 0.001). Therefore, we tested whether the change in neurofilament light contributed to delirium severity independent of IL-8. Neurofilament light was independently associated with delirium severity after adjusting for the change in inflammation (ΔR2 = 0.040, P = 0.038). These data suggest delirium is associated with exaggerated increases in neurofilament light and that this putative neurotoxicity may contribute to the pathogenesis of delirium itself, independent of changes in inflammation.

ObjectiveTo identify existing prognostic delirium prediction models and evaluate their validity and statistical methodology in the older adult (≥60 years) acute hospital population.DesignSystematic review.Data sources and methodsPubMed, CINAHL, PsychINFO, SocINFO, Cochrane, Web of Science and Embase were searched from 1 January 1990 to 31 December 2016. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses and CHARMS Statement guided protocol development. Inclusion criteria: age >60 years, inpatient, developed/validated a prognostic delirium prediction model. Exclusion criteria: alcohol-related delirium, sample size ≤50. The primary performance measures were calibration and discrimination statistics. Two authors independently conducted search and extracted data. The synthesis of data was done by the first author. Disagreement was resolved by the mentoring author.ResultsThe initial search resulted in 7,502 studies. Following full-text review of 192 studies, 33 were excluded based on age criteria (<60 years) and 27 met the defined criteria. Twenty-three delirium prediction models were identified, 14 were externally validated and 3 were internally validated. The following populations were represented: 11 medical, 3 medical/surgical and 13 surgical. The assessment of delirium was often non-systematic, resulting in varied incidence. Fourteen models were externally validated with an area under the receiver operating curve range from 0.52 to 0.94. Limitations in design, data collection methods and model metric reporting statistics were identified.ConclusionsDelirium prediction models for older adults show variable and typically inadequate predictive capabilities. Our review highlights the need for development of robust models to predict delirium in older inpatients. We provide recommendations for the development of such models.

Background: Delirium frequently affects older patients, increasing morbidity and mortality; however, the pathogenesis is poorly understood. Herein, we tested the cognitive disintegration model, which proposes that a breakdown in frontoparietal connectivity, provoked by increased slow-wave activity (SWA), causes delirium. Methods: We recruited 70 surgical patients to have preoperative and postoperative cognitive testing, EEG, blood biomarkers, and preoperative MRI. To provide evidence for causality, any putative mechanism had to differentiate on the diagnosis of delirium; change proportionally to delirium severity; and correlate with a known precipitant for delirium, inflammation. Analyses were adjusted for multiple corrections (MCs) where appropriate. Results: In the preoperative period, subjects who subsequently incurred postoperative delirium had higher alpha power, increased alpha band connectivity (MC P<0.05), but impaired structural connectivity (increased radial diffusivity; MC P<0.05) on diffusion tensor imaging. These connectivity effects were correlated (r 2 ¼0.491; P¼0.0012). Postoperatively, local SWA over frontal cortex was insufficient to cause delirium. Rather, delirium was associated with increased SWA involving occipitoparietal and frontal cortex, with an accompanying breakdown in functional connectivity. Changes in connectivity correlated with SWA (r 2 ¼0.257; P<0.0001), delirium severity rating (r 2 ¼0.195; P<0.001), interleukin 10 (r 2 ¼0.152; P¼0.008), and monocyte chemoattractant protein 1 (r 2 ¼0.253; P<0.001). Conclusions: Whilst frontal SWA occurs in all postoperative patients, delirium results when SWA progresses to involve posterior brain regions, with an associated reduction in connectivity in most subjects. Modifying SWA and connectivity may offer a novel therapeutic approach for delirium. Clinical trial registration: NCT03124303, NCT02926417

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

Objectives: To determine delirium occurrence rate, duration, and severity in patients admitted to the ICU with coronavirus disease 2019. Design: Retrospective data extraction study from March 1, 2020, to June 7, 2020. Delirium outcomes were assessed for up to the first 14 days in ICU. Setting: Two large, academic centers serving the state of Indiana. Patients: Consecutive patients admitted to the ICU with positive severe acute respiratory syndrome coronavirus 2 nasopharyngeal swab polymerase chain reaction test from March 1, 2020, to June 7, 2020, were included. Individuals younger than 18 years of age, without any delirium assessments, or without discharge disposition were excluded. Measurements and Main Results: Primary outcomes were delirium rates and duration, and the secondary outcome was delirium severity. Two-hundred sixty-eight consecutive patients were included in the analysis with a mean age of 58.4 years (sd, 15.6 yr), 40.3% were female, 44.4% African American, 20.7% Hispanic, and a median Acute Physiology and Chronic Health Evaluation II score of 18 (interquartile range, 13–25). Delirium without coma occurred in 29.1% of patients, delirium prior to coma in 27.9%, and delirium after coma in 23.1%. The first Confusion Assessment Method for the ICU assessment was positive for delirium in 61.9%. Hypoactive delirium was the most common subtype (87.4%). By day 14, the median number of delirium/coma-free were 5 days (interquartile range, 4–11 d), and median Confusion Assessment Method for the ICU-7 score was 6.5 (interquartile range, 5–7) indicating severe delirium. Benzodiazepines were ordered for 78.4% of patients in the cohort. Mechanical ventilation was associated with greater odds of developing delirium (odds ratio, 5.0; 95% CI, 1.1–22.2; p = 0.033) even after adjusting for sedative medications. There were no between-group differences in mortality. Conclusions: Delirium without coma occurred in 29.1% of patients admitted to the ICU. Delirium persisted for a median of 5 days and was severe. Mechanical ventilation was significantly associated with odds of delirium even after adjustment for sedatives. Clinical attention to manage delirium duration and severity, and deeper understanding of the virus’ neurologic effects is needed for patients with coronavirus disease 2019.

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