Postoperative delirium and changes in the blood-brain barrier, neuroinflammation, and cerebrospinal fluid lactate: a prospective cohort study

Abstract

Background: Case-control studies have associated delirium with blood-brain barrier (BBB) permeability. However, this approach cannot determine whether delirium is attributable to high pre-existing permeability or to perioperative changes. We tested whether perioperative changes in cerebrospinal fluid/plasma albumin ratio (CPAR) and plasma S100B were associated with delirium severity.

Methods: Participants were recruited to two prospective cohort studies of non-intracranial surgery (NCT01980511, NCT03124303, and NCT02926417). Delirium severity was assessed using the Delirium Rating Scale-98. Delirium incidence was diagnosed with the 3D-Confusion Assessment Method (3D-CAM) or CAM-ICU (CAM for the ICU). CSF samples from 25 patients and plasma from 78 patients were analysed for albumin and S100B. We tested associations between change in CPAR (n=11) and S100B (n=61) and delirium, blood loss, CSF interleukin-6 (IL-6), and CSF lactate.

Results: The perioperative increase in CPAR and S100B correlated with delirium severity (CPAR ρ=0.78, P=0.01; S100B ρ=0.41, P<0.001), delirium incidence (CPAR P=0.012; S100B P<0.001) and CSF IL-6 (CPAR ρ=0.66 P=0.04; S100B ρ=0.75, P=0.025). Linear mixed-effect analysis also showed that decreased levels of S100B predicted recovery from delirium symptoms (P=0.001). Linear regression demonstrated that change in plasma S100B was independently associated with surgical risk, cardiovascular surgery, blood loss, and hypotension. Blood loss also correlated with CPAR (ρ=0.64, P=0.04), S100B (ρ=0.70, P<0.001), CSF lactate (R=0.81, P=0.01), and peak delirium severity (ρ=0.36, P=0.01).

Conclusion: Postoperative delirium is associated with a breakdown in the BBB. This increased permeability is dynamic and associated with a neuroinflammatory and lactate response. Strategies to mitigate blood loss may protect the BBB.

Keywords: delirium; dementia; inflammation; neuronal injury; older adults; surgery.

Fig 1

STROBE diagram. CPAR, CSF/plasma albumin ratio; STROBE, Strengthening the Reporting of Observational Studies in Epidemiology.

Fig 2

Perioperative time course of CPAR and plasma S100B, and pre-postoperative change in delirium incidence, and peak DRS. (a) Time course of change in log10 CPAR normalised to baseline. (b) Time course of change in log10 plasma S100B normalised to baseline. (c) Boxplot of change in log10 CPAR by delirium incidence (delirium ever over postoperative days 1–4). (d) Boxplot of change in log10 plasma S100B by delirium incidence. (e) Correlation plot of change in log10 CPAR to peak DRS-R-98. (f) Correlation plot of change in log10 of plasma S100B to peak DRS. (g) Correlation plot of change in log10 CSF IL-6 to change in log10 CPAR. (h) Change in log10 CSF interleukin-6 (IL-6) to change in log10 plasma S100B. CPAR and plasma S100B were normalised by log10 transformation and subtracting baseline from postoperative values. Plasma S100B excludes two outliers, and CSF IL-6 excludes one, based on Cook's distance (>4∗mean). Delirium incidence is measured by the 3 min Diagnostic Cognitive Assessment Method (3D-CAM). Spearman's correlations were used given peak DRS is not normally distributed (Shapiro–Wilks’ normality test, P<0.001). The original unit used for biomarkers was pg ml⁻¹. Chg, change; CPAR, CSF/plasma albumin ratio; DRS-98, Delirium Rating Scale-98; Norm., normalised.

Fig 3

Correlation plots of preoperative–postoperative change in CPAR, plasma S100B, and other biomarkers with blood loss. (a) Correlation of change in log10 CPAR with log10 blood loss. (b) Correlation of change in log10 CSF IL-6 with log10 blood loss. (c) Correlation of change in log10 plasma S100B with log10 blood loss. (d) Correlation of change in log10 plasma IL-8 with log10 blood loss. (e) Correlation of log10 blood loss with peak DRS. Delirium incidence is measured by the 3-min Diagnostic Cognitive Assessment Method (3D-CAM). Outliers of blood loss were identified by Cook's distance (>4∗mean) and excluded as indicated. Spearman's correlation method used because blood loss is not normally distributed (Shapiro–Wilks’ normality test, P<0.001). The original unit of biomarkers is pg ml⁻¹ unless otherwise specified, and the original unit of blood loss is ml. Chg, change; CPAR, CSF/plasma albumin ratio; DRS, Delirium Rating Scale.

Fig 4

Correlation plots of change in log10 CSF lactate and biomarkers. Delirium incidence is measured by the 3-min Diagnostic Cognitive Assessment Method (3D-CAM). There was one CSF lactate outlier excluded based on Cook's distance and another excluded for plasma S100B. Pearson correlation method indicated by R. Spearman correlation method indicated by ρ (rho). Chg, change; CPAR, CSF/plasma albumin ratio; DRS, Delirium Rating Scale; NfL, neurofilament light.

Fig 5

Blood–brain barrier permeability hypothesis. We propose a mechanistic pathway by which peripheral inflammation, exacerbated by plasmin activation, leads to breakdown of the blood–brain barrier. Subsequent inflammatory changes lead to a central anti-inflammatory response, including lactate-induced activation of HCA receptors. The downstream effects on PGD2 lead to delirium though synaptic suppression. This results in reduced cerebral activity evident in EEG slowing. HCA, hydroxycarbolic acid; PGD2, prostaglandin D2.