Dysfunctional resting state network connectivity predicts postoperative delirium after major surgery

Area of Science:

• Neuroscience
• Geriatric Medicine
• Radiology

Background:

• Postoperative delirium (POD) is a serious complication in older adults, linked to adverse outcomes like mortality and cognitive decline.
• Identifying neural mechanisms of individual vulnerability is crucial for POD prevention and treatment.
• This study investigates resting-state functional connectivity (rsFC) as a potential biomarker for POD predisposition.

Purpose of the Study:

• To determine if preoperative rsFC predicts the occurrence of POD in older surgical patients.
• To identify specific resting-state networks associated with increased vulnerability to POD.

Main Methods:

• Functional MRI (fMRI) data were acquired preoperatively from 120 participants aged over 65 undergoing major non-intracranial surgery.
• rsFC was calculated within and between canonical resting-state networks using denoised BOLD signal time-series.
• A support vector machine classifier was employed to assess the predictive power of rsFC for POD.

Main Results:

• Participants who developed POD exhibited significantly reduced within-network connectivity in the salience-ventral attention, cognitive control, and default mode networks.
• Weaker overall connectivity within the default mode network and its subnetworks, particularly those involved in higher-order cognition, was observed in POD patients.
• Machine learning models accurately predicted POD incidence (68% accuracy) based on connectivity patterns in the visual and salience-ventral attentional networks.

Conclusions:

• Preoperative rsFC serves as a neural correlate for vulnerability to POD.
• Disrupted connectivity within higher-order cognitive association networks, including the default mode, salience attention, and cognitive control networks, is specifically associated with POD development.