Prediction and Prevention of Postoperative Mortality and Morbidity

Alzheimer Disease Clinical Trial

Official title: Real-world and Innovative Multimodal Prediction and Prevention of Postoperative Mortality and Multi-morbidities

Status Not yet recruiting

Clinical Trial Summary

This study will contribute to creating a prospective and robust automated preoperative risk assessment algorithm for 30-day mortality, major adverse cardiac and cerebrovascular events (MACCE) and perioperative neurocognitive disorders (PND) outcomes following elective general, orthopedic, cardiac, or vascular surgery. It will help to identify correlations between perioperative factors and Alzheimer's Disease (AD) or AD-related dementias (ADRD). Lastly, this study will create effective, validated multi-modal interventions to improve perioperative health. This study will explore two main hypotheses: 1. Preoperative prehabilitation and proactive cognitive/behavioral interventions will effectively improve postoperative cognitive outcomes, morbidities, and mortality, and; 2. The proactive bundled interventions are superior to current standard of care in reducing postoperative cognitive outcomes, MACCE and mortality. Expected Outcome: Improved EHR algorithm will have higher predictive accuracy for MACCE and mortality while predicting postoperative cognitive outcomes.

Clinical Trial Description

This study will cover the following two specific aims:

Aim 1. A randomized controlled trial (RCT) to assess the effectiveness of pre-operative personalized prehabilitation with proactive cognitive and behavioral interventions versus standard of care on reducing postoperative cognitive outcomes (POD, POCD, dementia), MACCE, and mortality in high-risk surgical elderly patients (≥65y). Our Electronic Health Record (EHR)-based automated machine-learning risk prediction algorithm for postoperative mortality and MACCE has been developed using >1.25 million surgical patients' data and implemented with superior performance to comparators. This EHR algorithm will identify 1000 patients at high risk for 30-day mortality and MACCE for Aim 1. Patients will be stratified by baseline cognition status and randomly assigned to standard of care (n=500) or personalized preoperative prehabilitation with proactive cognitive/behavioral interventions (physical exercise, cognitive training, enhanced social support, and proactive depression treatment) (n=500). Cognitive assessments will be performed at baseline, at discharge, 1-, 3-, 6-, and 12- months.

Aim 1 Hypothesis: Preoperative prehabilitation and proactive cognitive/behavioral interventions will effectively improve postoperative cognitive outcomes, morbidities, and mortality.

Aim 2: An RCT to examine the effectiveness of proactive intra-operative bundled interventions versus reactive standard of care to improve postoperative cognitive outcomes, MACCE, and mortality in high-risk surgical elderly patients scheduled for cardiac surgery with IONM. Intraoperative factors are associated with mortality, morbidity, and stroke. Intraoperative triple-low events (mean arterial pressure <75 mmHg, Bispectral Index <45, and minimum alveolar fraction <0.8) are associated with postoperative cognitive outcomes. Eligible patients scheduled for IONM from Aim 1 (n=500) will be stratified based on Aim 1 intervention groups and randomized to either reactive standard of care intervention (n=250) or proactive bundled interventions to determine if optimizing intraoperative physiology reduces postoperative cognitive outcomes and 30-day MACCE and mortality. Both groups will receive reactive response to shifts in electroencephalography (EEG) and somatosensory evoked potential (SSEP). Proactive bundled interventions91 include maintaining normal blood pressure, oxygen levels, opioid sparing analgesia92-94, avoiding deep anesthesia95 and benzodiazepines.

Aim 2 Hypothesis: The proactive bundled interventions are superior to current standard of care in reducing postoperative cognitive outcomes, MACCE and mortality. Expected Outcome: Improved EHR algorithm will have higher predictive accuracy for MACCE and mortality while predicting postoperative cognitive outcomes ;

Related Conditions & MeSH terms

• Alzheimer Disease

• NCT number: NCT06042413
• Study type: Interventional
• Source: University of Pittsburgh
• Contact: Alisha Maslanka, BS, CCRC
• Phone: 4128646779
• Email: maslankaaa@upmc.edu
• Status: Not yet recruiting
• Phase: N/A
• Start date: July 1, 2024
• Completion date: September 1, 2025