The purpose of this study is to determine the accuracy of the Pre-Interventional Preventive Risk Assessment (PIPRA) tool in predicting clinical cases of Intensive Care Units (ICU)-delirium, in a population at high risk of developing this syndrome (i.e., admitted patients to Cardiothoracic Intensive Care Units). The population to be studied has already been enrolled in a parallel study intended to determine the accuracy of an electroencephalogram (EEG)-based diagnosis for delirium.
Study investigators would like to determine the real-life accuracy of a new tool developed for the prediction of delirium: Pre-Interventional Preventive Risk Assessment (PIPRA) Tool. The importance of assessing the risk for delirium includes: providing clinicians and patients with accurate predictive information regarding the patient's risk for developing delirium as part of the risk/benefit calculation for surgical procedures and/or admission to an intensive care unit (ICU), and thus potential risk of subsequent cognitive impairment; as well as the ability to introduce timely prophylactic techniques that may prevent its onset. The PIPRA tools consists of nine items commonly found in any presurgical patient's electronic medical record (EMR). The tool has been designed to run in the background of the EMR and automatically calculate the patient's risk for developing delirium upon admission for surgical intervention. For this study, study investigators will be applying the PIPRA tool to the EMR of patients already enrolled in a parallel study as detailed above. The PIPRA tool predicts the risk of developing delirium based on its algorithm that takes into consideration the following nine clinical variables: age, height/weight or body mass index, the American Society of Anesthesiologist physical status Classification system (ASA), past history of delirium, past history of cognitive impairment (including dementia), number of medications, preoperative C-reactive protein (CRP) levels, surgical risk (as determined by the European Society of Anesthesiology), and type of surgery. The subsequent result predicts the risk (in percentage) of a patient developing delirium. The PIPRA tool is fully integrated into EMR systems, operating in the background, extracting relevant information, and automatically generating a delirium prediction score. In addition, this software possesses the flexibility to recalibrate the delirium risk based on the availability of the nine clinical variables.
Study Type
OBSERVATIONAL
Enrollment
199
Stanford Medical Center
Palo Alto, California, United States
Number of subjects with postoperative delirium accurately predicted by the PIPRA Tool
Assessment of the accuracy on the prediction of subjects identified as developing delirium by the PIPRA tool, as compared with post-operative standardized delirium assessment tools. We will compare the assessment of the PIPRA prediction tool (performed pre-op) with the actual development of delirium as assessed by a clinical assessment based on DSM; the CAM-ICU \& SPTD assessment tools.
Time frame: Detection of delirium presenting up to 30 days post-ICU admission
Development of post-operative Delirium
Number of subjects diagnosed with post-operative delirium
Time frame: Up to 30 days post-ICU admission
Development of ICU Delirium
Number of subjects diagnosed with ICU delirium
Time frame: Up to 30 days post-ICU admission
Determination of Delirium Phenotype
For those who develop delirium, the phenotype of delirium will be determined as per the Liptzin-Levkoff Criteria (based on DSM diagnostic Criteria). As such, all delirium episodes will be categorized as: hyperactive, hypoactive, mixed, or subsyndromal delirium.
Time frame: Up to 30 days post-ICU admission
Sensitivity and specificity of the PIPRA tool for detecting postoperative delirium.
Sensitivity and specificity of various cut off points of the PIPRA tool for detecting delirium.
Time frame: Baseline measurement of variables and detection of delirium presenting up to 30 days post-ICU admission
Receiver operating characteristic (ROC) curve analysis of PIPRA tool
Receiver operating characteristic (ROC) curve analysis of PIPRA tool
Time frame: Baseline measurement of variables and detection of delirium presenting up to 30 days post-ICU admission
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Immediate Postoperative Mortality
Mortality rate immediately after index surgery
Time frame: From date of ICU admission up to time of discharge from the Intensive Care Unit, an average of two weeks.
Immediate post-ICU admission Mortality
Mortality rate following ICU admission
Time frame: From date of ICU admission up to time of discharge from the Intensive Care Unit, an average of two weeks.
Length of ICU & Hospital Stay
Total number of days admitted to the hospital
Time frame: From date of ICU admission up to time of discharge from the ICU, and then from the hospital (assessed up to 1 year after admission)
Discharge Site
Site of discharge (e.g., home, rehabilitation, skilled nurse facility, etc)
Time frame: Type of facility the patient was discharge to from the hospital (assessed up to 6 months from admission)
Requirement of Intensive Care Unit Admission
Need for admission to an intensive care unit due to clinical necessity or deterioration
Time frame: Time to discharge from the hospital (assessed up to 6 months from admission)
Need of pharmacological protocol
Need of pharmacological agents required for the management of delirium
Time frame: From date of ICU admission up to time of discharge from the ICU (assessed up to 6 months from admission)