stanford icu delirium pipra study

Conditions: Delirium; Cognitive Impairment; Delirium, Postoperative

Summary: 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.

Eligibility criteria:
inclusion criteria: 1. age is 18 years or older 2. clinical suspicion of delirium or subject at risk for delirium 3. admitted to the intensive care unit (icu) 4. expected icu stay is greater than one (1) day 5. subject must be fluent in english exclusion criteria: 1. age is younger than 18 years 2. subjects with a primary neurological or neurosurgical condition such as stroke, epilepsy, brain tumor, or witnessed seizures, parkinson's disease, traumatic brain injury, craniectomy, known severe dementia, or central nervous system (cns) infection 3. active cns substance abuse, intoxication, or withdrawal 4. unarousable or unresponsive subjects with richmond agitation sedation scale (rass) \<-3 5. subject is blind, deaf, or unable to speak or understand english

Keywords: artificial intelligence delirium delirium risk factors cognitive impairment postoperative delirium