Stanford PIPRA Validation Study in an Elderly Orthopedic Population (PIPRA-ORTHO)

Stanford Study of the Validation of the Pre-Interventional Preventive Risk Assessment (PIPRA) Tool In The At-Risk Orthopedic Surgery Population

The purpose of this study is to determine the accuracy of an AI-based tool in the prediction of postoperative delirium (POD), in a population at moderately high risk of developing this syndrome (i.e., elderly orthopedic subjects). The population to be studied has already been enrolled in a parallel study regarding the likelihood of developing delirium, its relationship to the type of anesthetic, and the relationship between anesthetic type, development of delirium and risk for post-operative cognitive impairment (including risk for dementia) (Protocol ID#55169 [David Drover-Principal investigator; José Maldonado-Co-investigator]).

Study Overview

• Status: Completed
• Conditions: Delirium; Cognitive Impairment; Postoperative Delirium

Detailed Description

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 post-operative delirium (POD) 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 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 our study, we 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 POD 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 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 POD following surgery.

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 (Actual): 250

Contacts and Locations

Study Locations

• United States
  • California
    • Palo Alto, California, United States, 94304
      • Stanford Medical Center

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Older Adult
• Accepts Healthy Volunteers: Yes

• Sampling Method: Non-Probability Sample

Study Population

Stanford Hospital geriatric patients having surgery

Description

Inclusion Criteria:

• Surgical patients
• Greater than or equal to 65 years old
• ASA I, II or III
• Greater than 90 min of surgery
• Non-cardiac surgery

Exclusion Criteria:

• Dementia
• Alzheimer's
• Parkinson's
• Current Benzodiazepine use
• Alcoholism
• Previous surgery within the last 12 months or expected in the 12 months to come (except the expected surgery for which they are being enrolled).
• Color-blindness

Study Plan

How is the study designed?

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
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.	Baseline measurement of variables and detection of delirium presenting up to 72 hours post-operatively
Development of post-operative Delirium	Number of subjects diagnosed with post-operative delirium	Up to 72 hours post-operatively
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.	Up to 72 hours post-operatively.
Impact of delirium on post-operative cognitive impairment	Impact of delirium occurrence and emergence of cognitive impairment post-operatively	Up to 10-year post-operatively.
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 postoperative delirium.	Baseline measurement of variables and detection of delirium presenting up to 72 hours post-operatively
Receiver operating characteristic (ROC) curve analysis of PIPRA tool	Receiver operating characteristic (ROC) curve analysis of PIPRA tool	Baseline measurement of variables and detection of delirium presenting up to 72 hours post-operatively

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Discharge Site	Site of discharge (e.g., home, rehabilitation, skilled nurse facility, etc)	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 to discharge from the hospital (assessed up to 6 months from admission)
Immediate Postoperative Mortality	Mortality rate immediately after index surgery	From date of post-operative admission up to time of postoperative discharge, an average of 72 hours.
Length of Hospital Length of Stay	Total number of days admitted to the hospital	From date of post-operative admission up to time of postoperative discharge (assessed up to 1 year after admission).
Need of pharmacological protocol	Need of pharmacological protocol for management of delirium	From post-operative hospital admission up to time of postoperative discharge (assessed up to 6 months from admission)

Collaborators and Investigators

• Sponsor: Stanford University
• Investigators: Principal Investigator: José R Maldonado, MD, Stanford University

Publications and helpful links

General Publications

• Buchan TA, Sadeghirad B, Schmutz N, Goettel N, Foroutan F, Couban R, Mbuagbaw L, Dodsworth BT. Preoperative prognostic factors associated with postoperative delirium in older people undergoing surgery: protocol for a systematic review and individual patient data meta-analysis. Syst Rev. 2020 Nov 14;9(1):261. doi: 10.1186/s13643-020-01518-z.
• Dodsworth BT, Reeve K, Falco L, Hueting T, Sadeghirad B, Mbuagbaw L, Goettel N, Schmutz Gelsomino N. Development and validation of an international preoperative risk assessment model for postoperative delirium. Age Ageing. 2023 Jun 1;52(6):afad086. doi: 10.1093/ageing/afad086.
• Sadeghirad B, Dodsworth BT, Schmutz Gelsomino N, Goettel N, Spence J, Buchan TA, Crandon HN, Baneshi MR, Pol RA, Brattinga B, Park UJ, Terashima M, Banning LBD, Van Leeuwen BL, Neerland BE, Chuan A, Martinez FT, Van Vugt JLA, Rampersaud YR, Hatakeyama S, Di Stasio E, Milisen K, Van Grootven B, van der Laan L, Thomson Mangnall L, Goodlin SJ, Lungeanu D, Denhaerynck K, Dhakharia V, Sampson EL, Zywiel MG, Falco L, Nguyen AV, Moss SJ, Krewulak KD, Jaworska N, Plotnikoff K, Kotteduwa-Jayawarden S, Sandarage R, Busse JW, Mbuagbaw L. Perioperative Factors Associated With Postoperative Delirium in Patients Undergoing Noncardiac Surgery: An Individual Patient Data Meta-Analysis. JAMA Netw Open. 2023 Oct 2;6(10):e2337239. doi: 10.1001/jamanetworkopen.2023.37239.
• Maldonado JR. Acute Brain Failure: Pathophysiology, Diagnosis, Management, and Sequelae of Delirium. Crit Care Clin. 2017 Jul;33(3):461-519. doi: 10.1016/j.ccc.2017.03.013.
• Robinson TN, Eiseman B. Postoperative delirium in the elderly: diagnosis and management. Clin Interv Aging. 2008;3(2):351-5. doi: 10.2147/cia.s2759.

Study record dates

Study Major Dates

• Study Start (Actual): April 30, 2024
• Primary Completion (Actual): June 30, 2024
• Study Completion (Actual): June 30, 2024

Study Registration Dates

• First Submitted: August 20, 2024
• First Submitted That Met QC Criteria: August 20, 2024
• First Posted (Actual): August 22, 2024

Study Record Updates

• Last Update Posted (Actual): August 22, 2024
• Last Update Submitted That Met QC Criteria: August 20, 2024
• Last Verified: August 1, 2024

More Information

Terms related to this study

• Keywords: Cognitive Impairment; Artificial Intelligence; Delirium; Postoperative Delirium; Delirium Risk Factors
• Additional Relevant MeSH Terms: Mental Disorders; Pathologic Processes; Nervous System Diseases; Postoperative Complications; Neurologic Manifestations; Confusion; Neurobehavioral Manifestations; Neurocognitive Disorders; Cognition Disorders; Delirium; Cognitive Dysfunction; Emergence Delirium
• Other Study ID Numbers: IRB-73341

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No