Clinical trial NCT06961994: rSVO₂ and Postoperative Delirium Prediction
Official title: Association of Baseline and Intraoperative rSVO₂ With Postoperative Delirium in Older Noncardiac and Non-neurosurgical Patients: A Prospective Observational Study
Study type: OBSERVATIONAL
Overall status: COMPLETED
Conditions: Delirium, Postoperative
Lead sponsor: Wonkwang University Hospital
Sponsor class: OTHER
First posted: 2025-05-08
Enrollment: 300
Sex: ALL
Minimum age (years): 65
Standard ages: OLDER_ADULT
Accepts healthy volunteers: no
Observational model: COHORT
Time perspective: PROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: Older adults (≥65 years) undergoing elective noncardiac, non-neurosurgical surgery under general anesthesia. Patients were recruited from a university hospital in May 2025 and will be screened for eligibility based on cognitive ability, comorbidities, and frailty status.

Brief summary: This prospective observational cohort study will enroll 300 patients aged ≥65 years undergoing elective noncardiac, non-neurosurgical procedures . Baseline rSVO₂ will be measured preoperatively using Near-Infrared Spectroscopy (NIRS). Intraoperative rSVO₂ will be monitored, recording the absolute lowest value and the rate of rSVO₂ decrease (\[baseline - lowest\]/baseline × 100). Postoperative delirium (POD) will be assessed daily for 7 days post-surgery using the Confusion Assessment Method (CAM). Frailty will be assessed using the Fried Frailty Phenotype. Logistic regression models, adjusted for age, ASA physical status, Charlson Comorbidity Index (CCI), hemoglobin, and intraoperative factors, will evaluate rSVO₂ metrics as predictors of POD. Linear regression will assess factors influencing the rate of rSVO₂ decrease. Pearson correlation and multivariate regression will analyze associations between POD risk factors. Receiver Operating Characteristic (ROC) analysis will compare the predictive accuracy of rSVO₂ metrics.

Detailed description: Study Design and Population This prospective observational cohort study will be conducted at Wonkwang University School of Medicine Hospital from May 2025, upon approval by the Institutional Review Board (IRB#2025-04-010-0021). Written informed consent will be obtained from all participants.

Patients aged ≥65 years scheduled for elective noncardiac, non-neurosurgical procedures (e.g., general, orthopedic, urologic, vascular) under general anesthesia with an expected hospital stay ≥2 nights will be included. Exclusion criteria will include dementia, stroke, cerebral tumors, chronic use of antipsychotics or anticholinergics, inability to perform cognitive assessments, or non-English first language.

Data Collection Baseline rSVO₂ Measurement: Baseline rSVO₂ will be measured preoperatively using the O3® Regional Oximetry system (Masimo Corp., Irvine, CA, USA). Sensors will be placed on the patient's forehead while seated, breathing room air, and resting. The stable rSVO₂ value after 60 seconds will be recorded.

Intraoperative rSVO₂ Monitoring: Intraoperative rSVO₂ will be continuously monitored using the same O3® system. Two metrics will be extracted: (1) the absolute lowest intraoperative rSVO₂ value, and (2) the rate of rSVO₂ decrease, calculated as:

$$\\text{rate of rSVO₂ decrease (%)} = \\frac{\\text{Baseline rSVO₂} - \\text{Absolute lowest intraoperative rSVO₂}}{\\text{Baseline rSVO₂}} \\times 100$$

Postoperative Delirium Assessment: POD will be assessed daily for 7 days post-surgery using the Confusion Assessment Method (CAM) \[12\]. A positive CAM on any day will indicate POD.

Postoperative Patient Destination: This will be recorded as transfer to the ICU or general ward post-surgery.

Covariates: These will include age, sex, American Society of Anesthesiologists (ASA) physical status, Charlson Comorbidity Index (CCI), preoperative hemoglobin, frailty, and intraoperative factors: vital signs (mean arterial pressure \[MAP\], heart rate), blood loss (mL), transfusion (yes/no), fluid administration (crystalloid and colloid volumes in mL), and vasopressor use (norepinephrine, phenylephrine, or none). Frailty will be assessed using the Fried Frailty Phenotype, defined by five criteria: unintentional weight loss (\>4.5 kg in the past year), self-reported exhaustion, weak grip strength (measured by dynamometer), slow walking speed (timed 4.5-meter walk), and low physical activity (assessed via patient-reported activity levels) \[16\]. Patients meeting 0 criteria will be classified as robust, 1-2 as pre-frail, and ≥3 as frail. Frailty assessments will be conducted preoperatively by trained study personnel.

Sample Size Calculation

The sample size will be determined to address our primary objective of comparing the predictive performance of three rSVO₂ metrics (baseline rSVO₂, absolute lowest intraoperative rSVO₂, and rate of rSVO₂ decrease) for postoperative delirium (POD) in patients aged ≥65 years. Two complementary approaches will be used:

ROC AUC Comparison: From pilot data, baseline rSVO₂ yielded an AUC of 0.78, while the rate of rSVO₂ decrease had an AUC of 0.70-defining a minimum clinically relevant ΔAUC of 0.08. Using a two-sided α of 0.05, 80% power, and an anticipated POD incidence of 30% (event:non-event ratio ≈0.43:1), investigators will employ the power.roc.test() function in R's pROC package. This analysis indicates that 75 total patients (approximately 22 with POD and 53 without POD) will be sufficient to detect the specified AUC difference.

Multivariable Logistic Regression (EPV Rule): To ensure stable adjustment for covariates in multivariable models, investigators plan to include eight predictors: the three rSVO₂ metrics plus intraoperative blood loss, hypotension, vasopressor use, patient age, and ASA physical status. Applying the "events per variable" rule (minimum 10 events per predictor) will require 80 POD events. Assuming a 30% POD rate, this corresponds to 267 total patients (80 ÷ 0.30).

Finally, to accommodate an anticipated 10% rate of missing data or exclusions, investigators will inflate the larger of these estimates by dividing by 0.90, yielding a target enrollment of 297 patients, which will be rounded to 300 participants.

Statistical Analysis Continuous variables will be reported as mean (SD) or median \[IQR\], and categorical variables as number (%). Normality will be assessed using the Shapiro-Wilk test. Comparisons will use Student's t-test or Mann-Whitney U test for continuous variables and chi-square or Fisher's exact test for categorical variables. Logistic regression models, adjusted for age, ASA status, CCI, hemoglobin, frailty, and intraoperative factors, will evaluate rSVO₂ metrics as predictors of POD. Linear regression will assess factors influencing the rate of rSVO₂ decrease. Pearson correlation and multivariate regression will analyze associations between POD and risk factors. Receiver Operating Characteristic (ROC) curve analysis will compare the predictive accuracy of rSVO₂ metrics. A P-value \<0.05 will be considered significant. Analyses will be performed using SPSS v29.0 (IBM, NY) and R v4.3.0 (R Foundation for Statistical Computing).

Eligibility criteria: 1. Inclusion Criteria:

   Age ≥ 65 years Scheduled for elective noncardiac, non-neurosurgical surgery under general anesthesia Expected postoperative hospital stay ≥ 2 nights Able to provide informed consent Capable of completing preoperative frailty and cognitive assessments
2. Exclusion Criteria:

History of dementia, stroke, or cerebral tumors Chronic use of antipsychotic or anticholinergic medications Inability to complete cognitive assessments (e.g., language barrier, severe hearing/vision impairment) Current hemodialysis treatment Severe jaundice Missing baseline rSVO₂ data

Primary outcomes:
measure: Incidence of Postoperative Delirium (POD)
timeFrame: Postoperative Days 1 to 7
Secondary outcomes:
Other outcomes:
Locations:
city: Iksan
country: Korea, Republic of
facility: Wonkwang University School of Medicine Hospital
state: Jeollabuk-do
Study officials:
affiliation: Wonkwang University Hospital
name: Cheol Lee, M.D.,Ph.D
role: STUDY_DIRECTOR
References:
citation: Zhu J, Wang W, Shi H. The Association between Postoperative Cognitive Dysfunction and Cerebral Oximetry during Geriatric Orthopedic Surgery: A Randomized Controlled Study. Biomed Res Int. 2021 Oct 19;2021:5733139. doi: 10.1155/2021/5733139. eCollection 2021.
citation: Schoen J, Meyerrose J, Paarmann H, Heringlake M, Hueppe M, Berger KU. Preoperative regional cerebral oxygen saturation is a predictor of postoperative delirium in on-pump cardiac surgery patients: a prospective observational trial. Crit Care. 2011;15(5):R218. doi: 10.1186/cc10454. Epub 2011 Sep 19.