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The goal of this observational study is to learn if simple tests for frailty and muscle strength can help predict which older adults (age 65 and older) are at higher risk for problems after major abdominal surgery.
The main questions it aims to answer are:
Participants will:
This observational study aims to assess whether brief, objective frailty and muscle-strength tests can be feasibly incorporated into routine preoperative evaluations and whether these assessments predict postoperative complications in older adults undergoing elective major abdominal surgery. The broader clinical objective is to enhance perioperative risk stratification using multidimensional frailty measurements.
Study Procedures:
Eligible participants aged 65 years or older scheduled for elective major abdominal surgeries (including colorectal, hepatobiliary, gynecologic, and urologic procedures) will undergo a structured frailty assessment battery during their standard preoperative clinic visit. This battery includes:
All assessments will be performed by trained clinical research personnel. The entire battery is anticipated to take approximately 20 minutes per participant.
Postoperatively, participant medical records will be reviewed at 30 and 90 days to identify and document complications, ICU admissions, hospital length of stay, discharge disposition, and mortality.
Quality Assurance and Data Validation:
Data Dictionary and Coding:
A detailed data dictionary outlining each variable, units, normal range, and coding schemes is maintained in REDCap. Frailty measures include both raw continuous data and binary categorical flags indicating normal versus abnormal based on established normative values from published consensus guidelines.
Standard Operating Procedures (SOPs):
The following SOPs ensure standardized study execution:
Sample Size Justification:
The target enrollment of 100 participants provides 80% power to detect moderate correlations (rho ≥0.3) between frailty measures and postoperative complication outcomes, assuming a complication rate of approximately 25%. This sample size also enables adequate power for logistic regression analyses with up to 10 predictors.
Plan for Missing Data:
Missing data will be minimized by rigorous training and immediate data entry verification. In cases where missing data occur, multiple imputation techniques (using chained equations with five iterations) will be employed if ≥5% of values for key predictors or outcomes are missing. Single imputation methods will be avoided except in instances of minimal (<5%) missingness.
Statistical Analysis Plan:
Descriptive statistics will summarize demographic characteristics and frailty test results. Continuous variables will be assessed for normality and summarized appropriately.
For primary analyses:
Logistic regression models will evaluate the predictive capability of frailty measures for postoperative complications.
Model performance metrics will include Area Under the ROC (Receiver Operating Curve), calibration slope and intercept, Brier score, and calibration plots.
For correlations between frailty measures and Clinical Frailty Scale:
Spearman rank correlations and poly-serial correlations will be employed as appropriate for ordinal variables.
All analyses will be conducted using R version 4.3.2 with reproducible seeds set for transparency.
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Frailty assessment, nutrition assessment, cognition assessment, muscle strength testing | Diagnostic Test | Participants will undergo a structured frailty and muscle-strength assessment battery performed during their routine preoperative evaluation. These assessments serve as the primary exposure measures of interest and include: Clinical Frailty Scale (CFS) evaluation (functional frailty assessment) Respiratory muscle strength assessment (Maximal Inspiratory Pressure (MIP) and Maximal Expiratory Pressure (MEP) using a MicroRPM handheld respiratory pressure meter) Hand-grip strength measurement (using Jamar dynamometer) Physical performance evaluation (Timed Up-and-Go (TUG) test) Skeletal muscle mass estimation (Bioelectrical impedance analysis, InBody 120) Muscle thickness measurement (Rectus femoris muscle thickness using portable ultrasound) Cognitive function screening (Mini-Cog test) Nutritional risk screening (Perioperative Nutrition Screen [PONS]) No additional interventions beyond these observational assessments will be conducted. |
| Measure | Description | Time Frame |
|---|---|---|
| Feasibility of Frailty Assessment Integration | Percentage of participants successfully completing the entire frailty assessment battery within a 20-minute target during routine preoperative visits. | At the time of the preoperative assessment |
| Predictive Capability of Frailty Measures for Postoperative Complications | Association between preoperative frailty measures (Clinical Frailty Scale, muscle strength tests, respiratory pressure tests, physical function, cognitive screening, nutritional status, and ultrasound-based muscle thickness) and occurrence of postoperative complications at 30 and 90 days. | 30 and 90 days postoperatively |
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Inclusion Criteria:
Participants may be eligible for this study if they meet the following conditions:
Exclusion Criteria:
Participants will not be eligible for the study if they have any of the following conditions:
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Participants will be older adults (age 65 or older) undergoing planned major abdominal surgeries at the University of North Carolina (UNC) Medical Center. Patients will typically be recruited from the UNC Preoperative Anesthesia Clinic, where standard preoperative assessments are performed.
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| Name | Affiliation | Role |
|---|---|---|
| Monika Nanda, MBBS, MPH, FASA | University of North Carolina, Chapel Hill | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| University of North Carolina | Recruiting | Chapel Hill | North Carolina | 27599 | United States |
De-identified individual participant data (IPD) collected during the study, including frailty measures, complication outcomes, and demographic information, will be made available upon reasonable request.
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De-identified individual data that supports the results will be shared beginning 9 to 36 months following publication.
Data requests should include a clear scientific rationale and intended use. Requests will be reviewed by the principal investigator and the research team for approval. Approved researchers must sign a data-sharing agreement committing to protect participant confidentiality and use data solely for approved scientific purposes. Data will be shared provided the investigator who proposes to use the data has approval from an Institutional Review Board (IRB), Independent Ethics Committee (IEC), or Research Ethics Board (REB), as applicable, and executes a data use/sharing agreement with UNC.
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| ID | Term |
|---|---|
| D000073496 | Frailty |
| D055948 | Sarcopenia |
| ID | Term |
|---|---|
| D010335 | Pathologic Processes |
| D013568 | Pathological Conditions, Signs and Symptoms |
| D009133 | Muscular Atrophy |
| D020879 | Neuromuscular Manifestations |
| D009461 | Neurologic Manifestations |
| D009422 | Nervous System Diseases |
| D001284 | Atrophy |
| D020763 | Pathological Conditions, Anatomical |
| D012816 | Signs and Symptoms |
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