An Exploratory Factor Analysis of the National Institutes of Health Patient-Reported Outcomes Measurement Information System and the Single Assessment Numeric Evaluation in Knee Surgery Patients

INTRODUCTION

Patient-Reported Outcomes (PROs) have been suggested for use in measuring treatment effectiveness. To minimize patient burden, two approaches have been proposed: An orthopedic-specific Single Assessment Numeric Evaluation (SANE) or computer adaptive testing methods such as the National Institutes of Health (NIH) Patient-Reported Outcomes Measurement Information System (PROMIS). The goal of this work was to examine the constructs measured by the SANE and PROMIS system in a military orthopedic population undergoing knee surgery.

MATERIALS AND METHODS

In 732 patients and 2,166 complete observations, the SANE-Knee PRO and PROMIS surveys for Depression, Anxiety, Pain Interference, Sleep Disturbance, and Physical Function were obtained. A correlation matrix between the PROs was calculated, the number of latent factors to extract was determined via parallel plot, and the final principal axis exploratory factor analysis was performed.

RESULTS

The parallel plot analysis indicated that two latent factors existed. One latent factor corresponded to measures of psychological distress (PROMIS Sleep Disturbance, Depression, and Anxiety) and the second latent factor corresponded to physical capability (SANE, PROMIS Physical Function, Pain Interference, and Sleep Disturbance). Both PROMIS Physical Function (0.83) and Pain Interference (-0.80) more strongly weigh on the physical capability latent factor than SANE (0.69).

CONCLUSIONS

In a knee surgical population, the SANE, PROMIS Physical Function, and PROMIS Pain Interference measure the same human dimension of physical capability; however, PROMIS Physical Function and Pain Interference may measure this construct more effectively in isolation. The SANE may be a more viable option to gauge physical capability when computer adaptive testing is not possible.

The Glenoid Track Paradigm Does Not Reliably Affect Military Surgeons’ Approach to Managing Shoulder Instability

Purpose

To report the frequencies of surgical stabilization procedures performed by military shoulder surgeons and to use decision tree analysis to describe how bipolar bone loss affects surgeons' decision to perform arthroscopic versus open stabilization procedures.

Methods

The Military Orthopaedics Tracking Injuries and Outcomes Network (MOTION) database was queried for anterior shoulder stabilization procedures from 2016 to 2021. A nonparametric decision tree analysis was used to generate a framework for classifying surgeon decision making based on specified injury characteristics (labral tear location, glenoid bone loss [GBL], Hill-Sachs lesion [HSL] size, and on-track vs off-track HSL).

Results

A total of 525 procedures were included in the final analysis, with a mean patient age of 25.9 ± 7.2 years and a mean GBL percentage of 3.6% ± 6.8%. HSLs were described based on size as absent (n = 354), mild (n = 129), moderate (n = 40), and severe (n = 2) and as on-track versus off-track in 223 cases, with 17% (n = 38) characterized as off-track. Arthroscopic labral repair (n = 428, 82%) was the most common procedure, whereas open repair (n = 10, 1.9%) and glenoid augmentation (n = 44, 8.4%) were performed infrequently. Decision tree analysis identified a GBL threshold of 17% or greater that resulted in an 89% probability of glenoid augmentation. Shoulders with GBL less than 17% combined with a mild or absent HSL had a 95% probability of an isolated arthroscopic labral repair, whereas a moderate or severe HSL resulted in a 79% probability of arthroscopic repair with remplissage. The presence of an off-track HSL did not contribute to the decision-making process as defined by the algorithm and data available.

Conclusions

Among military shoulder surgeons, GBL of 17% or greater is predictive of a glenoid augmentation procedure whereas HSL size is predictive of remplissage for GBL less than 17%. However, the on-track/off-track paradigm does not appear to affect military surgeons' decision making.

Level of Evidence

Level III, retrospective cohort study.

High Incidence of Combined and Posterior Labral Tears in Military Patients With Operative Shoulder Instability

BACKGROUND

Anterior shoulder instability is the pattern most commonly reported in the civilian population, but military servicemembers may represent a unique population. At 1.7 per 1000 person-years, servicemembers not only have a higher incidence of instability events compared with civilians (reported rate of 0.2-0.8), but the distribution of labral tears in the military may differ significantly as well.

HYPOTHESIS

The incidence of combined and posterior labral tears in the military population will be greater than numbers previously reported.

STUDY DESIGN

Cross-sectional study; Level of evidence, 3.

METHODS

The Wounded, Ill, and Injured Registry, a Department of Defense patient reported outcomes data collection platform that includes all military branches, was queried retrospectively for all patients who had undergone a primary arthroscopic or open shoulder stabilization procedure (Current Procedural Terminology codes 29806, 23455, 23462) between October 2016 and January 2019. Demographic information was obtained through intake forms completed by patients at the time of enrollment into the Military Orthopaedics Tracking Injuries and Outcomes Network. Tear location was determined arthroscopically and labeled as anterior, inferior, posterior, superior, or any combination thereof. Chi-square analysis was used to compare the percentage of patients with isolated anterior, isolated posterior, isolated inferior, or combined labral tears in the current study cohort with those in a previously reported cohort of patients with operative shoulder instability at a single military treatment facility.

RESULTS

A total of 311 patients were included who had undergone primary shoulder stabilization during the study period. Of these patients, 94 (30.2%) had isolated anterior tears, 76 (24.4%) had isolated posterior tears, and 136 (43.7%) had combined tears. We observed a higher percentage of combined tears in our data set than in a data set from a single military treatment facility (χ²(2) = 48.2; P < .00001). Chi-square analysis demonstrated that significantly more female patients had an isolated anterior labral tear (51.2%) compared with male patients (27.1%; χ²(2) = 9.4; P = .009).

CONCLUSION

The incidence of combined and posterior labral tears in the military population is greater than numbers previously reported in both military and civilian populations.

A High-Sensitivity International Knee Documentation Committee Survey Index From the PROMIS System: The Next-Generation Patient-Reported Outcome for a Knee Injury Population

BACKGROUND

Patient-reported outcomes (PROs) measure progression and quality of care. While legacy PROs such as the International Knee Documentation Committee (IKDC) survey are well-validated, a lengthy PRO creates a time burden on patients, decreasing adherence. In recent years, PROs such as the Patient-Reported Outcomes Measurement Information System (PROMIS) Physical Function and Pain Interference surveys were developed as computer adaptive tests, reducing time to completion. Previous studies have examined correlation between legacy PROs and PROMIS; however, no studies have developed effective prediction models utilizing PROMIS to create an IKDC index. While the IKDC is the standard knee PRO, computer adaptive PROs offer numerous practical advantages.

PURPOSE

To develop a nonlinear predictive model utilizing PROMIS Physical Function and Pain Interference to estimate IKDC survey scores and examine algorithm sensitivity and validity.

STUDY DESIGN

Cohort study (diagnosis); Level of evidence, 3.

METHODS

The MOTION (Military Orthopaedics Tracking Injuries and Outcomes Network) database is a prospectively collected repository of PROs and intraoperative variables. Patients undergoing knee surgery completed the IKDC and PROMIS surveys at varying time points. Nonlinear multivariable predictive models using Gaussian and beta distributions were created to establish an IKDC index score, which was then validated using leave-one-out techniques and minimal clinically important difference analysis.

RESULTS

A total of 1011 patients completed the IKDC and PROMIS Physical Function and Pain Interference, providing 1618 complete observations. The algorithms for the Gaussian and beta distribution were validated to predict the IKDC (Pearson = 0.84-0.86; R² = 0.71-0.74; root mean square error = 9.3-10.0).

CONCLUSION

The publicly available predictive models can approximate the IKDC score. The results can be used to compare PROMIS Physical Function and Pain Interference against historical IKDC scores by creating an IKDC index score. Serial use of the IKDC index allows for a lower minimal clinically important difference than the conventional IKDC. PROMIS can be substituted to reduce patient burden, increase completion rates, and produce orthopaedic-specific survey analogs.

Generating the American Shoulder and Elbow Surgeons Score Using Multivariable Predictive Models and Computer Adaptive Testing to Reduce Survey Burden

BACKGROUND

The preferred patient-reported outcome measure for the assessment of shoulder conditions continues to evolve. Previous studies correlating the Patient-Reported Outcomes Measurement Information System (PROMIS) computer adaptive tests (CATs) to the American Shoulder and Elbow Surgeons (ASES) score have focused on a singular domain (pain or physical function) but have not evaluated the combined domains of pain and physical function that compose the ASES score. Additionally, previous studies have not provided a multivariable prediction tool to convert PROMIS scores to more familiar legacy scores.

PURPOSE

To establish a valid predictive model of ASES scores using a nonlinear combination of PROMIS domains for physical function and pain.

STUDY DESIGN

Cohort study (Diagnosis); Level of evidence, 3.

METHODS

The Military Orthopaedics Tracking Injuries and Outcomes Network (MOTION) database is a prospectively collected repository of patient-reported outcomes and intraoperative variables. Patients in MOTION research who underwent shoulder surgery and completed the ASES, PROMIS Physical Function, and PROMIS Pain Interference at varying time points were included in the present analysis. Nonlinear multivariable predictive models were created to establish an ASES index score and then validated using "leave 1 out" techniques and minimal clinically important difference /substantial clinical benefit (MCID/SCB) analysis.

RESULTS

A total of 909 patients completed the ASES, PROMIS Physical Function, and PROMIS Pain Interference at presurgery, 6 weeks, 6 months, and 1 year after surgery, providing 1502 complete observations. The PROMIS CAT predictive model was strongly validated to predict the ASES (Pearson coefficient = 0.76-0.78; R² = 0.57-0.62; root mean square error = 13.3-14.1). The MCID/SCB for the ASES was 21.7, and the best ASES index MCID/SCB was 19.4, suggesting that the derived ASES index is effective and can reliably re-create ASES scores.

CONCLUSION

The PROMIS CAT predictive models are able to approximate the ASES score within 13 to 14 points, which is 7 points more accurate than the ASES MCID/SCB derived from the sample. Our ASES index algorithm, which is freely available online (https://osf.io/ctmnd/), has a lower MCID/SCB than the ASES itself. This algorithm can be used to decrease patient survey burden by 11 questions and provide a reliable ASES analog to clinicians.