Can the Knee Outcome and Osteoarthritis Score (KOOS) Function Subscale Be Linked to the PROMIS Physical Function to Crosswalk Equivalent Scores?

BACKGROUND: An increased focus on patient-reported outcome measures (PROMs) has led to a proliferation of these measures in orthopaedic surgery. Mandating a single PROM in clinical and research orthopaedics is not feasible given the breadth of data already collected with older measures and the emergence of psychometrically superior measures. Creating crosswalk tables for scores between measures allows providers to maintain control of measure choice. Furthermore, crosswalk tables permit providers to compare scores collected with older outcome measures with newly collected ones. Given the widespread use of the newer Patient-reported Outcome Measure Information System Physical Function (PROMIS PF) and the established Knee Outcome and Osteoarthritis Score (KOOS), it would be clinically useful to link these two measures. QUESTION/PURPOSE: Can the KOOS Function in Activities of Daily Living (ADL) subscale be robustly linked to the PROMIS PF to create a crosswalk table of equivalent scores that accurately reflects a patient's reported physical function level on both scales? METHODS: We sought to establish a common standardized metric for collected responses to the PROMIS PF and the KOOS ADL to develop equations for converting a PROMIS PF score to a score for the KOOS-ADL subscale and vice versa. To do this, we performed a retrospective, observational study at two academic medical centers and two community hospitals in an urban and suburban healthcare system. Patients 18 years and older who underwent TKA were identified. Between January 2017 and July 2020, we treated 8165 patients with a TKA, 93% of whom had a diagnosis of primary osteoarthritis. Of those, we considered patients who had completed a full KOOS and PROMIS PF 10a on the same date as potentially eligible. Twenty-one percent (1708 of 8165) of patients were excluded because no PROMs were collected at any point, and another 67% (5454 of 8165) were excluded because they completed only one of the required PROMs, leaving 12% (1003 of 8165) for analysis here. PROMs were collected each time they visited the health system before and after their TKAs. Physical function was measured by the PROMIS PF version 1.0 SF 10a and KOOS ADL scale. Analyses to accurately create a crosswalk of equivalent scores between the measures were performed using the equipercentile linking method with both unsmoothed and log linear smoothed score distributions. RESULTS: Crosswalks were created, and adequate validation results supported their validity; we also created tables to allow clinicians and clinician scientists to convert individual patients' scores easily. The mean difference between the observed PROMIS PF scores and the scores converted by the crosswalk from the KOOS-ADL scores was -0.08 ± 4.82. A sensitivity analysis was conducted, confirming the effectiveness of these crosswalks to link the scores of two measures from patients both before and after surgery. CONCLUSION: The PROMIS PF 10a can be robustly linked to the KOOS ADL measure. The developed crosswalk table can be used to convert PROMIS PF scores from KOOS ADL and vice versa. CLINICAL RELEVANCE: The creation of a crosswalk table between the KOOS Function in ADL subscale and PROMIS PF allows clinicians and researchers to easily convert scores between the measures, thus permitting greater choice in PROM selection while preserving comparability between patient cohorts and PROM data collected from older outcome measures. Creating a crosswalk, or concordance table, between the two scales will facilitate this comparison, especially when pooling data for meta-analyses.

Establishing a recommended duration of blood glucose monitoring in nondiabetic patients following orthopaedic surgery.

Previous studies have demonstrated that blood glucose (BG) levels should be monitored for at least 1 week after orthopaedic surgery in diabetic patients, but no study has determined how long nondiabetic patients should be monitored. As postoperative elevations in BG have deleterious effects, determining a duration for monitoring the BG of nondiabetic patients after major orthopaedic surgery is needed to detect hyperglycemic events, create comprehensive protocols for nondiabetic orthopaedic patients, and reduce adverse outcomes. A retrospective study was conducted including consecutive patients who underwent a major orthopaedic surgery at a community hospital. A BG level of 150 mg/dl was the cutoff used to define hyperglycemia according to our institutional guidelines. A χ2 , analysis of variance, and subgroup analysis were performed separately. Greater than 67% of nondiabetic patients experienced a high BG level (>150 mg/dl) after surgery. We found that nondiabetic patients reached their postoperative maximum BG level at 20 h, which was sooner compared to diabetic patients. We discovered more than 92% of nondiabetic patients reached a maximum BG levels within the first 72 h of hospitalization, while the BG levels after this period were found to be within normal limits in greater than 87% of cases. We propose that BG management be instituted in nondiabetics from the preoperative period to 72 h after surgery, including patients who are same-day discharges. There may not be a need to continue inpatient BG monitoring beyond the first 72 h for nondiabetic hospitalized patients with extended hospitalizations.

Linking Hip Disability and Osteoarthritis Outcome Score-Physical Function Short Form and PROMIS Physical Function.

INTRODUCTION: Linking scores on patient-reported outcome measures can enable data aggregation for research, clinical care, and quality. We aimed to link scores on the Hip Disability and Osteoarthritis Outcome Score-Physical Function Short Form (HOOS-PS) and the Patient-reported Outcomes Measurement Information System Physical Function (PROMIS PF). METHODS: A retrospective study was conducted from 2017 to 2020 evaluating patients with hip osteoarthritis who received routine clinical care from an orthopaedic surgeon. Our sample included 3,382 unique patients with 7,369 pairs of HOOS-PS and PROMIS PF measures completed at a single nonsurgical, preoperative, or postoperative time point. We included one randomly selected time point of scores for each patient in our linking analysis sample. We compared the accuracy of linking using four methods, including equipercentile and item response theory-based approaches. RESULTS: PROMIS PF and HOOS-PS scores were strongly correlated ( r = -0.827 for raw HOOS-PS scores and r = 0.820 for summary HOOS-PS scores). The assumptions were met for equipercentile and item response theory approaches to linking. We selected the item response theory-based Stocking-Lord approach as the optimal crosswalk and estimated item parameters for the HOOS-PS items on the PROMIS metric. A sensitivity analysis demonstrated overall robustness of the crosswalk estimates in nonsurgical, preoperative, and postoperative patients. CONCLUSION: These crosswalks can be used to convert scores between HOOS-PS and PROMIS PF metric at the group level, which can be valuable for data aggregation. Conversion of individual patient-level data is not recommended secondary to increased risk of error.

Linking the KOOS-PS to PROMIS Physical Function in Knee Patients Evaluated for Surgery.

INTRODUCTION: The Knee Injury and Osteoarthritis Outcome Score-Physical Function Short-form and the Patient-Reported Outcomes Measurement Information System Physical Function are widely used patient-reported outcome measures in orthopaedic practice and research. It would be helpful for clinicians and researchers to compare scores obtained on one instrument with those collected on another. To achieve this goal, this study conducted a linking analysis and computed a crosswalk table between these two scales. DATA: The data of this study were collected as part of the clinical care of total knee arthroplasty patients in a large urban and suburban health system. The sample was a mix of responses from nonsurgical (no surgery performed), preoperative (before surgical intervention), and postoperative (after surgical intervention) groups. METHODS: This study applied five linking methods: the item response theory (IRT)-based linking methods including fixed-parameter calibration, separate-parameter calibration with Stocking-Lord constants, and calibrated projection; and the equipercentile methods with log-linear smoothing and nonsmoothing approaches. Before conducting the linking analysis, we checked the linking assumptions including the similar content of the two scales, the unidimensionality of the combined scales, and the population invariance. The results of the five linking methods were evaluated by mean difference, SD, root-mean-squared deviation, intraclass correlation coefficient of the observed T scores and the crosswalk-derived T scores. RESULTS: The linking assumptions were all met. T scores generated from the Stocking-Lord crosswalk had the smallest mean difference (= -0.03) and relatively small SD (= 4.91) and root-mean-squared deviation (= 4.91) among the five linking methods. We validated this crosswalk in a larger sample with the nonsurgical, preoperative, and postoperative groups and in an external sample. DISCUSSION: This study provides clinicians and researchers a practical tool (ie, a crosswalk table) to link scores from two popular physical function measures. Given the diversity of patient-reported outcome measures in use for knee conditions, these crosswalk tables would accelerate clinical and research interpretation of aggregating functional outcomes among the patients evaluated for knee surgery each year.