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Bone & Joint Open
Vol. 2, Issue 12 | Pages 1089 - 1095
21 Dec 2021
Luo W Ali MS Limb R Cornforth C Perry DC

Aims. The Patient-Reported Outcomes Measurement Information System (PROMIS) has demonstrated faster administration, lower burden of data capture and reduced floor and ceiling effects compared to traditional Patient Reported Outcomes Measurements (PROMs). We investigated the suitability of PROMIS Mobility score in assessing physical function in the sequelae of childhood hip disease. Methods. In all, 266 adolscents (aged ≥ 12 years) and adults were identified with a prior diagnosis of childhood hip disease (either Perthes’ disease (n = 232 (87.2%)) or Slipped Capital Femoral Epiphysis (n = 34 (12.8%)) with a mean age of 27.73 years (SD 12.24). Participants completed the PROMIS Mobility Computer Adaptive Test, the Non-Arthritic Hip Score (NAHS), EuroQol five-dimension five-level questionnaire, and the Numeric Pain Rating Scale. We investigated the correlation between the PROMIS Mobility and other tools to assess use in this population and any clustering of outcome scores. Results. There was a strong correlation between the PROMIS Mobility and other established PROMs; NAHS (rs = 0.79; p < 0.001). There was notable clustering in PROMIS at the upper end of the distribution score (42.5%), with less seen in the NAHS (20.3%). However, the clustering was broadly similar between PROMIS Mobility and the comparable domains of the NAHS; function (53.6%), and activity (35.0%). Conclusion. PROMIS Mobility strongly correlated with other tools demonstrating convergent construct validity. There was clustering of physical function scores at the upper end of the distributions, which may reflect truncation of the data caused by participants having excellent outcomes. There were elements of disease not captured within PROMIS Mobility alone, and difficulties in differentiating those with the highest levels of function. Cite this article: Bone Jt Open 2021;2(12):1089–1095


Bone & Joint Open
Vol. 5, Issue 3 | Pages 174 - 183
6 Mar 2024
Omran K Waren D Schwarzkopf R

Aims. Total hip arthroplasty (THA) is a common procedure to address pain and enhance function in hip disorders such as osteoarthritis. Despite its success, postoperative patient recovery exhibits considerable heterogeneity. This study aimed to investigate whether patients follow distinct pain trajectories following THA and identify the patient characteristics linked to suboptimal trajectories. Methods. This retrospective cohort study analyzed THA patients at a large academic centre (NYU Langone Orthopedic Hospital, New York, USA) from January 2018 to January 2023, who completed the Patient-Reported Outcomes Measurement Information System (PROMIS) pain intensity questionnaires, collected preoperatively at one-, three-, six-, 12-, and 24-month follow-up times. Growth mixture modelling (GMM) was used to model the trajectories. Optimal model fit was determined by Bayesian information criterion (BIC), Vuong-Lo-Mendell-Rubin likelihood ratio test (VLMR-LRT), posterior probabilities, and entropy values. Association between trajectory groups and patient characteristics were measured by multinomial logistic regression using the three-step approach. Results. Among the 1,249 patients, a piecewise GMM model revealed three distinct pain trajectory groups: 56 patients (4.5%) in group 1; 1,144 patients (91.6%) in group 2; and 49 patients (3.9%) in group 3. Patients in group 2 experienced swift recovery post-THA and minimal preoperative pain. In contrast, groups 1 and 3 initiated with pronounced preoperative pain; however, only group 3 exhibited persistent long-term pain. Multinomial regression indicated African Americans were exceedingly likely to follow trajectory groups 1 (odds ratio (OR) 2.73) and 3 (OR 3.18). Additionally, odds of membership to group 3 increased by 12% for each BMI unit rise, by 19% for each added postoperative day, and by over four if discharged to rehabilitation services (OR 4.07). Conclusion. This study identified three distinct pain trajectories following THA, highlighting the role of individual patient factors in postoperative recovery. This emphasizes the importance of preoperatively addressing modifiable risk factors associated with suboptimal pain trajectories, particularly in at-risk patients. Cite this article: Bone Jt Open 2024;5(3):174–183


Bone & Joint Open
Vol. 4, Issue 5 | Pages 299 - 305
2 May 2023
Shevenell BE Mackenzie J Fisher L McGrory B Babikian G Rana AJ

Aims

Obesity is associated with an increased risk of hip osteoarthritis, resulting in an increased number of total hip arthroplasties (THAs) performed annually. This study examines the peri- and postoperative outcomes of morbidly obese (MO) patients (BMI ≥ 40 kg/m2) compared to healthy weight (HW) patients (BMI 18.5 to < 25 kg/m2) who underwent a THA using the anterior-based muscle-sparing (ABMS) approach.

Methods

This retrospective cohort study observes peri- and postoperative outcomes of MO and HW patients who underwent a primary, unilateral THA with the ABMS approach. Data from surgeries performed by three surgeons at a single institution was collected from January 2013 to August 2020 and analyzed using Microsoft Excel and Stata 17.0.


The Bone & Joint Journal
Vol. 102-B, Issue 7 Supple B | Pages 90 - 98
1 Jul 2020
Florissi I Galea VP Sauder N Colon Iban Y Heng M Ahmed FK Malchau H Bragdon CR

Aims

The primary aim of this paper was to outline the processes involved in building the Partners Arthroplasty Registry (PAR), established in April 2016 to capture baseline and outcome data for patients undergoing arthroplasty in a regional healthcare system. A secondary aim was to determine the quality of PAR’s data. A tertiary aim was to report preliminary findings from the registry and contributions to quality improvement initiatives and research up to March 2019.

Methods

Structured Query Language was used to obtain data relating to patients who underwent total hip or knee arthroplasty (THA and TKA) from the hospital network’s electronic medical record (EMR) system to be included in the PAR. Data were stored in a secure database and visualized in dashboards. Quality assurance of PAR data was performed by review of the medical records. Capture rate was determined by comparing two months of PAR data with operating room schedules. Linear and binary logistic regression models were constructed to determine if length of stay (LOS), discharge to a care home, and readmission rates improved between 2016 and 2019.