DKF - Clinical Research Day 2022

(1) Introduction

Valid clinical outcome data are essential to assess the safety and effectiveness of surgical interventions, to perform benchmarking activities, and to foster a well-founded decision-making process in orthopedics. In this context, we designed a multicenter cohort study called ARCR_Pred following patients after an arthroscopic rotator cuff repair (ARCR), with a primary aim of developing a clinical prediction model intended to predict individualized shoulder function improvement during clinical examinations or to monitor the occurrence of frequently reported adverse events. The present abstract aims to describe the methodological processes ensuring patient recruitment and key baseline characteristics of the recruited patients before conducting further analyses.

(2) Methods

Patients were recruited in 19 University Hospitals, private clinics, or private practices in Switzerland and 1 in Germany (see Figure 1). We considered all adults patients preoperatively diagnosed with a partial or full-thickness rotator cuff tear by magnetic resonance imaging (MRI) and primarily repaired per arthroscopy eligible. A sample size of 970 patients was estimated necessary for adequate clinical prediction model development. Patients attended clinical examinations pre-operatively, at 6 weeks, 6 months, and 12 months after the surgery. We invited patients to fill out questionnaires before the surgery, at 6 months, 12 months, and 24 months after the surgery. Based on our systematic review results, multiple potential prognostic factors were recorded including patient baseline demographics, psychological, socioeconomic, and clinical factors, rotator cuff integrity and concomitant local findings, and operative or postoperative management factors. A REDCap database was designed for the study. Intensive remote monitoring activities were implemented with weekly-sent monitoring lists to avoid missing data and to ensure data quality. Intensive on-site monitoring activities were implemented with bi-yearly organized on-site monitoring visits to ensure patient safety and site compliance to the protocol. Processes and patient characteristics were described using means and standard deviations for continuous variables and numbers and percentages for categorical variables.

(3) Results – processes and cohort description

We recruited 985 participants operated by 54 surgeons between June 2020 and November 2021 (see Figure 2). Completion rate reached 98% for the 6 weeks clinical examination. Overall, 96% of 8231 forms were completely documented. Participants were on average 57 (± 9) years old at the time of surgery and were mostly men (63%, n = 621). A majority of participants presented at least one other comorbidity (51%, n = 512), affected notably by hypertension (21.5%, n = 212), hypercholesterolemia (11.2%, n = 110), or diabetes (4.4%, n = 43). Patients having shoulder complaints for at least 6 months were the most important group representing 49.5% of the cases (n = 488). Based on arthroscopic findings, the supraspinatus muscle was affected in 92% (n = 910) of the cases, whereas the infraspinatus and subscapularis muscles were involved in 41% (n = 403) and 48% (n = 517) of the cases, respectively. Participants had limitations in active range of motion reaching on average 128 (± 44) degrees in flexion and 116 (±46) degrees in abduction. The average score for the pain level experienced the week before the surgery was 6 (±2) points and the average shoulder functional score using the Oxford Shoulder Score were 27 (± 9) points.

(4) Conclusions

This project initiates the development of personalized risk predictions to support the surgical decision process in ARCR, which should rely on prospectively documented data. This study fosters the condition towards the development of a Swiss national ARCR register with a focus on patient-oriented outputs. Methodological insights gained from this work will be easily transferable to similar initiatives in orthopedics.

Thomas Stojanov
Thomas Stojanov
Postdoctoral researcher

I am mainly focused on the initiation and the analysis of observational studies with a life sciences and epidemiology background.