Clinical and Statistical Validation of a Probabilistic Prediction Tool of Total Knee Arthroplasty Outcome.

BACKGROUND: Predicting patients at risk of a poor outcome would be useful in patient selection for total knee arthroplasty (TKA). Existing models to predict outcome have seen limited functional implementation. This study aims to validate a model and shared decision-making tool for both clinical utility and predictive accuracy. METHODS: A Bayesian belief network statistical model was developed using data from the Osteoarthritis Initiative. A consecutive series of consultations for osteoarthritis before and after introduction of the tool was used to evaluate the clinical impact of the tool. A data audit of postoperative outcomes of TKA patients exposed to the tool was used to evaluate the accuracy of predictions. RESULTS: The tool changed consultation outcomes and identified patients at risk of limited improvement. After introduction of the tool, patients booked for surgery reported worse Knee Osteoarthritis and Injury Outcome Score pain scores (difference, 15.2; P < .001) than those not booked, with no significant difference prior. There was a 27% chance of not improving if predicted at risk, and a 1.4% chance if predicted to improve. This gives a risk ratio of 19× (P < .001) for patients not improving if predicted at risk. CONCLUSION: For a prediction tool to be clinically useful, it needs to provide a better understanding of the likely clinical outcome of an intervention than existed without its use when the clinical decisions are made. The tool presented here has the potential to direct patients to surgical or nonsurgical pathways on a patient-specific basis, ensuring patients who will benefit most from TKA surgery are selected.

Orthostatic Intolerance-Type Events Following Hip and Knee Arthroplasty: A Systematic Review and Meta-Analysis.

BACKGROUND: Orthostatic intolerance (OI)-type events following hip and knee arthroplasty increase the risk of falls, hospital length of stay, and health-care costs. There is a limited understanding of the incidence of and risk factors for OI-type events in patients during the acute hospital stay. Our aim was to systematically review the incidence of and risk factors for OI-type events during the acute hospital stay following hip and knee arthroplasty. METHODS: A systematic review and meta-analysis of studies that investigated the incidence of and risk factors for OI-type events was undertaken. A comprehensive search was performed in MEDLINE, Embase, and CINAHL from their inception to October 2021. The methodological quality of identified studies was assessed using the modified version of the Quality in Prognosis Studies (QUIPS) tool. RESULTS: Twenty-one studies (14,055 patients) were included. The incidence was 2% to 52% for an OI event, 1% to 46% for orthostatic hypotension, and 0% to 18% for syncope/vasovagal events. Two studies reported female sex, high peak pain levels (>5 out of 10) during mobilization, postoperative use of gabapentin, and the absence of postoperative intravenous dexamethasone as risk factors. There was no consensus on the definition and assessment of an OI-type event. CONCLUSIONS: OI-type events are common during the acute hospital stay following hip and knee arthroplasty, and 4 risk factors have been reported for OI-type events. High-quality prospective cohort studies are required to systematically and reliably determine the incidence of and risk factors for OI-type events. LEVEL OF EVIDENCE: Prognostic Level IV. See Instructions for Authors for a complete description of levels of evidence.

Variation in femoral anteversion in patients requiring total hip replacement.

BACKGROUND: Optimal implant alignment is important for total hip replacement (THR) longevity. Femoral stem anteversion is influenced by the native femoral anteversion. Knowing a patient's femoral morphology is therefore important when planning optimal THR alignment. We investigated variation in femoral anteversion across a patient population requiring THR. METHODS: Preoperatively, native femoral neck anteversion was measured from 3-dimensional CT reconstructions in 1215 patients. RESULTS: The median femoral anteversion was 14.4° (-27.1-54.5°, IQR 7.4-20.9°). There were significant gender differences (males 12.7°, females 16.0°; p < 0.0001). Femoral anteversion in males decreased significantly with increasing age. 14% of patients had extreme anteversion (<0° or >30°). CONCLUSIONS: This is the largest series investigating native femoral anteversion in a THR population. Patient variation was large and was similar to published findings of a non-THR population. Gender and age-related differences were observed. Native femoral anteversion is patient-specific and should be considered when planning THR.

Accurate determination of post-operative 3D component positioning in total knee arthroplasty: the AURORA protocol.

BACKGROUND: Successful component alignment is a major metric of success in total knee arthroplasty. Component translational placement, however, is less well reported despite being shown to affect patient outcomes. CT scans and planar X-rays are routinely used to report alignment but do not report measurements as precisely or accurately as modern navigation systems can deliver, or with reference to the pre-operative anatomy. METHODS: A method is presented here that utilises a CT scan obtained for pre-operative planning and a post-operative CT scan for analysis to recreate a computation model of the knee with patient-specific axes. This model is then used to determine the post-operative component position in 3D space. RESULTS: Two subjects were investigated for reproducibility producing 12 sets of results. The maximum error using this technique was 0.9° ± 0.6° in rotation and 0.5 mm ± 0.3 mm in translation. Eleven subjects were investigated for reliability producing 22 sets of results. The intra-class correlation coefficient for each of the three axes of rotation and three primary resection planes was > 0.93 indicating excellent reliability. CONCLUSIONS: Routine use of this analysis will allow surgeons and engineers to better understand the effect of component alignment as well as the placement on outcome.