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The Bone & Joint Journal
Vol. 102-B, Issue 9 | Pages 1183 - 1193
14 Sep 2020
Anis HK Strnad GJ Klika AK Zajichek A Spindler KP Barsoum WK Higuera CA Piuzzi NS

Aims. The purpose of this study was to develop a personalized outcome prediction tool, to be used with knee arthroplasty patients, that predicts outcomes (lengths of stay (LOS), 90 day readmission, and one-year patient-reported outcome measures (PROMs) on an individual basis and allows for dynamic modifiable risk factors. Methods. Data were prospectively collected on all patients who underwent total or unicompartmental knee arthroplasty at a between July 2015 and June 2018. Cohort 1 (n = 5,958) was utilized to develop models for LOS and 90 day readmission. Cohort 2 (n = 2,391, surgery date 2015 to 2017) was utilized to develop models for one-year improvements in Knee Injury and Osteoarthritis Outcome Score (KOOS) pain score, KOOS function score, and KOOS quality of life (QOL) score. Model accuracies within the imputed data set were assessed through cross-validation with root mean square errors (RMSEs) and mean absolute errors (MAEs) for the LOS and PROMs models, and the index of prediction accuracy (IPA), and area under the curve (AUC) for the readmission models. Model accuracies in new patient data sets were assessed with AUC. Results. Within the imputed datasets, the LOS (RMSE 1.161) and PROMs models (RMSE 15.775, 11.056, 21.680 for KOOS pain, function, and QOL, respectively) demonstrated good accuracy. For all models, the accuracy of predicting outcomes in a new set of patients were consistent with the cross-validation accuracy overall. Upon validation with a new patient dataset, the LOS and readmission models demonstrated high accuracy (71.5% and 65.0%, respectively). Similarly, the one-year PROMs improvement models demonstrated high accuracy in predicting ten-point improvements in KOOS pain (72.1%), function (72.9%), and QOL (70.8%) scores. Conclusion. The data-driven models developed in this study offer scalable predictive tools that can accurately estimate the likelihood of improved pain, function, and quality of life one year after knee arthroplasty as well as LOS and 90 day readmission. Cite this article: Bone Joint J 2020;102-B(9):1183–1193


The Bone & Joint Journal
Vol. 103-B, Issue 1 | Pages 113 - 122
1 Jan 2021
Kayani B Tahmassebi J Ayuob A Konan S Oussedik S Haddad FS

Aims

The primary aim of this study was to compare the postoperative systemic inflammatory response in conventional jig-based total knee arthroplasty (conventional TKA) versus robotic-arm assisted total knee arthroplasty (robotic TKA). Secondary aims were to compare the macroscopic soft tissue injury, femoral and tibial bone trauma, localized thermal response, and the accuracy of component positioning between the two treatment groups.

Methods

This prospective randomized controlled trial included 30 patients with osteoarthritis of the knee undergoing conventional TKA versus robotic TKA. Predefined serum markers of inflammation and localized knee temperature were collected preoperatively and postoperatively at six hours, day 1, day 2, day 7, and day 28 following TKA. Blinded observers used the Macroscopic Soft Tissue Injury (MASTI) classification system to grade intraoperative periarticular soft tissue injury and bone trauma. Plain radiographs were used to assess the accuracy of achieving the planned postioning of the components in both groups.


The Bone & Joint Journal
Vol. 103-B, Issue 6 Supple A | Pages 81 - 86
1 Jun 2021
Mahfouz MR Abdel Fatah EE Johnson JM Komistek RD

Aims

The objective of this study is to assess the use of ultrasound (US) as a radiation-free imaging modality to reconstruct 3D anatomy of the knee for use in preoperative templating in knee arthroplasty.

Methods

Using an US system, which is fitted with an electromagnetic (EM) tracker that is integrated into the US probe, allows 3D tracking of the probe, femur, and tibia. The raw US radiofrequency (RF) signals are acquired and, using real-time signal processing, bone boundaries are extracted. Bone boundaries and the tracking information are fused in a 3D point cloud for the femur and tibia. Using a statistical shaping model, the patient-specific surface is reconstructed by optimizing bone geometry to match the point clouds. An accuracy analysis was conducted for 17 cadavers by comparing the 3D US models with those created using CT. US scans from 15 users were compared in order to examine the effect of operator variability on the output.


The Bone & Joint Journal
Vol. 101-B, Issue 7 | Pages 838 - 847
1 Jul 2019
Robinson PG Clement ND Hamilton D Blyth MJG Haddad FS Patton JT

Aims

Robotic-assisted unicompartmental knee arthroplasty (UKA) promises accurate implant placement with the potential of improved survival and functional outcomes. The aim of this study was to present the current evidence for robotic-assisted UKA and describe the outcome in terms of implant positioning, range of movement (ROM), function and survival, and the types of robot and implants that are currently used.

Materials and Methods

A search of PubMed and Medline was performed in October 2018 in line with the Preferred Reporting Items for Systematic Review and Meta-Analysis statement. Search terms included “robotic”, “knee”, and “surgery”. The criteria for inclusion was any study describing the use of robotic UKA and reporting implant positioning, ROM, function, and survival for clinical, cadaveric, or dry bone studies.


The Bone & Joint Journal
Vol. 100-B, Issue 1 | Pages 50 - 55
1 Jan 2018
Kono K Tomita T Futai K Yamazaki T Tanaka S Yoshikawa H Sugamoto K

Aims

In Asia and the Middle-East, people often flex their knees deeply in order to perform activities of daily living. The purpose of this study was to investigate the 3D kinematics of normal knees during high-flexion activities. Our hypothesis was that the femorotibial rotation, varus-valgus angle, translations, and kinematic pathway of normal knees during high-flexion activities, varied according to activity.

Materials and Methods

We investigated the in vivo kinematics of eight normal knees in four male volunteers (mean age 41.8 years; 37 to 53) using 2D and 3D registration technique, and modelled the knees with a computer aided design program. Each subject squatted, kneeled, and sat cross-legged. We evaluated the femoral rotation and varus-valgus angle relative to the tibia and anteroposterior translation of the medial and lateral side, using the transepicodylar axis as our femoral reference relative to the perpendicular projection on to the tibial plateau. This method evaluates the femur medially from what has elsewhere been described as the extension facet centre, and differs from the method classically applied.


The Bone & Joint Journal
Vol. 100-B, Issue 8 | Pages 1033 - 1042
1 Aug 2018
Kayani B Konan S Pietrzak JRT Huq SS Tahmassebi J Haddad FS

Aims

The primary aim of this study was to determine the surgical team’s learning curve for introducing robotic-arm assisted unicompartmental knee arthroplasty (UKA) into routine surgical practice. The secondary objective was to compare accuracy of implant positioning in conventional jig-based UKA versus robotic-arm assisted UKA.

Patients and Methods

This prospective single-surgeon cohort study included 60 consecutive conventional jig-based UKAs compared with 60 consecutive robotic-arm assisted UKAs for medial compartment knee osteoarthritis. Patients undergoing conventional UKA and robotic-arm assisted UKA were well-matched for baseline characteristics including a mean age of 65.5 years (sd 6.8) vs 64.1 years (sd 8.7), (p = 0.31); a mean body mass index of 27.2 kg.m2 (sd 2.7) vs 28.1 kg.m2 (sd 4.5), (p = 0.25); and gender (27 males: 33 females vs 26 males: 34 females, p = 0.85). Surrogate measures of the learning curve were prospectively collected. These included operative times, the Spielberger State-Trait Anxiety Inventory (STAI) questionnaire to assess preoperative stress levels amongst the surgical team, accuracy of implant positioning, limb alignment, and postoperative complications.


The Bone & Joint Journal
Vol. 95-B, Issue 10 | Pages 1359 - 1365
1 Oct 2013
Baker PN Rushton S Jameson SS Reed M Gregg P Deehan DJ

Pre-operative variables are increasingly being used to determine eligibility for total knee replacement (TKR). This study was undertaken to evaluate the relationships, interactions and predictive capacity of variables available pre- and post-operatively on patient satisfaction following TKR. Using nationally collected patient reported outcome measures and data from the National Joint Registry for England and Wales, we identified 22 798 patients who underwent TKR for osteoarthritis between August 2008 and September 2010. The ability of specific covariates to predict satisfaction was assessed using ordinal logistic regression and structural equational modelling. Only 4959 (22%) of 22 278 patients rated the results of their TKR as ‘excellent’, despite the majority (71%, n = 15 882) perceiving their knee symptoms to be much improved. The strongest predictors of satisfaction were post-operative variables. Satisfaction was significantly and positively related to the perception of symptom improvement (operative success) and the post-operative EuroQol-5D score. While also significant within the models pre-operative variables were less important and had a minimal influence upon post-operative satisfaction. The most robust predictions of satisfaction occurred only when both pre- and post-operative variables were considered together. These findings question the appropriateness of restricting access to care based on arbitrary pre-operative thresholds as these factors have little bearing on post-operative satisfaction.

Cite this article: Bone Joint J 2013;95-B:1359–65.


The Bone & Joint Journal
Vol. 96-B, Issue 3 | Pages 332 - 338
1 Mar 2014
Dawson J Beard DJ McKibbin H Harris K Jenkinson C Price AJ

The primary aim of this study was to develop a patient-reported Activity & Participation Questionnaire (the OKS-APQ) to supplement the Oxford knee score, in order to assess higher levels of activity and participation. The generation of items for the questionnaire involved interviews with 26 patients. Psychometric analysis (exploratory and confirmatory factor analysis and Rasch analysis) guided the reduction of items and the generation of a scale within a prospective study of 122 relatively young patients (mean age 61.5 years (42 to 71)) prior to knee replacement. A total of 99, completed pre-operative and six month post-operative assessments (new items, OKS, Short-Form 36 and American Knee Society Score).

The eight-item OKS-APQ scale is unidimensional, reliable (Cronbach’s alpha 0.85; intraclass correlation coefficient (ICC) 0.79; or 0.92 when one outlier was excluded), valid (r >  0.5 with related scales) and responsive (effect size 4.16).

We recommend that it is used with the OKS with adults of all ages when further detail regarding the levels of activity and participation of a patient is required.

Cite this article: Bone Joint J 2014;96-B:332–8.