Development and validation of cardiovascular risk prediction equations in 76 000 people with known cardiovascular disease.

AIMS: Multiple health administrative databases can be individually linked in Aotearoa New Zealand, using encrypted identifiers. These databases were used to develop cardiovascular risk prediction equations for patients with known cardiovascular disease (CVD). METHODS AND RESULTS: Administrative health databases were linked to identify all people aged 18-84 years with known CVD, living in Auckland and Northland, Aotearoa New Zealand, on 1 January 2014. The cohort was followed until study outcome, death, or 5 years. The study outcome was death or hospitalization due to ischaemic heart disease, stroke, heart failure, or peripheral vascular disease. Sex-specific 5-year CVD risk prediction equations were developed using multivariable Fine and Gray models. A total of 43 862 men {median age: 67 years [interquartile range (IQR): 59-75]} and 32 724 women [median age: 70 years (IQR: 60-77)] had 14 252 and 9551 cardiovascular events, respectively. Equations were well calibrated with good discrimination. Increasing age and deprivation, recent cardiovascular hospitalization, Mori ethnicity, smoking history, heart failure, diabetes, chronic renal disease, atrial fibrillation, use of blood pressure lowering and anti-thrombotic drugs, haemoglobin A1c, total cholesterol/HDL cholesterol, and creatinine were statistically significant independent predictors of the study outcome. Fourteen per cent of men and 23% of women had predicted 5-year cardiovascular risk <15%, while 28 and 24% had ≥40% risk. CONCLUSION: Robust cardiovascular risk prediction equations were developed from linked routine health databases, a currently underutilized resource worldwide. The marked heterogeneity demonstrated in predicted risk suggests that preventive therapy in people with known CVD would be better informed by risk stratification beyond a one-size-fits-all high-risk categorization.

Using regionwide New Zealand health databases, methods of predicting hospitalization risk in patients with existing heart disease were developed. Using only data from health databases, it was possible to predict the risk accurately.Among patients with existing heart disease, the predicted risk varied markedly which could help improve preventive strategies.

Tibial metaphyseal cones combined with short stems perform as well as long stems in revision total knee arthroplasty.

BACKGROUNDS: There is uncertainty around optimal tibial stem length in revision total knee arthroplasty (rTKA) utilizing a tibial trabecular metal (TM) cone. The purpose of this study was to compare: (1) functional outcomes, (2) radiographic outcomes and (3) implant survivorship in rTKA utilizing TM cones combined with either short stems (SS) or long stems (LS) at minimum 2 years follow-up. METHODS: In this retrospective, multi-centre study, patients undergoing rTKA utilizing a TM cone between 2008 and 2019 were included. Patients were divided into: SS group (no diaphyseal engagement), and LS group (diaphyseal engagement). All relevant clinical charts and post-operative radiographs were examined. Oxford Knee Score (OKS) and EuroQol-5D (EQ-5D-5L) data were collected at most recent follow-up. RESULTS: In total, 44 patients were included: 18 in the SS group and 26 in the LS group. The mean time of follow-up was 4.0 years. Failure free survival was 94.4% for the SS group and 92.3% for the LS group. All failures were for prosthetic joint infections managed with debridement, antibiotics, and implant retention. At most recent follow-up, 3 patients demonstrated radiographic signs of lucency (1 SS 2 LS, P = 1) and the mean OKS were 37 ± 4 and 36 ± 6 (P = 0.73) in the SS and LS groups, respectively. CONCLUSION: Tibial SS combined with TM cones performed as well as LS in rTKA at minimum 2 years follow-up. A tibial SS in combination with a TM cone is a reliable technique to achieve stable and durable fixation in rTKA.

Remote Patient Monitoring with Wearable Sensors Following Knee Arthroplasty.

(Background) Inertial Measurement Units (IMUs) provide a low-cost, portable solution to obtain functional measures similar to those captured with three-dimensional gait analysis, including spatiotemporal gait characteristics. The primary aim of this study was to determine the feasibility of a remote patient monitoring (RPM) workflow using ankle-worn IMUs measuring impact load, limb impact load asymmetry and knee range of motion in combination with patient-reported outcome measures. (Methods) A pilot cohort of 14 patients undergoing primary knee arthroplasty for osteoarthritis was prospectively enrolled. RPM in the community was performed weekly from 2 up to 6 weeks post-operatively using wearable IMUs. The following data were collected using IMUs: mobility (Bone Stimulus and cumulative impact load), impact load asymmetry and maximum knee flexion angle. In addition, scores from the Oxford Knee Score (OKS), EuroQol Five-dimension (EQ-5D) with EuroQol visual analogue scale (EQ-VAS) and 6 Minute Walk Test were collected. (Results) On average, the Bone Stimulus and cumulative impact load improved 52% (p = 0.002) and 371% (p = 0.035), compared to Post-Op Week 2. The impact load asymmetry value trended (p = 0.372) towards equal impact loading between the operative and non-operative limb. The mean maximum flexion angle achieved was 99.25° at Post-Operative Week 6, but this was not significantly different from pre-operative measurements (p = 0.1563). There were significant improvements in the mean EQ-5D (0.20; p = 0.047) and OKS (10.86; p < 0.001) scores both by 6 weeks after surgery, compared to pre-operative scores. (Conclusions) This pilot study demonstrates the feasibility of a reliable and low-maintenance workflow system to remotely monitor post-operative progress in knee arthroplasty patients. Preliminary data indicate IMU outputs relating to mobility, impact load asymmetry and range of motion can be obtained using commercially available IMU sensors. Further studies are required to directly correlate the IMU sensor outputs with patient outcomes to establish clinical significance.