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        Impact of Tibial Tubercle Osteotomy on Final Outcome in Revision Total Knee Arthroplasty: Our Experience and Technique in Pakistan

        Abdul Rafay Qazi,Faizan Iqbal,Syed Shahid Noor,Nasir Ahmed,Akram Ali Uddin,Nouman Memon,Naveed Memon 대한정형외과학회 2021 Clinics in Orthopedic Surgery Vol.13 No.1

        Background: Due to extensive fibrosis during revision surgery, adequate exposure is essential and it can be achieved with several extensile approach options, such as tibial tubercle osteotomy. Information regarding surgical exposure during revision arthroplasty is limited in developing countries, such as Pakistan, due to the lack of adequate data collection and follow-up. Therefore, the purpose of this study was to evaluate the impact of tibial tubercle osteotomy on final outcome of revision total knee arthroplasty (TKA). Methods: A total of 231 revision TKAs were performed between January 2008 and December 2017. Twenty-nine patients underwent tibial tubercle osteotomy for adequate exposure during revision surgery. Of these, 27 patients with complete follow-up were included in our study. Factors examined include age at the time of revision surgery, gender, comorbidities, arthroplasty site (right or left), body mass index (BMI), and primary indications for the tibial tubercle osteotomy during revision TKA. Functional outcome was measured by using Knee Society score (KSS) at 3 months and the final follow-up. All statistical analysis was done using SPSS version 20.0 with a p-value < 0.05 considered significant. Results: Out of 27 patients, 6 patients (22.2%) were men and 21 patients (77.7%) were women. Right knee revision arthroplasty was performed in 15 patients (55.5%), left knee revision arthroplasty was performed in 12 patients (44.4%), and bilateral revision surgery was performed in only 1 patient (3.7%). The mean BMI was 29.2 kg/m2. We used a constrained condylar knee in 20 patients (74%), a rotating hinge knee in 5 patients (18.5%), and mobile bearing tray plus metaphyseal sleeves in 2 patients (7.4%). The KSS was 52.21 ± 4.05 preoperatively, and 79.42 ± 2.2 and 80.12 ± 1.33 at 3 months and 12 months, respectively. Radiological union was achieved in all patients at 3 months. Of 27 patients, only 1 patient (3.7%) had proximal migration of the osteotomy site at 6 months: the patient was asymptomatic and union was also achieved and, therefore, no surgical intervention was performed. Conclusions: Tibial tubercle osteotomy during revision TKA can be a safe and reliable technique with superior outcomes and minimal complication rates.

      • LSTM based Supply Imbalance Detection and Identification in Loaded Three Phase Induction Motors

        Majid, Hussain,Fayaz Ahmed, Memon,Umair, Saeed,Babar, Rustum,Kelash, Kanwar,Abdul Rafay, Khatri International Journal of Computer ScienceNetwork S 2023 International journal of computer science and netw Vol.23 No.1

        Mostly in motor fault detection the instantaneous values 3 axis vibration and 3phase current in time domain are acquired and converted to frequency domain. Vibrations are more useful in diagnosing the mechanical faults and motor current has remained more useful in electrical fault diagnosis. With having some experience and knowledge on the behavior of acquired data the electrical and mechanical faults are diagnosed through signal processing techniques or combine machine learning and signal processing techniques. In this paper, a single-layer LSTM based condition monitoring system is proposed in which the instantaneous values of three phased motor current are firstly acquired in simulated motor in in health and supply imbalance conditions in each of three stator currents. The acquired three phase current in time domain is then used to train a LSTM network, which can identify the type of fault in electrical supply of motor and phase in which the fault has occurred. Experimental results shows that the proposed single layer LSTM algorithm can identify the electrical supply faults and phase of fault with an average accuracy of 88% based on the three phase stator current as raw data without any processing or feature extraction.

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