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1.
Eur J Orthop Surg Traumatol ; 34(2): 1065-1071, 2024 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-37930425

RESUMO

PURPOSE: This study aims to examine whether Pridie drilling, a form of bone marrow stimulation, can expedite the healing process and enable a faster return to sports activity in patients with knee Osteochondritis dissecans (OCD). The primary objective is to assess the effectiveness of Pridie drilling in stable OCD lesions that do not respond to non-operative treatment, by evaluating the absence of painful symptoms 6 months after the procedure. Secondary objectives include evaluating radiographic reconstruction 6 months post-surgery and determining the time it takes to resume sports participation. MATERIALS AND METHODS: This single-center retrospective study included all cases of stable OCD in the knee that underwent anterograde chondral drilling between 2008 and 2020. Diagnosis of OCD was established using knee radiographs, and the surgical technique involved multiple multidirectional subchondral drilling. Treatment efficacy was defined by the absence of painful symptoms for 6 months postoperatively. RESULTS: A total of 41 knees were included in the study, and no complications were observed before or after surgery. At 6 months postoperatively, 32 knees (78%) showed complete resolution of symptoms. Complete radiographic reconstruction was observed in 66% of cases. Asymptomatic patients at 6 months returned to sports activity of similar intensity to that practiced previously in an average time of 7.9 months; while, patients who were symptomatic at 6 months returned in an average time of 16.5 months. CONCLUSION: This study provides evidence supporting the short-term efficacy of anterograde chondral drilling in stable lesion of OCD in children and adolescents after failed functional treatment. LEVEL OF EVIDENCE: Level III (retrospective cohort study).


Assuntos
Osteocondrite Dissecante , Criança , Adolescente , Humanos , Adulto Jovem , Osteocondrite Dissecante/diagnóstico por imagem , Osteocondrite Dissecante/cirurgia , Estudos Retrospectivos , Seguimentos , Articulação do Joelho/diagnóstico por imagem , Articulação do Joelho/cirurgia , Articulação do Joelho/patologia , Joelho , Resultado do Tratamento , Dor
2.
Int Orthop ; 45(9): 2209-2217, 2021 09.
Artigo em Inglês | MEDLINE | ID: mdl-34351462

RESUMO

PURPOSE: Axial alignment of the talar implant in total ankle arthroplasty remains a major issue, since the real axis of motion of each patient is impossible to determine with usual techniques. Further knowledge regarding individual axis of motion of the ankle is therefore needed. MATERIAL AND METHODS: Therefore, digital twins, artificial intelligence, and machine learning technology were used to identify a real personalized motion axis of the tibiotalar joint. Three-dimensional (3D) models of distal extremities were generated using computed tomography data of normal patients. Digital twins were used to reproduce the mobility of the ankles, and the real ankle of the patients was matched to the digital twin with machine learning technology. RESULTS: The results showed that a personalized axis can be obtained for each patient. When the origin of the axis is the centre of mass of the talus, this axis can be represented in a geodesic system. The mean value of the axis is a line passing in first approximation through the centre of the sphere (with a variation of 3 mm from the centre of the mass of the talus) and through a point with the coordinates 91.6° west and 7.4° north (range 84° to 98° west; - 2° to 12° north). This study improves the understanding of the axis of the ankle, as well as its relationship to the possibility to use the geodesic system for robotic in ankle arthroplasty. CONCLUSION: The consideration of a personalized axis of the ankle might be helpful for better understanding of ankle surgery and particularly total ankle arthroplasty.


Assuntos
Artroplastia de Substituição do Tornozelo , Tálus , Tornozelo , Articulação do Tornozelo/diagnóstico por imagem , Articulação do Tornozelo/cirurgia , Inteligência Artificial , Humanos , Aprendizado de Máquina , Tecnologia
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