Purpose:Non-prosthetic peri-implant fractures are challenging injuries.Multiple factors must be care-fully evaluated for an adequate therapeutic strategy,such as the state of bone healing,the type of implant,the time ...Purpose:Non-prosthetic peri-implant fractures are challenging injuries.Multiple factors must be care-fully evaluated for an adequate therapeutic strategy,such as the state of bone healing,the type of implant,the time and performed personnel of previous surgery,and the stability of fixation.The aim of this study is to propose a rationale for the treatment.Methods:The peri-implant femoral fractures(PIFFs)system,a therapeutic algorithm was developed for the management of all patients presenting a subtype A PIFF,based on the type of the original implant(extra-vs.intra-medulllary),implant length and fracture location.The adequacy and reliability of the proposed algorithm and the fracture healing process were assessed at the last clinical follow-up using the Parker mobility score and radiological assessment,respectively.In addition,all complications were noticed.Continuous variables were expressed as mean and standard deviation,or median and range according to their distribution.Categorical variables were expressed as frequency and percentages.Results:This is a retrospective case series of 33 PIFFs,and the mean post-operative Parker mobility score was(5.60±2.54)points.Five patients(15.1%)achieved complete mobility without aids(9 points)and 1(3.0%)patient was not able to walk.Two other patients(6.1%)were non-ambulatory prior to PPIF.The mean follow-up was(21.51±9.12)months(range 6-48 months).There were 7(21.2%)complications equally distributed between patients managed either with nailing or plating.There were no cases of nonunion or mechanical failure of the original implant.Conclusion:The proposed treatment algorithm shows adequate,reliable and straightforward to assist the orthopaedic trauma surgeon on the difficult decision-making process regarding the management of PIFF occurring in previously healed fractures.In addition,it may become a useful tool to optimize the use of the classification,thus potentially improving the outcomes and minimizing complications.展开更多
文摘Purpose:Non-prosthetic peri-implant fractures are challenging injuries.Multiple factors must be care-fully evaluated for an adequate therapeutic strategy,such as the state of bone healing,the type of implant,the time and performed personnel of previous surgery,and the stability of fixation.The aim of this study is to propose a rationale for the treatment.Methods:The peri-implant femoral fractures(PIFFs)system,a therapeutic algorithm was developed for the management of all patients presenting a subtype A PIFF,based on the type of the original implant(extra-vs.intra-medulllary),implant length and fracture location.The adequacy and reliability of the proposed algorithm and the fracture healing process were assessed at the last clinical follow-up using the Parker mobility score and radiological assessment,respectively.In addition,all complications were noticed.Continuous variables were expressed as mean and standard deviation,or median and range according to their distribution.Categorical variables were expressed as frequency and percentages.Results:This is a retrospective case series of 33 PIFFs,and the mean post-operative Parker mobility score was(5.60±2.54)points.Five patients(15.1%)achieved complete mobility without aids(9 points)and 1(3.0%)patient was not able to walk.Two other patients(6.1%)were non-ambulatory prior to PPIF.The mean follow-up was(21.51±9.12)months(range 6-48 months).There were 7(21.2%)complications equally distributed between patients managed either with nailing or plating.There were no cases of nonunion or mechanical failure of the original implant.Conclusion:The proposed treatment algorithm shows adequate,reliable and straightforward to assist the orthopaedic trauma surgeon on the difficult decision-making process regarding the management of PIFF occurring in previously healed fractures.In addition,it may become a useful tool to optimize the use of the classification,thus potentially improving the outcomes and minimizing complications.
