Risk factors for cut-out of double lag screw fixation in proximal femoral fractures

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Abstract

Objective We assessed factors associated with cut-out after internal fixation of proximal femoral fractures using double lag screw nails. Design Retrospective cohort study. Setting A university hospital. Patients and methods Patients with non-pathological intertrochanteric femur fractures and a minumum 90 days follow-up who underwent internal fixation with dual lag screw nails were included. Potential risk factors for lag screw cut-out investigated by our study were: age, gender, body mass index, comorbidities (American Society of Anesthesiologists [ASA] classification), type of fracture (AO/OTA classification), fracture stability, side, operation time, implant length, reduction quality, tip-apex distance (TAD), and lag screw configuration. Logistic regression was used to investigate potential predictors of screw cut-out. Results Eighty-five of the 118 patients with hip fractures treated between February 2010 and November 2013 at our institution met the inclusion criteria for the study. Fifty-eight patients were female (68.2%), mean age was 77.4 (range: 50–95 years), mean follow up was 380 days (range: 150 days-2.5 years), and cut of was observed in 9 patients (10.5%). The following variables identified through univariate analysis with p < 0.2 were included in multivariant logistic regression model: age, side, reduction quality, implant length, TAD and ASA score. Only TAD (p = 0.003) was found to be significant in the multivariant model. Conclusions Our study confirmed that risk factors for cut-out with single-lag screw devices are also applicable to dual-lag screw implants. We found that TAD was a significant factor for cut-out in dual-lag screw implants. Thus, screw cut-out can be minimized by optimizing screw position.

Original languageEnglish
Pages (from-to)414-418
Number of pages5
JournalInjury
Volume48
Issue number2
DOIs
Publication statusPublished - 1 Feb 2017

Keywords

  • Cut-out
  • Intertrochanteric fractures
  • Logistic regression
  • Risk factors
  • Tip-apex distance

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