Predicting outcomes of rectus femoris transfer surgery

Rectus femoris transfer surgery is a common treatment for stiff knee gait in children with cerebral palsy. Unfortunately, the improvement in knee motion after surgery is inconsistent. There is great interest in understanding the causes of stiff knee gait and determining predictors of improved knee motion after surgery. This study demonstrates that it is possible to predict whether or not a patient's knee motion will improve following rectus femoris transfer surgery with greater than 80% accuracy. A predictive model was developed that requires only a few preoperative gait analysis measurements, already collected as a routine part of treatment planning. Our examination of 62 patients before and after rectus femoris transfer revealed that a combination of hip power, knee power, and knee flexion velocity at toe-off correctly predicted postoperative outcome for 80% of cases. With the addition of two more preoperative measurements, hip flexion and internal rotation, prediction accuracy increased to nearly 88%. Other combinations of preoperative gait analysis measurements also predicted outcomes with high accuracy. These results provide insight into factors related to positive outcomes and suggest that predictive models provide a valuable tool for determining indications for rectus femoris transfer.     

Accelerating regional atrophy rates in the progression from normal aging to Alzheimer’s disease

We investigated progression of atrophy in vivo, in Alzheimer’s disease (AD), and mild cognitive impairment (MCI). We included 64 patients with AD, 44 with MCI and 34 controls with serial MRI examinations (interval 1.8?±?0.7 years). A nonlinear registration algorithm (fluid) was used to calculate atrophy rates in six regions: frontal, medial temporal, temporal (extramedial), parietal, occipital lobes and insular cortex. In MCI, the highest atrophy rate was observed in the medial temporal lobe, comparable with AD. AD patients showed even higher atrophy rates in the extramedial temporal lobe. Additionally, atrophy rates in frontal, parietal and occipital lobes were increased. Cox proportional hazard models showed that all regional atrophy rates predicted conversion to AD. Hazard ratios varied between 2.6 (95% confidence interval (CI) = 1.1–6.2) for occipital atrophy and 15.8 (95% CI?=?3.5–71.8) for medial temporal lobe atrophy. In conclusion, atrophy spreads through the brain with development of AD. MCI is marked by temporal lobe atrophy. In AD, atrophy rate in the extramedial temporal lobe was even higher. Moreover, atrophy rates also accelerated in parietal, frontal, insular and occipital lobes. Finally, in nondemented elderly, medial temporal lobe atrophy was most predictive of progression to AD, demonstrating the involvement of this region in the development of AD.