BACKGROUND
With an aging population, elderly patients with multiple comorbidities are more frequently undergoing spine surgery and may be at increased risk for complications. Objective measurement of frailty may predict the incidence of postoperative adverse events.
OBJECTIVE
To investigate the associations between preoperative frailty and postoperative spine surgery outcomes including mortality, length of stay, readmission, surgical site infection, and venous thromboembolic disease.
METHODS
As part of a system-wide quality improvement initiative, frailty assessment was added to the routine assessment of patients considering spine surgery beginning in July 2016. Frailty was assessed with the Risk Analysis Index (RAI), and patients were categorized as nonfrail (RAI 0-29) or prefrail/frail (RAI ≥ 30). Comparisons between nonfrail and prefrail/frail patients were analyzed using Fisher's exact test for categorical data or by Wilcoxon rank sum tests for continuous data.
RESULTS
From August 2016 through September 2018, 668 patients (age of 59.5 ± 13.3 yr) had a preoperative RAI score recorded and underwent scheduled spine surgery. Prefrail and frail patients suffered comparatively higher rates of mortality at 90 d (1.9% vs 0.2%, P < .05) and 1 yr (5.1% vs 1.2%, P < .01) from the procedure date. They also had longer in-hospital length of stay (LOS) (3.9 d ± 3.6 vs 3.1 d ± 2.8, P < .001) and higher rates of 60 d (14.6% vs 8.2%, P < .05) and 90 d (15.8% vs 9.8%, P < .05) readmissions.
CONCLUSION
Preoperative frailty, as measured by the RAI, was associated with an increased risk of readmission and 90-d and 1-yr mortality following spine surgery. The RAI can be used to stratify spine patients and inform preoperative surgical decision making.
This paper considers the non-linear inverse problem of reconstructing an electric conductivity distribution from the interior power density in a bounded domain. Applications include the novel tomographic method known as acousto-electric tomography, in which the measurement setup in Electrical Impedance Tomography is modulated by ultrasonic waves thus giving rise to a method potentially having both high contrast and high resolution. We formulate the inverse problem as a regularized non-linear optimization problem, show the existence of a minimizer, and derive optimality conditions. We propose a non-linear conjugate gradient scheme for finding a minimizer based on the optimality conditions. All our numerical experiments are done in two-dimensions. The experiments reveal new insight into the non-linear effects in the reconstruction. One of the interesting features we observe is that, depending on the choice of regularization, there is a trade-off between high resolution and high contrast in the reconstructed images. Our proposed non-linear optimization framework can be generalized to other hybrid imaging modalities.
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