Outcomes of Fusions From the Cervical Spine to the Pelvis.

Study designRetrospective cohort study.ObjectiveDetermine the indications, complications, and clinical outcomes in patients requiring fusions from the cervical spine to the pelvis. Several investigators have examined fusions from the thoracic spine to the sacrum, but no similar study has been performed for cervical-to-pelvis fusions.MethodsPatients from 2003 to 2014 with an upper instrumented vertebrae (UIV) in the cervical spine (any level) and a lower instrumented vertebrae (LIV) in the sacrum or pelvis were included in the study. Those with infectious or acute trauma-related deformities were excluded. Patient demographics, medical history, diagnosis, operative procedure, and health-related quality of life measures were analyzed. Student's t test, Kruskal-Wallis test, and χ2 test were used as appropriate; significance was set at P < .05 for all tests.ResultsFifty-five patients met inclusion criteria for the study. Average follow-up was 2.8 years. Proximal junctional kyphosis was the most common indication for cervical-to-pelvis fusions (36%). The most common UIV was C2 (29%) followed by C7 (24%). There was an average 31° correction in maximum kyphosis and a 3.3 cm improvement in sagittal vertical axis. In adults, the rate of complication was 71.4%, with a major complication rate of 39.3% and reoperation rate of 53.6%. There was significant improvement in the Scoliosis Research Society (SRS-22r) score (3.0 to 3.5; P < .01).ConclusionProximal junctional kyphosis is the most common indication for patients requiring fusion to the cervical spine. Adult patients incur a significant risk of major complications and reoperations. However, significant improvement in SRS-22r outcomes are noted in these patients

Comparison of Best Versus Worst Clinical Outcomes for Adult Cervical Deformity Surgery.

Study Design: Retrospective cohort study. Objective: Factors that predict outcomes for adult cervical spine deformity (ACSD) have not been well defined. To compare ACSD patients with best versus worst outcomes. Methods: This study was based on a prospective, multicenter observational ACSD cohort. Best versus worst outcomes were compared based on Neck Disability Index (NDI), Neck Pain Numeric Rating Scale (NP-NRS), and modified Japanese Orthopaedic Association (mJOA) scores. Results: Of 111 patients, 80 (72%) had minimum 1-year follow-up. For NDI, compared with best outcome patients (n = 28), worst outcome patients (n = 32) were more likely to have had a major complication ( Conclusions: Factors distinguishing best and worst ACSD surgery outcomes included patient, surgical, and radiographic factors. These findings suggest areas that may warrant greater awareness to optimize patient counseling and outcomes

The number of transmission channels through a single-molecule junction

We calculate transmission eigenvalue distributions for Pt-benzene-Pt and Pt-butadiene-Pt junctions using realistic state-of-the-art many-body techniques. An effective field theory of interacting $\pi$-electrons is used to include screening and van der Waals interactions with the metal electrodes. We find that the number of dominant transmission channels in a molecular junction is equal to the degeneracy of the molecular orbital closest to the metal Fermi level.Comment: 9 pages, 8 figure

Evaluation of rate law approximations in bottom-up kinetic models of metabolism.

BackgroundThe mechanistic description of enzyme kinetics in a dynamic model of metabolism requires specifying the numerical values of a large number of kinetic parameters. The parameterization challenge is often addressed through the use of simplifying approximations to form reaction rate laws with reduced numbers of parameters. Whether such simplified models can reproduce dynamic characteristics of the full system is an important question.ResultsIn this work, we compared the local transient response properties of dynamic models constructed using rate laws with varying levels of approximation. These approximate rate laws were: 1) a Michaelis-Menten rate law with measured enzyme parameters, 2) a Michaelis-Menten rate law with approximated parameters, using the convenience kinetics convention, 3) a thermodynamic rate law resulting from a metabolite saturation assumption, and 4) a pure chemical reaction mass action rate law that removes the role of the enzyme from the reaction kinetics. We utilized in vivo data for the human red blood cell to compare the effect of rate law choices against the backdrop of physiological flux and concentration differences. We found that the Michaelis-Menten rate law with measured enzyme parameters yields an excellent approximation of the full system dynamics, while other assumptions cause greater discrepancies in system dynamic behavior. However, iteratively replacing mechanistic rate laws with approximations resulted in a model that retains a high correlation with the true model behavior. Investigating this consistency, we determined that the order of magnitude differences among fluxes and concentrations in the network were greatly influential on the network dynamics. We further identified reaction features such as thermodynamic reversibility, high substrate concentration, and lack of allosteric regulation, which make certain reactions more suitable for rate law approximations.ConclusionsOverall, our work generally supports the use of approximate rate laws when building large scale kinetic models, due to the key role that physiologically meaningful flux and concentration ranges play in determining network dynamics. However, we also showed that detailed mechanistic models show a clear benefit in prediction accuracy when data is available. The work here should help to provide guidance to future kinetic modeling efforts on the choice of rate law and parameterization approaches

Semantic text mining support for lignocellulose research

Biofuels produced from biomass are considered to be promising sustainable alternatives to fossil fuels. The conversion of lignocellulose into fermentable sugars for biofuels production requires the use of enzyme cocktails that can efficiently and economically hydrolyze lignocellulosic biomass. As many fungi naturally break down lignocellulose, the identification and characterization of the enzymes involved is a key challenge in the research and development of biomass-derived products and fuels. One approach to meeting this challenge is to mine the rapidly-expanding repertoire of microbial genomes for enzymes with the appropriate catalytic properties. Semantic technologies, including natural language processing, ontologies, semantic Web services and Web-based collaboration tools, promise to support users in handling complex data, thereby facilitating knowledge-intensive tasks. An ongoing challenge is to select the appropriate technologies and combine them in a coherent system that brings measurable improvements to the users. We present our ongoing development of a semantic infrastructure in support of genomics-based lignocellulose research. Part of this effort is the automated curation of knowledge from information on fungal enzymes that is available in the literature and genome resources. Working closely with fungal biology researchers who manually curate the existing literature, we developed ontological natural language processing pipelines integrated in a Web-based interface to assist them in two main tasks: mining the literature for relevant knowledge, and at the same time providing rich and semantically linked information

Predictive modeling of complications

Predictive analytic algorithms are designed to identify patterns in the data that allow for accurate predictions without the need for a hypothesis. Therefore, predictive modeling can provide detailed and patient-specific information that can be readily applied when discussing the risks of surgery with a patient. There are few studies using predictive modeling techniques in the adult spine surgery literature. These types of studies represent the beginning of the use of predictive analytics in spine surgery outcomes. We will discuss the advancements in the field of spine surgery with respect to predictive analytics, the controversies surrounding the technique, and the future directions

Incidence of Chronic Periscapular Pain After Adult Thoracolumbar Deformity Correction and Impact on Outcomes.

ObjectiveExtension of the posterior upper-most instrumented vertebra (UIV) into the upper thoracic (UT) spine allows for greater deformity correction and reduced incidence of proximal junction kyphosis (PJK) in adult spinal deformity (ASD) patients. However, it may be associated with chronic postoperative scapular pain (POSP). The goal of this study was to assess the relationship between UT UIV and persistent POSP, describe the pain, and assess its impact on patient disability.MethodsASD patients who underwent multilevel posterior fusion were retrospectively identified then administered a survey regarding scapular pain and the Oswestry Disability Index (ODI), by telephone. Univariate and multivariate analysis were utilized.ResultsA total of 74 ASD patients were included in the study: 37 patients with chronic POSP and 37 without scapular pain. The mean age was 70.5 years, and 63.9% were women. There were no significant differences in clinical characteristics, including mechanical complications (PJK, pseudarthrosis, and rod fracture) or reoperation between groups. Patients with persistent POSP were more likely to have a UT than a lower thoracic UIV (p = 0.018). UT UIV was independently associated with chronic POSP on multivariate analysis (p = 0.022). ODI score was significantly higher in patients with scapular pain (p = 0.001). Chronic POSP (p = 0.001) and prior spine surgery (p = 0.037) were independently associated with ODI on multivariate analysis.ConclusionA UT UIV is independently associated with increased odds of chronic POSP, and this pain is associated with significant increases in patient disability. It is a significant clinical problem despite solid radiographic fusion and the absence of PJK

Incidence of Chronic Periscapular Pain After Adult Thoracolumbar Deformity Correction and Impact on Outcomes.

ObjectiveExtension of the posterior upper-most instrumented vertebra (UIV) into the upper thoracic (UT) spine allows for greater deformity correction and reduced incidence of proximal junction kyphosis (PJK) in adult spinal deformity (ASD) patients. However, it may be associated with chronic postoperative scapular pain (POSP). The goal of this study was to assess the relationship between UT UIV and persistent POSP, describe the pain, and assess its impact on patient disability.MethodsASD patients who underwent multilevel posterior fusion were retrospectively identified then administered a survey regarding scapular pain and the Oswestry Disability Index (ODI), by telephone. Univariate and multivariate analysis were utilized.ResultsA total of 74 ASD patients were included in the study: 37 patients with chronic POSP and 37 without scapular pain. The mean age was 70.5 years, and 63.9% were women. There were no significant differences in clinical characteristics, including mechanical complications (PJK, pseudarthrosis, and rod fracture) or reoperation between groups. Patients with persistent POSP were more likely to have a UT than a lower thoracic UIV (p = 0.018). UT UIV was independently associated with chronic POSP on multivariate analysis (p = 0.022). ODI score was significantly higher in patients with scapular pain (p = 0.001). Chronic POSP (p = 0.001) and prior spine surgery (p = 0.037) were independently associated with ODI on multivariate analysis.ConclusionA UT UIV is independently associated with increased odds of chronic POSP, and this pain is associated with significant increases in patient disability. It is a significant clinical problem despite solid radiographic fusion and the absence of PJK

State-of-the-art reviews predictive modeling in adult spinal deformity: applications of advanced analytics.

Adult spinal deformity (ASD) is a complex and heterogeneous disease that can severely impact patients' lives. While it is clear that surgical correction can achieve significant improvement of spinopelvic parameters and quality of life measures in adults with spinal deformity, there remains a high risk of complication associated with surgical approaches to adult deformity. Over the past decade, utilization of surgical correction for ASD has increased dramatically as deformity correction techniques have become more refined and widely adopted. Along with this increase in surgical utilization, there has been a massive undertaking by spine surgeons to develop more robust models to predict postoperative outcomes in an effort to mitigate the relatively high complication rates. A large part of this revolution within spine surgery has been the gradual adoption of predictive analytics harnessing artificial intelligence through the use of machine learning algorithms. The development of predictive models to accurately prognosticate patient outcomes following ASD surgery represents a dramatic improvement over prior statistical models which are better suited for finding associations between variables than for their predictive utility. Machine learning models, which offer the ability to make more accurate and reproducible predictions, provide surgeons with a wide array of practical applications from augmenting clinical decision making to more wide-spread public health implications. The inclusion of these advanced computational techniques in spine practices will be paramount for improving the care of patients, by empowering both patients and surgeons to more specifically tailor clinical decisions to address individual health profiles and needs