Background and objective To take full advantage of decision support, machine learning, and patient-level prediction models, it is important that models are not only created, but also deployed in a clinical setting. The KETOS platform demonstrated in this work implements a tool for researchers allowing them to perform statistical analyses and deploy resulting models in a secure environment.
Background
The introduction of next-generation sequencing (NGS) into molecular cancer diagnostics has led to an increase in the data available for the identification and evaluation of driver mutations and for defining personalized cancer treatment regimens. The meaningful combination of omics data, ie, pathogenic gene variants and alterations with other patient data, to understand the full picture of malignancy has been challenging.
Objective
This study describes the implementation of a system capable of processing, analyzing, and subsequently combining NGS data with other clinical patient data for analysis within and across institutions.
Methods
On the basis of the already existing NGS analysis workflows for the identification of malignant gene variants at the Institute of Pathology of the University Hospital Erlangen, we defined basic requirements on an NGS processing and analysis pipeline and implemented a pipeline based on the GEMINI (GEnome MINIng) open source genetic variation database. For the purpose of validation, this pipeline was applied to data from the 1000 Genomes Project and subsequently to NGS data derived from 206 patients of a local hospital. We further integrated the pipeline into existing structures of data integration centers at the University Hospital Erlangen and combined NGS data with local nongenomic patient-derived data available in Fast Healthcare Interoperability Resources format.
Results
Using data from the 1000 Genomes Project and from the patient cohort as input, the implemented system produced the same results as already established methodologies. Further, it satisfied all our identified requirements and was successfully integrated into the existing infrastructure. Finally, we showed in an exemplary analysis how the data could be quickly loaded into and analyzed in KETOS, a web-based analysis platform for statistical analysis and clinical decision support.
Conclusions
This study demonstrates that the GEMINI open source database can be augmented to create an NGS analysis pipeline. The pipeline generates high-quality results consistent with the already established workflows for gene variant annotation and pathological evaluation. We further demonstrate how NGS-derived genomic and other clinical data can be combined for further statistical analysis, thereby providing for data integration using standardized vocabularies and methods. Finally, we demonstrate the feasibility of the pipeline integration into hospital workflows by providing an exemplary integration into the data integration center infrastructure, which is currently being established across Germany.
Background:Knee braces are prescribed by physicians to protect the knee from various loading conditions during sports or after surgery, even though the effect of bracing for various loading scenarios remains unclear.Purpose:To extensively investigate whether bracing protects the knee against impacts from the lateral, medial, anterior, or posterior directions at different heights as well as against tibial moments.Study Design:Controlled laboratory study.Methods:Eight limb specimens were exposed to (1) subcritical impacts from the medial, lateral, anterior, and posterior directions at 3 heights (center of the joint line and 100 mm inferior and superior) and (2) internal/external torques. Using a prophylactic brace, both scenarios were conducted under braced and unbraced conditions with moderate muscle loads and intact soft tissue. The change in anterior cruciate ligament (ACL) strain, joint acceleration in the tibial and femoral bones (for impacts only), and joint kinematics were recorded and analyzed.Results:Bracing reduced joint acceleration for medial and lateral center impacts. The ACL strain change was decreased for medial superior impacts and increased for anterior inferior impacts. Impacts from the posterior direction had substantially less effect on the ACL strain change and joint acceleration than anterior impacts. Bracing had no effect on the ACL strain change or kinematics under internal or external moments.Conclusion:Our results indicate that the effect of bracing during impacts depends on the direction and height of the impact and is partly positive, negative, or neutral and that soft tissue absorbs impact energy. An effect during internal or external torque was not detected.Clinical Relevance:Bracing in contact sports with many lateral or medial impacts might be beneficial, whereas athletes who play sports with rotational moments on the knee or anterior impacts may be safer without a brace.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.