External Validation of ASPECT (Algorithm for Suspected Pulmonary Embolism Confirmation and Treatment).

BACKGROUND: Administrative health care databases are increasingly being used to study pulmonary embolism (PE), but the validity of single PE codes is variable. Using data from Quebec, Canada, we developed ASPECT (Algorithm for Suspected Pulmonary Embolism Confirmation and Treatment), combining 3 components to ascertain confirmed PE: emergency department (ED) diagnoses, imaging codes, and dispensed prescriptions or hospital diagnoses. Herein, we used unrelated administrative health care databases to externally validate ASPECT. METHODS: We used ED electronic health records (ED-EHRs) to identify all residents of Calgary (Alberta, Canada) with PE codes between January and June, 2016. We applied ASPECT by identifying imaging studies in the ED-EHR, admission diagnoses in linked discharge abstract database and filled prescriptions in linked pharmacy information. Confirmed PE in ASPECT was validated against chart review in the ED-EHR. RESULTS: The cohort included 498 patients. Overall, 258 (51.9%) were managed as outpatients and 327 were adjudicated to have confirmed PE; the positive predictive value (PV) of single PE codes was 65.6%. With ASPECT the positive PV was 96.5% [95% confidence interval (CI), 94.4-98.5%] and positive likelihood ratio was 10.9 (95% CI, 6.8-15.1). The negative PV and negative likelihood ratio were 85.1% (95% CI, 80.0-90.2%) and 0.1 (95% CI, 0.0-0.1), respectively. Overall agreement of ASPECT with confirmed PE was 92.2%. Further, ASPECT was similarly robust in inpatients and outpatients and was more precise than any 2-component combination of ASPECT. CONCLUSIONS: Our findings reiterate the limitations of using single administrative codes for PE and suggest ASPECT as an acceptable tool to study PE.

NGS++: a library for rapid prototyping of epigenomics software tools.

MOTIVATION: The development of computational tools to enable testing and analysis of high-throughput-sequencing data is essential to modern genomics research. However, although multiple frameworks have been developed to facilitate access to these tools, comparatively little effort has been made at implementing low-level programming libraries to increase the speed and ease of their development. RESULTS: We propose NGS++, a programming library in C++11 specialized in manipulating both next-generation sequencing (NGS) datasets and genomic information files. This library allows easy integration of new formats and rapid prototyping of new functionalities with a focus on the analysis of genomic regions and features. It offers a powerful, yet versatile and easily extensible interface to read, write and manipulate multiple genomic file formats. By standardizing the internal data structures and presenting a common interface to the data parser, NGS++ offers an effective framework for epigenomics tool development. AVAILABILITY: NGS++ was written in C++ using the C++11 standard. It requires minimal efforts to build and is well-documented via a complete docXygen guide, online documentation and tutorials. Source code, tests, code examples and documentation are available via the website at http://www.ngsplusplus.ca and the github repository at https://github.com/NGS-lib/NGSplusplus. CONTACT: nicolas.gevry@usherbrooke.ca or arnaud.droit@crchuq.ulaval.ca.