Building Data-Driven Pathways From Routinely Collected Hospital Data:A Case Study on Prostate Cancer

Background: Routinely collected data in hospitals is complex, typically heterogeneous, and scattered across multiple Hospital Information Systems (HIS). This big data, created as a byproduct of health care activities, has the potential to provide a better understanding of diseases, unearth hidden patterns, and improve services and cost. The extent and uses of such data rely on its quality, which is not consistently checked, nor fully understood. Nevertheless, using routine data for the construction of data-driven clinical pathways, describing processes and trends, is a key topic receiving increasing attention in the literature. Traditional algorithms do not cope well with unstructured processes or data, and do not produce clinically meaningful visualizations. Supporting systems that provide additional information, context, and quality assurance inspection are needed. Objective: The objective of the study is to explore how routine hospital data can be used to develop data-driven pathways that describe the journeys that patients take through care, and their potential uses in biomedical research; it proposes a framework for the construction, quality assessment, and visualization of patient pathways for clinical studies and decision support using a case study on prostate cancer. Methods: Data pertaining to prostate cancer patients were extracted from a large UK hospital from eight different HIS, validated, and complemented with information from the local cancer registry. Data-driven pathways were built for each of the 1904 patients and an expert knowledge base, containing rules on the prostate cancer biomarker, was used to assess the completeness and utility of the pathways for a specific clinical study. Software components were built to provide meaningful visualizations for the constructed pathways. Results: The proposed framework and pathway formalism enable the summarization, visualization, and querying of complex patient-centric clinical information, as well as the computation of quality indicators and dimensions. A novel graphical representation of the pathways allows the synthesis of such information. Conclusions: Clinical pathways built from routinely collected hospital data can unearth information about patients and diseases that may otherwise be unavailable or overlooked in hospitals. Data-driven clinical pathways allow for heterogeneous data (ie, semistructured and unstructured data) to be collated over a unified data model and for data quality dimensions to be assessed. This work has enabled further research on prostate cancer and its biomarkers, and on the development and application of methods to mine, compare, analyze, and visualize pathways constructed from routine data. This is an important development for the reuse of big data in hospitals

An \emph{ab initio} method for locating characteristic potential energy minima of liquids

It is possible in principle to probe the many--atom potential surface using density functional theory (DFT). This will allow us to apply DFT to the Hamiltonian formulation of atomic motion in monatomic liquids [\textit{Phys. Rev. E} {\bf 56}, 4179 (1997)]. For a monatomic system, analysis of the potential surface is facilitated by the random and symmetric classification of potential energy valleys. Since the random valleys are numerically dominant and uniform in their macroscopic potential properties, only a few quenches are necessary to establish these properties. Here we describe an efficient technique for doing this. Quenches are done from easily generated "stochastic" configurations, in which the nuclei are distributed uniformly within a constraint limiting the closeness of approach. For metallic Na with atomic pair potential interactions, it is shown that quenches from stochastic configurations and quenches from equilibrium liquid Molecular Dynamics (MD) configurations produce statistically identical distributions of the structural potential energy. Again for metallic Na, it is shown that DFT quenches from stochastic configurations provide the parameters which calibrate the Hamiltonian. A statistical mechanical analysis shows how the underlying potential properties can be extracted from the distributions found in quenches from stochastic configurations

Stellar wind interaction and pick-up ion escape of the Kepler-11 "super-Earths"

We study the interactions between stellar wind and the extended hydrogen-dominated upper atmospheres of planets and the resulting escape of planetary pick-up ions from the 5 "super-Earths" in the compact Kepler-11 system and compare the escape rates with the efficiency of the thermal escape of neutral hydrogen atoms. Assuming the stellar wind of Kepler-11 is similar to the solar wind, we use a polytropic 1D hydrodynamic wind model to estimate the wind properties at the planetary orbits. We apply a Direct Simulation Monte Carlo Model to model the hydrogen coronae and the stellar wind plasma interaction around Kepler-11b-f within a realistic expected heating efficiency range of 15-40%. The same model is used to estimate the ion pick-up escape from the XUV heated and hydrodynamically extended upper atmospheres of Kepler-11b-f. From the interaction model we study the influence of possible magnetic moments, calculate the charge exchange and photoionization production rates of planetary ions and estimate the loss rates of pick-up H+ ions for all five planets. We compare the results between the five "super-Earths" and in a more general sense also with the thermal escape rates of the neutral planetary hydrogen atoms. Our results show that for all Kepler-11b-f exoplanets, a huge neutral hydrogen corona is formed around the planet. The non-symmetric form of the corona changes from planet to planet and is defined mostly by radiation pressure and gravitational effects. Non-thermal escape rates of pick-up ionized hydrogen atoms for Kepler-11 "super-Earths" vary between approximately 6.4e30 1/s and 4.1e31 1/s depending on the planet's orbital location and assumed heating efficiency. These values correspond to non-thermal mass loss rates of approximately 1.07e7 g/s and 6.8e7 g/s respectively, which is a few percent of the thermal escape rates.Comment: 8 pages, 3 figures, accepted to A&

Clinical management of 52 consecutive retro-rectal tumours treated at a tertiary referral centre

Abstract Aim The aim of this single institution study was to analyse the diagnostic methods, pre-operative work-up and outcomes of 52 retrorectal tumours. Method All patients treated for retro-rectal tumours from 2012 to 2017 were included. Results Out of 52 patients, 40 (77%) were women. The patients? median age at the time of surgery was 43 (19-76) years, and 30 (58%) of the patients were asymptomatic at the time of diagnosis. All tumours were visible on magnetic resonance imaging (MRI) prior to surgery. The sensitivity and specificity for predicting malignancy on pre-operative imaging for retro-rectal tumours were 25% and 98%, respectively. Forty-four procedures (85%) were performed using the perineal approach. The median hospital stay was three (1-18) days. There was no 30-day post-operative mortality. Eleven (21%) patients developed post-operative complications, mostly surgical site infections. Twenty-nine tumours (56%) were benign tailgut cysts. Four (8%) tumours were malignant and were considered to be removed with a tumour-free resection margin. Local recurrent disease was detected on MRI in 14 (27%) patients at a median of 1.05 (range: 0.78-1.77) years after primary surgery. Only the multi-lobular shape of the tumour was found to be an independent risk factor for recurrence (p=0.030). Conclusion A pre-operative MRI is mandatory in order to plan the surgical strategy for retro-rectal tumours. Symptomatic, solid, large tumours should be removed because of the risk of malignancy. Minor cystic lesions with thin walls as well as asymptomatic recurrences of benign tumours are suitable to be followed conservatively.Peer reviewe

Liquid state properties from first principles DFT calculations: Static properties

In order to test the Vibration-Transit (V-T) theory of liquid dynamics, ab initio density functional theory (DFT) calculations of thermodynamic properties of Na and Cu are performed and compared with experimental data. The calculations are done for the crystal at T = 0 and T_m, and for the liquid at T_m. The key theoretical quantities for crystal and liquid are the structural potential and the dynamical matrix, both as function of volume. The theoretical equations are presented, as well as details of the DFT computations. The properties compared with experiment are the equilibrium volume, the isothermal bulk modulus, the internal energy and the entropy. The agreement of theory with experiment is uniformly good. Our primary conclusion is that the application of DFT to V-T theory is feasible, and the resulting liquid calculations achieve the same level of accuracy as does ab initio lattice dynamics for crystals. Moreover, given the well established reliability of DFT, the present results provide a significant confirmation of V-T theory itself.Comment: 9 pages, 3 figures, 5 tables, edited to more closely match published versio

An open and parallel multiresolution framework using block-based adaptive grids

A numerical approach for solving evolutionary partial differential equations in two and three space dimensions on block-based adaptive grids is presented. The numerical discretization is based on high-order, central finite-differences and explicit time integration. Grid refinement and coarsening are triggered by multiresolution analysis, i.e. thresholding of wavelet coefficients, which allow controlling the precision of the adaptive approximation of the solution with respect to uniform grid computations. The implementation of the scheme is fully parallel using MPI with a hybrid data structure. Load balancing relies on space filling curves techniques. Validation tests for 2D advection equations allow to assess the precision and performance of the developed code. Computations of the compressible Navier-Stokes equations for a temporally developing 2D mixing layer illustrate the properties of the code for nonlinear multi-scale problems. The code is open source

Comparison of Non-human Primate versus Human Induced Pluripotent Stem Cell-Derived Cardiomyocytes for Treatment of Myocardial Infarction.

Non-human primates (NHPs) can serve as a human-like model to study cell therapy using induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs). However, whether the efficacy of NHP and human iPSC-CMs is mechanistically similar remains unknown. To examine this, RNU rats received intramyocardial injection of 1 × 107 NHP or human iPSC-CMs or the same number of respective fibroblasts or PBS control (n = 9-14/group) at 4 days after 60-min coronary artery occlusion-reperfusion. Cardiac function and left ventricular remodeling were similarly improved in both iPSC-CM-treated groups. To mimic the ischemic environment in the infarcted heart, both cultured NHP and human iPSC-CMs underwent 24-hr hypoxia in vitro. Both cells and media were collected, and similarities in transcriptomic as well as metabolomic profiles were noted between both groups. In conclusion, both NHP and human iPSC-CMs confer similar cardioprotection in a rodent myocardial infarction model through relatively similar mechanisms via promotion of cell survival, angiogenesis, and inhibition of hypertrophy and fibrosis