Curation of an intensive care research dataset from routinely collected patient data in an NHS trust.
ABSTRACT: In this data note we provide the details of a research database of 4831 adult intensive care patients who were treated in the Bristol Royal Infirmary, UK between 2015 and 2019. The purposes of this publication are to describe the dataset for external researchers who may be interested in making use of it, and to detail the methods used to curate the dataset in order to help other intensive care units make secondary use of their routinely collected data. The curation involves linkage between two critical care datasets within our hospital and the accompanying code is available online. For reasons of data privacy the data cannot be shared without researchers obtaining appropriate ethical consents. In the future we hope to obtain a data sharing agreement in order to publicly share the de-identified data, and to link our data with other intensive care units who use a Philips clinical information system.
Project description:The database here described contains data relevant to preterm infants' movement acquired in neonatal intensive care units (NICUs). The data consists of 16 depth videos recorded during the actual clinical practice. Each video consists of 1000 frames (i.e., 100s). The dataset was acquired at the NICU of the Salesi Hospital, Ancona (Italy). Each frame was annotated with the limb-joint location. Twelve joints were annotated, i.e., left and right shoul- der, elbow, wrist, hip, knee and ankle. The database is freely accessible at http://doi.org/10.5281/zenodo.3891404. This dataset represents a unique resource for artificial intelligence researchers that want to develop algorithms to provide healthcare professionals working in NICUs with decision support. Hence, the babyPose dataset is the first annotated dataset of depth images relevant to preterm infants' movement analysis.
Project description:We conducted a prospective observational study on 100 consecutive patients admitted to intensive care units at Leeds General Infirmary following out-of-hospital cardiac arrest. In the non-survivors, we reviewed their potential for organ donation via donation after circulatory death. Out of the 100 patients, 53 did not survive to hospital discharge. Out of these non-survivors, 13 died very suddenly within the intensive care unit and 3 other patients subsequently died in a general ward following discharge from the intensive care unit. One patient became brainstem dead, with out-of-hospital cardiac arrest secondary to a subarachnoid haemorrhage, rather than a primary cardiac cause. This patient went on to donate via the brain death mode. The remaining 36 patients had treatment withdrawn in the intensive care unit. Of these, 29 were referred to the transplant team for potential donation after circulatory death, and 14 were deemed to be medically suitable for organ donation. However, the families of only seven agreed to proceed with the donation process. Of these seven, only one went on to donate, primarily because the majority did not die within the 3-h window for acceptable warm ischaemia. In this series, the potential for donation after circulatory death following out-of-hospital cardiac arrest was limited. We would suggest an open dialogue between intensive care unit staff and transplant teams about the realistic potential for organ donation in each case. When clinicians believe it is unlikely that donation after circulatory death will proceed due to a failure to die within the pre-requisite time, then not starting with the donation after circulatory death process should be seriously considered.
Project description:We assayed leukocyte global gene expression for a prospective discovery cohort of 106 adult patients admitted to UK intensive care units with sepsis due to community acquired pneumonia or faecal peritonitis. We assigned all samples to sepsis response signature groups after performing unsupervised analysis of the transcriptomic data.
Project description:We assayed leukocyte global gene expression for a prospective discovery cohort of 265 adult patients admitted to UK intensive care units with severe sepsis due to community acquired pneumonia.
Project description:We assayed leukocyte global gene expression for a prospective validation cohort of 106 adult patients admitted to UK intensive care units with severe sepsis due to community acquired pneumonia.
Project description:OBJECTIVE:The primary objective is to develop an automated method for detecting patients that are ready for discharge from intensive care. DESIGN:We used two datasets of routinely collected patient data to test and improve on a set of previously proposed discharge criteria. SETTING:Bristol Royal Infirmary general intensive care unit (GICU). PATIENTS:Two cohorts derived from historical datasets: 1870 intensive care patients from GICU in Bristol, and 7592 from Medical Information Mart for Intensive Care (MIMIC)-III. RESULTS:In both cohorts few successfully discharged patients met all of the discharge criteria. Both a random forest and a logistic classifier, trained using multiple-source cross-validation, demonstrated improved performance over the original criteria and generalised well between the cohorts. The classifiers showed good agreement on which features were most predictive of readiness-for-discharge, and these were generally consistent with clinical experience. By weighting the discharge criteria according to feature importance from the logistic model we showed improved performance over the original criteria, while retaining good interpretability. CONCLUSIONS:Our findings indicate the feasibility of the proposed approach to ready-for-discharge classification, which could complement other risk models of specific adverse outcomes in a future decision support system. Avenues for improvement to produce a clinically useful tool are identified.
Project description:We assayed leukocyte global gene expression for a prospective validation cohort of 221 adult patients admitted to UK intensive care units with sepsis due to community acquired pneumonia or faecal peritonitis. 10 samples from patients scheduled for elective cardiac surgery were also assayed as non-septic controls. We assigned all samples to sepsis response signature groups after performing unsupervised analysis of the transcriptomic data.
2017-05-01 | E-MTAB-5273 | ArrayExpress
Project description:Sequential Pseudomonas aeruginosa isolates from patients hospitalized in intensive care units