Critical care unit bed availability and postoperative outcomes: a multinational cohort study.

Background: Critical care beds are a limited resource, yet research indicates that recommendations for postoperative critical care admission based on patient-level risk stratification are not followed. It is unclear how prioritisation decisions are made in real-world settings and the effect of this prioritisation on outcomes.

Methods: This was a prespecified analysis of an observational cohort study of adult patients undergoing inpatient surgery, conducted in 274 hospitals across the UK and Australasia during 2017.

Can Machine Learning Personalize Cardiovascular Therapy in Sepsis?

Large randomized trials in sepsis have generally failed to find effective novel treatments. This is increasingly attributed to patient heterogeneity, including heterogeneous cardiovascular changes in septic shock. We discuss the potential for machine learning systems to personalize cardiovascular resuscitation in sepsis.

How far back do we need to look to capture diagnoses in electronic health records? A retrospective observational study of hospital electronic health record data.

Objectives: Analysis of routinely collected electronic health data is a key tool for long-term condition research and practice for hospitalised patients. This requires accurate and complete ascertainment of a broad range of diagnoses, something not always recorded on an admission document at a single point in time. This study aimed to ascertain how far back in time electronic hospital records need to be interrogated to capture long-term condition diagnoses.

Age-specific Reference Intervals of Abbott Intact PTH-Potential Impacts on Clinical Care.

Background: PTH assays are not standardized; therefore, method-specific PTH reference intervals are required for interpretation of results. PTH increases with age in adults but age-related reference intervals for the Abbott intact PTH (iPTH) assay are not available.

Methods: Deidentified serum PTH results from September 2015 to November 2022 were retrieved from the laboratory information system of a laboratory serving a cosmopolitan population in central-west England for individuals aged 18 years and older if the estimated glomerular filtration rate was ≥60 mL/min, serum 25-hydroxyvitamin D was >50 nmol/L, and serum albumin-adjusted calcium and serum phosphate were within reference intervals.

Pathways to interoperable electronic patient records in health and social care, Part 2: introduction for commissioners, chief clinical information officers and senior medical and social care leaders involved in health IT commissioning and strategy.

Since the start of the 2020 Coronavirus 2019 (COVID-19) pandemic, new models of care have rapidly emerged in both health and social care in the UK. The sharing of structured and unstructured data across care organisations has become increasingly important, especially in transfer of care situations and other services, such as hospital at home. At the same time synchronous and asynchronous communication between professionals, patients and their carers, which integrates with patients' records, is optimising care pathways, improving access to care and enhancing self-management of care, particularly for people with long-term conditions.

Mixed methods study protocol for combining stakeholder-led rapid evaluation with near real-time continuous registry data to facilitate evaluations of quality of care in intensive care units.

Background: Improved access to healthcare in low- and middle-income countries (LMICs) has not equated to improved health outcomes. Absence or unsustained quality of care is partly to blame. Improving outcomes in intensive care units (ICUs) requires delivery of complex interventions by multiple specialties working in concert, and the simultaneous prevention of avoidable harms associated with the illness and the treatment interventions.

Integrated rapid-cycle comparative effectiveness trials using flexible point of care randomisation in electronic health record systems.

Whilst the Randomised Controlled Trial remains the gold standard for deriving robust causal estimates of treatment efficacy, too often a traditional design proves prohibitively expensive or cumbersome when it comes to assessing questions regarding the comparative effectiveness of routinely used treatments. As a result, patients experience variation in practice as clinicians lack the evidence needed to personalise treatments effectively. This variation may be classified as unwarranted, where existing evidence is ignored, or legitimate where in the absence of evidence, clinicians rely on experience, expert opinion, and inferred principles from basic science to make decisions.

Clinician preference instrumental variable analysis of the effectiveness of magnesium supplementation for atrial fibrillation prophylaxis in critical care.

Atrial fibrillation is a frequently encountered condition in critical illness and causes adverse effects including haemodynamic decompensation, stroke and prolonged hospital stay. It is a common practice in critical care to supplement serum magnesium for the purpose of preventing episodes of atrial fibrillation. However, no randomised studies support this practice in the non-cardiac surgery critical care population, and the effectiveness of magnesium supplementation is unclear.

Embedded point of care randomisation for evaluating comparative effectiveness questions: PROSPECTOR-critical care feasibility study protocol.

Introduction: Many routinely administered treatments lack evidence as to their effectiveness. When treatments lack evidence, patients receive varying care based on the preferences of clinicians. Standard randomised controlled trials are unsuited to comparisons of different routine treatment strategies, and there remains little economic incentive for change.

Clinical deployment environments: Five pillars of translational machine learning for health.

Machine Learning for Health (ML4H) has demonstrated efficacy in computer imaging and other self-contained digital workflows, but has failed to substantially impact routine clinical care. This is no longer because of poor adoption of Electronic Health Records Systems (EHRS), but because ML4H needs an infrastructure for development, deployment and evaluation within the healthcare institution. In this paper, we propose a design pattern called a Clinical Deployment Environment (CDE).

Machine learning for real-time aggregated prediction of hospital admission for emergency patients.

Machine learning for hospital operations is under-studied. We present a prediction pipeline that uses live electronic health-records for patients in a UK teaching hospital's emergency department (ED) to generate short-term, probabilistic forecasts of emergency admissions. A set of XGBoost classifiers applied to 109,465 ED visits yielded AUROCs from 0.

Establishing a colorectal cancer research database from routinely collected health data: the process and potential from a pilot study.

Objective: Colorectal cancer is a common cause of death and morbidity. A significant amount of data are routinely collected during patient treatment, but they are not generally available for research. The National Institute for Health Research Health Informatics Collaborative in the UK is developing infrastructure to enable routinely collected data to be used for collaborative, cross-centre research.

A Mass Spectrometric Approach to the Proteomic Profiling of the Acquired Enamel Pellicle on Hydroxyapatite Discs.

The acquired enamel pellicle (AEP) is a multi-protein film attached to the surface of teeth, which functions to lubricate the dental surface, form an anti-erosive barrier and exhibits antimicrobial properties. The initiation of AEP formation occurs within seconds of exposure to saliva, a biofluid rich in protein species. While there have been many publications on the formation of human AEP there is little research on the composition of canine AEP during its acquisition.

Combining faecal immunochemical testing with blood test results for colorectal cancer risk stratification: a consecutive cohort of 16,604 patients presenting to primary care.

Background: Faecal immunochemical tests (FITs) are used to triage primary care patients with symptoms that could be caused by colorectal cancer for referral to colonoscopy. The aim of this study was to determine whether combining FIT with routine blood test results could improve the performance of FIT in the primary care setting.

Methods: Results of all consecutive FITs requested by primary care providers between March 2017 and December 2020 were retrieved from the Oxford University Hospitals NHS Foundation Trust.

Nudging within learning health systems: next generation decision support to improve cardiovascular care.

The increasing volume and richness of healthcare data collected during routine clinical practice have not yet translated into significant numbers of actionable insights that have systematically improved patient outcomes. An evidence-practice gap continues to exist in healthcare. We contest that this gap can be reduced by assessing the use of nudge theory as part of clinical decision support systems (CDSS).

An informatics consult approach for generating clinical evidence for treatment decisions.

Background: An Informatics Consult has been proposed in which clinicians request novel evidence from large scale health data resources, tailored to the treatment of a specific patient. However, the availability of such consultations is lacking. We seek to provide an Informatics Consult for a situation where a treatment indication and contraindication coexist in the same patient, i.

Longitudinal Analysis of the Utility of Liver Biochemistry as Prognostic Markers in Hospitalized Patients With Corona Virus Disease 2019.

The association of liver biochemistry with clinical outcomes of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is currently unclear, and the utility of longitudinally measured liver biochemistry as prognostic markers for mortality is unknown. We aimed to determine whether abnormal liver biochemistry, assessed at baseline and at repeat measures over time, was associated with death in hospitalized patients with COVID-19 compared to those without COVID-19, in a United Kingdom population. We extracted routinely collected clinical data from a large teaching hospital in the United Kingdom, matching 585 hospitalized patients who were SARS-CoV-2 real-time reverse transcription-polymerase chain reaction (RT-PCR) positive to 1,165 hospitalized patients who were RT-PCR negative for age, sex, ethnicity, and preexisting comorbidities.

The future of acute and emergency care.

Improved outcomes for acutely unwell patients are predicated on early identification of deterioration, accelerating the time to accurate diagnosis of the underlying condition, selection and titration of treatments that target biological phenotypes, and personalised endpoints to achieve optimal benefit yet minimise iatrogenic harm. Technological developments entering routine clinical practice over the next decade will deliver a sea change in patient management. Enhanced point of care diagnostics, more sophisticated physiological and biochemical monitoring with superior analytics and computer-aided support tools will all add considerable artificial intelligence to complement clinical skills.

Descriptors of Sepsis Using the Sepsis-3 Criteria: A Cohort Study in Critical Care Units Within the U.K. National Institute for Health Research Critical Care Health Informatics Collaborative.

Objectives: To describe the epidemiology of sepsis in critical care by applying the Sepsis-3 criteria to electronic health records.

Design: Retrospective cohort study using electronic health records.

Setting: Ten ICUs from four U.