Is age associated with different vital signs in adults presenting to hospital with bacterial infection? A systematic review and meta-analysis.

Background: It has long been suspected that the vital sign abnormalities that accompany bacterial infection are subtle or absent in older adults. This review summarises the evidence for whether older adults present with different vital sign abnormalities to younger adults when hospitalised with bacterial infection.

Methods: MEDLINE, EMBASE and CINAHL EBSCO were searched from inception to 19 December 2024 for English-language research articles of patients hospitalised with bacterial infection reporting age and admission vital signs.

Oxygen therapy in early warning scores: a systematic review and meta-analysis.

Background: Early warning systems (EWS) used across the world typically assign a fixed number of points to patients receiving supplemental oxygen, regardless of amount. This ordinal binary approach may fail to recognise deteriorating patients who have an increasing oxygen requirement with otherwise stable observations. It is unclear whether weighting oxygen beyond binary scoring improves recognition of deterioration.

Why vital signs observations are delayed and interrupted on acute hospital wards: A multisite observational study.

Background: Vital signs monitoring is key to identifying deteriorating hospital patients. However, adherence to monitoring protocols is limited, with observations frequently missed or delayed. Previous studies of interruptions and delays to vital signs observations have been descriptive, with none attempting to conceptualise the types of tasks that are prioritised over vital signs observations.

Perioperative risk scores: prediction, pitfalls, and progress.

Purpose Of Review: Perioperative risk scores aim to risk-stratify patients to guide their evaluation and management. Several scores are established in clinical practice, but often do not generalize well to new data and require ongoing updates to improve their reliability. Recent advances in machine learning have the potential to handle multidimensional data and associated interactions, however their clinical utility has yet to be consistently demonstrated.

COVID-19 pandemic impact on hypertension management in North East London: an observational cohort study using electronic health records.

Objective: There are established inequities in the monitoring and management of hypertension in England. The COVID-19 pandemic had a major impact on primary care management of long-term conditions such as hypertension. This study investigated the possible disproportionate impact of the pandemic across patient groups.

Development of a national maternity early warning score: centile based score development and Delphi informed escalation pathways.

Objective: To derive a new maternity early warning score (MEWS) from prospectively collected data on maternity vital signs and to design clinical response pathways with a Delphi consensus exercise.

Design: Centile based score development and Delphi informed escalation pathways.

Setting: Pregnancy Physiology Pattern Prediction (4P) prospective UK cohort study, 1 August 2012 to 28 December 2016.

Safer and more efficient vital signs monitoring protocols to identify the deteriorating patients in the general hospital ward: an observational study.

Background: The frequency at which patients should have their vital signs (e.g. blood pressure, pulse, oxygen saturation) measured on hospital wards is currently unknown.

Outlier detection of vital sign trajectories from COVID-19 patients.

In this work, we present a novel trajectory comparison algorithm to identify abnormal vital sign trends, with the aim of improving recognition of deteriorating health.There is growing interest in continuous wearable vital sign sensors for monitoring patients remotely at home. These monitors are usually coupled to an alerting system, which is triggered when vital sign measurements fall outside a predefined normal range.

Inequities in hypertension management: observational cross-sectional study in North East London using electronic health records.

Background: Hypertension is a key modifiable risk factor for cardiovascular disease - the leading cause of death in the UK. Good blood pressure (BP) control reduces mortality. However, health inequities may lead to variability in hypertension monitoring and control.

Multivariable prediction models for atrial fibrillation after cardiac surgery: a systematic review protocol.

Introduction: Dozens of multivariable prediction models for atrial fibrillation after cardiac surgery (AFACS) have been published, but none have been incorporated into regular clinical practice. One of the reasons for this lack of adoption is poor model performance due to methodological weaknesses in model development. In addition, there has been little external validation of these existing models to evaluate their reproducibility and transportability.

Protocol describing a systematic review and mixed methods consensus process to define the deteriorated ward patient.

Introduction: Most patients admitted to hospital recover with treatments that can be administered on the general ward. A small but important group deteriorate however and require augmented organ support in areas with increased nursing to patient ratios. In observational studies evaluating this cohort, proxy outcomes such as unplanned intensive care unit admission, cardiac arrest and death are used.

New-onset atrial fibrillation in intensive care: epidemiology and outcomes.

Aims: New-onset atrial fibrillation (NOAF) is common in patients treated on an intensive care unit (ICU), but the long-term impacts on patient outcomes are unclear. We compared national hospital and long-term outcomes of patients who developed NOAF in ICU with those who did not, before and after adjusting for comorbidities and ICU admission factors.

Methods And Results: Using the RISK-II database (Case Mix Programme national clinical audit of adult intensive care linked with Hospital Episode Statistics and mortality data), we conducted a retrospective cohort study of 4615 patients with NOAF and 27 690 matched controls admitted to 248 adult ICUs in England, from April 2009 to March 2016.

Artificial intelligence and clinical deterioration.

Purpose Of Review: To provide an overview of the systems being used to identify and predict clinical deterioration in hospitalised patients, with focus on the current and future role of artificial intelligence (AI).

Recent Findings: There are five leading AI driven systems in this field: the Advanced Alert Monitor (AAM), the electronic Cardiac Arrest Risk Triage (eCART) score, Hospital wide Alert Via Electronic Noticeboard, the Mayo Clinic Early Warning Score, and the Rothman Index (RI). Each uses Electronic Patient Record (EPR) data and machine learning to predict adverse events.

Evaluation of a digital system to predict unplanned admissions to the intensive care unit: A mixed-methods approach.

Background: We have developed the Hospital Alerting Via Electronic Noticeboard (HAVEN) which aims to identify hospitalised patients most at risk of reversible deterioration. HAVEN combines patients' vital-sign measurements with laboratory results, demographics and comorbidities using a machine learnt algorithm.

Objectives: The aim of this study was to identify variables or concepts that could improve HAVEN predictive performance.

Comparative effectiveness of common treatments for new-onset atrial fibrillation within the ICU: Accounting for physiological status.

Background: New-onset atrial fibrillation (NOAF) is common in patients on an intensive care unit (ICU). Evidence guiding treatments is limited, though recent reports suggest beta blocker (BB) therapy is associated with reduced mortality.

Methods: We conducted a multicentre cohort study of adult patients admitted to 3 ICUs in the UK and 5 ICUs in the USA.

Circadian variation in new-onset atrial fibrillation in patients in ICUs.

New-onset atrial fibrillation (NOAF) is common in patients treated on an intensive care unit (ICU). Onset of certain arrhythmias exhibit circadian variation. Whether NOAF follows a circadian rhythm in patients in ICU is unknown.

How long do nursing staff take to measure and record patients' vital signs observations in hospital? A time-and-motion study.

Introduction: Monitoring vital signs in hospital is an important part of safe patient care. However, there are no robust estimates of the workload it generates for nursing staff. This makes it difficult to plan adequate staffing to ensure current monitoring protocols can be delivered.

Detecting Deteriorating Patients in the Hospital: Development and Validation of a Novel Scoring System.

Late recognition of patient deterioration in hospital is associated with worse outcomes, including higher mortality. Despite the widespread introduction of early warning score (EWS) systems and electronic health records, deterioration still goes unrecognized. To develop and externally validate a Hospital- wide Alerting via Electronic Noticeboard (HAVEN) system to identify hospitalized patients at risk of reversible deterioration.

Trajectories of vital signs in patients with COVID-19.

Background: The global pandemic of coronavirus disease 2019 (COVID-19) has placed a huge strain on UK hospitals. Early studies suggest that patients can deteriorate quickly after admission to hospital. The aim of this study was to model changes in vital signs for patients hospitalised with COVID-19.

Night work for hospital nurses and sickness absence: a retrospective study using electronic rostering systems.

There is conflicting evidence on the effect of night work on sickness absence. Most previous studies used self-reporting to identify shift patterns and measure levels of sickness absence. In contrast, this study used objective data from electronic rosters to explore the association of nurses' patterns of night work and sickness absence.