Update on early warning scores

The effect of early warning scoring systems on adverse outcome in surgical patients: A systematic review

Background

An early warning scoring system aims to detect clinical deterioration at an early stage and prevent failure-to-rescue in hospitalized patients. In this systematic review we studied the effect of an early warning scoring system on adverse outcome in surgical patients.

Methods

This review was conducted and reported according to PRISMA and the protocol of this review is registered at PROSPERO, under the registration number CRD42018107799. PubMed, Embase.com, CINAHL (Ebsco) and Wiley/Cochrane Library were searched from inception up to 20-06-2023 for randomized controlled trials and non-randomized studies of interventions. Studies were eligible for inclusion if the effect of an early warning scoring system using spot check monitoring was studied.

Results

Eight articles were included, of which two were randomised controlled trials. The overall risk of bias was high. A statistically significant decrease in mortality was seen in three studies. Two studies reported a decrease in cardiopulmonary arrests, and three studies found a decrease in ICU-admissions. There was heterogeneity among studies regarding the types of complications that were reported.

Conclusions

The evidence in favor of an early warning scoring system to reduce complications and mortality in surgical patients is low, mainly due to a limited number of studies and poor study design. Well-designed trials are needed to investigate whether an early warning scoring system improves outcome in surgical patients.

Contactless and continuous monitoring of respiratory rate in a hospital ward: a clinical validation study

Introduction

Continuous monitoring of respiratory rate in hospital wards can provide early detection of clinical deterioration, thereby reducing mortality, reducing transfers to intensive care units, and reducing the hospital length of stay. Despite the advantages of continuous monitoring, manually counting every 1-12 h remains the standard of care in most hospital wards. The objective of this study was to validate continuous respiratory rate measurements from a radar-based contactless patient monitor [Vitalthings Guardian M10 (Vitalthings AS, Norway)] in a hospital ward.

Methods

An observational study (clinicaltrials.gov: NCT06083272) was conducted at the emergency ward of a university hospital. Adult patients were monitored during rest with Vitalthings Guardian M10 in both a stationary and mobile configuration simultaneously with a reference device [Nox T3s (Nox Medical, Alpharetta, GA, United States)]. The agreement was assessed using Bland-Altman 95% limits of agreement. The sensitivity and specificity of clinical alarms were evaluated using a Clarke Error grid modified for continuous monitoring of respiratory rate. Clinical aspects were further evaluated in terms of trend analysis and examination of gaps between valid measurements.

Results

32 patients were monitored for a median duration of 42 min [IQR (range) 35-46 (30-59 min)]. The bias was 0.1 and 0.0 breaths min-1 and the 95% limits of agreement ranged from -1.1 to 1.2 and -1.1 to 1.1 breaths min-1 for the stationary and mobile configuration, respectively. The concordances for trends were 96%. No clinical alarms were missed, and no false alarms or technical alarms were generated. No interval without a valid measurement was longer than 5 min.

Conclusion

Vitalthings Guardian M10 measured respiratory rate accurately and continuously in resting patients in a hospital ward.

Exploring the potential impact of adding upper limit single trigger MET thresholds to a paediatric early warning scoring tool at a tertiary children's hospital: a retrospective review

Objective

This study aims to determine the impact of incorporating upper threshold vital sign triggers into the digital Children's Early Warning Tool (CEWT) on the number of medical emergency team (MET) alerts.

Methods

De-identified vital set data from the Cerner Millennium Integrated Electronic Medical Records were obtained for all paediatric patients aged ≤16 years at a tertiary children's hospital in Brisbane over a 12-month period in 2022. Patients in the paediatric intensive care unit, post-anaesthetic care unit, or the emergency department were excluded as they would not trigger MET alerts in these locations. Microsoft Excel scripts were used to tabulate and graph the data to compare the number of MET alerts in the current system vs. the system with proposed upper thresholds for heart rate, respiratory rate, systolic blood pressure, and severe respiratory distress.

Results

A total of 389,352 vital sets were used for analysis after exclusions. Total cumulative MET alerts increased by 229% from 1,707 to 5,623. The number of increased alerts was inversely proportional to the age group. Respiratory rate and systolic blood pressure were the vital signs most associated with increased alerts. The largest number of new alerts came from patients with lower CEWT scores, while the largest proportional increase in alerts came from those with higher CEWT scores.

Conclusions

Incorporating upper threshold vital sign triggers into the digital CEWT leads to a substantial increase in MET alerts. The consequent workload is not justified, given the lack of evidence suggesting a failure of the current CEWT system in recognising deteriorating patients.

Missing data imputation techniques for wireless continuous vital signs monitoring

Wireless vital signs sensors are increasingly used for remote patient monitoring, but data analysis is often challenged by missing data periods. This study explored the performance of various imputation techniques for continuous vital signs measurements. Wireless vital signs measurements (heart rate, respiratory rate, blood oxygen saturation, axillary temperature) from surgical ward patients were used for repeated random simulation of missing data periods (gaps) of 5-60 min in two-hour windows. Gaps were imputed using linear interpolation, spline interpolation, last observation- and mean carried forwards technique, and cluster-based prognosis. Imputation performance was evaluated using the mean absolute error (MAE) between original and imputed gap samples. Besides, effects on signal features (window's slope, mean) and early warning scores (EWS) were explored. Gaps were simulated in 1743 data windows, obtained from 52 patients. Although MAE ranges overlapped, median MAE was structurally lowest for linear interpolation (heart rate: 0.9-2.6 beats/min, respiratory rate: 0.8-1.8 breaths/min, temperature: 0.04-0.17 °C, oxygen saturation: 0.3-0.7% for 5-60 min gaps) but up to twice as high for other techniques. Three techniques resulted in larger ranges of signal feature bias compared to no imputation. Imputation led to EWS misclassification in 1-8% of all simulations. Imputation error ranges vary between imputation techniques and increase with gap length. Imputation may result in larger signal feature bias compared to performing no imputation, and can affect patient risk assessment as illustrated by the EWS. Accordingly, careful implementation and selection of imputation techniques is warranted.

Early Warning Scores to Support Continuous Wireless Vital Sign Monitoring for Complication Prediction in Patients on Surgical Wards: Retrospective Observational Study

BACKGROUND

Wireless vital sign sensors are increasingly being used to monitor patients on surgical wards. Although early warning scores (EWSs) are the current standard for the identification of patient deterioration in a ward setting, their usefulness for continuous monitoring is unknown.

OBJECTIVE

This study aimed to explore the usability and predictive value of high-rate EWSs obtained from continuous vital sign recordings for early identification of postoperative complications and compares the performance of a sensor-based EWS alarm system with manual intermittent EWS measurements and threshold alarms applied to individual vital sign recordings (single-parameter alarms).

METHODS

Continuous vital sign measurements (heart rate, respiratory rate, blood oxygen saturation, and axillary temperature) collected with wireless sensors in patients on surgical wards were used for retrospective simulation of EWSs (sensor EWSs) for different time windows (1-240 min), adopting criteria similar to EWSs based on manual vital signs measurements (nurse EWSs). Hourly sensor EWS measurements were compared between patients with (event group: 14/46, 30%) and without (control group: 32/46, 70%) postoperative complications. In addition, alarms were simulated for the sensor EWSs using a range of alarm thresholds (1-9) and compared with alarms based on nurse EWSs and single-parameter alarms. Alarm performance was evaluated using the sensitivity to predict complications within 24 hours, daily alarm rate, and false discovery rate (FDR).

RESULTS

The hourly sensor EWSs of the event group (median 3.4, IQR 3.1-4.1) was significantly higher (P<.004) compared with the control group (median 2.8, IQR 2.4-3.2). The alarm sensitivity of the hourly sensor EWSs was the highest (80%-67%) for thresholds of 3 to 5, which was associated with alarm rates of 2 (FDR=85%) to 1.2 (FDR=83%) alarms per patient per day respectively. The sensitivity of sensor EWS-based alarms was higher than that of nurse EWS-based alarms (maximum=40%) but lower than that of single-parameter alarms (87%) for all thresholds. In contrast, the (false) alarm rates of sensor EWS-based alarms were higher than that of nurse EWS-based alarms (maximum=0.6 alarm/patient/d; FDR=80%) but lower than that of single-parameter alarms (2 alarms/patient/d; FDR=84%) for most thresholds. Alarm rates for sensor EWSs increased for shorter time windows, reaching 70 alarms per patient per day when calculated every minute.

CONCLUSIONS

EWSs obtained using wireless vital sign sensors may contribute to the early recognition of postoperative complications in a ward setting, with higher alarm sensitivity compared with manual EWS measurements. Although hourly sensor EWSs provide fewer alarms compared with single-parameter alarms, high false alarm rates can be expected when calculated over shorter time spans. Further studies are recommended to optimize care escalation criteria for continuous monitoring of vital signs in a ward setting and to evaluate the effects on patient outcomes.