A critical assessment of early warning score records in 168,000 patients

Reliability of an all-in-one wearable sensor for continuous vital signs monitoring in high-risk patients: the NIGHTINGALE clinical validation study

Continuous vital signs monitoring with wearable systems may improve early recognition of patient deterioration on hospital wards. The objective of this study was to determine whether the wearable Checkpoint Cardio's CPC12S, can accurately measure heart rate (HR), respiratory rate (RR), oxygen saturation (SpO2), blood pressure (BP) and temperature continuously. In an observational multicenter method comparison study of 70 high-risk surgical patients admitted to high-dependency wards; HR, RR, SpO2, BP and temperature were simultaneously measured with the CPC12S system and with ICU-grade monitoring systems in four European hospitals. Outcome measures were bias and 95% limits of agreement (LoA). Clinical accuracy was assessed with Clarke Error Grid analyses for HR and RR. A total of 3,212 h of vital signs data (on average 26 h per patient) were analyzed. For HR, bias (95% LoA) of the pooled analysis was 0.0 (-3.5 to 3.4), for RR 1.5 (-3.7 to 7.5) and for SpO2 0.4 (-3.1 to 4.0). The CPC12S system overestimated BP, with a bias of 8.9 and wide LoA (-23.3 to 41.2). Temperature was underestimated with a bias of -0.6 and LoA of -1.7 to 0.6. Clarke Error Grid analyses showed that adequate treatment decisions regarding changes in HR and RR would have been made in 99.2% and 92.0% of cases respectively. The CPC12S system showed high accuracy for measurements of HR. The accuracy of RR, SpO2 were slightly overestimated and core temperature underestimated, with LoA outside the predefined clinical acceptable range. The accuracy of BP was unacceptably low.

The optimal duration of continuous respiratory rate monitoring to predict in-hospital mortality within seven days of admission - A pilot study in a low resource setting

Background

Currently there are no established benefits from the continuous monitoring of vital signs, and the optimal time period for respiratory rate measurement is unknown.

Setting

Low resource Ugandan hospital.

Methods

Prospective observational study. Respiratory rates of acutely ill patients were continuously measured by a piezoelectric device for up to seven hours after admission to hospital.

Results

22 (5.5%) out of 402 patients died within 7 days of hospital admission. The highest c-statistic of discrimination for 7-day mortality (0.737 SE 0.078) was obtained after four hours of continuously measured respiratory rates transformed into a weighted respiratory rate score (wRRS). After seven hours of measurement the c-statistic of the wRRS fell to 0.535 SE 0.078. 20% the patients who died within seven days did not have an elevated National Early Warning Score (NEWS) on admission but were identified by the 4-hour wRRS. None of the 88 patients whose average respiratory rate remained between 12 and 20 bpm throughout four hours of observation died within 7 days of admission. A simple predictive model that included the four-hour wRRS, Shock Index and altered mental status had a c-statistic for 7-day in-hospital mortality of 0.843 SE. 0.057.

Conclusion

Four hours of continuously measured respiratory rates was the observation period that best predicted 7-day in-hospital mortality. After four hours the discrimination of a weighted respiratory rate score deteriorated rapidly.

Prognostic value of heart rate variability for risk of serious adverse events in continuously monitored hospital patients

Technological advances allow continuous vital sign monitoring at the general ward, but traditional vital signs alone may not predict serious adverse events (SAE). This study investigated continuous heart rate variability (HRV) monitoring's predictive value for SAEs in acute medical and major surgical patients. Data was collected from four prospective observational studies and two randomized controlled trials using a single-lead ECG. The primary outcome was any SAE, secondary outcomes included all-cause mortality and specific non-fatal SAE groups, all within 30 days. Subgroup analyses of medical and surgical patients were performed. The primary analysis compared the last 24 h preceding an SAE with the last 24 h of measurements in patients without an SAE. The area under a receiver operating characteristics curve (AUROC) quantified predictive performance, interpretated as low prognostic ability (0.5-0.7), moderate prognostic ability (0.7-0.9), or high prognostic ability (> 0.9). Of 1402 assessed patients, 923 were analysed, with 297 (32%) experiencing at least one SAE. The best performing threshold had an AUROC of 0.67 (95% confidence interval (CI) 0.63-0.71) for predicting cardiovascular SAEs. In the surgical subgroup, the best performing threshold had an AUROC of 0.70 (95% CI 0.60-0.81) for neurologic SAE prediction. In the medical subgroup, thresholds for all-cause mortality, cardiovascular, infectious, and neurologic SAEs had moderate prognostic ability, and the best performing threshold had an AUROC of 0.85 (95% CI 0.76-0.95) for predicting neurologic SAEs. Predicting SAEs based on the accumulated time below thresholds for individual continuously measured HRV parameters demonstrated overall low prognostic ability in high-risk hospitalized patients. Certain HRV thresholds had moderate prognostic ability for prediction of specific SAEs in the medical subgroup.

Discrepancies between Promised and Actual AI Capabilities in the Continuous Vital Sign Monitoring of In-Hospital Patients: A Review of the Current Evidence

Continuous vital sign monitoring (CVSM) with wireless sensors in general hospital wards can enhance patient care. An artificial intelligence (AI) layer is crucial to allow sensor data to be managed by clinical staff without over alerting from the sensors. With the aim of summarizing peer-reviewed evidence for AI support in CVSM sensors, we searched PubMed and Embase for studies on adult patients monitored with CVSM sensors in general wards. Peer-reviewed evidence and white papers on the official websites of CVSM solutions were also included. AI classification was based on standard definitions of simple AI, as systems with no memory or learning capabilities, and advanced AI, as systems with the ability to learn from past data to make decisions. Only studies evaluating CVSM algorithms for improving or predicting clinical outcomes (e.g., adverse events, intensive care unit admission, mortality) or optimizing alarm thresholds were included. We assessed the promised level of AI for each CVSM solution based on statements from the official product websites. In total, 467 studies were assessed; 113 were retrieved for full-text review, and 26 studies on four different CVSM solutions were included. Advanced AI levels were indicated on the websites of all four CVSM solutions. Five studies assessed algorithms with potential for applications as advanced AI algorithms in two of the CVSM solutions (50%), while 21 studies assessed algorithms with potential as simple AI in all four CVSM solutions (100%). Evidence on algorithms for advanced AI in CVSM is limited, revealing a discrepancy between promised AI levels and current algorithm capabilities.

Variation in nurses' compliance with an Early Warning Score protocol: A retrospective cohort study

Introduction

Early Warning Score (EWS) protocols are based on intermittent vital sign measurements, and aim to detect clinical deterioration in a timely manner. Despite its predictive value, its effectiveness remains suboptimal. An important limitation appears to be poor compliance with the EWS protocol and its variation between general wards. The current research does not yet provide an understanding of EWS compliance and variation in different nursing wards.

Aim

To explore the variation in nurses' compliance with the EWS protocol among patients with and without complications and between different nursing wards.

Methods

In a retrospective single-center cohort study, all patient files from three nursing wards of a tertiary teaching hospital in the Netherlands were reviewed over a 1-month period. Compliance was divided into three categories:1) calculation accuracy, 2) monitoring frequency end 3) clinical response.

Results

The cohort of 210 patients contained 5864 measurements, of which 4125 (70.6 %) included EWS. Significant differences in the measured vital signs within incomplete measurements were found among nursing wards. Compliance to monitoring frequency was higher within EWSs of 0-1 (78.4 %) than within EWSs of ≥2 (26.1 %). The proportion of correct follow-up was significantly higher in patients with complications, as was the correct clinical response to an EWS of ≥3 (84.8 % vs. 55.0; p = .011).

Conclusion

Our results suggest suboptimal compliance with the EWS protocol, with large variations between patients with and without complications and between different general care wards. Nurses tended to be more compliant with the EWS protocol for patients with complications.

Health care workers' experiences of calling-for-help when taking care of critically ill patients in hospitals in Tanzania and Kenya

BACKGROUND

When caring for critically ill patients, health workers often need to 'call-for-help' to get assistance from colleagues in the hospital. Systems are required to facilitate calling-for-help and enable the timely provision of care for critically ill patients. Evidence around calling-for-help systems is mostly from high income countries and the state of calling-for-help in hospitals in Tanzania and Kenya has not been formally studied. This study aims to describe health workers' experiences about calling-for-help when taking care of critically ill patients in hospitals in Tanzania and Kenya.

METHODS

Ten hospitals across Kenya and Tanzania were visited and in-depth interviews conducted with 30 health workers who had experience of caring for critically ill patients. The interviews were transcribed, translated and the data thematically analyzed.

RESULTS

The study identified three thematic areas concerning the systems for calling-for-help when taking care of critically ill patients: 1) Calling-for-help structures: there is lack of functioning structures for calling-for-help; 2) Calling-for-help processes: the calling-for-help processes are innovative and improvised; and 3) Calling-for-help outcomes: the help that is provided is not as requested.

CONCLUSION

Calling-for-help when taking care of a critically ill patient is a necessary life-saving part of care, but health workers in Tanzanian and Kenyan hospitals experience a range of significant challenges. Hospitals lack functioning structures, processes for calling-for-help are improvised and help that is provided is not as requested. These challenges likely cause delays and decrease the quality of care, potentially resulting in unnecessary mortality and morbidity.

Improving patient outcomes following vital sign monitoring protocol failure: A retrospective cohort study

Background and Aims

Vital sign monitoring needs to be timely and correct to recognize deteriorating patients early and trigger the relevant clinical response. The aim of this study is to retrospectively evaluate compliance specifically toward the regional vital sign monitoring protocol the so called early warning score protocol (EWS-protocol) 72 h before a medical emergency team response (MET-response) and thereby illuminate whether poor compliance translates into a worse patient outcome.

Methods

It was investigated all eligible patients that underwent MET responses during the calendar year 2019. The inclusion criteria encompassed somatic patients above 18 years of age admitted to the hospital and detailed evaluations of the medical records of the included patients were conducted.

Results

Four hundred and twenty-nine MET-responses were included in the final analysis. EWS-protocol failure was observed for more than half the patients within all the time frames assessed. Thirty-day mortality was significantly higher for patients subject to EWS protocol failure in the timeframes 24-16, 16-8, 8-0 h before MET response. Adjusting for admission length, age, and gender, patients subject to EWS-protocol failure had an odds ratio (OR) of 1.9, 2.0, 2.1, 2.3 for mortality in the time frames 72-48, 24-16, 16-8, and 8-0 h before the MET-response, respectively. The adjusted OR for ICU-admission was 1.7, and 1.6 for patients subject to EWS-protocol failure in the time frames 16-8 and 8-0 h before MET-response, respectively.

Conclusion

According to all the data analysis in this article, there is evidence that compliance toward the NEWS-protocol is poor. EWS-protocol failure is associated with a significant higher mortality and ICU-admission rate.

Indicators of patient deterioration in poorly resourced private hospitals: Which vital sign to watch? A retrospective case-control study

BACKGROUND

Patient vital signs are a measure of wellness if monitored regularly and accurately. Staff shortages in poorly resourced regional hospitals often result in inadequate patient monitoring, putting patients at risk of undetected deterioration.

OBJECTIVE

This study aims to explore the pattern and completeness of vital sign monitoring and the contribution of each vital sign in predicting clinical deterioration events in resource-poor regional/rural hospitals.

METHOD

Using a retrospective case-control study design, we compared 24 h of vital sign data from deteriorating and nondeteriorating patients from two poorly-resourced regional hospitals. Descriptive statistics, t-tests, and analysis of variance are used to compare patient-monitoring frequency and completeness. The contribution of each vital sign in predicting patient deterioration was determined using the Area Under the Receiver Operator Characteristic curve and binary logistical regression analysis.

RESULTS

Deteriorating patients were monitored more frequently (9.58 [7.02] times) in the 24-h period than nondeteriorating patients (4.93 [2.66] times). However, the completeness of vital sign documentation was higher in nondeteriorating (85.2%) than in deteriorating patients (57.7%). Body temperature was the most frequently omitted vital sign. Patient deterioration was positively linked to the frequency of abnormal vital signs and the number of abnormal vital signs per set (Area Under the Receiver Operator Characteristic curve: 0.872 and 0.867, respectively). No single vital sign strongly predicts patient outcomes. However, a supplementary oxygen value of >3 L/min and a heart rate of >139 beats/min were the best predictors of patient deterioration.

CONCLUSION

Given the poor resourcing and often geographical remoteness of small regional hospitals, it is prudent that the nursing staff are made aware of the vital signs that best indicate deterioration for the cohort of patients in their care. Tachycardic patients on supplementary oxygen are at high risk of deterioration.

Workload associated with manual assessment of vital signs as compared with continuous wireless monitoring

BACKGROUND

Vital sign monitoring is considered an essential aspect of clinical care in hospitals. In general wards, this relies on intermittent manual assessments performed by clinical staff at intervals of up to 12 h. In recent years, continuous monitoring of vital signs has been introduced to the clinic, with improved patient outcomes being one of several potential benefits. The aim of this study was to determine the workload difference between continuous monitoring and manual monitoring of vital signs as part of the National Early Warning Score (NEWS).

METHODS

Three wireless sensors continuously monitored blood pressure, heart rate, respiratory rate, and peripheral oxygen saturation in 20 patients admitted to the general hospital ward. The duration needed for equipment set-up and maintenance for continuous monitoring in a 24-h period was recorded and compared with the time spent on manual assessments and documentation of vital signs performed by clinical staff according to the NEWS.

RESULTS

The time used for continuous monitoring was 6.0 (IQR 3.2; 7.2) min per patient per day vs. 14 (9.7; 32) min per patient per day for the NEWS. Median difference in duration for monitoring of vital signs was 9.9 (95% CI 5.6; 21) min per patient per day between NEWS and continuous monitoring (p < .001). Time used for continuous monitoring in isolated patients was 6.6 (4.6; 12) min per patient per day as compared with 22 (9.7; 94) min per patient per day for NEWS.

CONCLUSION

The use of continuous monitoring was associated with a significant reduction in workload in terms of time for monitoring as compared with manual assessment of vital signs.

Quantifying physiological stability in the general ward using continuous vital signs monitoring: the circadian kernel density estimator

Technological advances seen in recent years have introduced the possibility of changing the way hospitalized patients are monitored by abolishing the traditional track-and-trigger systems and implementing continuous monitoring using wearable biosensors. However, this new monitoring paradigm raise demand for novel ways of analyzing the data streams in real time. The aim of this study was to design a stability index using kernel density estimation (KDE) fitted to observations of physiological stability incorporating the patients' circadian rhythm. Continuous vital sign data was obtained from two observational studies with 491 postoperative patients and 200 patients with acute exacerbation of chronic obstructive pulmonary disease. We defined physiological stability as the last 24 h prior to discharge. We evaluated the model against periods of eight hours prior to events defined either as severe adverse events (SAE) or as a total score in the early warning score (EWS) protocol of ≥ 6,  ≥ 8, or ≥ 10. The results found good discriminative properties between stable physiology and EWS-events (area under the receiver operating characteristics curve (AUROC): 0.772-0.993), but lower for the SAEs (AUROC: 0.594-0.611). The time of early warning for the EWS events were 2.8-5.5 h and 2.5 h for the SAEs. The results showed that for severe deviations in the vital signs, the circadian KDE model can alert multiple hours prior to deviations being noticed by the staff. Furthermore, the model shows good generalizability to another cohort and could be a simple way of continuously assessing patient deterioration in the general ward.

The effect of technical filtering and clinical criteria on alert rates from continuous vital sign monitoring in the general ward

OBJECTIVES

Continuous vital sign monitoring at the general hospital ward has major potential advantages over intermittent monitoring but generates many alerts with risk of alert fatigue. We hypothesized that the number of alerts would decrease using different filters.

METHODS

This study was an exploratory analysis of the alert reducing effect from adding two different filters to continuously collected vital sign data (peripheral oxygen saturation, blood pressure, heart rate, and respiratory rate) in patients admitted after major surgery or severe medical disease. Filtered data were compared to data without artifact removal. Filter one consists of artifact removal, filter two consists of artifact removal plus duration criteria adjusted for severity of vital sign deviation. Alert thresholds were based on the National Early Warning Score (NEWS) threshold.

RESULTS

A population of 716 patients admitted for severe medical disease or major surgery with continuous wireless vital sign monitoring at the general ward with a mean monitoring time of 75.8 h, were included for the analysis. Without artifact removal, we found a median of 137 [IQR: 87-188] alerts per patient/day, artifact removal resulted in a median of 101 [IQR: 56-160] alerts per patient/day and with artifact removal combined with a duration-severity criterion, we found a median of 19 [IQR: 9-34] alerts per patient/day. Reduction of alerts was 86.4% (p < 0.001) for values without artifact removal (137 alerts) vs. the duration criteria and a reduction (19 alerts) of 81.5% (p < 0.001) for the criteria with artifact removal (101 alerts) vs. the duration criteria (19 alerts).

CONCLUSION

We conclude that a combination of artifact removal and duration-severity criteria approach substantially reduces alerts generated by continuous vital sign monitoring.

Associations between clinical interventions and transcutaneous blood gas values in postoperative patients

PURPOSE

Postoperative monitoring of circulation and respiration is pivotal to guide intervention strategies and ensure patient outcomes. Transcutaneous blood gas monitoring (TCM) may allow for noninvasive assessment of changes in cardiopulmonary function after surgery, including a more direct assessment of local micro-perfusion and metabolism. To form the basis for studies assessing the clinical impact of TCM complication detection and goal-directed-therapy, we examined the association between clinical interventions in the postoperative period and changes in transcutaneous blood gasses.

METHODS

Two-hundred adult patients who have had major surgery were enrolled prospectively and monitored with transcutaneous blood gas measurements (oxygen (TcPO2) and carbon dioxide (TcPCO2)) for 2 h in the post anaesthesia care unit, with recording of all clinical interventions. The primary outcome was changes in TcPO2, secondarily TcPCO2, from 5 min before a clinical intervention versus 5 min after, analysed with paired t-test.

RESULTS

Data from 190 patients with 686 interventions were analysed. During clinical interventions, a mean change in TcPO2 of 0.99 mmHg (95% CI-1.79-0.2, p = 0.015) and TcPCO2 of-0.67 mmHg (95% CI 0.36-0.98, p < 0.001) was detected.

CONCLUSION

Clinical interventions resulted in significant changes in transcutaneous oxygen and carbon dioxide. These findings suggest future studies to assess the clinical value of changes in transcutaneous PO2 and PCO2 in a postoperative setting.

TRIAL REGISTRY

Clinical trial number: NCT04735380.

CLINICAL TRIAL REGISTRY

https://clinicaltrials.gov/ct2/show/NCT04735380.

Development of a dynamic prediction model for unplanned ICU admission and mortality in hospitalized patients

Frequent assessment of the severity of illness for hospitalized patients is essential in clinical settings to prevent outcomes such as in-hospital mortality and unplanned admission to the intensive care unit (ICU). Classical severity scores have been developed typically using relatively few patient features. Recently, deep learning-based models demonstrated better individualized risk assessments compared to classic risk scores, thanks to the use of aggregated and more heterogeneous data sources for dynamic risk prediction. We investigated to what extent deep learning methods can capture patterns of longitudinal change in health status using time-stamped data from electronic health records. We developed a deep learning model based on embedded text from multiple data sources and recurrent neural networks to predict the risk of the composite outcome of unplanned ICU transfer and in-hospital death. The risk was assessed at regular intervals during the admission for different prediction windows. Input data included medical history, biochemical measurements, and clinical notes from a total of 852,620 patients admitted to non-intensive care units in 12 hospitals in Denmark's Capital Region and Region Zealand during 2011-2016 (with a total of 2,241,849 admissions). We subsequently explained the model using the Shapley algorithm, which provides the contribution of each feature to the model outcome. The best model used all data modalities with an assessment rate of 6 hours, a prediction window of 14 days and an area under the receiver operating characteristic curve of 0.898. The discrimination and calibration obtained with this model make it a viable clinical support tool to detect patients at higher risk of clinical deterioration, providing clinicians insights into both actionable and non-actionable patient features.

The impact of continuous wireless monitoring on adverse device effects in medical and surgical wards: a review of current evidence

Novel technologies allow continuous wireless monitoring systems (CWMS) to measure vital signs and these systems might be favorable compared to intermittent monitoring regarding improving outcomes. However, device safety needs to be validated because uncertain evidence challenges the clinical implementation of CWMS. This review investigates the frequency of device-related adverse events in patients monitored with CWMS in general hospital wards. Systematic literature searches were conducted in PubMed and Embase. We included trials of adult patients in general hospital wards monitored with CWMS. Our primary outcome was the frequency of unanticipated serious adverse device effects (USADEs). Secondary outcomes were adverse device effects (ADEs) and serious adverse device effects (SADE). Data were extracted from eligible studies and descriptive statistics were applied to analyze the data. Seven studies were eligible for inclusion with a total of 1485 patients monitored by CWMS. Of these patients, 54 patients experienced ADEs (3.6%, 95% CI 2.8-4.7%) and no USADEs or SADEs were reported (0%, 95% CI 0-0.31%). The studies of the SensiumVitals® patch, the iThermonitor, and the ViSi Mobile® device reported 28 (9%), 25 (5%), and 1 (3%) ADEs, respectively. No ADEs were reported using the HealthPatch, WARD 24/7 system, or Coviden Alarm Management. Current evidence suggests that CWMS are safe to use but systematic reporting of all adverse device effects is warranted.

Continuous wireless pre- and postoperative vital sign monitoring reveal new, severe desaturations after vascular surgery

OBJECTIVES

Postoperative deviating physiologic values (vital signs) may represent postoperative stress or emerging complications. But they can also reflect chronic preoperative values. Distinguishing between the two circumstances may influence the utility of using vital signs in patient monitoring. Thus, we aimed to describe the occurrence of vital sign deviations before and after major vascular surgery, hypothesising that preoperative vital sign deviations were longer in duration postoperatively.

METHODS

In this prospective observational study, arterial vascular patients were continuously monitored wirelessly - from the day before until 5 days after surgery. Recorded values were: heart rate, respiration rate, peripheral arterial oxygen saturation (SpO₂ ) and blood pressure. The outcomes were 1. cumulative duration of SpO₂  < 85% / 24 h, and 2. cumulative duration per 24 h of vital sign deviations.

RESULTS

Forty patients were included with a median monitoring time of 21 h preoperatively and 42 h postoperatively. The median duration of SpO₂  < 85% preoperatively was 14.4 min/24 h whereas it was 28.0 min/24 h during day 0 in the ward (p = .09), and 16.8 min/24 h on day 1 in the ward (p = 0.61). Cumulative duration of SpO₂  < 80% was significantly longer on day 0 in the ward 2.4 min/24 h (IQR 0.0-4.6) versus 6.7 min/24 h (IQR 1.8-16.2) p = 0.01.

CONCLUSION

Deviating physiology is common in patients before and after vascular surgery. A longer duration of severe desaturation was found on the first postoperative day in the ward compared to preoperatively, whereas moderate desaturations were reflected in postoperative desaturations. Cumulative duration outside thresholds is, in some cases, exacerbated after surgery.

Agreement between standard and continuous wireless vital sign measurements after major abdominal surgery: a clinical comparison study

Objective. Continuous wireless monitoring outside the post-anesthesia or intensive care units may enable early detection of patient deterioration, but good accuracy of measurements is required. We aimed to assess the agreement between vital signs recorded by standard and novel wireless devices in postoperative patients.Approach. In 20 patients admitted to the post-anesthesia care unit, we compared heart rate (HR), respiratory rate (RR), peripheral oxygen saturation (SpO₂), and systolic and diastolic blood pressure (SBP and DBP) as paired data. The primary outcome measure was the agreement between standard wired and wireless monitoring, assessed by mean bias and 95% limits of agreement (LoA). LoA was considered acceptable for HR and PR, if within ±5 beats min^-1(bpm), while RR, SpO2, and BP were deemed acceptable if within ±3 breaths min^-1(brpm), ±3%-points, and ±10 mmHg, respectively.Main results.The mean bias between standard versus wireless monitoring was -0.85 bpm (LoA -6.2 to 4.5 bpm) for HR, -1.3 mmHg (LoA -19 to 17 mmHg) for standard versus wireless SBP, 2.9 mmHg (LoA -17 to 22) for standard versus wireless DBP, and 1.7% (LoA -1.4 mmHg to 4.8 mmHg) for SpO₂, comparing standard versus wireless monitoring. The mean bias of arterial blood gas analysis versus wireless SpO₂measurements was 0.02% (LoA -0.02% to 0.06%), while the mean bias of direct observation of RR compared to wireless measurements was 0.0 brpm (LoA -2.6 brpm to 2.6 brpm). 80% of all values compared were within predefined clinical limits.Significance.The agreement between wired and wireless HR, RR, and PR recordings in postoperative patients was acceptable, whereas the agreement for SpO₂recordings (standard versus wireless) was borderline. Standard wired and wireless BP measurements may be used interchangeably in the clinical setting.

Clinical impact of vital sign abnormalities in patients admitted with acute exacerbation of chronic obstructive pulmonary disease: an observational study using continuous wireless monitoring

Early detection of abnormal vital signs is critical for timely management of acute hospitalised patients and continuous monitoring may improve this. We aimed to assess the association between preceding vital sign abnormalities and serious adverse events (SAE) in patients hospitalised with acute exacerbation of chronic obstructive pulmonary disease (AECOPD). Two hundred patients' vital signs were wirelessly and continuously monitored with peripheral oxygen saturation, heart rate, and respiratory rate during the first 4 days after admission for AECOPD. Non-invasive blood pressure was also measured every 30-60 min. The primary outcome was occurrence of SAE according to international definitions within 30 days and physiological data were analysed for preceding vital sign abnormalities. Data were presented as the mean cumulative duration of vital sign abnormalities per 24 h and analysed using Wilcoxon rank sum test. SAE during ongoing continuous monitoring occurred in 50 patients (25%). Patients suffering SAE during the monitoring period had on average 455 min (SD 413) per 24 h of any preceding vital sign abnormality versus 292 min (SD 246) in patients without SAE, p = 0.08, mean difference 163 min [95% CI 61-265]. Mean duration of bradypnea (respiratory rate < 11 min^-1) was 48 min (SD 173) compared with 30 min (SD 84) in patients without SAE, p = 0.01. In conclusion, the duration of physiological abnormalities was substantial in patients with AECOPD. There were no statistically significant differences between patients with and without SAE in the overall duration of preceding physiological abnormalities.Study registration: http://ClinicalTrials.gov (NCT03660501). Date of registration: Sept 6 2018.

Forecasting of Continuous Vital Sign Using Multivariate Auto-Regressive Models

This project assessed the use of multivariate auto-regressive (MAR) models to create forecasts of continuous vital signs in hospitalized patients. A total of 20 hours continuous (1/60Hz) heart rate and respiration rate from eight postoperative patients, where used to fit a centered MAR model for forecasting in windows of 15 minutes. The model was fitted using Markov Chain Monte Carlo sampling, and the model was evaluated on data from five additional patients. The results demonstrate an average RMSE in the forecast window of 11.4 (SD: 7.30) beats per minute for heart rate and 3.3 (SD:1.3) breaths per minute for respiration rate. These results indicate potential for forecasting vital signs in a clinical setting.

Continuous monitoring of vital sign abnormalities; association to clinical complications in 500 postoperative patients

Background

Patients undergoing major surgery are at risk of complications, so‐called serious adverse events (SAE). Continuous monitoring may detect deteriorating patients by recording abnormal vital signs. We aimed to assess the association between abnormal vital signs inspired by Early Warning Score thresholds and subsequent SAEs in patients undergoing major abdominal surgery.

Methods

Prospective observational cohort study continuously monitoring heart rate, respiratory rate, peripheral oxygen saturation, and blood pressure for up to 96 h in 500 postoperative patients admitted to the general ward. Exposure variables were vital sign abnormalities, primary outcome was any serious adverse event occurring within 30 postoperative days. The primary analysis investigated the association between exposure variables per 24 h and subsequent serious adverse events.

Results

Serious adverse events occurred in 37% of patients, with 38% occurring during monitoring. Among patients with SAE during monitoring, the median duration of vital sign abnormalities was 272 min (IQR 110–447), compared to 259 min (IQR 153–394) in patients with SAE after monitoring and 261 min (IQR 132–468) in the patients without any SAE (p = .62 for all three group comparisons). Episodes of heart rate ≥110 bpm occurred in 16%, 7.1%, and 3.9% of patients in the time before SAE during monitoring, after monitoring, and without SAE, respectively (p < .002). Patients with SAE after monitoring experienced more episodes of hypotension ≤90 mm Hg/24 h (p = .001).

Conclusion

Overall duration of vital sign abnormalities at current thresholds were not significantly associated with subsequent serious adverse events, but more patients with tachycardia and hypotension had subsequent serious adverse events.

Trial registration

Clinicaltrials.gov, identifier NCT03491137.

Variable oxygen administration in surgical and medical wards evaluated by 30-day mortality-An observational study

BACKGROUND

Several studies in surgery and initial management of critical illness have indicated harmful effects of short-term exposure to hyperoxia. Exposure to and consequences of excessive oxygen administration in hospital wards are sparsely investigated. The aim of this study was to investigate the association between excessive oxygen administration in patients admitted to surgical or medical wards and 30-day mortality.

METHODS

We included patients in the Capital Region of Denmark who were admitted to hospital in 2014 for either myocardial infarction, acute exacerbation of chronic obstructive pulmonary disease (COPD), hip fracture or open abdominal surgery. We defined groups of inadequate, adequate or excessive oxygen administration based on peripheral oxygen saturation and oxygen administration values in the first 48 hours after admission. The primary outcome was mortality within 30 days, and data were analysed with multivariable logistic regression for age, gender and comorbidities.

RESULTS

We retrieved data from 11 196 patients, of which 81% had adequate, 18% had excessive and 1.8% inadequate oxygen administration. Mortality at 30 days was 4.2%, 7.6% and 27%, respectively, OR 1.46 (95%CI 1.16-1.84), P = .001 for patients with excessive compared to adequate oxygen administration. The association was significant in subgroups of patients admitted for acute exacerbation of COPD (OR 1.67, 95%CI 1.19-2.34) and myocardial infarction (OR 3.50, 95%CI 1.55-7.89).

CONCLUSION

Patients who received excessive oxygen administration in surgical and medical wards during the first 48 hours of admission had a higher mortality risk within 30 days compared to patients with adequate oxygen administration. However, inadequate oxygen therapy still renders highest mortality and should be avoided.

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

Rationale: 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. Objectives: To develop and externally validate a Hospital- wide Alerting via Electronic Noticeboard (HAVEN) system to identify hospitalized patients at risk of reversible deterioration. Methods: This was a retrospective cohort study of patients 16 years of age or above admitted to four UK hospitals. The primary outcome was cardiac arrest or unplanned admission to the ICU. We used patient data (vital signs, laboratory tests, comorbidities, and frailty) from one hospital to train a machine-learning model (gradient boosting trees). We internally and externally validated the model and compared its performance with existing scoring systems (including the National EWS, laboratory-based acute physiology score, and electronic cardiac arrest risk triage score). Measurements and Main Results: We developed the HAVEN model using 230,415 patient admissions to a single hospital. We validated HAVEN on 266,295 admissions to four hospitals. HAVEN showed substantially higher discrimination (c-statistic, 0.901 [95% confidence interval, 0.898-0.903]) for the primary outcome within 24 hours of each measurement than other published scoring systems (which range from 0.700 [0.696-0.704] to 0.863 [0.860-0.865]). With a precision of 10%, HAVEN was able to identify 42% of cardiac arrests or unplanned ICU admissions with a lead time of up to 48 hours in advance, compared with 22% by the next best system. Conclusions: The HAVEN machine-learning algorithm for early identification of in-hospital deterioration significantly outperforms other published scores such as the National EWS.

Agreement between wireless and standard measurements of vital signs in acute exacerbation of chronic obstructive pulmonary disease: a clinical validation study

Objective.Wireless sensors for continuous monitoring of vital signs have potential to improve patient care by earlier detection of deterioration in general ward patients. We aimed to assess agreement between wireless and standard (wired) monitoring devices in patients hospitalized with acute exacerbation of chronic obstructive pulmonary disease (AECOPD).Approach.Paired measurements of vital signs were recorded with 15 min intervals for two hours. The primary outcome was agreement between wireless and standard monitor measurements using the Bland and Altman method to calculate bias with 95% limits of agreement (LoA). We considered LoA of less than ±5 beats min^-1(bpm) acceptable for heart rate (HR), whereas agreement of peripheral oxygen saturation (SpO₂), respiratory rate (RR), and blood pressure (BP) were acceptable if within ±3%-points, ±3 breaths min^-1(brpm), and ±10 mmHg, respectively.Main results.180 sample-pairs of vital signs from 20 with AECOPD patients were recorded for comparison. The wireless versus standard monitor bias was 0.03 (LoA -3.2 to 3.3) bpm for HR measurements, 1.4% (LoA -0.7% to 3.6%) for SpO₂, -7.8 (LoA -22.3 to 6.8) mmHg for systolic BP and -6.2 (LoA -16.8 to 4.5) mmHg for diastolic BP. The wireless versus standard monitor bias for RR measurements was 0.75 (LoA -6.1 to 7.6) brpm.Significance.Commercially available wireless monitors could accurately measure HR in patients admitted with AECOPD compared to standard wired monitoring. Agreement for SpO₂were borderline acceptable while agreement for RR and BP should be interpreted with caution.

In-hospital cardiac arrest and preceding National Early Warning Score (NEWS): A retrospective case-control study

We aimed to describe and evaluate the National Early Warning Score (NEWS) in the 24 hours preceding an in-hospital cardiac arrest among general somatic ward patients.The 24 hours preceding the in-hospital cardiac arrest were divided into four timespans and analysed by a medical record review of 127:254 matched case-control patients. The median NEWS ranged from 3 (2-6) to 6 (3-9) points for cases vs 1 (0-3) to 1 (0-3) point for controls. The proportion of cases ranged from 23-45% at high risk vs 3-6% for controls. The NEWS high-risk category was associated with an increase of 3.17 (95% confidence interval (CI) 1.66-6.04) to 4.43 (95% CI 2.56-7.67) in odds of in-hospital cardiac arrest compared to the low-risk category.NEWS, with its intuitive and for healthcare staff easy to interpret risk classification, is suitable for discriminating deteriorating patients with major deviating vital signs scoring high risk on NEWS.

Quantitative systematic review: Sources of inaccuracy in manually measured adult respiratory rate data

AIMS

To identify the potential sources of inaccuracy in manually measured adult respiratory rate (RR) data and quantify their effects.

DESIGN

Quantitative systematic review with meta-analyses where appropriate.

DATA SOURCES

Medline, CINAHL, and Cochrane Library (from database inception to 31 July 2019).

REVIEW METHODS

Studies presenting data on individual sources of inaccuracy in the manual measurement of adult RR were analysed, assessed for quality, and grouped according to the source of inaccuracy investigated. Quantitative data were extracted and synthesized and meta-analyses performed where appropriate.

RESULTS

Included studies (N = 49) identified five sources of inaccuracy. The awareness effect creates an artefactual reduction in actual RR, and observation methods involving shorter counts cause systematic underscoring. Individual RR measurements can differ substantially in either direction between observations due to inter- or intra-observer variability. Value bias, where particular RRs are over-represented (suggesting estimation), is a widespread problem. Recording omission is also widespread, with higher average rates in inpatient versus triage/admission contexts.

CONCLUSION

This review demonstrates that manually measured RR data are subject to several potential sources of inaccuracy.

IMPACT

RR is an important indicator of clinical deterioration and commonly included in track-and-trigger systems. However, the usefulness of RR data depends on the accuracy of the observations and documentation, which are subject to five potential sources of inaccuracy identified in this review. A single measurement may be affected by several factors. Hence, clinicians should interpret recorded RR data cautiously unless systems are in place to ensure its accuracy. For nurses, this includes counting rather than estimating RRs, employing 60-s counts whenever possible, ensuring patients are unaware that their RR is being measured, and documenting the resulting value. For any given site, interventions to improve measurement should take into account the local organizational and cultural context, available resources, and the specific measurement issues that need to be addressed.

The impact of a modified New Zealand Early Warning Score (M-NZEWS) and NZEWS on ward patients triggering a medical emergency team activation: A mixed methods sequential design

INTRODUCTION

Limited research exists on the effectiveness of the New Zealand Early Warning Score (NZEWS).

AIM

To determine the impact of a modified NZEWS (M-NZEWS) and NZEWS on ward patients' medical emergency team activation triggers.

RESEARCH DESIGN

Mixed methods sequential design.

METHODS

Three phases included: 1) review of M-NZEWS electronic data to determine the effect of a M-NZEWS and NZEWS on ward patients; 2) an in-depth review of 20 Māori patients allocated to lower escalation zones if the NZEWS were adopted and 3) the number of electronic medical emergency team activation triggers compared to the number of actual medical emergency team activations.

RESULTS

1255 patients and 3505 vital sign data sets were analysed. Adopting the NZEWS would result in 396 (26.8%) fewer patients triggering a medical emergency team activation. The biggest impact would be on Māori, with 38.6% of Māori allocated to a lower escalation zone. Only 51.2% of patients with a medical emergency team activation had vital signs triggering the response electronically documented.

CONCLUSION

Changing from the M-NZEWS to NZEWS will reduce the number of medical emergency team activation triggers, with the biggest impact on Māori. Electronic vital sign data does not accurately reflect the number of ward medical emergency team triggers or activations.

Current clinical methods of measurement of respiratory rate give imprecise values

Background

Respiratory rate is a basic clinical measurement used for illness assessment. Errors in measuring respiratory rate are attributed to observer and equipment problems. Previous studies commonly report rate differences ranging from 2 to 6 breaths·min^-1 between observers.

Methods

To study why repeated observations should vary so much, we conducted a virtual experiment, using continuous recordings of breathing from acutely ill patients. These records allowed each breathing cycle to be precisely timed. We made repeated random measures of respiratory rate using different sample durations of 30, 60 and 120 s. We express the variation in these repeated rate measurements for the different sample durations as the interquartile range of the values obtained for each subject. We predicted what values would be found if a single measure, taken from any patient, were repeated and inspected boundary values of 12, 20 or 25 breaths·min^-1, used by the UK National Early Warning Score, for possible mis-scoring.

Results

When the sample duration was nominally 30 s, the mean interquartile range of repeated estimates was 3.4 breaths·min^-1. For the 60 s samples, the mean interquartile range was 3 breaths·min^-1, and for the 120 s samples it was 2.5 breaths·min^-1. Thus, repeat clinical counts of respiratory rate often differ by >3 breaths·min^-1. For 30 s samples, up to 40% of National Early Warning Scores could be misclassified.

Conclusions

Early warning scores will be unreliable when short sample durations are used to measure respiratory rate. Precision improves with longer sample duration, but this may be impractical unless better measurement methods are used.

A simple prognostic score predicts one-year mortality of alert and calm emergency department patients: A prospective two-center observational study

STUDY OBJECTIVE

To derive and validate a prognostic score to predict 1-year mortality using vital signs, mobility and other variables that are readily available at the bedside at no additional cost.

METHODS

Post hoc analysis of two independent prospective observational studies in two emergency departments, one in Denmark and the other in Switzerland.

PARTICIPANTS

Alert and calm emergency department patients.

MEASUREMENTS

The prediction of mortality from presentation to 365 days by vital signs, mobility and other variables that are readily available at the bedside at no additional cost.

RESULTS

One thousand six hundred and eighteen alert and calm patients were in the Danish cohort and 1331 in the Swiss cohort. Logistic regression identified age >68 years, abnormal vital signs, impaired mobility and the decision to admit as significant predictors of 365-day mortality. A simple prognostic score awarded one point to each of these predictors. Less than two of these predictors were present in 45.6% of patients, and only 0.4% of these patients died within a year. If two or more of these predictors were present, 365-day mortality increased exponentially.

CONCLUSION

Age >68 years, the decision for hospital admission, any vital sign abnormality at presentation and impaired mobility at presentation are equally powerful predictors of 1-year mortality in alert and calm emergency department patients. If validated by others these predictors could be used to discharge patients with confidence since nearly half of these patients had less than two predictors and none of them died within 30 days. However, when two or more predictors were present 365-day mortality increased exponentially.

National Early Warning Score: A survey of registered nurses' perceptions, experiences and barriers

AIMS & OBJECTIVES

To describe registered nurses' perceptions, experiences and barriers for using the National Early Warning Score in relation to their work experience and medical affiliation.

BACKGROUND

Indications of inconsistencies in adherence to the National Early Warning Score have emerged.

DESIGN

Web-based questionnaire study.

METHODS

The questionnaire was sent to 3,165 registered nurses working in somatic hospitals in the southern part of Sweden. Strengthening the Reporting of Observational Studies in Epidemiology was adhered.

RESULTS

Seventy-one per cent of the 1,044 respondents reported adherence to the National Early Warning Score guidelines recommended frequency of monitoring and 74% to the clinical response scale. The shorter the working experience, the higher the proportion of registered nurses who answered positively to the National Early Warning Score allowing them to better prioritise their care with short nursing experience. When categorising nurses according to their workplace's medical affiliation, adherence to the National Early Warning Score guidelines recommended frequency of monitoring was reported highest in surgery and orthopaedics (66%) and lowest in the cardiac high dependency unit (52%). Corresponding proportions of reported adherence to the clinical response scale were highest in orthopaedics (82%) and lowest in the cardiac high dependency unit (48%). Lack of response from the doctor was reported as one of the main reasons for not adhering to the National Early Warning Score by 50% of the registered nurse.

CONCLUSION

In general, registered nurses perceived the National Early Warning Score as a useful tool, supporting their gut feeling about an unstable patient. Barriers to the National Early Warning Score were found in doctors and the most experienced registered nurses, indicating the need for resources to be focused on the adherence of these members of the healthcare team.

RELEVANCE TO CLINICAL PRACTICE

In general, the registered nurses answered positively to the National Early Warning Score. We found indications that there is a need to focus resources on the adherence of the most experienced registered nurse and the doctors.

Adjusting Early Warning Score by clinical assessment: a study protocol for a Danish cluster-randomised, multicentre study of an Individual Early Warning Score (I-EWS)

INTRODUCTION

Track and trigger systems (TTSs) based on vital signs are implemented in hospitals worldwide to identify patients with clinical deterioration. TTSs may provide prognostic information but do not actively include clinical assessment, and their impact on severe adverse events remain uncertain. The demand for prospective, multicentre studies to demonstrate the effectiveness of TTSs has grown the last decade. Individual Early Warning Score (I-EWS) is a newly developed TTS with an aggregated score based on vital signs that can be adjusted according to the clinical assessment of the patient. The objective is to compare I-EWS with the existing National Early Warning Score (NEWS) algorithm regarding clinical outcomes and use of resources.

METHOD AND ANALYSIS

In a prospective, multicentre, cluster-randomised, crossover, non-inferiority study. Eight hospitals are randomised to use either NEWS in combination with the Capital Region of Denmark NEWS Override System (CROS) or implement I-EWS for 6.5 months, followed by a crossover. Based on their clinical assessment, the nursing staff can adjust the aggregated score with a maximum of -4 or +6 points. We expect to include 150 000 unique patients. The primary endpoint is all-cause mortality at 30 days. Coprimary endpoint is the average number of times per day a patient is NEWS/I-EWS-scored, and secondary outcomes are all-cause mortality at 48 hours and at 7 days as well as length of stay.

ETHICS AND DISSEMINATION

The study was presented for the Regional Ethics committee who decided that no formal approval was needed according to Danish law (J.no. 1701733). The I-EWS study is a large prospective, randomised multicentre study that investigates the effect of integrating a clinical assessment performed by the nursing staff in a TTS, in a head-to-head comparison with the internationally used NEWS with the opportunity to use CROS.

TRIAL REGISTRATION NUMBER

NCT03690128.

Physiological abnormalities in patients admitted with acute exacerbation of COPD: an observational study with continuous monitoring

Acute exacerbations of chronic obstructive pulmonary disease (AECOPD) may rapidly require intensive care treatment. Evaluation of vital signs is necessary to detect physiological abnormalities (micro events), but patients may deteriorate between measurements. We aimed to assess if continuous monitoring of vital signs in patients admitted with AECOPD detects micro events more often than routine ward rounds. In this observational pilot study (NCT03467815), 30 adult patients admitted with AECOPD were included. Patients were continuously monitored with peripheral oxygen saturation (SpO₂), heart rate, and respiratory rate during the first 4 days after admission. Hypoxaemic events were defined as decreased SpO₂ for at least 60 s. Non-invasive blood pressure was also measured every 15-60 min. Clinical ward staff measured vital signs as part of Early Warning Score (EWS). Data were analysed using Fisher's exact test or Wilcoxon rank sum test. Continuous monitoring detected episodes of SpO₂ < 92% in 97% versus 43% detected by conventional EWS (p < 0.0001). Events of SpO₂ < 88% was detected in 90% with continuous monitoring compared with 13% with EWS (p < 0.0001). Sixty-three percent of patients had episodes of SpO₂ < 80% recorded by continuous monitoring and 17% had events lasting longer than 10 min. No events of SpO₂ < 80% was detected by EWS. Micro events of tachycardia, tachypnoea, and bradypnoea were also more frequently detected by continuous monitoring (p < 0.02 for all). Moderate and severe episodes of desaturation and other cardiopulmonary micro events during hospitalization for AECOPD are common and most often not detected by EWS.

Myocardial injury and mortality in patients with excessive oxygen administration before cardiac arrest

INTRODUCTION

Hyperoxia after cardiac arrest may be associated with higher mortality, and trials have found that excess oxygen administration in patients with myocardial infarction is associated with increased infarct size. The effect of hyperoxia before cardiac arrest is sparsely investigated. Our aim was to assess the association between excessive oxygen administration before cardiac arrest and the extent of subsequent myocardial injury.

METHODS

We performed a retrospective study including patients who had in-hospital cardiac arrest during 2014 in the Capital Region of Denmark. We excluded patients without peripheral oxygen saturation measurements within 48 hours before cardiac arrest. Patients were divided in three groups of pre-arrest oxygen exposure, based on average peripheral oxygen saturation and supplemental oxygen. Primary outcome was peak troponin concentration within 30 days. Secondary outcomes included 30-day mortality. Data were analyzed using multiple logistic regression and Wilcoxon rank sum test.

RESULTS

Of 163 patients with cardiac arrest, 28 had excessive oxygen administration (17%), 105 had normal oxygen administration (64%) and 30 had insufficient oxygen administration (18%) before cardiac arrest. Peak troponin was median 224 ng/L in the excessive oxygen administration group vs 365 ng/L in the normal oxygen administration group (P = .54); 20 of 28 (71%) in the excessive oxygen administration group died within 30 days compared to 54 of 105 (51%) in the normal oxygen administration group. (OR 1.87, 95% CI 0.56-6.19) CONCLUSIONS: Excessive oxygen administration within 48 hours before in-hospital cardiac arrest was not statistically associated with significantly higher peak troponin or mortality.

Comparison of Reverse Triage with National Early Warning Score, Sequential Organ Failure Assessment and Charlson Comorbidity Index to classify medical inpatients of an Italian II level hospital according to their resource's need

Resource allocation in our overcrowded hospitals would require classification of inpatients according to the severity of illness, the evolving risk and the clinical complexity. Reverse triage (RT) is a method used in disasters to identify inpatients according to their use of hospital resources. The aim of this observational prospective study is to evaluate the use of RT in medical inpatients of an Italian Hospital and to compare the RT score with National Early Warning Score, Sequential Organ Failure Assessment and Charlson Comorbidity Index. Cluster sampling was performed on high dependency unit (HDU), geriatrics (Ger) and internal medicine (IM) wards. We calculate RT, NEWS, SOFA and CCI from inpatient charts. Length of stay (LOS), transfer to a higher level of care, death and discharge date were collected after 30 days. We obtained demographics, comorbidities, severity and clinical complexity of 260 inpatients. We highlighted differences in NEWS, SOFA and CCI in the three divisions. On the contrary RT score was uniformly high (median 7), with 85% of patients with RT = 8. NEWS, SOFA and CCI were higher in patients with higher RT score. We used the sum of the interventions listed by RT (RT sum) as a proxy of the level of care needed. RT-sum showed moderate correlation with NEWS (r = 0.52 Spearman, p < 0.001). RT-sum was the highest in HDU, related to the evolving severity of HDU patients. Ger patients that showed the highest CCI score (with all patients in the CCI ≥ 3 category) had the second highest RT-sum. RT score showed similar values in the majority of the inpatients regardless of differences in NEWS, SOFA and CCI in different ward subgroups. RT-sum is related both to evolving severity (NEWS) and to clinical complexity (CCI). RT and NEWS could predict inpatient level of care and resource need associated with CCI.

Use of National Early Warning Score for observation for increased risk for clinical deterioration during post-ICU care at a surgical ward

Purpose

Patients transferred from an intensive care unit (ICU) to a general ward are at risk for clinical deterioration. The aim of the study was to determine if an increase in National Early Warning Score (NEWS) value predicted worse outcomes in surgical ward patients previously treated in the ICU.

Patients and methods

A retrospective observational study was conducted in a cohort of gastrointestinal surgery patients after transfer from an ICU/high dependency unit (HDU). NEWS values were collected throughout the ward admission. Clinical deterioration was defined by ICU readmission or death. The ability of NEWS to predict clinical deterioration was determined using a linear mixed effect model.

Results

We included 124 patients, age 65.9±14.5, 60% males with an ICU Simplified Acute Physiology Score II 33.8±12.7. No patients died unexpectedly at the ward and 20 were readmitted to an ICU/HDU. The NEWS values increased by a mean of 0.15 points per hour (intercept 3.7, P<0.001) before ICU/HDU readmission according to the linear mixed effect model. NEWS at transfer from ICU was the only factor that predicted readmission (OR 1.32; 95% CI 1.01–1.72; P=0.04) at the time of admission to the ward.

Conclusion

Clinical deterioration of surgical patients was preceded by an increase in NEWS.

The association between pre-operative sepsis and 30-day mortality in hip fracture patients-A cohort study

BACKGROUND

Post-operative sepsis considerably increases mortality, but the extent of pre-operative sepsis in hip fracture patients and its consequences are sparsely elucidated. The aim of this study was to assess the association between pre-operative sepsis and 30-day mortality after hip fracture surgery.

METHODS

We conducted a retrospective analysis of data collected among 1894 patients who underwent hip fracture surgery in the Capital Region of Denmark in 2014 (NCT03201679). Data on vital signs, cultures and laboratory data were obtained. Sepsis was defined as a positive culture of any kind and presence of systemic inflammatory response syndrome within 24 hours and was assessed within 72 hours before surgery and 30 days post-operatively. Primary outcome was 30-day mortality. Secondary outcomes included length of hospital stay and admission to intensive care unit.

RESULTS

A total of 144 (7.6%) of the hip fracture patients met the criteria for pre-operative sepsis. The 30-day mortality was 13.9% in patients with pre-operative sepsis as compared to 9.0% in those without (OR 1.69, 95% CI [1.00; 2.85], P = .08). Patients with pre-operative sepsis had longer hospital stays (median 10 days vs 9 days, mean difference 2.1 [SD 9.4] days, P = .03), and higher frequency of ICU admission (11.1% vs 2.7%, OR 4.15, 95% CI [2.19; 7.87], P < .0001).

CONCLUSION

Pre-operative sepsis in hip fracture patients was associated with an increased length of hospital stay and tended to increase mortality. Pre-operative sepsis in hip fracture patients merits more intensive surveillance and increased attention to timely treatment.