Lack of improvement in sepsis care on the wards: results of four consecutive yearly point-prevalence studies in Wales

Abstract Background: The ‘Sepsis Six’ bundle was promoted as a more deliverable tool outside of the critical care settings, but there is very little data available on the progress and change of sepsis care outside the critical care environment in the UK. Our aim was to compare the yearly prevalence, outcome and the Sepsis Six bundle compliance in patients at risk of mortality from sepsis in non-intensive care environments. Methods: Patients with a National Early Warning Score (NEWS) of 3 or above and suspected or proven infection were enrolled into four yearly 24-hour point prevalence studies, carried out in fourteen hospitals across Wales from 2016-2019. Results: Out of the 26,947 patients screened 1,651 fulfilled inclusion criteria and were recruited. The full ‘Sepsis Six’ care bundle was completed on 223 (14.0%) occasions, with no significant difference between the years. On 190 (11.5%) occasions none of the bundle elements were completed. There was no significant correlation between bundle element compliance, NEWS or year of study. One hundred and seventy (10.7%) patients were seen by critical care outreach; the ‘Sepsis Six’ bundle was completed significantly more often in this group (54/170, 32.0%) than for patients who were not reviewed by critical care outreach (168/1385, 11.6%; p<0.0001)Overall, 1349 patients (81.2%) survived to 30 days with a mean survival time of 26.5 days (95% CI 26.1-26.9) with no difference between each year of study. 90-day survival for years 2017 – 2019 was 74.7%, with no difference between the years. In multivariate regression we identified older age, heart failure, recent chemotherapy, higher frailty score and do not attempt cardiopulmonary resuscitation orders as significantly associated with increased 30-day mortality. Conclusions: Our data suggests that despite efforts to increase sepsis awareness within the NHS, there is poor compliance with the sepsis care bundles and no change in the high mortality over the study period. Further research is needed to determine which time-sensitive ward-based interventions can reduce mortality in patients with sepsis and how can these results be embedded to routine clinical practice.Trial registration: Defining Sepsis on the Wards ISRCTN 86502304 https://doi.org/10.1186/ISRCTN86502304 prospectively registered 09/05/2016

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Four consecutive yearly point-prevalence studies in Wales indicate lack of improvement in sepsis care on the wards

Scientific Reports ◽

10.1038/s41598-021-95648-6 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Maja Kopczynska ◽

Harry Unwin ◽

Richard J. Pugh ◽

Ben Sharif ◽

Thomas Chandy ◽

...

Keyword(s):

Critical Care ◽

Point Prevalence ◽

Early Warning Score ◽

Care Bundle ◽

Resuscitation Orders ◽

Prevalence Studies ◽

Significant Difference ◽

Patients At Risk ◽

Sepsis Care ◽

Critical Care Outreach

AbstractThe ‘Sepsis Six’ bundle was promoted as a deliverable tool outside of the critical care settings, but there is very little data available on the progress and change of sepsis care outside the critical care environment in the UK. Our aim was to compare the yearly prevalence, outcome and the Sepsis Six bundle compliance in patients at risk of mortality from sepsis in non-intensive care environments. Patients with a National Early Warning Score (NEWS) of 3 or above and suspected or proven infection were enrolled into four yearly 24-h point prevalence studies, carried out in fourteen hospitals across Wales from 2016 to 2019. We followed up patients to 30 days between 2016–2019 and to 90 days between 2017 and 2019. Out of the 26,947 patients screened 1651 fulfilled inclusion criteria and were recruited. The full ‘Sepsis Six’ care bundle was completed on 223 (14.0%) occasions, with no significant difference between the years. On 190 (11.5%) occasions none of the bundle elements were completed. There was no significant correlation between bundle element compliance, NEWS or year of study. One hundred and seventy (10.7%) patients were seen by critical care outreach; the ‘Sepsis Six’ bundle was completed significantly more often in this group (54/170, 32.0%) than for patients who were not reviewed by critical care outreach (168/1385, 11.6%; p < 0.0001). Overall survival to 30 days was 81.7% (1349/1651), with a mean survival time of 26.5 days (95% CI 26.1–26.9) with no difference between each year of study. 90-day survival for years 2017–2019 was 74.7% (949/1271), with no difference between the years. In multivariate regression we identified older age, heart failure, recent chemotherapy, higher frailty score and do not attempt cardiopulmonary resuscitation orders as significantly associated with increased 30-day mortality. Our data suggests that despite efforts to increase sepsis awareness within the NHS, there is poor compliance with the sepsis care bundles and no change in the high mortality over the study period. Further research is needed to determine which time-sensitive ward-based interventions can reduce mortality in patients with sepsis and how can these results be embedded to routine clinical practice.Trial registration Defining Sepsis on the Wards ISRCTN 86502304 https://doi.org/10.1186/ISRCTN86502304 prospectively registered 09/05/2016.

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A quality improvement project for delirium prevention and management over the Greater Manchester Critical Care Network

Journal of the Intensive Care Society ◽

10.1177/1751143720912700 ◽

2020 ◽

pp. 175114372091270

Author(s):

Jessica Davis ◽

Karen Berry ◽

Rebecca McIntyre ◽

Daniel Conway ◽

Anthony Thomas ◽

...

Keyword(s):

Critical Care ◽

Best Practice ◽

Point Prevalence ◽

Screening Tools ◽

Care Bundle ◽

Improvement Project ◽

Care Network ◽

Critical Care Units ◽

Patient Morbidity ◽

Delirium Prevention

Background Delirium is a common complication of critical illness with a significant impact on patient morbidity and mortality. The Greater Manchester Critical Care Network established the Delirium Reduction Working Group in 2015. This article describes a region-wide delirium improvement project launched by that group. Methods Multiple Plan-Do-Study-Act cycles were undertaken. Cycle 1: April 2015 demonstrated only 48% of patients had a formal delirium screen. Following this a network-wide event took place and the Delirium Standards for the Greater Manchester Critical Care Network were produced. Cycle 2: May 2016 quarterly audits across the network monitored compliance against the agreed standards. Group events involved implementation of a delirium care bundle, sharing best practice, educating staff and providing guidance on the management of delirium. Cycle 3: November 2016 quarterly audit continued and a regional delirium study day was rolled out across the region. Results We have 14 different units across our network, all of which have participated in the audit. The first audit showed a delirium point prevalence of 28%, subsequent point prevalence audits demonstrated rates as low as 13%. There has also been an improvement in the use of delirium screening tools. In the first audit 37% of patients had two delirium screens in 24 h, this has increased to 60% in the latest audit. Improvements were also made in availability of sensory aids and pain assessments. Conclusion The project has demonstrated the feasibility of delivering a coordinated delirium improvement project across multiple critical care units.

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Outcomes in patients with acute kidney injury reviewed by Critical Care Outreach: What is the role of the National Early Warning Score?

Journal of the Intensive Care Society ◽

10.1177/1751143717715968 ◽

2017 ◽

Vol 18 (4) ◽

pp. 300-309 ◽

Cited By ~ 1

Author(s):

Daniel A Potter ◽

Nicholas Wroe ◽

Helen Redhead ◽

Andrew JP Lewington

Keyword(s):

Acute Kidney Injury ◽

Critical Care ◽

Early Warning ◽

Kidney Injury ◽

Early Warning Score ◽

Acute Kidney Injury Stage ◽

National Early Warning Score ◽

One Year ◽

Critical Care Outreach

Introduction This study investigated outcomes in critically unwell acute kidney injury patients and the role of the National Early Warning Score and other factors in identifying patients who experience negative outcomes. Methods Retrospective cohort study investigating 64 patients seen by Critical Care Outreach between November 2014 and February 2015. Mortality at one year was analysed using multivariate regression; all other statistical tests were non-parametric. Results Forty-four per cent of patients required escalation to higher level care, 56% failed to survive beyond one year and 30% of those who did survive had a deterioration in renal function. Previous acute kidney injury significantly predicted mortality but the National Early Warning Score did not. A subgroup of patients developed Stage 3 acute kidney injury before a rise in National Early Warning Score. Conclusions Acute kidney injury in the Critical Care Outreach patient population is associated with high morbidity and mortality. Previous acute kidney injury and acute kidney injury stage may be superior to the National Early Warning Score at identifying patients in need of Critical Care Outreach review.

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Developing a deep learning system to drive the work of the critical care outreach team

10.1101/2020.07.07.20148064 ◽

2020 ◽

Author(s):

Georgina Kennedy ◽

John Rihari-Thomas ◽

Mark Dras ◽

Blanca Gallego

Keyword(s):

Critical Care ◽

Deep Learning ◽

Critical Care Nurses ◽

Learning System ◽

Patient Death ◽

Outreach Team ◽

Patients At Risk ◽

Nurses And Physicians ◽

Watch List ◽

Critical Care Outreach

Care of patients at risk of deterioration on acute medical and surgical wards requires timely identification, increased monitoring and robust escalation procedures. The critical care outreach role brings specialist-trained critical care nurses and physicians into acute wards to facilitate these processes. Performing this role is challenging, as the breadth of information synthesis required is both high and rapidly updating. We propose a novel automated `watch-list' to identify patients at high risk of deterioration, to help prioritise the work of the outreach team. This system takes data from the electronic medical record in real-time and creates a discrete tokenized trajectory, which is fed into a recurrent neural network model. These models achieve an AUROC of 0.928 for in-patient death and 0.778 for unplanned ICU admission (within 24 hours), which compares favourably with existing early warning scores and is comparable with proof of concept deep learning systems requiring significantly more input data.

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P-165 Sepsis care bundle for a hospice in-patient unit

10.1136/bmjspcare-2017-hospice.190 ◽

2017 ◽

Author(s):

Paula Powell ◽

Daniel Monnery ◽

Susan Schofield

Keyword(s):

Care Bundle ◽

Sepsis Care

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G211 Designing a critical care outreach service – an audit and national survey

10.1136/archdischild-2020-rcpch.179 ◽

2020 ◽

Author(s):

N Peshimam ◽

S Stockinger ◽

J Weber ◽

R Mitting

Keyword(s):

Critical Care ◽

National Survey ◽

Outreach Service ◽

Critical Care Outreach

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Comparing Patient Characteristics, Clinical Outcomes, and Biomarkers of Severe Asthma Patients in Taiwan

Biomedicines ◽

10.3390/biomedicines9070764 ◽

2021 ◽

Vol 9 (7) ◽

pp. 764

Author(s):

Shih-Lung Cheng ◽

Kuo-Chin Chiu ◽

Hsin-Kuo Ko ◽

Diahn-Warng Perng ◽

Hao-Chien Wang ◽

...

Keyword(s):

Severe Asthma ◽

Clinical Characteristics ◽

Linear Models ◽

Patient Characteristics ◽

Emergency Department Visits ◽

Receiver Operating Characteristic Curves ◽

Increased Risk ◽

Significant Difference ◽

Asthma Patients ◽

Patients At Risk

Purpose: To understand the association between biomarkers and exacerbations of severe asthma in adult patients in Taiwan. Materials and Methods: Demographic, clinical characteristics and biomarkers were retrospectively collected from the medical charts of severe asthma patients in six hospitals in Taiwan. Exacerbations were defined as those requiring asthma-specific emergency department visits/hospitalizations, or systemic steroids. Enrolled patients were divided into: (1) those with no exacerbations (non-exacerbators) and (2) those with one or more exacerbations (exacerbators). Receiver operating characteristic curves were used to determine the optimal cut-off value for biomarkers. Generalized linear models evaluated the association between exacerbation and biomarkers. Results: 132 patients were enrolled in the study with 80 non-exacerbators and 52 exacerbators. There was no significant difference in demographic and clinical characteristics between the two groups. Exacerbators had significantly higher eosinophils (EOS) counts (367.8 ± 357.18 vs. 210.05 ± 175.24, p = 0.0043) compared to non-exacerbators. The optimal cut-off values were 292 for EOS counts and 19 for the Fractional exhaled Nitric Oxide (FeNO) measure. Patients with an EOS count ≥ 300 (RR = 1.88; 95% CI, 1.26–2.81; p = 0.002) or FeNO measure ≥ 20 (RR = 2.10; 95% CI, 1.05–4.18; p = 0.0356) had a significantly higher risk of exacerbation. Moreover, patients with both an EOS count ≥ 300 and FeNO measure ≥ 20 had a significantly higher risk of exacerbation than those with lower EOS count or lower FeNO measure (RR = 2.16; 95% CI, 1.47–3.18; p = < 0.0001). Conclusions: Higher EOS counts and FeNO measures were associated with increased risk of exacerbation. These biomarkers may help physicians identify patients at risk of exacerbations and personalize treatment for asthma patients.

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Predicting mortality in adults with suspected infection in a Rwandan hospital: an evaluation of the adapted MEWS, qSOFA and UVA scores

BMJ Open ◽

10.1136/bmjopen-2020-040361 ◽

2021 ◽

Vol 11 (2) ◽

pp. e040361

Author(s):

Amanda Klinger ◽

Ariel Mueller ◽

Tori Sutherland ◽

Christophe Mpirimbanyi ◽

Elie Nziyomaze ◽

...

Keyword(s):

Decision Making ◽

Quality Improvement ◽

Clinical Decision Making ◽

Clinical Decision ◽

Tertiary Hospital ◽

Early Warning Score ◽

Receiver Operating Curve ◽

Predictive Capacity ◽

Suspected Infection ◽

Significant Difference

RationaleMortality prediction scores are increasingly being evaluated in low and middle income countries (LMICs) for research comparisons, quality improvement and clinical decision-making. The modified early warning score (MEWS), quick Sequential (Sepsis-Related) Organ Failure Assessment (qSOFA), and Universal Vital Assessment (UVA) score use variables that are feasible to obtain, and have demonstrated potential to predict mortality in LMIC cohorts.ObjectiveTo determine the predictive capacity of adapted MEWS, qSOFA and UVA in a Rwandan hospital.Design, setting, participants and outcome measuresWe prospectively collected data on all adult patients admitted to a tertiary hospital in Rwanda with suspected infection over 7 months. We calculated an adapted MEWS, qSOFA and UVA score for each participant. The predictive capacity of each score was assessed including sensitivity, specificity, positive and negative predictive value, OR, area under the receiver operating curve (AUROC) and performance by underlying risk quartile.ResultsWe screened 19 178 patient days, and enrolled 647 unique patients. Median age was 35 years, and in-hospital mortality was 18.1%. The proportion of data missing for each variable ranged from 0% to 11.7%. The sensitivities and specificities of the scores were: adapted MEWS >4, 50.4% and 74.9%, respectively; qSOFA >2, 24.8% and 90.4%, respectively; and UVA >4, 28.2% and 91.1%, respectively. The scores as continuous variables demonstrated the following AUROCs: adapted MEWS 0.69 (95% CI 0.64 to 0.74), qSOFA 0.65 (95% CI 0.60 to 0.70), and UVA 0.71 (95% CI 0.66 to 0.76); there was no statistically significant difference between the discriminative capacities of the scores.ConclusionThree scores demonstrated a modest ability to predict mortality in a prospective study of inpatients with suspected infection at a Rwandan tertiary hospital. Careful consideration must be given to their adequacy before using them in research comparisons, quality improvement or clinical decision-making.

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Glucose as an additional parameter to National Early Warning Score (NEWS) in prehospital setting enhances identification of patients at risk of death: an observational cohort study

Emergency Medicine Journal ◽

10.1136/emermed-2018-208309 ◽

2020 ◽

pp. emermed-2018-208309

Author(s):

Hanna Vihonen ◽

Mitja Lääperi ◽

Markku Kuisma ◽

Jussi Pirneskoski ◽

Jouni Nurmi

Keyword(s):

At Risk ◽

Blood Glucose ◽

Regression Model ◽

Early Warning ◽

Prehospital Setting ◽

Early Warning Score ◽

Calibration Model ◽

Risk Of Death ◽

Patients At Risk ◽

National Early Warning Score

BackgroundTo determine if prehospital blood glucose could be added to National Early Warning Score (NEWS) for improved identification of risk of short-term mortality.MethodsRetrospective observational study (2008–2015) of adult patients seen by emergency medical services in Helsinki metropolitan area for whom all variables for calculation of NEWS and a blood glucose value were available. Survival of 24 hours and 30 days were determined. The NEWS parameters and glucose were tested by multivariate logistic regression model. Based on ORs we formed NEWSgluc model with hypoglycaemia (≤3.0 mmol/L) 3, normoglycaemia 0 and hyperglycaemia (≥11.1 mmol/L) 1 points. The scores from NEWS and NEWSgluc were compared using discrimination (area under the curve), calibration (Hosmer-Lemeshow test), likelihood ratio tests and reclassification (continuous net reclassification index (cNRI)).ResultsData of 27 141 patients were included in the study. Multivariable regression model for NEWSgluc parameters revealed a strong association with glucose disturbances and 24-hour and 30-day mortality. Likelihood ratios (LRs) for mortality at 24 hours using a cut-off point of 15 were for NEWSgluc: LR+ 17.78 and LR− 0.96 and for NEWS: LR+ 13.50 and LR− 0.92. Results were similar at 30 days. Risks per score point estimation and calibration model showed glucose added benefit to NEWS at 24 hours and at 30 days. Although areas under the curve were similar, reclassification test (cNRI) showed overall improvement of classification of survivors and non-survivors at 24 days and 30 days with NEWSgluc.ConclusionsIncluding glucose in NEWS in the prehospital setting seems to improve identification of patients at risk of death.

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