Stuart William Jarvis

Decision-tree early warning score (DTEWS) validates the design of the National Early Warning Score (NEWS).

AIM OF STUDY To compare the performance of a human-generated, trial and error-optimised early warning score (EWS), i.e., National Early Warning Score (NEWS), with one generated entirely algorithmically using Decision Tree (DT) analysis. MATERIALS AND METHODS We used DT analysis to construct a decision-tree EWS (DTEWS) from a database of 198,755 vital signs observation sets collected from 35,585 consecutive, completed acute medical admissions. We evaluated the ability of DTEWS to discriminate patients at risk of cardiac arrest, unanticipated intensive care unit admission or death, each within 24h of a given vital signs observation. We compared the performance of DTEWS and NEWS using the area under the receiver-operating characteristic (AUROC) curve. RESULTS The structures of DTEWS and NEWS were very similar. The AUROC (95% CI) for DTEWS for cardiac arrest, unanticipated ICU admission, death, and any of the outcomes, all within 24h, were 0.708 (0.669-0.747), 0.862 (0.852-0.872), 0.899 (0.892-0.907), and 0.877 (0.870-0.883), respectively. Values for NEWS were 0.722 (0.685-0.759) [cardiac arrest], 0.857 (0.847-0.868) [unanticipated ICU admission}, 0.894 (0.887-0.902) [death], and 0.873 (0.866-0.879) [any outcome]. CONCLUSIONS The decision-tree technique independently validates the composition and weightings of NEWS. The DT approach quickly provided an almost identical EWS to NEWS, although one that admittedly would benefit from fine-tuning using clinical knowledge. We believe that DT analysis could be used to quickly develop candidate models for disease-specific EWSs, which may be required in future.

Development and validation of a decision tree early warning score based on routine laboratory test results for the discrimination of hospital mortality in emergency medical admissions

AIM OF STUDY To build an early warning score (EWS) based exclusively on routinely undertaken laboratory tests that might provide early discrimination of in-hospital death and could be easily implemented on paper. MATERIALS AND METHODS Using a database of combined haematology and biochemistry results for 86,472 discharged adult patients for whom the admission specialty was Medicine, we used decision tree (DT) analysis to generate a laboratory decision tree early warning score (LDT-EWS) for each gender. LDT-EWS was developed for a single set (n=3496) (Q1) and validated in 22 other discrete sets each of three months long (Q2, Q3…Q23) (total n=82,976; range of n=3428 to 4093) by testing its ability to discriminate in-hospital death using the area under the receiver-operating characteristic (AUROC) curve. RESULTS The data generated slightly different models for male and female patients. The ranges of AUROC values (95% CI) for LDT-EWS with in-hospital death as the outcome for the validation sets Q2-Q23 were: 0.755 (0.727-0.783) (Q16) to 0.801 (0.776-0.826) [all patients combined, n=82,976]; 0.744 (0.704-0.784, Q16) to 0.824 (0.792-0.856, Q2) [39,591 males]; and 0.742 (0.707-0.777, Q10) to 0.826 (0.796-0.856, Q12) [43,385 females]. CONCLUSIONS This study provides evidence that the results of commonly measured laboratory tests collected soon after hospital admission can be represented in a simple, paper-based EWS (LDT-EWS) to discriminate in-hospital mortality. We hypothesise that, with appropriate modification, it might be possible to extend the use of LDT-EWS throughout the patients hospital stay.

A Comparison of the Ability of the Physiologic Components of Medical Emergency Team Criteria and the U.k. National Early Warning Score to Discriminate Patients at Risk of a Range of Adverse Clinical Outcomes.

Objective:To compare the ability of medical emergency team criteria and the National Early Warning Score to discriminate cardiac arrest, unanticipated ICU admission and death within 24 hours of a vital signs measurement, and to quantify the associated workload. Design:Retrospective cohort study. Setting:A large U.K. National Health Service District General Hospital. Patients:Adults hospitalized from May 25, 2011, to December 31, 2013. Interventions:None. Measurements and Main Results:We applied the National Early Warning Score and 44 sets of medical emergency team criteria to a database of 2,245,778 vital signs sets (103,998 admissions). The National Early Warning Score’s performance was assessed using the area under the receiver-operating characteristic curve and compared with sensitivity/specificity for different medical emergency team criteria. Area under the receiver-operating characteristic curve (95% CI) for the National Early Warning Score for the combined outcome (i.e., death, cardiac arrest, or unanticipated ICU admission) was 0.88 (0.88–0.88). A National Early Warning Score value of 7 had sensitivity/specificity values of 44.5% and 97.4%, respectively. For the 44 sets of medical emergency team criteria studied, sensitivity ranged from 19.6% to 71.2% and specificity from 71.5% to 98.5%. For all outcomes, the position of the National Early Warning Score receiver-operating characteristic curve was above and to the left of all medical emergency team criteria points, indicating better discrimination. Similarly, the positions of all medical emergency team criteria points were above and to the left of the National Early Warning Score efficiency curve, indicating higher workloads (trigger rates). Conclusions:When medical emergency team systems are compared to a National Early Warning Score value of greater than or equal to 7, some medical emergency team systems have a higher sensitivity than National Early Warning Score values of greater than or equal to 7. However, all of these medical emergency team systems have a lower specificity and would generate greater workloads.

Parameter Optimisation for the ITRAX Core Scanner

A range of parameters affects Itrax core scanner response. These include operational instrument factors such as anode tube type, current and voltage settings, the effect of protective films applied to prevent sample desiccation and also physical factors related to the sample itself such as surface topography, textural variation and water content. This paper examines the significance of these factors on recorded counts and hence allows an assessment of their impact on data integrity.

How many children and young people with life-limiting conditions are clinically unstable? A national data linkage study

Objective To determine the clinical stage (stable, unstable, deteriorating or dying) for children and young people (CYP) aged 0–25 years in Scotland with life-limiting conditions (LLCs). Design National cohort of CYP with LLCs using linked routinely collected healthcare data. Setting Scotland. Patients 20 436 CYP identified as having LLCs and resident in Scotland between 1 April 2009 and 31 March 2014. Main outcome Clinical stage based on emergency inpatient and intensive care unit admissions and date of death. Results Over 2200 CYP with LLCs in Scotland were unstable, deteriorating or dying in each year. Compared with 1-year-olds to 5-year-olds, children under 1 year of age had the highest risk of instability (OR 6.4, 95% CI 5.7 to 7.1); all older age groups had lower risk. Girls were more likely to be unstable than boys (OR 1.15, 95% CI 1.06 to 1.24). CYP of South Asian (OR 1.61, 95% CI 1.28 to 2.01), Black (OR 1.58, 95% CI 1.04 to 2.41) and Other (OR 1.33, 95% CI 1.02 to 1.74) ethnicity were more likely to experience instability than White CYP. Deprivation was not a significant predictor of instability. Compared with congenital abnormalities, CYP with most other primary diagnoses had a higher risk of instability; only CYP with a primary perinatal diagnosis had significantly lower risk (OR 0.23, 95% CI 0.19 to 0.29). Conclusions The large number of CYP with LLCs who are unstable, deteriorating or dying may benefit from input from specialist paediatric palliative care. The age group under 1 and CYP of South Asian, Black and Other ethnicities should be priority groups.

Comparison of the National Early Warning Score in non-elective medical and surgical patients

The National Early Warning Score (NEWS) is used to identify deteriorating patients in hospital. NEWS is a better discriminator of outcomes than other early warning scores in acute medical admissions, but it has not been evaluated in a surgical population. The study aims were to evaluate the ability of NEWS to discriminate cardiac arrest, death and unanticipated ICU admission in patients admitted to surgical specialties, and to compare the performance of NEWS in admissions to medical and surgical specialties.

Comparing routine inpatient data and death records as a means of identifying children and young people with life-limiting conditions:

Background: Recent estimates of the number of children and young people with life-limiting conditions derived from routine inpatient data are higher than earlier estimates using death record data. Aim: To compare routine inpatient data and death records as means of identifying life-limiting conditions in children and young people. Design: Two national cohorts of children and young people with a life-limiting condition (primary cohort from England with a comparator cohort from Scotland) were identified using linked routinely collected healthcare and administrative data. Participants: A total of 37,563 children and young people with a life-limiting condition in England who died between 1 April 2001 and 30 March 2015 and 2249 children and young people with a life-limiting condition in Scotland who died between 1 April 2003 and 30 March 2014. Results: In England, 16,642 (57%) non-neonatal cohort members had a life-limiting condition recorded as the underlying cause of death; 3364 (12%) had a life-limiting condition-related condition recorded as the underlying cause and 3435 (12%) had life-limiting conditions recorded only among contributing causes. In all, 5651 (19%) non-neonates and 3443 (41%) neonates had no indication of a life-limiting condition recorded in their death records. Similar results were seen in Scotland (overall, 16% had no indication of life-limiting conditions). In both cohorts, the recording of life-limiting condition was highest among those with haematology or oncology diagnoses and lowest for genitourinary and gastrointestinal diagnoses. Conclusion: Using death record data alone to identify children and young people with life-limiting condition – and therefore those who would require palliative care services – would underestimate the numbers. This underestimation varies by age, deprivation, ethnicity and diagnostic group.