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

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.

scholarly journals Clinical and scientific letters: The national early warning score gives misleading scores for oxygen saturation in patients at risk of hypercapnia

2015 ◽  
Vol 15 (1) ◽  
pp. 98.2-98 ◽  
Author(s):  
B Ronan O’Driscoll ◽  
Kirstie Grant ◽  
Darren Green ◽  
Simon Edeghere ◽  
Nawar Diar Bakerly ◽  
...  
Keyword(s):  
At Risk ◽  
Oxygen Saturation ◽  
Early Warning ◽  
Early Warning Score ◽  
Patients At Risk ◽  
National Early Warning Score

Can the prehospital National Early Warning Score 2 identify patients at risk of in-hospital early mortality? A prospective, multicenter cohort study

Heart & Lung ◽  
2020 ◽  
Vol 49 (5) ◽  
pp. 585-591 ◽  
Author(s):  
Francisco Martín-Rodríguez ◽  
Raúl López-Izquierdo ◽  
Carlos del Pozo Vegas ◽  
Irene Sánchez-Soberón ◽  
Juan F. Delgado-Benito ◽  
...  
Keyword(s):  
At Risk ◽  
Cohort Study ◽  
Early Warning ◽  
Early Mortality ◽  
Early Warning Score ◽  
Multicenter Cohort Study ◽  
Multicenter Cohort ◽  
Patients At Risk ◽  
National Early Warning Score

scholarly journals Examining the utility of the Hamilton early warning scores (HEWS) at triage: Retrospective pilot study in a Canadian emergency department

CJEM ◽  
2017 ◽  
Vol 20 (2) ◽  
pp. 266-274 ◽  
Author(s):  
Steven Skitch ◽  
Benjamin Tam ◽  
Michael Xu ◽  
Laura McInnis ◽  
Anthony Vu ◽  
...  
Keyword(s):  
At Risk ◽  
Emergency Department ◽  
Early Warning ◽  
Vital Signs ◽  
Roc Curves ◽  
Early Warning Score ◽  
Critical Event ◽  
Discriminative Ability ◽  
Early Warning Scores ◽  
Patients At Risk

ABSTRACTObjectivesEarly warning scores use vital signs to identify patients at risk of critical illness. The current study examines the Hamilton Early Warning Score (HEWS) at emergency department (ED) triage among patients who experienced a critical event during their hospitalization. HEWS was also evaluated as a predictor of sepsis.MethodsThe study population included admissions to two hospitals over a 6-month period. Cases experienced a critical event defined by unplanned intensive care unit admission, cardiopulmonary resuscitation, or death. Controls were randomly selected from the database in a 2-to-1 ratio to match cases on the burden of comorbid illness. Receiver operating characteristic (ROC) curves were used to evaluate HEWS as a predictor of the likelihood of critical deterioration and sepsis.ResultsThe sample included 845 patients, of whom 270 experienced a critical event; 89 patients were excluded because of missing vitals. An ROC analysis indicated that HEWS at ED triage had poor discriminative ability for predicting the likelihood of experiencing a critical event 0.62 (95% CI 0.58-0.66). HEWS had a fair discriminative ability for meeting criteria for sepsis 0.77 (95% CI 0.72-0.82) and good discriminative ability for predicting the occurrence of a critical event among septic patients 0.82 (95% CI 0.75-0.90).ConclusionThis study indicates that HEWS at ED triage has limited utility for identifying patients at risk of experiencing a critical event. However, HEWS may allow earlier identification of septic patients. Prospective studies are needed to further delineate the utility of the HEWS to identify septic patients in the ED.

Can the prehospital National Early Warning Score identify patients most at risk from subsequent deterioration?

2017 ◽  
Vol 34 (8) ◽  
pp. 533-537 ◽  
Author(s):  
Joanna Shaw ◽  
Rachael T Fothergill ◽  
Sophie Clark ◽  
Fionna Moore
Keyword(s):  
At Risk ◽  
Early Warning ◽  
Early Warning Score ◽  
National Early Warning Score

scholarly journals In-hospital Mortality and the Predictive Ability of the Modified Early Warning Score in Ghana: Single-Center, Retrospective Study (Preprint)

2020 ◽  
Author(s):  
Enoch Joseph Abbey ◽  
Jennifer S R Mammen ◽  
Samara E Soghoian ◽  
Maureen A F Cadorette ◽  
Promise Ariyo
Keyword(s):  
At Risk ◽  
Retrospective Study ◽  
Critically Ill ◽  
Teaching Hospital ◽  
Early Warning ◽  
Roc Curve ◽  
Predictive Ability ◽  
Early Warning Score ◽  
Risk Of Death ◽  
Medical Inpatients

BACKGROUND The modified early warning score (MEWS) is an objective measure of illness severity that promotes early recognition of clinical deterioration in critically ill patients. Its primary use is to facilitate faster intervention or increase the level of care. Despite its adoption in some African countries, MEWS is not standard of care in Ghana. In order to facilitate the use of such a tool, we assessed whether MEWS, or a combination of the more limited data that are routinely collected in current clinical practice, can be used predict to mortality among critically ill inpatients at the Korle-Bu Teaching Hospital in Accra, Ghana. OBJECTIVE The aim of this study was to identify the predictive ability of MEWS for medical inpatients at risk of mortality and its comparability to a measure combining routinely measured physiologic parameters (limited MEWS [LMEWS]). METHODS We conducted a retrospective study of medical inpatients, aged ≥13 years and admitted to the Korle-Bu Teaching Hospital from January 2017 to March 2019. Routine vital signs at 48 hours post admission were coded to obtain LMEWS values. The level of consciousness was imputed from medical records and combined with LMEWS to obtain the full MEWS value. A predictive model comparing mortality among patients with a significant MEWS value or LMEWS ≥4 versus a nonsignificant MEWS value or LMEWS <4 was designed using multiple logistic regression and internally validated for predictive accuracy, using the receiver operating characteristic (ROC) curve. RESULTS A total of 112 patients were included in the study. The adjusted odds of death comparing patients with a significant MEWS to patients with a nonsignificant MEWS was 6.33 (95% CI 1.96-20.48). Similarly, the adjusted odds of death comparing patients with a significant versus nonsignificant LMEWS value was 8.22 (95% CI 2.45-27.56). The ROC curve for each analysis had a C-statistic of 0.83 and 0.84, respectively. CONCLUSIONS LMEWS is a good predictor of mortality and comparable to MEWS. Adoption of LMEWS can be implemented now using currently available data to identify medical inpatients at risk of death in order to improve care.

scholarly journals The Admission Hamilton Early Warning Score (HEWS) Predicts the Risk of Critical Event during Hospitalization

2017 ◽  
Vol 11 (4) ◽  
Author(s):  
Benjamin Tam BHSc MD ◽  
Michael Xu BHSc ◽  
Michelle Kwong BHSc Cand. ◽  
Christine Wardell BHSc Cand. ◽  
Andrew Kwong BHSc Cand. ◽  
...  
Keyword(s):  
At Risk ◽  
High Risk ◽  
Early Warning ◽  
Early Warning Score ◽  
Surgical Patients ◽  
Critical Event ◽  
Critical Events ◽  
Patients At Risk ◽  
Icu Transfer ◽  
Very High

Background: Early warning scores detect patients at risk of deterioration in hospital. Our objective was to first, demonstrate that the admission Hamilton Early Warning Score (HEWS) predicts critical events and second, estimate the workload required to identify critical events during hospitalization.Methods: We prospectively identified a consecutive cohort of medical/surgical patients for retrospective review. Critical events were defined as a composite of inpatient death, cardio-pulmonary arrest or ICU transfer. Likelihood of a critical event during hospitalization and the number needed to evaluate to detect a critical event was based on highest admission HEWS.Results: We found 506 critical events occurred in 7130 cases. HEWS identified graduated levels of risk at admission. We found 2.6 and 1.8 patients needed to be evaluated in the ‘high-risk’ and very ‘high-risk’ subgroups to detect a critical event.Conclusions: HEWS identified patients at risk for critical events during hospitalization at ward admission. Few patients with high HEWS required evaluation to detect a critical event.

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