Showing papers on "Early warning score published in 2014"
TL;DR: The EWS itself is a simple and easy to use tool at the bedside, which may be of help in recognizing patients with potential for acute deterioration, and there was a trend towards reduction of these endpoints after introduction of the EWS.
334 citations
TL;DR: An accurate ward risk stratification tool using commonly collected electronic health record variables in a large multicenter dataset was developed and validated and was more accurate than the MEWS in the validation dataset for all outcomes.
Abstract: Rationale: Most ward risk scores were created using subjective opinion in individual hospitals and only use vital signs.Objectives: To develop and validate a risk score using commonly collected electronic health record data.Methods: All patients hospitalized on the wards in five hospitals were included in this observational cohort study. Discrete-time survival analysis was used to predict the combined outcome of cardiac arrest (CA), intensive care unit (ICU) transfer, or death on the wards. Laboratory results, vital signs, and demographics were used as predictor variables. The model was developed in the first 60% of the data at each hospital and then validated in the remaining 40%. The final model was compared with the Modified Early Warning Score (MEWS) using the area under the receiver operating characteristic curve and the net reclassification index (NRI).Measurements and Main Results: A total of 269,999 patient admissions were included, with 424 CAs, 13,188 ICU transfers, and 2,840 deaths occurring du...
193 citations
TL;DR: Rapid response system implementation reversed an increasing trend of critical deterioration, and hospitals seeking to measure rapid response system performance may consider using valid proximate outcomes like critical deterioration in addition to rare, catastrophic outcomes.
Abstract: Importance Rapid response systems aim to identify and rescue deteriorating hospitalized patients. Previous pediatric rapid response system implementation studies have shown variable effectiveness in preventing rare, catastrophic outcomes such as cardiac arrest and death. Objective To evaluate the impact of pediatric rapid response system implementation inclusive of a medical emergency team and an early warning score on critical deterioration, a proximate outcome defined as unplanned transfer to the intensive care unit with noninvasive or invasive mechanical ventilation or vasopressor infusion in the 12 hours after transfer. Design, Setting, and Participants Quasi-experimental study with interrupted time series analysis using piecewise regression. At an urban, tertiary care children’s hospital in the United States, we evaluated 1810 unplanned transfers from the general medical and surgical wards to the pediatric and neonatal intensive care units that occurred during 370 504 non–intensive care patient-days between July 1, 2007, and May 31, 2012. Interventions Implementation of a hospital-wide rapid response system inclusive of a medical emergency team and an early warning score in February 2010. Main Outcomes and Measures Rate of critical deterioration events, adjusted for season, ward, and case mix. Results Rapid response system implementation was associated with a significant downward change in the preintervention trajectory of critical deterioration and a 62% net decrease relative to the preintervention trend (adjusted incidence rate ratio = 0.38; 95% CI, 0.20-0.75). We observed absolute reductions in ward cardiac arrests (from 0.03 to 0.01 per 1000 non–intensive care patient-days) and deaths during ward emergencies (from 0.01 to 0.00 per 1000 non–intensive care patient-days), but these were not statistically significant (P = .21 andP = .99, respectively). Among all unplanned transfers, critical deterioration was associated with a 4.97-fold increased risk of death (95% CI, 3.33-7.40;P Conclusions and Relevance Rapid response system implementation reversed an increasing trend of critical deterioration. Cardiac arrest and death were extremely rare at baseline, and their reductions were not statistically significant despite using nearly 5 years of data. Hospitals seeking to measure rapid response system performance may consider using valid proximate outcomes like critical deterioration in addition to rare, catastrophic outcomes.
143 citations
TL;DR: An increased NEWS on arrival at ED is associated with higher odds of adverse outcome among patients with sepsis, and the use of NEWS could facilitate patient pathways to ensure triage to a high acuity area of the ED and senior clinician involvement at an early stage.
Abstract: Background An important element in improving the care of patients with sepsis is early identification and early intervention. Early warning score (EWS) systems allow earlier identification of physiological deterioration. A standardised national EWS (NEWS) has been proposed for use across the National Health Service in the UK. Aim To determine whether a single NEWS on emergency department (ED) arrival is a predictor of outcome, either in-hospital death within 30 days or intensive care unit (ICU) admission within 2 days, in patients with sepsis. Methods Data were collected over a 3-month period as part of a national audit in 20 EDs in Scotland. All adult patients who were admitted for at least 2 days or who died within 2 days were screened for sepsis criteria. Patients with systemic inflammatory response syndrome criteria were included. An EWS was calculated based on initial physiological observations made in the ED using the NEWS. Results Complete data were available for 2003 patients. Each rise in NEWS category was associated with an increased risk of mortality when compared to the lowest category (5–6: OR 1.95, 95% CI 1.21 to 3.14), (7–8: OR 2.26, 95% CI 1.42 to 3.61), (9–20: OR 5.64, 95% CI 3.70 to 8.60). This was also the case for the combined outcome (ICU and/or mortality). Conclusions An increased NEWS on arrival at ED is associated with higher odds of adverse outcome among patients with sepsis. The use of NEWS could facilitate patient pathways to ensure triage to a high acuity area of the ED and senior clinician involvement at an early stage.
125 citations
TL;DR: Compared the accuracy of MEWS against the Rothman Index (RI), a patient acuity score based upon summation of excess risk functions that utilize additional data from the electronic medical record (EMR), found the positive likelihood ratio (LR+) for MewS was 7.8, and for the RI was 16.9 with false alarms reduced by 53%.
Abstract: Early detection of an impending cardiac or pulmonary arrest is an important focus for hospitals trying to improve quality of care. Unfortunately, all current early warning systems suffer from high false-alarm rates. Most systems are based on the Modified Early Warning Score (MEWS); 4 of its 5 inputs are vital signs. The purpose of this study was to compare the accuracy of MEWS against the Rothman Index (RI), a patient acuity score based upon summation of excess risk functions that utilize additional data from the electronic medical record (EMR). MEWS and RI scores were computed retrospectively for 32,472 patient visits. Nursing assessments, a category of EMR inputs only used by the RI, showed sharp differences 24 hours before death. Receiver operating characteristic curves for 24-hour mortality demonstrated superior RI performance with c-statistics, 0.82 and 0.93, respectively. At the point where MEWS triggers an alarm, we identified the RI point corresponding to equal sensitivity and found the positive likelihood ratio (LR+) for MEWS was 7.8, and for the RI was 16.9 with false alarms reduced by 53%. At the RI point corresponding to equal LR+, the sensitivity for MEWS was 49% and 77% for RI, capturing 54% more of those patients who will die within 24 hours. Journal of Hospital Medicine 2014;9:116–119. 2013 The Authors. Journal of Hospital Medicine published by Wiley Periodicals, Inc. on behalf of Society of Hospital Medicine
105 citations
TL;DR: C-CHEWS has excellent discrimination to identify deterioration in children with cardiac disease and performed significantly better than PEWS both as an ordinal variable and when choosing cut points to maximize AUROC.
Abstract: Objective
Most inpatient pediatric arrests are preventable by early recognition/treatment of deterioration. Children with cardiac disease have the highest arrest rates; however, early warning scoring systems have not been validated in this population. The objective of this study was to validate the Cardiac Children's Hospital Early Warning Score (C-CHEWS) tool in inpatient pediatric cardiac patients. The associated escalation of care algorithm directs: routine care (score 0–2), increased assessment/intervention (3–4), or cardiac intensive care unit (CICU) consult/transfer (≥5).
Design
Sensitivity and specificity were estimated based on retrospective review of patients that experienced unplanned CICU transfer/arrest (n = 64) and a comparison sample (n = 248) of admissions. The previously validated Pediatric Early Warning Score (PEWS) tool was used for comparison. Patients' highest C-CHEWS scores were compared with calculated PEWS scores. Area under the receiver operating characteristic (AUROC) curve was calculated for PEWS and C-CHEWS to measure discrimination.
Results
The AUROC curve for C-CHEWS was 0.917 compared with PEWS 0.785 (P < .001). The algorithm AUROC curve was 0.902 vs. PEWS of 0.782. C-CHEWS algorithm sensitivity was 96.9 (score ≥ 2), 79.7 (≥4), and 67.2 (≥5) vs. PEWS of 81.1(≥2), 37.5 (≥4), and 23.4 (≥5). C-CHEWS specificity was 58.1 (≥2), 85.5 (≥4), and 93.6 (≥5) vs. PEWS of 81.1 (≥2), 94.8 (≥4) and 97.6 (≥5). Lead time of elevated C-CHEWS scores (≥2) was a median of 9.25 hours prior to event vs. PEWS, which was 2.25 hours and lead time for critical C-CHEWS scores (≥5) was 2 hours vs. 0 hours for PEWS (P < .001).
Conclusions
C-CHEWS has excellent discrimination to identify deterioration in children with cardiac disease and performed significantly better than PEWS both as an ordinal variable and when choosing cut points to maximize AUROC. C-CHEWS has a higher sensitivity than PEWS at all cut points.
61 citations
TL;DR: It is observed that a few predictors outperformed the whole set of variables in predicting MACE within 72 h and machine learning-based variable selection seems promising in discovering a few relevant and significant measures as predictors.
Abstract: The key aim of triage in chest pain patients is to identify those with high risk of adverse cardiac events as they require intensive monitoring and early intervention. In this study, we aim to discover the most relevant variables for risk prediction of major adverse cardiac events (MACE) using clinical signs and heart rate variability. A total of 702 chest pain patients at the Emergency Department (ED) of a tertiary hospital in Singapore were included in this study. The recruited patients were at least 30 years of age and who presented to the ED with a primary complaint of non-traumatic chest pain. The primary outcome was a composite of MACE such as death and cardiac arrest within 72 h of arrival at the ED. For each patient, eight clinical signs such as blood pressure and temperature were measured, and a 5-min ECG was recorded to derive heart rate variability parameters. A random forest-based novel method was developed to select the most relevant variables. A geometric distance-based machine learning scoring system was then implemented to derive a risk score from 0 to 100. Out of 702 patients, 29 (4.1%) met the primary outcome. We selected the 3 most relevant variables for predicting MACE, which were systolic blood pressure, the mean RR interval and the mean instantaneous heart rate. The scoring system with these 3 variables produced an area under the curve (AUC) of 0.812, and a cutoff score of 43 gave a sensitivity of 82.8% and specificity of 63.4%, while the scoring system with all the 23 variables had an AUC of 0.736, and a cutoff score of 49 gave a sensitivity of 72.4% and specificity of 63.0%. Conventional thrombolysis in myocardial infarction score and the modified early warning score achieved AUC values of 0.637 and 0.622, respectively. It is observed that a few predictors outperformed the whole set of variables in predicting MACE within 72 h. We conclude that more predictors do not necessarily guarantee better prediction results. Furthermore, machine learning-based variable selection seems promising in discovering a few relevant and significant measures as predictors.
61 citations
TL;DR: The efficiency of REMS was found to be superior to MEWS as a predictor of in-hospital mortality and hospitalisation in medical and surgical patients admitted to ED.
Abstract: Objective There are a few scoring systems in emergency departments (ED) to establish critically ill patients quickly and properly and to predict hospitalisation. We aim to compare the efficacy of Modified Early Warning Score (MEWS) and Rapid Emergency Medicine Score (REMS) on in-hospital mortality, and as predictor of hospitalisation in general medical and surgical patients admitted to ED. Methods This is a prospective, multicentre and observational cohort study. The study included general medical and surgical patients admitted to the EDs of three education and research hospitals during a period of 6 months. The primary outcome of the study is the admission of the patient to a ward/an intensive care unit (ICU)/high dependency unit (HDU) and in-hospital mortality. Receiver operating characteristics (ROC) curve analysis was performed to evaluate and compare the performances of two scores. Results Total patients were 2000 (51.95% male, 48.05% female). The mean age was 61.41±18.92. Median MEWS and REMS values of the patients admitted to the ICU/HDU from ED were 1 and 6, respectively; and there was a significant difference in terms of REMS values, compared with patients discharged from ED. REMS (area under the curve (AUC): 0.642) was found to have a better predictive strength than MEWS (AUC: 0.568) in discriminating in-patients and discharged patients. Additionally, REMS (0.707) was superior to MEWS (AUC 0.630) in terms of predicting in-hospital mortality of patients presenting to ED. Conclusions The efficiency of REMS was found to be superior to MEWS as a predictor of in-hospital mortality and hospitalisation in medical and surgical patients admitted to ED.
61 citations
TL;DR: Introducing the philosophy of pain as the fifth vital sign and making pain assessment more visible on the patient observation chart improved the uptake of pain assessment.
51 citations
TL;DR: Vital signs and MEWS determination three times daily, results in better detection of physiological abnormalities and more reliable activations of the RRT.
51 citations
TL;DR: The most widely used weighted track-and-trigger scores do not offer good predictive capabilities for use as criteria for an automated alarm system, and better criteria need to be developed and validated before implementation.
TL;DR: Poor compliance with the escalation protocol was commonly found when serious adverse events occurred but level of care provided by physicians was also a problem in a hospital with implemented early warning system.
TL;DR: ICU- and emergency room-based prediction scores can be used to prognosticate risk of clinical deterioration for non-ICU ward patients, and this performance is better than that of any SOFA scoring model based on a single set of physiologic variables.
Abstract: The rising prevalence of rapid response teams has led to a demand for risk-stratification tools that can estimate a ward patient’s risk of clinical deterioration and subsequent need for intensive care unit (ICU) admission. Finding such a risk-stratification tool is crucial for maximizing the utility of rapid response teams. This study compares the ability of nine risk prediction scores in detecting clinical deterioration among non-ICU ward patients. We also measured each score serially to characterize how these scores changed with time. In a retrospective nested case-control study, we calculated nine well-validated prediction scores for 328 cases and 328 matched controls. Our cohort included non-ICU ward patients admitted to the hospital with a diagnosis of infection, and cases were patients in this cohort who experienced clinical deterioration, defined as requiring a critical care consult, ICU admission, or death. We then compared each prediction score’s ability, over the course of 72 hours, to discriminate between cases and controls. At 0 to 12 hours before clinical deterioration, seven of the nine scores performed with acceptable discrimination: Sequential Organ Failure Assessment (SOFA) score area under the curve of 0.78, Predisposition/Infection/Response/Organ Dysfunction Score of 0.76, VitalPac Early Warning Score of 0.75, Simple Clinical Score of 0.74, Mortality in Emergency Department Sepsis of 0.74, Modified Early Warning Score of 0.73, Simplified Acute Physiology Score II of 0.73, Acute Physiology and Chronic Health Evaluation II of 0.72, and Rapid Emergency Medicine Score of 0.67. By measuring scores over time, it was found that average SOFA scores of cases increased as early as 24 to 48 hours prior to deterioration (P = 0.01). Finally, a clinical prediction rule which also accounted for the change in SOFA score was constructed and found to perform with a sensitivity of 75% and a specificity of 72%, and this performance is better than that of any SOFA scoring model based on a single set of physiologic variables. ICU- and emergency room-based prediction scores can also be used to prognosticate risk of clinical deterioration for non-ICU ward patients. In addition, scoring models that take advantage of a score’s change over time may have increased prognostic value over models that use only a single set of physiologic measurements.
TL;DR: The DT approach quickly provided an almost identical EWS to NEWS, although one that admittedly would benefit from fine-tuning using clinical knowledge, and could be used to quickly develop candidate models for disease-specific EWSs, which may be required in future.
TL;DR: CREWS is a simple variant of NEWS for patients with chronic hypoxaemia that could reduce clinically insignificant triggers and alarm fatigue, whilst still identifying the sickest patients.
TL;DR: The dichotomised activation criteria used at this institution and the recently published national early warning score were evaluated.
Abstract: BackgroundTo activate the hospital's medical emergency team (MET), either conventional dichotomised activation criteria or an early warning scoring system may be used. The relative performance of t ...
TL;DR: The proposed ensemble-based scoring system was compared with established scoring methods such as the modified early warning score and the thrombolysis in myocardial infarction score, and showed its effectiveness in predicting acute cardiac complications within 72 h in terms of the receiver operation characteristic analysis.
Abstract: Fast and accurate risk stratification is essential in the emergency department (ED) as it allows clinicians to identify chest pain patients who are at high risk of cardiac complications and require intensive monitoring and early intervention. In this paper, we present a novel intelligent scoring system using heart rate variability, 12-lead electrocardiogram (ECG), and vital signs where a hybrid sampling-based ensemble learning strategy is proposed to handle data imbalance. The experiments were conducted on a dataset consisting of 564 chest pain patients recruited at the ED of a tertiary hospital. The proposed ensemble-based scoring system was compared with established scoring methods such as the modified early warning score and the thrombolysis in myocardial infarction score, and showed its effectiveness in predicting acute cardiac complications within 72 h in terms of the receiver operation characteristic analysis.
TL;DR: Analysis of workflow variables surrounding calculation and documentation of one pediatric hospital's use of an early warning score indicated that there were significant delays in documentation of early warning scores by RNs and inconsistencies between theEarly warning scores and vital signs collected and documented by non-RN personnel.
Abstract: Early warning scores calculated by registered nurses (RNs) are used in hospitals to enhance the recognition of and communication about patient deterioration. This study evaluated workflow variables surrounding calculation and documentation of one pediatric hospital's use of an early warning score. Results indicated that there were significant delays in documentation of early warning scores by RNs and inconsistencies between the early warning scores and vital signs collected and documented by non-RN personnel. These findings reflected information obtained from the RNs about how they prioritize tasks and use work-arounds to specific systems issues regarding assessment and documentation in the electronic medical record.
TL;DR: The aim of this study is to directly compare published prediction tools with triage nurse (TN) predictions within a defined paediatric population.
Abstract: Aim The aim of this study is to directly compare published prediction tools with triage nurse (TN) predictions within a defined paediatric population. Method A prospective observational study carried out over a week in May 2010 in the Emergency Department (ED) at Princess Margaret Hospital for Children in Perth, Western Australia. TN predicted which patients would be admitted to hospital at the time of ED presentation. Data required for the other prediction tools (paediatric early warning score (PEWS); triage category and the Pediatric Risk of Admission Score (PRISA) and PRISA II were obtained from the notes following the patient's ED attendance. Results A total of 1223 patients presented during the study week, 91 patients were excluded and a total of 946 patients (83.6%) had TN predictions and were included in the analysis. TN predictions were compared against a PEWS ≥ 4, triage category 1, 2 and 3, PRISA ≥ 9 and PRISA II ≥ 2. TNs had the highest prediction accuracy (87.7%), followed by an elevated PEWS (82.9%), triage category of 1, 2, or 3 (82.9%). The PRISA and PRISA II score had an accuracy of 80.1% and 79.7%, respectively. Conclusion When compared with validated prediction tools, the TN is the most accurate predictor of need to admit. This study provides valuable information in planning efficient flow of patients through the ED.
TL;DR: 2 conceptual models of situation awareness in health care are presented and how proactive multimodal risk assessment might drive situation awareness is discussed.
Abstract: Health care systems, including acute care hospitals, have historically been designed to respond to, rather than predict and prevent, events. The move to a prevention-based health care system continues to mature in outpatient care, particularly around screening and chronic care management. The use of prediction and prevention is more limited in the acute care environment. This is the case despite growing evidence that failure to rescue from preventable deterioration and complications is associated with devastating outcomes.1,2 Clinical antecedents occur before most in-hospital cardiorespiratory arrests but may not be fully recognized or acted on.3 Interventions such as rapid response teams, early warning scores, and virtual monitoring target the quality of monitoring and the response taken when abnormalities are identified.
We believe that rapid response systems work to improve the situation awareness of the clinical teams and that situation awareness, with its focus on projection and prediction, provides a model for their further improvement. Situation awareness is achieved by (1) gathering information, (2) understanding that information in context, and (3) making short-term projections based on current state. A health care system that supports excellent clinician situation awareness would actively scan for risk across multiple domains (eg, proactively eliciting family concerns and using early warning scores to detect vital sign abnormalities). It would then couple these reliably with clear, expected actions.
A system that reliably identifies, mitigates, and escalates multiple categories of patient risk will likely result in safer and less costly care. We have begun to test a system to improve situation awareness and prevent unrecognized deterioration at our center.4 Herein, we present 2 conceptual models of situation awareness in health care and discuss how proactive multimodal risk assessment might drive situation awareness.
More than a decade ago, the Institute of Medicine challenged health care to learn …
TL;DR: Pediatric Early Warning Score is associated with the level of care at ED disposition but does not provide adequate sensitivity and specificity to be used in isolation, and performance characteristics are better for patients with respiratory complaints.
Abstract: ObjectiveThe objective of this study was to determine the association between the Pediatric Early Warning Score (PEWS) at time of emergency department (ED) disposition and level of care.MethodsWe conducted a prospective observational study with a convenience sample of patients aged 0 to 21 years in
TL;DR: In contrast to prior studies of patients based in the emergency department, ICU scores outperformed ED scores in critically ill patients admitted from theEmergency department, and this difference seemed to be primarily due to the complexity of the scores rather than the time window from which the data was derived.
Abstract: Multiple scoring systems have been developed for both the intensive care unit (ICU) and the emergency department (ED) to risk stratify patients and predict mortality. However, it remains unclear whether the additional data needed to compute ICU scores improves mortality prediction for critically ill patients compared to the simpler ED scores. We studied a prospective observational cohort of 227 critically ill patients admitted to the ICU directly from the ED at an academic, tertiary care medical center. We compared Acute Physiology and Chronic Health Evaluation (APACHE) II, APACHE III, Simplified Acute Physiology Score (SAPS) II, Modified Early Warning Score (MEWS), Rapid Emergency Medicine Score (REMS), Prince of Wales Emergency Department Score (PEDS), and a pre-hospital critical illness prediction score developed by Seymour et al. (JAMA 2010, 304(7):747–754). The primary endpoint was 60-day mortality. We compared the receiver operating characteristic (ROC) curves of the different scores and their calibration using the Hosmer-Lemeshow goodness-of-fit test and visual assessment. The ICU scores outperformed the ED scores with higher area under the curve (AUC) values (p = 0.01). There were no differences in discrimination among the ED-based scoring systems (AUC 0.698 to 0.742; p = 0.45) or among the ICU-based scoring systems (AUC 0.779 to 0.799; p = 0.60). With the exception of the Seymour score, the ED-based scoring systems did not discriminate as well as the best-performing ICU-based scoring system, APACHE III (p = 0.005 to 0.01 for comparison of ED scores to APACHE III). The Seymour score had a superior AUC to other ED scores and, despite a lower AUC than all the ICU scores, was not significantly different than APACHE III (p = 0.09). When data from the first 24 h in the ICU was used to calculate the ED scores, the AUC for the ED scores improved numerically, but this improvement was not statistically significant. All scores had acceptable calibration. In contrast to prior studies of patients based in the emergency department, ICU scores outperformed ED scores in critically ill patients admitted from the emergency department. This difference in performance seemed to be primarily due to the complexity of the scores rather than the time window from which the data was derived.
TL;DR: The Early Warning Scoring (EWS) surveillance system is used to identify deteriorating patients and enable appropriate staff to be called promptly and a lack of evidence that EWS surveillance systems lead to a reduction in severe morbidity.
Abstract: Background: The Early Warning Scoring (EWS) surveillance system is used to identify deteriorating patients and enable appropriate staff to be called promptly. However, there is a lack of evidence that EWS surveillance systems lead to a reduction in severe morbidity. Aims: To determine whether as EWS may have improved the detection of severe maternal morbidity or lessened the severity of illness among women with severe morbidity at a large tertiary maternity unit at Auckland City Hospital (ACH), New Zealand. Methods: Admissions to intensive care, cardiothoracic and vascular intensive care, or an obstetric high-dependency unit (HDU) were identified from clinical and hospital administrative databases. Case reviews and transcribed observation charts were presented to a multidisciplinary review group who, through group consensus, determined whether an EWS might have hastened recognition and/or escalation and effective treatment. Results: The multidisciplinary review team determined that an EWS might have reduced the seriousness of maternal morbidity in five cases (7.6%), including three admissions for obstetric sepsis to intensive care unit and two to obstetric HDU for post-partum haemorrhage. No patient had a complete set of respiratory rate, heart rate, blood pressure and temperature recordings at every time period. Conclusions: These findings have been used to support introduction of an EWS to the maternity unit at ACH.
TL;DR: The MEWS provides a useful scoring system for interpreting clinical deterioration and guiding intervention and exploration of the ability of the Cape Town MewS chart plus reporting algorithm to expedite recognition of signs of clinical and physiological deterioration and securing more skilled assistance is essential.
Abstract: Objectives
1) To explore the adequacy of: vital signs’ recordings (respiratory and heart rate, oxygen saturation, systolic blood pressure (BP), temperature, level of consciousness and urine output) in the first 8 post-operative hours; responses to clinical deterioration. 2) To identify factors associated with death on the ward between transfer from the theatre recovery suite and the seventh day after operation.
Design
Retrospective review of records of 11 patients who died plus four controls for each case.
Participants
We reviewed clinical records of 55 patients who met inclusion criteria (general anaesthetic, age >13, complete records) from six surgical wards in a teaching hospital between 1 May and 31 July 2009.
Methods
In the absence of guidelines for routine post-operative vital signs’ monitoring, nurses’ standard practice graphical plots of recordings were recoded into MEWS formats (0 = normal, 1–3 upper or lower limit) and their responses to clinical deterioration were interpreted using MEWS reporting algorithms.
Results
No patients’ records contained recordings for all seven parameters displayed on the MEWS. There was no evidence of response to: 22/36 (61.1%) abnormal vital signs for patients who died that would have triggered an escalated MEWS reporting algorithm; 81/87 (93.1%) for controls. Death was associated with age, ≥61 years (OR 14.2, 3.0–68.0); ≥2 pre-existing co-morbidities (OR 75.3, 3.7–1527.4); high/low systolic BP on admission (OR 7.2, 1.5–34.2); tachycardia (≥111–129 bpm) (OR 6.6, 1.4–30.0) and low systolic BP (≤81–100 mmHg), as defined by the MEWS (OR 8.0, 1.9–33.1).
Conclusions
Guidelines for post-operative vital signs’ monitoring and reporting need to be established. The MEWS provides a useful scoring system for interpreting clinical deterioration and guiding intervention. Exploration of the ability of the Cape Town MEWS chart plus reporting algorithm to expedite recognition of signs of clinical and physiological deterioration and securing more skilled assistance is essential.
TL;DR: The prognostic value of the ViewS-L score in terms of discrimination was better than that of TRISS in the blunt trauma patients admitted to the emergency department with an injury severity score of 9 or higher, and the ViEWS- L score showed good calibration.
Abstract: OBJECTIVE: The aim of this study was to compare the predictive value of the VitalPAC Early Warning Score-lactate (ViEWS-L) score with that of the trauma and injury severity score (TRISS), which is a pre-existing risk scoring system used in trauma patients. METHODS: The patients were blunt trauma victims admitted consecutively to the study hospital between 1 April 2010 and 31 March 2011, who were 15 years or older and had an injury severity score of 9 or higher. The lactate level, the ViEWS and revised trauma score upon arrival at the emergency department, and the injury severity score and TRISS were evaluated. The ViEWS-L score was calculated according to the formula: ViEWS-L=ViEWS+lactate (mmol/l). The ability to predict mortality was assessed by area under the receiver operating characteristic curve (AUC) analysis and calibration analysis. RESULTS: A total of 299 patients were available for analysis, of whom 33 died (11.0%). The median ViEWS-L score was 3.7 (interquartile range:1.8-6.4) and the median TRISS was 96.8 (interquartile range: 93.4-98.6). The ViEWS-L score was better than TRISS at predicting hospital mortality (AUC, 0.838; 95% confidence interval, 0.771-0.906 vs. AUC, 0.734; 95% confidence interval, 0.635-0.833, P=0.031). Calibration of the ViEWS-L score (χ=11.13, P=0.194) was good but that of TRISS was not (χ=16.97, P=0.018). CONCLUSION: The prognostic value of the ViEWS-L score in terms of discrimination was better than that of TRISS in the blunt trauma patients admitted to the emergency department with an injury severity score of 9 or higher, and the ViEWS-L score showed good calibration. Language: en
TL;DR: This process improvement project aimed to improve the early identification of clinically deteriorating hematology-oncology patients in order to prevent the development of critical illness and to facilitate timely intensive care unit (ICU) transfers.
Abstract: This process improvement project aimed to improve the early identification of clinically deteriorating hematology-oncology patients in order to prevent the development of critical illness and to facilitate timely intensive care unit (ICU) transfers. Using failure modes and effects analysis, a protocol employing the Modified Early Warning Score and serum lactate level was implemented to identify deteriorating patients who required the attention of the rapid response team. Control charts revealed a significant decrease in codes and preventable codes, while ICU transfers remained stable. A retrospective analysis to control for age, sex, race, severity of illness, and do not resuscitate status was performed, yielding a codes odds ratio of 0.51 (95% confidence interval = 0.31-0.85) and a preventable codes odds ratio of 0.25 (95% confidence interval = 0.07-0.82). At the study team's institution, implementation of this protocol reduced codes and preventable codes without an associated increase in ICU transfers.
TL;DR: The authors' experiences whilst implementing NEWS across one large inner London NHS Trust and one of the challenges was the Trust's geographical location over three sites.
Abstract: In 2012, The Royal College of Physicians (RCP) developed a National Early Warning Score (NEWS) as a standardised approach to assessment and response to critical illness. This paper reports the authors' experiences whilst implementing NEWS across one large inner London NHS Trust. NEWS was introduced to all adult areas between November 2013 and January 2014. All healthcare staff completed the RCP's online e-learning module and received scenario-based teaching. One of the challenges was the Trust's geographical location over three sites. Comparisons across all sites will be made over time as data become available. Introducing NEWS has been a challenging but exciting initiative.
TL;DR: In this article, the Modified Early Warning Score (MEWS) was used to predict ICU transfer for patients with severe sepsis or septic shock admitted to general wards.
Abstract: Purpose To assess whether the Modified Early Warning Score (MEWS) predicts the need for intensive care unit (ICU) transfer for patients with severe sepsis or septic shock admitted to general wards Methods A retrospective chart review of 100 general ward patients with severe sepsis or septic shock was implemented Clinical information and MEWS according to point of time between ICU group and general ward group were reviewed Data were analyzed using multivariate logistic regression and the area under the receiver operating characteristic curves with SPSS/WIN 180 program Results Thirty-eight ICU patients and sixty-two general ward patients were included In multivariate logistic regression, MEWS (odds ratio [OR] 202, 95% confidence interval [CI] 143-285), lactic acid (OR 183, 95% CI 122-273) and diastolic blood pressure (OR 089, 95% CI 080-100) were predictive of ICU transfer The sensitivity and the specificity of MEWS used with cut-off value of six were 895% and 677% for ICU transfer Conclusion MEWS is an effective predictor of ICU transfer A clinical algorithm could be created to respond to high MEWS and intervene with appropriate changes in clinical management
TL;DR: Alarm fatigue and clinical judgement of staff might result in deviation from escalation protocols, and wards that had more patients with a NEWS>=6 had lower escalation rates.
Abstract: Background Early Warning Scores alert staff to preventable deterioration. Raised scores should lead to escalation of care. Aims To establish response of staff to patients scoring National Early Warning Score (NEWS) of six or above and to identify patient and environmental factors affecting escalation by nursing staff. Methods Service evaluation with prospective review of patient records of 118 beds on four medical wards during 20 night-shifts. Results During 2360 observed bed days 109 patients triggered NEWS>=6 at least once during the observation period. Nursing staff escalated only 18 (17%) of these patients; nearly all of them had predefined chronic health conditions, the majority fulfilled criteria for frailty. Despite their higher 30-day mortality patients with COPD had lower escalation rates. Additionally wards that had more patients with a NEWS>=6 had lower escalation rates. Conclusion Alarm fatigue and clinical judgement of staff might result in deviation from escalation protocols.
TL;DR: AbEWS cannot be used to detect those patients who do not need to be admitted to hospital or are suitable for discharge, and a period of observation of at least 12h is required before the trajectory of AbEWS is of prognostic value.