Modified Early Warning System Research Articles

Analysis of Relevant Predictive Indicators for Postoperative Condition Change in Brain Tumor Patients.

Novice nurse need more guidance and professional confidence. This study aimed to explore early relevant predictive indicators for postoperative condition changes in brain tumor patients, which can be used to map patients' condition changes for novice nurses. The authors prospectively collected clinical data, including nursing records of cerebral tumor patients after operation from July 2020 to June 2021 in the Department of Neurosurgery. Univariant analysis and multivariable logistic regression analysis were performed to identify independent predictors, the satisfaction questionnaire for teaching nurses is used to evaluate the new nurse's performance during perioperative period, psychometric scale is used to assess nurses' psychological stress. Nine hundred ninety-five cerebral tumor patients were enrolled in this study, and 115 (11.6%) patients' conditions were changed. Relevant predictive indicators, including vision, myodynamia, urine volume, nausea, vomit, pain, Glasgow Coma Scale (GCS), and Modified Early Warning System (MEWS), among them GCS, MEWS, and vision can basically cover the above indicators through simulation and calculation of the integrated model was set as Z=22*vision+1*GCS+3*MEWS. The satisfaction rate of teaching nurses has increased from 78.125 to 86.25%. Novice nurses' psychological stress was dropped from 30.637% to 19.844%. GCS and MEWS. GCS, MEWS and vision can map patients' condition change after cerebral tumor operation. The warning model has reduced their psychological stress, and the teaching nurse expressed that the effective evaluation of postoperative patient conditions by novice nurses reduces their nursing and teaching work greatly.

Predictors of massive transfusion protocols activation in patients with trauma in Korea: a systematic review.

Massive transfusion protocols (MTPs) implementation improves clinical outcomes of the patient's resuscitation with hemorrhagic trauma. Various predictive scoring system have been used and studied worldwide to improve clinical decision. However, such research has not yet been studied in Korea. This systematic review aimed to assess the predictors of MTPs activation in patients with trauma in Korea. The PubMed, Embase, Cochrane Library, Research Information Sharing Service databases, KoreaMed, and KMbase were searched from November 2022. All studies conducted in Korea that utilized predictors of MTPs activation in adult patients with trauma were included. Ten articles were eligible for analysis, and the predictors were assessed. Clinical assessments such as systolic and diastolic blood pressure, shock index (SI), prehospital modified SI, modified early warning system (MEWS) and reverse SI multiplied by the Glasgow Coma Scale (rSIG) were used. Laboratory values such as lactate level, fibrinogen degradation product/fibrinogen ratio, and rotational thromboelastometry (ROTEM) were used. Imaging examinations such as pelvic bleeding score were used as predictors of MTPs activation. Our systematic review identified predictors of MTPs activation in patients with trauma in Korea; predictions were performed using tools that requires clinical assessments, laboratory values or imaging examinations only. Among them, ROTEM, rSIG, MEWS, SI, and lactate level showed good effects for predictions of MTPs activation. The application of predictors for MTP's activation should be individualized based on hospital resource and skill set, also should be performed as a clinical decision supporting tools.

Effectiveness of Implementing Modified Early Warning System and Rapid Response Team for General Ward Inpatients.

This retrospective study assessed the effectiveness and impact of implementing a Modified Early Warning System (MEWS) and Rapid Response Team (RRT) for inpatients admitted to the general ward (GW) of a medical center. This study included all inpatients who stayed in GWs from Jan. 2017 to Feb. 2022. We divided inpatients into GWnon-MEWS and GWMEWS groups according to MEWS and RRT implementation in Aug. 2019. The primary outcome, unexpected deterioration, was defined by unplanned admission to intensive care units. We defined the detection performance and effectiveness of MEWS according to if a warning occurred within 24 h before the unplanned ICU admission. There were 129,039 inpatients included in this study, comprising 58,106 GWnon-MEWS and 71,023 GWMEWS. The numbers of inpatients who underwent an unplanned ICU admission in GWnon-MEWS and GWMEWS were 488 (.84%) and 468 (.66%), respectively, indicating that the implementation significantly reduced unexpected deterioration (p < .0001). Besides, 1,551,525 times MEWS assessments were executed for the GWMEWS. The sensitivity, specificity, positive predicted value, and negative predicted value of the MEWS were 29.9%, 98.7%, 7.09%, and 99.76%, respectively. A total of 1,568 warning signs accurately occurred within the 24 h before an unplanned ICU admission. Among them, 428 (27.3%) met the criteria for automatically calling RRT, and 1,140 signs necessitated the nursing staff to decide if they needed to call RRT. Implementing MEWS and RRT increases nursing staff's monitoring and interventions and reduces unplanned ICU admissions.

Clinical decision support tools useful for identifying sepsis risk.

Evaluate the effectiveness of the clinical decision support tools (CDSTs), POC Advisor (POCA), and Modified Early Warning System (MEWS) in identifying sepsis risk and influencing time to treatment for inpatients, comparing their respective alert mechanisms. This study was conducted at two academic university medical center hospitals. Data from adult inpatients in medical-surgical and telemetry units were analyzed from January 1, 2020, to December 31, 2020. Criteria included sepsis-related ICD-10 codes, antibiotic administration, and ordered sepsis labs. Subsequent statistical analyses utilized Fisher's exact test and Wilcoxon Rank Sum test, focusing on mortality differences by age, sex, and race/ethnicity. Among 744 patients, 143 sepsis events were identified, with 83% already receiving treatment upon CDST alert. Group 1 (POCA alert) showed reduced response time compared with MEWS, while Group 3 (MEWS) experienced longer time to treatment. Group 4 included sepsis events missed by both systems. Mortality differences were not significant among the groups. While CDSTs play a role, nursing assessment and clinical judgment are crucial. This study recognized the potential for alarm fatigue due to a high number of CDST-driven alerts, while emphasizing the importance of a collaborative approach for prompt sepsis treatment and potential reduction in sepsis-related mortality.

Clinical Study of a New Modified Early Warning Scoring System for Rapidly Evaluating Shock in Adults.

Shock is one of the most common severe syndromes requiring emergency treatment. Acute myocardial infarction guidelines, the surviving sepsis campaign, and low blood volume resuscitation guidelines indicate the prioritization ofearly identification of shock. APACHE II(Acute Physiology and Chronic Health Evaluation II), SOFA (Sequential Organ Failure Assessment), and MEWS (Modified Early Warning System) scores are used to predict mortality in ICU (intensive care unit) patients. However, similar to APACHE II, SOFA cannot be used forrapid assessment. Hence the need for a new scoring system that is simple, faster, and efficacious in predicting and preventing mortality among shock patients. The present study was conducted to evaluate a new MEWS scoring system for early identification and estimate mortality risk in patients with shock. A total of 170 patients with shock meeting the inclusion criteria who presented to the ICU of Ramaiah Hospitals from November 2019 to August 2021 were included in the study. Baseline variables, laboratory parameters, APACHE II score, SOFA score, MEWS score, and new MEWS score were compared between the two groups. Patients were followed up till mortality or discharge from ICU. Among the 170 patients included in the studyseptic shock (69.4%) was the most common type of shock followed by cardiogenic(7.64%) and hypovolemic shock (7.64%). The requirement of inotropic support and mechanical ventilation was associated with significantly higher mortality (55.6% and 52.6% respectively). The AUROC (area under the curve) for SOFA in predicting mortality was 0.738 (p<0.001). The AUROCfor APACHE II score in predicting mortality was 0.758 (p<0.001). The AUROC for MEWS score in predicting mortality was 0.655 (p=0.0002). The AUROC for the new MEWS score in predicting mortality was 0.684 which is more than that of the conventional MEWS score (p <0.001). New MEWS score is better than the MEWS score in predicting mortality. The new MEWS score is a simple, entirely clinical, inexpensive scoring system that can be done within a short time as a patient contact in an emergency. Hence, the new MEWS score can help in the quick identification of patients who are at high risk for developing shock and can be used as a better predictor of mortality.

The Latest Research Progress in the Application of MEWS Scoring System in Clinical Nursing

This paper summarizes the background of the formation of the Modified Early Warning System (MEWS) evaluation system, its current status of clinical teaching applications in different fields of hospitals, and its significance on the medical and nursing career, aiming to provide specific theoretical basis for medical staff and lay a foundation for continuing to carry out related work on MEWS.

Evaluation of Three Clinical Prediction Tools to Predict Mortality in Hospitalized Patients with Lassa Fever.

Lassa fever is a viral hemorrhagic illness with a case fatality rate for hospitalized patients as high as 69%. Identifying cases before they progress to serious illness can lead to earlier treatment and improved clinical outcomes. Three existing clinical prediction tools were evaluated on their ability to predict the in-hospital mortality in Lassa fever: the quick Sequential Organ Failure Assessment (qSOFA), the Modified Early Warning System (MEWS), and the Universal Vital Assessment (UVA). This was a retrospective cohort study of patients admitted to the dedicated Lassa fever ward of the Kenema Government Hospital in Sierra Leone between May 2013 and December 2019. Data among three serology groups were analyzed: Lassa antigen-positive (Ag+) regardless of IgM status, Lassa Ag- and IgM+, and Lassa Ag- and IgM- cases. There were 123 cases of suspected Lassa fever included in this study. Abnormalities in respiratory rate, oxygenation status, mental status, and serum markers of kidney and liver dysfunction were more likely seen in the Ag+ group, which had an in-hospital mortality of 85.7%. For the Lassa Ag+ group, the sensitivity and positive predictive value of qSOFA ≥ 2 was 70.6% and 92.3%, MEWS ≥ 5 was 96.9% and 86.1%, and UVA ≥ 5 was 60.0% and 100.0%. The MEWS and UVA scores show potential for use in Lassa fever, but there is opportunity for future development of a tool that includes the clinical and laboratory markers specific to Lassa fever.

Updates in Sepsis Management Show Thoughtful Approach

Updates in Sepsis Management Show Thoughtful Approach

Sepsis scoring systems and use of the Sepsis six care bundle in maternity hospitals

BackgroundThis study aimed to assess the predictive power of three different Sepsis Scoring Systems (SSSs), namely maternity Systematic Inflammatory Response Syndrome (mSIRS), quick Sepsis-related Organ Failure Assessment (qSOFA) and Modified Early Warning System (MEWS) in identifying sepsis by comparing them with positive culture. This study also sought to evaluate compliance with using the Sepsis Six Care Bundle (SSCB) operated in an individual health board.MethodsA retrospective cohort study was conducted in 3 maternity hospitals of a single Scottish health board that admitted 2690 pregnancies in a 12 weeks period in 2016. Data for study was obtained from medical notes, handheld and electronic health records for women who were prescribed antibiotics with a confirmed or suspected diagnosis of sepsis. Data on clinical parameters was used to classify women according to mSIRS, qSOFA and MEWS as having sepsis or not and this was compared to results of positive culture to obtain sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and area under Receiver Operating Characteristic curve (AUROC) along with their 95% confidence intervals. Data was also obtained on SSCB compliance.ResultsA total of 89 women were diagnosed with sepsis, of which 14 had missing data, leaving 75 for final analysis. Sensitivity, specificity, PPV, NPV and AUROC of mSIRS and MEWS were almost similar with AUROC of both being around 50%. Only 33 (37.1%) had identifiable sepsis six sticker displayed on medical notes and only 2 (2.2%) had all elements of SSCB delivered within the recommended one-hour post-diagnosis period. Blood culture and full blood count with other lab tests had been performed for most women (97%) followed by intravenous antibiotics and fluids (93.9%).ConclusionsmSIRS and MEWS were quite similar in detecting sepsis when compared to positive culture, with their ability to detect sepsis being close to chance. This underlines the need for creating a valid SSS with high sensitivity and specificity for clinical use in obstetric settings. Clinical use of SSCB was limited despite it being a health board policy, although there is considerable possibility of improvement following detailed audits and removal of barriers for implementing SSCB.

Low daily MEWS scores as predictors of low-risk hospitalized patients.

The Modified Early Warning System (MEWS) is a well-validated tool used by hospitals to identify patients at high risk for an adverse event to occur. However, there has been little evaluation into whether a low MEWS score can be predictive of patients with a low likelihood of an adverse event. The present study aims to evaluate the MEWS score as a method of identifying patients at low risk for adverse events. Retrospective cohort study of 5676 patient days and analysis of associated MEWS scores, medical comorbidities and adverse events. The primary outcome was the association of average daily MEWS scores in those who had an adverse event compared with those who did not. Those with an average MEWS score of >2 were over 9 times more likely to have an adverse event compared with those with an average MEWS score of 1-2, and over 15 times more likely to have an adverse event compared to those with an average MEWS score of <1. Our study shows that those with average daily MEWS scores <2 are at a significantly lower likelihood of having an adverse event compared with a score of >2, deeming them 'low-risk patients'. Formal recognition of such patients can have major implications in a hospital setting, including more efficient resource allocation in hospitals and better patient satisfaction and safety by adjusting patient monitoring according to their individual risk profile.

A Validation Study of Maternal Early Warning Systems: A Retrospective Cohort Study.

We compare validation characteristics of four early warning systems for maternal morbidity. We used a retrospective cohort of severe maternal morbidity cases between January 2016 and December 2016 compared with a cohort of controls. We determined if the modified early obstetric warning score (MEOWS), maternal early recognition criteria (MERC), modified early warning system (MEWS), or maternal early warning trigger (MEWT) would have alerted. We developed criteria to determine which of these alerts was considered clinically "relevant." We reviewed 79 morbidity cases and 123 controls. MEOWS and MERC were more sensitive than MEWS or MEWT (67.1 and 67.1% vs. 19% and 40.5%, p < 0.001); however, MEWT and MEWS were more specific (88.6% MEWT and 93.5% MEWS vs. 51.2% MEOWS and 60.2% MERC, p < 0.001). In the control population, 70% of MEWT alerts still appeared "relevant" to the clinical scenario in contrast to the MEOWS (32%) or MERC systems (31%). There are limited comparative data regarding how early warning systems perform in an American population for maternal morbidity. None of the systems performs with high sensitivity and specificity. High-volume, high-acuity units may decide that the lower sensitivity of the MEWT is relatively acceptable when considering the high false trigger rate of the other more sensitive systems. In addition, triggers in the MEWT system were more likely to be clinically relevant even in cases that did not have severe morbidity.

Effectiveness of Competency Training Program on Modified Early Warning System (MEWS) upon the Knowledge of Nurses in Selected Hospitals, Chennai

Effectiveness of Competency Training Program on Modified Early Warning System (MEWS) upon the Knowledge of Nurses in Selected Hospitals, Chennai

Effectiveness of Competency Training Program on Modified Early Warning System (MEWS) upon the Knowledge of Nurses in Selected Hospitals, Chennai

Background: Adverse events results in unintended harm to the patients including permanent disability and death. MEWS was introduced to identify and document the deteriorating patients in hospital settings. Adequate training and education of nurses will enhance early recognition and response in preventing adverse events. Objective: The objective of the study was to assess the effectiveness of competency training program on MEWS among nurses. Methodology: A Quasi experimental study was conducted among nurses who were working in inpatient units of selected hospitals, Chennai. 140 nurses were selected as participants out of which (n=70) is constituted to experimental group and (n=70) was constituted to control group. Pre-test knowledge was assessed in both groups. Competency training program on MEWS was given to experimental group of nurses and post test was assessed after one month. Results: The mean post-test knowledge scores was significantly higher in experimental group (M=18.2) to that of control group (M=10.6) which shows the effectiveness of competency training program on MEWS with (t=22.29, p&lt;0.001). Conclusion: The present study reveals that Competency training program on MEWS had a significant increase in the knowledge of nurses in the experimental group.

177 Predictive Value of SEPSIS-3 Criteria in the Emergency Department

In 2016 the Sepsis-3 Task Force proposed the quick Sequential Organ Failure Assessment (qSOFA) score to predict adverse outcomes in patients with a suspected infection in non-intensive care unit (ICU) settings. We aimed to compare the qSOFA to previous used scoring systems including the Systemic Inflammatory Response Syndrome (SIRS) criteria, Modified Early Warning System (MEWS) and National Early Warning Score (NEWS) for the prediction of adverse outcomes in patients admitted to the emergency department (ED) with a suspected or proven systemic infection. It was a prospective Dutch multicenter observational study performed at 4 large EDs. All patients ≥ 18 years presenting a suspected or proven systemic infection were included between November 2016 and February 2018. At ED arrival the vital signs and laboratory tests were recorded. Follow-up time was 30 days. The qSOFA, SIRS, MEWS and NEWS were calculated and receiver operating characteristics analysis was performed to determine the predictive value for adverse outcomes (ie, ICU admission, 30-day mortality and the composite outcome of ICU admission or 30-day mortality). A total of 1228 patients were included in the study, aged 63 (± 18.0) years and 592 (48.2%) were woman. Of the included patients, 59 (4.9%) were admitted to the ICU and 55 (4.5%) died within 30 days of admission. From those, 15 were previously admitted to the ICU (composite outcome of 8.1% of the patients). For ICU admission, the qSOFA had the lowest area under the curve (AUC) compared to other scorings systems (AUC 0.69 versus AUC > 0.73, P <0.001). The most accurate predictor of mortality at 30-days was NEWS with AUC = 0.75 (p<0.001). The AUC of qSOFA was qSOFA AUC = 0.69 (<0.001). The composite outcome was better predicted by NEWS with a AUC = 0.77 (P<.001) and again poorly by the other scoring systems (qSOFA = 0.69, P<0.001). The pairwise comparisons for composite outcome and 30-day mortality between qSOFA versus NEWS were statistically significant (P <0.008). Compared with the other scoring systems, qSOFA had the lowest sensitivity (18.2%) in predicting 30-day mortality in patients with (suspected) infection at the ED (sensitivity > 61%). Optimal cutoff values for predicting 30-day mortality were found for qSOFA ≥1 (sensitivity 69%, specificity of 66%), SIRS ≥2 (sensitivity 76%, specificity of 44%), MEWS ≥2 (sensitivity 86%, specificity 41%) and NEWS ≥5 (sensitivity 78%, specificity 66%). Due to its low sensitivity, qSOFA is not a proper bedside tool to predict adverse outcomes in the ED. For patients presenting to the ED with suspected or proven infection NEWS provides the most accurate tool for predicting adverse outcomes with an optimal cutoff value of NEWS ≥5.

Clinical Early Warning Scores: New Clinical Tools in Evolution

Clinical Early Warning Scores are tools intended to alert clinical staff to possible future clinical deterioration, often related to the onset of sepsis. Since their introduction, they have increased greatly in popularity. Their operation is conceptually simple: an elevated early warning score triggers a formal assessment by the responsible clinician. While the best-known system is the Royal College of Physicians National Early Warning Score (NEWS), a number of other scores are in use, such as an adaptation known as the Modified Early Warning System (MEWS) or warning systems for pediatric patients (PEWS). However, while promising, such instruments need to be studied in more detail to better characterize their eventual role in monitoring hospital patients. In particular, a central question concerns the identification of the best system (NEWS, MEWS, PEWS etc.) for a given clinical population (pediatric, trauma, prehospital etc.).

886: A validation study of maternal early warning systems

We aim to compare validation characteristics for four proposed early warning systems for maternal morbidity. This is a retrospective cohort of cases of severe maternal morbidity (SMM) identified by CDC ICD9 codes between 1/2016-12/2016. We determined if the modified early obstetric warning score (MEOWS), maternal early recognition criteria (MERC), modified early warning system (MEWS) or maternal early warning tool (MEWT) would have alerted in each morbidity case. Controls (deliveries without CDC defined morbidity) within the same year were also evaluated to determine if the same systems would have alerted. We reviewed 88 morbidity cases and 124 controls. MEOWS and MERC were significantly more sensitive than MEWS or MEWT, however MEWT and MEWS were significantly more specific. MEWT had the highest positive predictive value for SMM: 80.7% (figure 1). 27% of SMM cases required greater than four units of packed red blood cells (pRBCs) and 78% of SMM cases received any transfusion. The sensitivity and specificity of the tools to predict cases that required > 4 units pRBCs (n=21) varied: MEOWS (90%, 53%), MERC (86%, 60%), MEWS (48%, 94%) and MEWT (76%, 91%) (p=.001, p<.001). MEWT requires repeating abnormal values over 20 minutes. This improved tool specificity for all SMM cases from 69% to 91%, however also decreased sensitivity from 81% to 58% (figure 2). Evidence from maternal mortality surveillance in California suggests 41% of maternal deaths had a “good to strong” chance of being preventable, and 90% had “some” chance. Delayed response to clinical warning signs was the most common contributing factor identified in these cases. Early warning systems have been proposed however there is limited validation for the proposed systems. Validating systems to CDC defined morbidity provides a more generalizable and commonly used metric. Additionally, alarm fatigue is a concerning characteristic of any system. Implementation of a system may be expensive and time consuming and current validation data in an urban US based population is valuable for obstetric units deciding which, if any system to implement. We confirm that repeating values over a period of time is an important component of the MEWT as it significantly improves tool specificity.View Large Image Figure ViewerDownload Hi-res image Download (PPT)

A fuzzy logic-based warning system for patients classification.

Typically acute deterioration in sick people is preceded by subtle changes in the physiological parameters such as pulse and blood pressure. The Modified Early Warning Score is a scoring system developed to assist hospital staff in gauging these physiological changes and identifying patients in need of urgent medical care to avoid catastrophic deterioration. This work discusses the design and implementation of an equivalent warning system that utilizes fuzzy logic techniques to categorize patients' status. The system is implemented and tested in Rashid Centre for Diabetes and Research in UAE. Results are compared with those obtained using the Modified Early Warning System that is currently used in practice. We demonstrate that the implemented system provides reliable results that are in agreement with the current Modified Early Warning Score system, with the added benefit of a scoring scheme that provides a better insight into the status or medical condition of each patient.

Abstract 11192: Correlation of the Predictive Ability of Early Warning Metrics and Mortality for Cardiac Arrest Patients Receiving in-Hospital Cardiopulmonary Resuscitation

Introduction: The Modified Early Warning System (MEWS) is a tool to help monitor patients and improve how quickly a patient experiencing a sudden decline in clinical status receives clinical care. Hypothesis/Aims: We assessed the risk factors that may be associated with hospital survival following cardiopulmonary resuscitation (CPR) in response to cardiac arrest (CA). In this study, we also examined the role of Modified Early Warning Score (MEWS) implementation on patients’ survival. Methods: Retrospective chart review of all patients who were treated with CPR after experiencing in-hospital CA (n=417) was conducted between January 2007 and December 2013, at a tertiary care hospital in the New York metropolitan area. The investigators determined survival rate for these patients and evaluated their MEWS on admission and during the 4 hours preceding the CA. Multivariable logistic regression was used to adjust for possible confounding factors. Specifically, we analyzed the relationship between MEWS and risk factors such as age, gender, type of electrographic cardiac rhythms, return of spontaneous circulation (ROSC) and MEWS using logistic regression. Results: Only 60% of the patient charts reviewed (256/417), indicated a return of spontaneous circulation (ROSC) following CPR. The overall survival rate, defined as survival to hospital discharge, was 21%. Strong predictors for survival were ventricular fibrillation (VF) (p&lt;.0001) and ventricular tachycardia (VT) rhythm (p&lt;.0001). MEWS values at hospital admission (p&lt;.005) and patients of younger age (p&lt;.005) were also significantly associated with survival to hospital discharge. In contrast, gender and MEWS prior to CA were not significantly associated with survival. Conclusions: Survival following CPR in response to in-hospital cardiac arrest is significantly associated with VF and VT rhythms and age. Moreover, MEWS at admission was significantly associated with survival, suggesting that higher MEWS scores at admission may be an important predictor of survival. MEWS monitoring may be an effective tool in identifying significant changes in a patient’s vital signs prior CA.

Clinical study of a new Modified Early Warning System scoring system for rapidly evaluating shock in adults

ObjectiveShock, the most common severe emergency syndrome, has a complicated etiopathogenesis, is difficult to identify, progresses quickly, and is dangerous. Early identification and intervention play determining roles in the final outcomes of shock patients, but no specific scoring system for shock has been established to date. MethodsWe collected 292 shock patients and analyzed the correlation between 28-day prognosis and the Acute Physiologic Assessment and Chronic Health Evaluation II (APACHE II), Modified Early Warning System (MEWS), and Sequential Organ Failure Assessment scoring systems. According to the previous result, we established a new MEWS scoring system based on the conventional MEWS, which also included age and transcutaneous oxygen saturation. Some of the items with a strong correlation with the 28-day prognosis were selected to establish the new MEWS scoring system. We then evaluated the predictive efficacy of the new MEWS scoring system on 28-day prognosis and the correlation with other scoring systems. ResultsSome indexes, including age, transcutaneous oxygen saturation, arterial blood pH and blood lactic acid, serum sodium, serum potassium, HCO3, and red blood cells deposited, differed significantly between the nonsurviving and surviving groups (P<.05). The area under the curve (AUC) of the APACHE II, MEWS, shock index, and Sequential Organ Failure Assessment scoring systems for 28-day prognosis indicated a critical predictive efficacy. Receiver operating characteristic curves indicated that the MEWS AUC was 0.614, new MEWS AUC was 0.696, and APACHE II AUC was 0.785, suggesting superiority of the new MEWS to the conventional MEWS but inferiority to the APACHE II. Interestingly, the correlation efficient of the traditional MEWS and the new MEWS was 0.81. The correlation efficient of these scoring systems with other indexes, including lactic acid and hemoglobin, was less than 0.3. ConclusionsThe new MEWS scoring system could be an independent indicator to reflect shock severity. It has higher predictive efficacy in septic shock, especially for 28-day prognosis.

Validation of the Intensive Care Unit Early Warning Dashboard: Quality Improvement Utilizing a Retrospective Case-Control Evaluation.

Risk stratification with the Modified Early Warning System (MEWS) or electronic cardiac arrest trigger (eCART) has been utilized with ward patients to preemptively identify high-risk patients who might benefit from enhanced monitoring, including early intensive care unit (ICU) transfer. In-hospital mortality from cardiac arrest is ∼80%, making preventative interventions an important focus area. ICUs have lower patient to nurse ratios than wards, resulting in less emphasis on the development of ICU early warning systems. Our institution developed an early warning dashboard (EWD) identifying patients who may benefit from earlier interventions. Using the adverse outcomes of cardiac arrest, ICU mortality, and ICU readmissions, a retrospective case-control study was performed using three demographic items (age, diabetes, and morbid obesity) and 24 EWD measured items, including vital signs, laboratory values, ventilator information, and other clinical information, to validate the EWD. Ten statistically significant areas were identified for cardiac arrest and 13 for ICU death. Identified items included heart rate, dialysis, leukocytosis, and lactate. The ICU readmission outcome was compared to controls from both ICU patients and ward patients, and statistical significance was identified for respiratory rate >30. With several statistically significant data elements, the EWD parameters have been incorporated into advanced clinical decision algorithms to identify at-risk ICU patients. Earlier identification and treatment of organ failure in the ICU improve outcomes and the EWD can serve as a safety measure for both at-risk in-house patients and also extend critical care expertise through telemedicine to smaller hospitals.