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Journal articles on the topic 'Modified early warning score (MEWS)'

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Published: 4 June 2021

Last updated: 1 February 2022

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Blumenthal, Elizabeth A., Nina Hooshvar, Miriam McQuade, and Jennifer McNulty. "A Validation Study of Maternal Early Warning Systems: A Retrospective Cohort Study." American Journal of Perinatology 36, no. 11 (2019): 1106–14. http://dx.doi.org/10.1055/s-0039-1681097.

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Objective We compare validation characteristics of four early warning systems for maternal morbidity. Study Design 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.” Results 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%). Conclusion 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.

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Aygun, Huseyin, Suna Eraybar, Fatma Ozdemir, and Erol Armagan. "Predictive Value of Modified Early Warning Scoring System for Identifying Critical Patients with Malignancy in Emergency Department." Archives of Iranian Medicine 23, no. 8 (2020): 536–41. http://dx.doi.org/10.34172/aim.2020.56.

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Background: Identification of critically ill patient is particularly important in the emergency department (ED). The prolonged duration from hospital admission to delivering intensive care service is related to increased mortality. The aim of this study is to evaluate the effectiveness of Modified Early Warning Score (MEWS) for identifying critical patients with malignancy in ED settings. Methods: We evaluated patients with malignancy who were admitted to our ED of a tertiary university hospital in Turkey over a three-month period. We evaluated MEWS on admission as MEWS 1. After the initial treatment depending on the patients’ health status in ED, at 2 hours after admission, we evaluated MEWS again and recorded as MEWS 2. All patients were followed up for 30 days after the initial admission. Results: Mean age (SD) was 59.2 (13.5) and male/female ratio was 295/206. MEWS1 was higher than MEWS2, (MEWS1: 3.05 ± 3.31, MEWS2: 2.35 ± 3.17, P < 0.001). A total of 362 patients (72.3%) survived and 139 (27.7%) died within 30 days of initial admission. MEWS1/MEWS2 values for alive and dead patients were 1.66/0.87, and 6.67/6.21, respectively, and the difference was significant (P < 0.001). ROC analysis was performed for MEWS 1; the area under curve (AUC) for hospitalization was 0.768 (95% CI 0.729 to 0.804) and for mortality was 0.900 (95% CI 0.870 to 0.924). ROC analysis revealed a cut-off value of 2 for predicting both hospitalization and mortality in these patients. The sensitivity of the presented cut-off was 77.32% (72.1%–82.0%) for hospitalization and 76.24% (95% CI 71.5–80.5) for mortality; the specificity was 69.52 (95% CI 62.8–75.7) for hospitalization and 90.65 (95% CI 84.65–94.9) for mortality. Conclusion: We found in our study that MEWS evaluation for patients with malignancy on admission to ED is predictive of mortality in the subsequent 30 days, and it is a valuable tool for identifying the critical group. Also, AVPU scores alone can predict mortality in patients admitted to ED.

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Jiang, Xiaobin. "An improved modified early warning score that incorporates the abdomen score for identifying multiple traumatic injury severity." PeerJ 8 (October 27, 2020): e10242. http://dx.doi.org/10.7717/peerj.10242.

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Background Rapid identification of trauma severity is essential for the timely triage of multiple trauma patients. Tools such as the modified early warning score (MEWS) are used for determining injury severity. Although the conventional MEWS is a good predictor of mortality, its performance assessing injury severity is moderate. This study hypothesized that adding an injury site severity-related score (e.g., abdomen score) may enhance the capability of the MEWS for identifying severe trauma. Method To validate the hypothesis, we propose an improved modified early warning score called MEWS-A, which incorporates an injury site-specific severity-related abdomen score to MEWS. The utility of MEWS and MEWS-A were retrospectively evaluated and compared for identifying trauma severity in adult multiple trauma patients admitted to the emergency department. Results We included 1,230 eligible multiple trauma patients and divided them into minor and severe trauma groups based on the injury severity score. Results of logistic regression and receiver operating characteristic (ROC) curve analyses showed that the MEWS-A had a higher area under the ROC curve (AUC: 0.81 95% CI [0.78–0.83]) than did the MEWS (AUC: 0.77 95% CI [0.74–0.79]), indicating that the MEWS-A is superior to the MEWS in identifying severe trauma. The optimal MEWS-A cut-off score is 4, with a specificity of 0.93 and a sensitivity of 0.54. MEWS-A ≥ 4 can be used as a protocol for decision-making in the emergency department. Conclusions Our study suggests that while the conventional MEWS is sufficient for predicting mortality risk, adding an injury site-specific score (e.g., abdomen score) can enhance its performance in determining injury severity in multiple trauma patients.

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Khan, Amena, Digvijoy Sarma, Chiranth Gowda, and Gabriel Rodrigues. "The Role of Modified Early Warning Score (MEWS) in the Prognosis of Acute Pancreatitis." Oman Medical Journal 36, no. 3 (2021): e272-e272. http://dx.doi.org/10.5001/omj.2021.72.

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Objectives: Modified Early Warning Score (MEWS) is a reliable, safe, instant, and inexpensive score for prognosticating patients with acute pancreatitis (AP) due to its ability to reflect ongoing changes of the systemic inflammatory response syndrome associated with AP. Our study sought to determine an optimal MEWS value in predicting severity in AP and determine its accuracy in doing so. Methods: Patients diagnosed with AP and admitted to a single institution were analyzed to determine the value of MEWS in identifying severe AP (SAP). The highest MEWS (hMEWS) score for the day and the mean of all the scores of a given day (mMEWS) were determined for each day. Sensitivity, specificity, negative predictive value (NPV), and positive predictive values (PPV) were calculated for the optimal MEWS values obtained. Results: Two hundred patients were included in the study. The data suggested that an hMEWS value > 2 on day one is most accurate in predicting SAP, with a specificity of 90.8% and PPV of 83.3%. An mMEWS of > 1.2 on day two was the most accurate in predicting SAP, with a sensitivity of 81.2%, specificity of 76.6%, PPV of 69.8%, and NPV of 85.9%. These were found to be more accurate than previous studies. Conclusions: MEWS provides a novel, easy, instant, repeatable, and reliable prognostic score that is comparable, if not superior, to existing scoring systems. However, its true value may lie in its use in resource-limited settings such as primary health care centers.

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Somasundaram, Umesh Raj, and Esakki Santhiyagappan. "A tertiary care centre experience of modified early warning score (MEWS) in post-operative patients." International Surgery Journal 5, no. 11 (2018): 3536. http://dx.doi.org/10.18203/2349-2902.isj20184618.

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Background: The aim of the study is to analyse and implement the modified early warning score (MEWS) in assessment of need of early intervention and surgical intensive care unit (SICU) admission in patients undergoing elective and emergency major surgical procedures.Methods: This prospective study was done in Coimbatore Medical College and Hospital, Coimbatore, Tamil Nadu. It included 150 patients who underwent major emergency and elective surgical procedures under regional or general anaesthesia with monitoring of physiological parameters in the P.O period.Results: The predictability of MEWS system was analyzed with the following results: MEWS 1=77 patients were alive (51.3%) of the study population. MEWS 8=3 patients were alive (2.1%) and 7 patients died (100%) of the study population. This indicates that the greater MEWS the mortality of the patient rises, and the lesser MEWS score the chances of mortality in the P.O period is very minimal. In our study, we have derived that MEWS score of 7 or 8 implicates the need for SICU admission and it indicates an increased mortality of the patient in the P.O period.Conclusions: The Modified Early Warning Score (MEWS) is an effective tool in identifying the early deterioration of the patients undergoing major surgical procedures and assessing the need for admission in SICU for further interventions.

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Montenegro, Sayane Marlla Silva Leite, and Carlos Henrique Miranda. "Evaluation of the performance of the modified early warning score in a Brazilian public hospital." Revista Brasileira de Enfermagem 72, no. 6 (2019): 1428–34. http://dx.doi.org/10.1590/0034-7167-2017-0537.

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ABSTRACT Objective: To evaluate the performance of the modified early warning score (Mews) in a nursing ward for patients in clinical deterioration. Method: This is an analytical, quantitative and predictive study. Mews’ parameters (systolic blood pressure, heart rate, respiratory rate, temperature and level of consciousness) were evaluated every six hours. The following events were reported: death, cardiopulmonary arrest and transfer to intensive care. The evaluations were performed in a hospital of reference in the state of São Paulo, Brazil. Results: A total of 300 patients were included (57 ± 18 years old, males: 65%). There number of combined events was observed to be greater the higher the score’s value (00%; 00%; 01; 09%; 19%; 28%; 89%, respectively, for Mews 0; 1; 2; 3; 4; 5 and 6; p < 0.0001). Mews ≥ 4 was the most appropriate cut-off point for prediction of these events (sensitivity: 87%, specificity: 85% and accuracy: 0.86). Conclusion: Mews properly measured the occurrence of severe events in hospitalized patients of a Brazilian public hospital’s nursing ward. Mews ≥ 4 seems to be the most appropriate cut-off point for prediction of these events.

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Mussa, Constance, and Afnan Al-Raimi. "2495 Respiratory therapists’ awareness and intention to use the electronic modified early warning score (eMEWS)." Journal of Clinical and Translational Science 2, S1 (2018): 60. http://dx.doi.org/10.1017/cts.2018.224.

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OBJECTIVES/SPECIFIC AIMS: To determine if an educational intervention designed to increase respiratory therapists’ knowledge of the modified early warning score (MEWS) would influence their intention to use the MEWS. METHODS/STUDY POPULATION: A web-based self-administered survey based on the constructs of the TAM as well as awareness, attitude, and job-relevance was developed and validated using traditional scale development process and distributed to 75 respiratory therapists (RTs) from the respiratory care department of Rush University Medical Center. RTs were recruited for participation in the study using consecutive sampling. The RTs were then given a training session on the MEWS after which they were again asked to complete the survey. RESULTS/ANTICIPATED RESULTS: The response rate to both the pre and post survey was 60 percent. Of the 46 participants recruited to the study, the educational intervention elicited an increase in the MEWS knowledge score in 45 participants compared with the knowledge score prior to the educational intervention. Additionally, there was an increase in the behavioral intention score post intervention in 30 participants compared with the behavioral intention score before the educational intervention. A Wilcoxon signed-rank test determined that there was a statistically significant median increase in MEWS knowledge score (2.0) post educational intervention (4.0) compared with pre-educational intervention (2.0), p<0.0005. There was also a statistically significant median increase in behavioral intention score (0.667) pre-educational intervention (4.0) compared with posteducational intervention (3.0), p<0.0005. DISCUSSION/SIGNIFICANCE OF IMPACT: Numerous studies over the last 4 decades have demonstrated that change in behavioral intention is a good predictor of change in behavior. Consequently, the increase in the respiratory therapists’ behavioral intention score post MEWS education suggests that they may be more inclined to incorporate the MEWS score in their assessment of patients if they are educated about its clinical relevance. Additionally, the study results verified key postulates of the TAM, suggesting that the TAM is an appropriate model for assessing respiratory therapists’ perception and reaction to new systems, and may also help respiratory care managers develop new mechanisms that facilitate respiratory therapists’ adoption of new systems and processes.

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Colombo, Fabrizio, Lucia Taurino, Giulia Colombo, et al. "The Niguarda MEWS, a new and refined tool to determine criticality and instability in Internal Medicine Ward and Emergency Medicine Unit." Italian Journal of Medicine 11, no. 3 (2017): 310. http://dx.doi.org/10.4081/itjm.2017.826.

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This study compares the effect of the modified early warning score (MEWS) <em>versus</em> a new early warning system (Niguarda MEWS) for detecting instability and criticality in hospital medical departments. A retrospective observational study was conducted in the Internal Medicine ward of Niguarda Ca’ Granda Hospital in Milan between November 2013 and October 2014. MEWS and Niguarda-MEWS were gathered using: systolic blood pressure, respiratory frequency, heart rate, temperature, level of consciousness, oxygen saturation, creatinine level, hematocrit level and age. In order to determine if the patient was critical or not the MEWS criticality cut-off value chosen was 3, while in the Niguarda MEWS it was 6. The primary outcome was the correlation between the critical level of the two scores and in-hospital mortality. The secondary endpoint was the correlation between a specific disease and the two scores. In the study, 471 patients were included, using both the MEWS and the Niguarda MEWS score at admittance: 33.4% of patients turned out to be critically ill using the former, 40.98% when using the latter. Therefore, the specificity of scores was 70% for MEWS and 73% for Niguarda MEWS, the sensitivity 58% for MEWS and 63% for Niguarda MEWS, Niguarda MEWS area under the curve (AUC): 0.736, MEWS AUC: 0.670. For the secondary outcome, the new score is higher for genitourinary and respiratory diseases. Niguarda-MEWS could be an optimal tool to detect criticality and instability in order to address the patient to the right level of care.

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Gardner-Thorpe, J., N. Love, J. Wrightson, S. Walsh, and N. Keeling. "The Value of Modified Early Warning Score (MEWS) in Surgical In-Patients: A Prospective Observational Study." Annals of The Royal College of Surgeons of England 88, no. 6 (2006): 571–75. http://dx.doi.org/10.1308/003588406x130615.

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INTRODUCTION The Modified Early Warning Score (MEWS) is a simple, physiological score that may allow improvement in the quality and safety of management provided to surgical ward patients. The primary purpose is to prevent delay in intervention or transfer of critically ill patients. PATIENTS AND METHODS A total of 334 consecutive ward patients were prospectively studied. MEWS were recorded on all patients and the primary end-point was transfer to ITU or HDU. RESULTS Fifty-seven (17%) ward patients triggered the call-out algorithm by scoring four or more on MEWS. Emergency patients were more likely to trigger the system than elective patients. Sixteen (5% of the total) patients were admitted to the ITU or HDU. MEWS with a threshold of four or more was 75% sensitive and 83% specific for patients who required transfer to ITU or HDU. CONCLUSIONS The MEWS in association with a call-out algorithm is a useful and appropriate risk-management tool that should be implemented for all surgical in-patients.

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Aligawesa, Mariam, and Di Marks-Maran. "Meeting physical health needs: The Modified Early Warning Score (MEWS) project." British Journal of Mental Health Nursing 6, no. 2 (2017): 73–80. http://dx.doi.org/10.12968/bjmh.2017.6.2.73.

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Kim, Dong-Ki, Dong-Hun Lee, Byung-Kook Lee, et al. "Performance of Modified Early Warning Score (MEWS) for Predicting In-Hospital Mortality in Traumatic Brain Injury Patients." Journal of Clinical Medicine 10, no. 9 (2021): 1915. http://dx.doi.org/10.3390/jcm10091915.

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The present study aimed to analyze and compare the prognostic performances of the Revised Trauma Score (RTS), Injury Severity Score (ISS), Shock Index (SI), and Modified Early Warning Score (MEWS) for in-hospital mortality in patients with traumatic brain injury (TBI). This retrospective observational study included severe trauma patients with TBI who visited the emergency department between January 2018 and December 2020. TBI was considered when the Abbreviated Injury Scale was 3 or higher. The primary outcome was in-hospital mortality. In total, 1108 patients were included, and the in-hospital mortality was 183 patients (16.3% of the cohort). Receiver operating characteristic curve analyses were performed for the ISS, RTS, SI, and MEWS with respect to the prediction of in-hospital mortality. The area under the curves (AUCs) of the ISS, RTS, SI, and MEWS were 0.638 (95% confidence interval (CI), 0.603–0.672), 0.742 (95% CI, 0.709–0.772), 0.524 (95% CI, 0.489–0.560), and 0.799 (95% CI, 0.769–0.827), respectively. The AUC of MEWS was significantly different from the AUCs of ISS, RTS, and SI. In multivariate analysis, age (odds ratio (OR), 1.012; 95% CI, 1.000–1.023), the ISS (OR, 1.040; 95% CI, 1.013–1.069), the Glasgow Coma Scale (GCS) score (OR, 0.793; 95% CI, 0.761–0.826), and body temperature (BT) (OR, 0.465; 95% CI, 0.329–0.655) were independently associated with in-hospital mortality after adjustment for confounders. In the present study, the MEWS showed fair performance for predicting in-hospital mortality in patients with TBI. The GCS score and BT seemed to have a significant role in the discrimination ability of the MEWS. The MEWS may be a useful tool for predicting in-hospital mortality in patients with TBI.

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Pong, Jeremy Zhenwen, Stephanie Fook-Chong, Zhi Xiong Koh, et al. "Combining Heart Rate Variability with Disease Severity Score Variables for Mortality Risk Stratification in Septic Patients Presenting at the Emergency Department." International Journal of Environmental Research and Public Health 16, no. 10 (2019): 1725. http://dx.doi.org/10.3390/ijerph16101725.

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The emergency department (ED) serves as the first point of hospital contact for many septic patients, where risk-stratification would be invaluable. We devised a combination model incorporating demographic, clinical, and heart rate variability (HRV) parameters, alongside individual variables of the Sequential Organ Failure Assessment (SOFA), Acute Physiology and Chronic Health Evaluation II (APACHE II), and Mortality in Emergency Department Sepsis (MEDS) scores for mortality risk-stratification. ED patients fulfilling systemic inflammatory response syndrome criteria were recruited. National Early Warning Score (NEWS), Modified Early Warning Score (MEWS), quick SOFA (qSOFA), SOFA, APACHE II, and MEDS scores were calculated. For the prediction of 30-day in-hospital mortality, combination model performed with an area under the receiver operating characteristic curve of 0.91 (95% confidence interval (CI): 0.88–0.95), outperforming NEWS (0.70, 95% CI: 0.63–0.77), MEWS (0.61, 95% CI 0.53–0.69), qSOFA (0.70, 95% CI 0.63–0.77), SOFA (0.74, 95% CI: 0.67–0.80), APACHE II (0.76, 95% CI: 0.69–0.82), and MEDS scores (0.86, 95% CI: 0.81–0.90). The combination model had an optimal sensitivity and specificity of 91.4% (95% CI: 81.6–96.5%) and 77.9% (95% CI: 72.6–82.4%), respectively. A combination model incorporating clinical, HRV, and disease severity score variables showed superior predictive ability for the mortality risk-stratification of septic patients presenting at the ED.

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Adebusoye, L. A., M. O. Owolabi, and A. Ogunniyi. "Biomarkers, shock index and modified early warning score among older medical hospital inpatients in Nigeria." South African Family Practice 61, no. 3 (2019): 78. http://dx.doi.org/10.4102/safp.v61i3.4964.

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Background: Biomarkers, shock index and modified early warning score (MEWS) are of public health importance because identification and prompt attention to them have been found to reduce mortality among older patients on admission.Objectives: A study was undertaken to determine the biomarkers, shock index and MEWS that predict mortality on admission among older medical hospital inpatients.Methods: This was a prospective study of 450 patients (≥ 60 years) on the medical wards of University College Hospital, Ibadan. Biomarkers recommended by the National Institute on Aging such as blood pressure, heart rate and pulse rate (cardiovascular functioning); cholesterol and triglycerides (metabolic processes); T-cell counts (immune system status) and weight, body mass index and waist-to-hip ratio (indicators of obesity, chronic metabolic disorders and fat deposits) were assessed. Vital signs were recorded on admission and used to calculate the shock index and MEWS. Multivariate and survival analyses were carried out at p 0.05.Results: Baseline temperature ≥ 39.0°c (p = 0.049), pulse rate ≥ 100 beats/minute (p = 0.034), systolic blood pressure (SBP) 120 mmHg (p = 0.048), shock index ≥1.0 (p = 0.041), age shock index (p = 0.032) and critical illness score (MEWS ≥5) p = 0.019 were significantly associated with mortality. Independent predictors of mortality on Cox regression analysis were temperature ≥ 39.0°C (HR = 3.317 [1.281–8.590]) and SBP 120 mmHg (HR = 1.845 [1.025–3.322]).Conclusion: Prompt identification and management of fever and low blood pressure should improve the survival of older medical hospital inpatients.

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Stark, Alexander P., Robert C. Maciel, William Sheppard, Greg Sacks, and O. Joe Hines. "An Early Warning Score Predicts Risk of Death after In-hospital Cardiopulmonary Arrest in Surgical Patients." American Surgeon 81, no. 10 (2015): 916–21. http://dx.doi.org/10.1177/000313481508101001.

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In-hospital cardiopulmonary arrest can contribute significantly to publicly reported mortality rates. Systems to improve mortality are being implemented across all specialties. A review was conducted for all surgical patients >18 years of age who experienced a “Code Blue” event between January 1, 2013 and March 9, 2014 at a university hospital. A previously validated Modified Early Warning Score (MEWS) using routine vital signs and neurologic status was calculated at regular intervals preceding the event. In 62 patients, the most common causes of arrest included respiratory failure, arrhythmia, sepsis, hemorrhage, and airway obstruction, but remained unknown in 27 per cent of cases. A total of 56.5 per cent of patients died before hospital discharge. In-hospital death was associated with American Society of Anesthesiologists status ( P = 0.039) and acute versus elective admission ( P = 0.003). Increasing MEWS on admission, 24 hours before the event, the event-day, and a maximum MEWS score on the day of the event increased the odds of death. Max MEWS remained associated with death after multivariate analysis (odds ratio 1.39, P = 0.025). Simple and easy to implement warning scores such as MEWS can identify surgical patients at risk of death after arrest. Such recognition may provide an opportunity for clinical intervention resulting in improved patient outcomes and hospital mortality rates.

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Bunkenborg, Gitte, Ingrid Poulsen, Karin Samuelson, Steen Ladelund, and Jonas Akeson. "Bedside vital parameters that indicate early deterioration." International Journal of Health Care Quality Assurance 32, no. 1 (2019): 262–72. http://dx.doi.org/10.1108/ijhcqa-10-2017-0206.

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Purpose The purpose of this paper is to determine associations between initially recorded deviations in individual bedside vital parameters that contribute to total Modified Early Warning Score (MEWS) levels 2 or 3 and further clinical deterioration (MEWS level=4). Design/methodology/approach This was a prospective study in which 27,504 vital parameter values, corresponding to a total MEWS level⩾2, belonging to 1,315 adult medical and surgical inpatient patients admitted to a 90-bed study setting at a university hospital, were subjected to binary logistic and COX regression analyses to determine associations between vital parameter values initially corresponding to total MEWS levels 2 or 3 and later deterioration to total MEWS level ⩾4, and to evaluate corresponding time intervals. Findings Respiratory rate, heart rate and patient age were significantly (p=0.012, p<0.001 and p=0.028, respectively) associated with further deterioration from a total MEWS level 2, and the heart rate also (p=0.009) from a total MEWS level 3. Within 24 h from the initially recorded total MEWS levels 2 or 3, 8 and 17 percent of patients, respectively, deteriorated to a total MEWS level=4. Patients initially scoring MEWS 2 had a 27 percent 30-day mortality rate if they later scored MEWS level=4, and 8.7 percent if they did not. Practical implications It is important to observe all patients closely, but especially elderly patients, if total MEWS levels 2 or 3 are tachypnoea and/or tachycardia related. Originality/value Findings might contribute to patient safety by facilitating appropriate clinical and organizational decisions on adequate time spans for early warning scoring in general ward patients.

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Wykes, Benjamin, Syed Ahmed, Sacha Dubois, et al. "Implementation of the Modified Early Warning Score (MEWS) in a Community Hospital." Chest 148, no. 4 (2015): 485A. http://dx.doi.org/10.1378/chest.2280079.

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Abbey, Enoch Joseph, Jennifer S. R. Mammen, Samara E. Soghoian, Maureen A. F. Cadorette, and Promise Ariyo. "In-hospital Mortality and the Predictive Ability of the Modified Early Warning Score in Ghana: Single-Center, Retrospective Study." JMIRx Med 2, no. 3 (2021): e24645. http://dx.doi.org/10.2196/24645.

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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.

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Xie, Xiaohua, Wenlong Huang, Qiongling Liu, et al. "Prognostic value of Modified Early Warning Score generated in a Chinese emergency department: a prospective cohort study." BMJ Open 8, no. 12 (2018): e024120. http://dx.doi.org/10.1136/bmjopen-2018-024120.

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ObjectivesThis study aimed to validate the performance of the Modified Early Warning Score (MEWS) in a Chinese emergency department and to determine the best cut-off value for in-hospital mortality prediction.DesignA prospective, single-centred observational cohort study.SettingThis study was conducted at a tertiary hospital in South China.ParticipantsA total of 383 patients aged 18 years or older who presented to the emergency department from 17 May 2017 through 27 September 2017, triaged as category 1, 2 or 3, were enrolled.OutcomesThe primary outcome was a composite of in-hospital mortality and admission to the intensive care unit. The secondary outcome was using MEWS to predict hospitalised and discharged patients.ResultsA total of 383 patients were included in this study. In-hospital mortality was 13.6% (52/383), and transfer to the intensive care unit was 21.7% (83/383). The area under the receiver operating characteristic curve of MEWS for in-hospital mortality prediction was 0.83 (95% CI 0.786 to 0.881). When predicting in-hospital mortality with the cut-off point defined as 3.5, 158 patients had MEWS >3.5, with a specificity of 66%, a sensitivity of 87%, an accuracy of 69%, a positive predictive value of 28% and a negative predictive value of 97%, respectively.ConclusionOur findings support the use of MEWS for in-hospital mortality prediction in patients who were triaged category 1, 2 or 3 in a Chinese emergency department. The cut-off value for in-hospital mortality prediction defined in this study was different from that seen in many other studies.

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Chang, Su-Han, Chiao-Hsuan Hsieh, Yi-Ming Weng, et al. "Performance Assessment of the Mortality in Emergency Department Sepsis Score, Modified Early Warning Score, Rapid Emergency Medicine Score, and Rapid Acute Physiology Score in Predicting Survival Outcomes of Adult Renal Abscess Patients in the Emergency Department." BioMed Research International 2018 (September 19, 2018): 1–8. http://dx.doi.org/10.1155/2018/6983568.

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Background. Renal abscess is a relatively uncommon yet debilitating and potentially fatal disease. There is no clearly defined, objective risk stratification tool available for emergency physicians’ and surgeons’ use in the emergency department (ED) to quickly determine the appropriate management strategy for these patients, despite early intervention having a beneficial impact on survival outcomes. Objective. This case control study evaluates the performance of Mortality in Emergency Department Sepsis Score (MEDS), Modified Early Warning Score (MEWS), Rapid Emergency Medicine Score (REMS), and Rapid Acute Physiology Score (RAPS) in predicting risk of mortality in ED adult patients with renal abscess. This will help emergency physicians, surgeons, and intensivists expedite the time-sensitive decision-making process. Methods. Data from 152 adult patients admitted to the EDs of two training and research hospitals who had undergone a contrast-enhanced computed tomography scan of the abdomen and was diagnosed with renal abscess from January 2011 to December 2015 were analyzed, with the corresponding MEDS, MEWS, REMS, RAPS, and mortality risks calculated. Ability to predict patient mortality was assessed via receiver operating curve analysis and calibration analysis. Results. MEDS was found to be the best performing physiologic scoring system, with sensitivity, specificity, and accuracy of 87.50%, 88.89%, and 88.82%, respectively. Area under receiver operating characteristic curve (AUROC) value was 0.9440, and negative predictive value was 99.22% with a cutoff of 9 points. Conclusion. Our study is the largest of its kind in examining ED patients with renal abscess. MEDS has been demonstrated to be superior to MEWS, REMS, and RAPS in predicting mortality for this patient population. We recommend its use for evaluation of disease severity and risk stratification in these patients, to expedite identification of critically ill patients requiring urgent intervention.

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Shaddel, F. "390 – Introduction of “modified early warning score” (MEWS) to a learning disability ward." European Psychiatry 28 (January 2013): 1. http://dx.doi.org/10.1016/s0924-9338(13)75751-1.

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Yu, Zhejun, Feng Xu, and Du Chen. "Predictive value of Modified Early Warning Score (MEWS) and Revised Trauma Score (RTS) for the short-term prognosis of emergency trauma patients: a retrospective study." BMJ Open 11, no. 3 (2021): e041882. http://dx.doi.org/10.1136/bmjopen-2020-041882.

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ObjectivesThis study aimed to assess the predictive value of the Modified Early Warning Score (MEWS) and Revised Trauma Score (RTS) for emergency trauma patients who died within 24 hours.DesignA retrospective, single-centred study.SettingThis study was conducted at a tertiary hospital in Southern China.ParticipantsA total of 1739 patients with acute trauma, aged 16 years or older who presented to the emergency department from 1 November 2016 to 30 November 2019, were included.Interventions noneNone.Outcome24-hour mortality was the primary outcome of trauma.Results1739 patients were divided into the survival group (1709 patients,98.27%), and the non-survival group (30 patients,1.73%). Crude OR and adjusted OR of MEWS were 1.99, 95% CI (1.73 to 2.29), and 2.00, 95% CI (1.74 to 2.31), p<0.001, respectively. Crude OR and adjusted OR of RTS were 0.62, 95% CI (0.55 to 0.69) and 0.61, 95% CI (0.55 to 0.68), p<0.001, respectively. The area under the curve of MEWS was significantly higher than that of RTS (p=0.005): 0.927, 95% CI (0.914 to 0.939) vs 0.799, 95% CI (0.779 to 0.817).ConclusionsBoth MEWS and RTS were independent predictors of the short-term prognosis in emergency trauma patients, MEWS had better predictive efficacy.

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Mizrahi, J., J. Kott, E. Taub, and N. Goolsarran. "Low daily MEWS scores as predictors of low-risk hospitalized patients." QJM: An International Journal of Medicine 113, no. 1 (2019): 20–24. http://dx.doi.org/10.1093/qjmed/hcz213.

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Summary Background 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. Aim The present study aims to evaluate the MEWS score as a method of identifying patients at low risk for adverse events. Design 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. Results Those with an average MEWS score of &gt;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 &lt;1. Conclusions Our study shows that those with average daily MEWS scores &lt;2 are at a significantly lower likelihood of having an adverse event compared with a score of &gt;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.

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Yu, Min, Bowen Huang, Peizhen Liu, et al. "Detection of deteriorating patients after Whipple surgery by a modified early warning score (MEWS)." Annals of Translational Medicine 7, no. 20 (2019): 574. http://dx.doi.org/10.21037/atm.2019.09.24.

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Lam, TS, PSK Mak, WS Siu, MY Lam, TF Cheung, and TH Rainer. "Validation of a Modified Early Warning Score (Mews) in Emergency Department Observation Ward Patients." Hong Kong Journal of Emergency Medicine 13, no. 1 (2006): 24–30. http://dx.doi.org/10.1177/102490790601300102.

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Wang, An-Yi, Cheng-Chung Fang, Shyr-Chyr Chen, Shin-Han Tsai, and Wei-Fong Kao. "Periarrest Modified Early Warning Score (MEWS) predicts the outcome of in-hospital cardiac arrest." Journal of the Formosan Medical Association 115, no. 2 (2016): 76–82. http://dx.doi.org/10.1016/j.jfma.2015.10.016.

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Horton, Devin J., Kencee K. Graves, Polina V. Kukhareva, et al. "Modified early warning score-based clinical decision support: cost impact and clinical outcomes in sepsis." JAMIA Open 3, no. 2 (2020): 261–68. http://dx.doi.org/10.1093/jamiaopen/ooaa014.

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Abstract Objective The objective of this study was to assess the clinical and financial impact of a quality improvement project that utilized a modified Early Warning Score (mEWS)-based clinical decision support intervention targeting early recognition of sepsis decompensation. Materials and Methods We conducted a retrospective, interrupted time series study on all adult patients who received a diagnosis of sepsis and were exposed to an acute care floor with the intervention. Primary outcomes (total direct cost, length of stay [LOS], and mortality) were aggregated for each study month for the post-intervention period (March 1, 2016–February 28, 2017, n = 2118 visits) and compared to the pre-intervention period (November 1, 2014–October 31, 2015, n = 1546 visits). Results The intervention was associated with a decrease in median total direct cost and hospital LOS by 23% (P = .047) and .63 days (P = .059), respectively. There was no significant change in mortality. Discussion The implementation of an mEWS-based clinical decision support system in eight acute care floors at an academic medical center was associated with reduced total direct cost and LOS for patients hospitalized with sepsis. This was seen without an associated increase in intensive care unit utilization or broad-spectrum antibiotic use. Conclusion An automated sepsis decompensation detection system has the potential to improve clinical and financial outcomes such as LOS and total direct cost. Further evaluation is needed to validate generalizability and to understand the relative importance of individual elements of the intervention.

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Kumar, Sajeesh. "Impact of Health Informatics Technology on the Implementation of a Modified Early Warning Score (MEWS)." Health Informatics - An International Journal 4, no. 3/4 (2015): 27–37. http://dx.doi.org/10.5121/hiij.2015.4403.

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Jiang, Xiaobin, Ping Jiang, and Yuanshen Mao. "Performance of Modified Early Warning Score (MEWS) and Circulation, Respiration, Abdomen, Motor, and Speech (CRAMS) score in trauma severity and in-hospital mortality prediction in multiple trauma patients: a comparison study." PeerJ 7 (June 25, 2019): e7227. http://dx.doi.org/10.7717/peerj.7227.

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Background With an increasing number of motor vehicle crashes, there is an urgent need in emergency departments (EDs) to assess patients with multiple trauma quickly, easily, and reliably. Trauma severity can range from a minor to major threats to life or bodily function. In-hospital mortality and trauma severity prediction in such cases is crucial in the ED for the management of multiple trauma and improvement of the outcome of these patients. Previous studies have examined the performance of Modified Early Warning Score (MEWS) or Circulation, Respiration, Abdomen, Motor, and Speech (CRAMS) score based solely on mortality prediction or injury severity prediction. However, to the best of our knowledge, the performances of both scoring systems on in-hospital mortality and trauma severity prediction have not been compared previously. This retrospective study evaluated the value of MEWS and CRAMS score to predict in-hospital mortality and trauma severity in patients presenting to the ED with multiple traumatic injuries. Methods All study subjects were multiple trauma patients. Medical data of 1,127 patients were analyzed between January 2014 and April 2018. The MEWS and CRAMS score were calculated, and logistic regression and receiver operating characteristic curve analysis were conducted to investigate their performances regarding in-hospital mortality and trauma severity prediction. Results For in-hospital mortality prediction, the areas under the receiver operating characteristic curve (AUROCs) for MEWS and CRAMS score were 0.90 and 0.91, respectively, indicating that both of them were good in-hospital mortality predictors. Further, our study indicated that the CRAMS score performed better in trauma severity prediction, with an AUROC value of 0.84, which was higher than that of MEWS (AUROC = 0.77). For trauma severity prediction, the optimal cut-off value for MEWS was 2, while that of the CRAMS score was 8. Conclusions We found that both MEWS and CRAMS score can be used as predictors for trauma severity and in-hospital mortality for multiple trauma patients, but that CRAMS score was superior to MEWS for trauma severity prediction. CRAMS score should be prioritized in the prediction of trauma severity due to its excellence as a multiple trauma triage tool and potential contribution to rapid emergency rescue decisions.

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Nyberg, P. Benjaminsson, B. Björnsson, P. Sandstrom, and T. Gasslander. "The Modified Early Warning Score (MEWS): A possible tool for early detection of moderately severe acute pancreatitis." HPB 22 (2020): S409—S410. http://dx.doi.org/10.1016/j.hpb.2020.04.482.

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Perera, Yashasvi Sanja, Priyanga Ranasinghe, Adikari Mudiyanselage Madura Adikari, et al. "The value of the Modified Early Warning Score and biochemical parameters as predictors of patient outcome in acute medical admissions: a prospective study." Acute Medicine Journal 10, no. 3 (2011): 126–32. http://dx.doi.org/10.52964/amja.0491.

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Abstract We evaluated the effectiveness of MEWS and biochemical parameters in predicting outcomes for acute medical admissions. Data from consecutive admissions to the Acute Medical Unit (AMU) of National Hospital of Sri Lanka were collected. C-reactive protein (CRP), albumin, white cell count, platelet count and haemoglobin values were collected. Adverse endpoints were HDU/ICU admission, cardio-respiratory emergency/resuscitation and death. A MEWS score of >=5 together with increasing age, pulse rate, respiratory rate, AVPU score, CRP, CRP/Albumin ratio and reduced platelet and albumin level all increased the odds of reaching ‘adverse endpoints”. Adding a score for biochemical parameters increased the area under the ROC curve for reaching “adverse endpoints’. Biochemical parameters better predicted length of hospitalstay and adverse outcomes. A combined scoring system improved the sensitivity of prediction.

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De Giorgi, Alfredo, Carlo Contini, Salvatore Greco, et al. "Is venous thromboembolism a predictable marker in older patients with COVID-19 infection? A single-center observational study." Journal of Infection in Developing Countries 15, no. 05 (2021): 639–345. http://dx.doi.org/10.3855/jidc.14523.

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Venous thromboembolism (VTE) represents an important clinical complication of patients with SARS-CoV-2 infection, and high plasma D-dimer levels could suggest a higher risk of hypercoagulability. We aimed to analyse if laboratory exams, risk assessment scores, comorbidity scores were useful in predicting the VTE in SARS-CoV-2 patients admitted in internal medicine (IM). We evaluated 49 older adults with suspected VTE analysing history and blood chemistry, besides we calculated the Padua Prediction Score, the modified early warning scoring (MEWS) and the modified Elixhauser index (mEI). All patients underwent venous color-doppler ultrasounds of the lower limbs. Out of the 49 patients enrolled (mean age 79.3±14 years), 10 (20.4%) had deep vein thrombosis (DVT), and they were more frequently female (80% vs 20%, p = 0.04). We could not find any association with the Padua Prediction Score, the MEWS, and the mEI. D-dimer plasma levels were also not associated with DVT. In elderly people hospitalized with SARS-CoV-2 infection hospitalized in IM, our data, although limited by the sample size, suggest that prediction and diagnosis of VTE is difficult, due to lack of precise biomarkers and scores.

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Obradovic, Dusanka, Biljana Joves, Ivana Vujovic, Marija Vukoja, Srdjan Stefanovic, and Stanislava Sovilj-Gmizic. "Is age-adjusted mews upon admission a relevant prognostic tool for final outcome?" Srpski arhiv za celokupno lekarstvo, no. 00 (2020): 58. http://dx.doi.org/10.2298/sarh181008058o.

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Introduction/Objective. Early warning scoring systems are important for timely identification of the critically ill, but are they a relevant prognostic tool? Our objective was to test if Modified Early Warning Score (MEWS), lactate and base excess (BE) have any prognostic value in high dependency unit (HDU) patients. Methods. This was a prospective observational study that included 364 patients who were treated at respiratory HDU. The values of MEWS, lactate and BE at admission were recorded with patients' age, sex and comorbidities. Negative outcome was defined as death or transfer to Intensive Care Unit (ICU). Independent predictors of negative outcome were identified with the use of multivariable logistic regression. Results. Of 369 patients, 203 (55%) were male. Mean age was 62 ? 16. There were 138 (37. 4%) patients with negative outcome: 27.37% died, while 10.03% patients required ICU transfer. The median length of hospital stay was 13 days [IQR 7-15]. Patients with negative outcome had a significantly higher MEWS (3.68 ? 1.965 vs. 4.57 ? 2.33, p < 0.001), lower BE (-0.139 ? 7.48 vs. -3.751 ? 6.159, p < 0.001), and a higher lactate (2.299 ? 2.350 vs. 3.498 ? 3.578, p < 0.001). MEWS ? 4 (OR 1.90, CI 1.082-3.340, p = 0.026) was the only independent predictor of mortality. Area under the curve for MEWS with regard to in-hospital mortality prediction was 0.633 (95% CI 0.569-0.697). When age was added to MEWS, the AUC was 0.76 (95% CI 0. 707-0.814). Conclusion. Our findings support the prognostic value of MEWS for final outcome of patients admitted to High Dependency Unit.

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Stefanovic, Srdjan, Dusanka Obradovic, Biljana Joves-Sevic, and Marija Vukoja. "Prognostic value of Modified Early Warning Score (MEWS) in patients admitted to a high dependency unit." Resuscitation 83 (October 2012): e33. http://dx.doi.org/10.1016/j.resuscitation.2012.08.083.

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Worton, SA, L. Higgins, G. Stephen, and GC Gillham. "Modified early warning score (MEWS) identifies clinical deterioration prior to development of unexpected acute pulmonary oedema." Archives of Disease in Childhood - Fetal and Neonatal Edition 97, Suppl 1 (2012): A52.3—A53. http://dx.doi.org/10.1136/fetalneonatal-2012-301809.168.

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Bhatnagar, Mini, Nikita Sirohi, and ArunaBhagat Dubey. "Prediction of hospital outcome in emergency medical admissions using modified early warning score (MEWS): Indian experience." Journal of Family Medicine and Primary Care 10, no. 1 (2021): 192. http://dx.doi.org/10.4103/jfmpc.jfmpc_1426_20.

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Choukalas, Christopher G., Suzanne Kellman, Michelle L. Keese, et al. "Intervention- versus physiology-based risk assessment scores for predicting cardiac arrest: a pilot study." F1000Research 2 (March 15, 2013): 91. http://dx.doi.org/10.12688/f1000research.2-91.v1.

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There is increasing interest in predicting and avoiding cardiac arrest in hospitalized patients. Multiple studies have used vital signs or scores based upon them, such as the Modified Early Warning Score (MEWS). Scoring systems that measure supportive care, such as the Sequential Organ Failure Assessment (SOFA) and the 28-item Therapeutic Interventions Scoring System (TISS-28) might be superior to systems used in previous studies. This study was performed to determine if a system using SOFA and/or TISS would be superior in detecting clinical deterioration prior to cardiac arrest.Using a retrospective chart review, MEWS, SOFA and TISS-28 scores were calculated for twenty patients at baseline and then in the 24 hours prior to their cardiac arrest. Supportive interventions and nursing care (SOFA and TISS-28) changed more than measures of physiology (MEWS) in the period prior to cardiac arrest, likely due to the fact that vital sign deterioration can be delayed by supportive measures. These results support the idea that a SOFA and/or TISS-28 scoring system might be superior to the MEWS, which could be used to make hospital rapid response teams more effective.

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Klinger, Amanda, Ariel Mueller, Tori Sutherland, et al. "Predicting mortality in adults with suspected infection in a Rwandan hospital: an evaluation of the adapted MEWS, qSOFA and UVA scores." BMJ Open 11, no. 2 (2021): e040361. http://dx.doi.org/10.1136/bmjopen-2020-040361.

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

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T. V. D., Sasi Sekhar, Anjani Kumar C., Bhavya Ch., Sameera B., and Rama Devi Ch. "Comparative study of scoring systems in ICU and emergency department in predicting mortality of critically ill." International Journal of Research in Medical Sciences 5, no. 4 (2017): 1352. http://dx.doi.org/10.18203/2320-6012.ijrms20171225.

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Background: Scoring systems can be used to define critically ill patients, estimate their prognosis, help in clinical decision making, and guide the allocation of resources and to estimate the quality of care. 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.Methods: We have done a prospective observational study of consecutively admitted 400 critically ill patients to ICU directly from Emergency Department in Dr PSIMS and RF over a period of 2 years. Clinical and laboratory data conforming to the modified early warning score (MEWS), rapid emergency medicine score (REMS), acute physiology and chronic health evaluation (APACHE II), and simplified acute physiology score (SAPS II) were recorded for all patients. A comparison was made between ED scoring systems MEWS, REMS and ICU scoring systems APACHE II, SAPSII. The outcome was recorded in two categories: survived and non-survived with a primary end point of 30-day mortality. Discrimination was evaluated using receiver operating characteristic (ROC) curves.Results: The ICU scores outperformed the ED scores with more area under curve values. The predicted mortality percentage of ICU based scoring systems is high compared to emergency scores (predicted mortality % of SAPS II-63%, APACHE II-33.3%, MEWS-18.5%, REMS-14.8%).Conclusions: ICU scores showed more predictive accuracy than ED scores in prognosticating the outcomes in critically ill patients. This difference is seemed more due to complexity of ICU scores.

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Wu, Kuan-Han, Fu-Jen Cheng, Hsiang-Ling Tai, et al. "Predicting in-hospital mortality in adult non-traumatic emergency department patients: a retrospective comparison of the Modified Early Warning Score (MEWS) and machine learning approach." PeerJ 9 (August 24, 2021): e11988. http://dx.doi.org/10.7717/peerj.11988.

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Background A feasible and accurate risk prediction systems for emergency department (ED) patients is urgently required. The Modified Early Warning Score (MEWS) is a wide-used tool to predict clinical outcomes in ED. Literatures showed that machine learning (ML) had better predictability in specific patient population than traditional scoring system. By analyzing a large multicenter dataset, we aim to develop a ML model to predict in-hospital morality of the adult non traumatic ED patients for different time stages, and comparing performance with other ML models and MEWS. Methods A retrospective observational cohort study was conducted in five Taiwan EDs including two tertiary medical centers and three regional hospitals. All consecutively adult (>17 years old) non-traumatic patients admit to ED during a 9-year period (January first, 2008 to December 31th, 2016) were included. Exclusion criteria including patients with (1) out-of-hospital cardiac arrest and (2) discharge against medical advice and transferred to other hospital (3) missing collect variables. The primary outcome was in-hospital mortality and were categorized into 6, 24, 72, 168 hours mortality. MEWS was calculated by systolic blood pressure, pulse rate, respiratory rate, body temperature, and level of consciousness. An ensemble supervised stacking ML model was developed and compared to sensitive and unsensitive Xgboost, Random Forest, and Adaboost. We conducted a performance test and examine both the area under the receiver operating characteristic (AUROC) and the area under the precision and recall curve (AUPRC) as the comparative measures. Result After excluding 182,001 visits (7.46%), study group was consisted of 24,37,326 ED visits. The dataset was split into 67% training data and 33% test data for ML model development. There was no statistically difference found in the characteristics between two groups. For the prediction of 6, 24, 72, 168 hours in-hospital mortality, the AUROC of MEW and ML mode was 0.897, 0.865, 0.841, 0.816 and 0.939, 0.928, 0.913, 0.902 respectively. The stacking ML model outperform other ML model as well. For the prediction of in-hospital mortality over 48-hours, AUPRC performance of MEWS drop below 0.1, while the AUPRC of ML mode was 0.317 in 6 hours and 0.2150 in 168 hours. For each time frame, ML model achieved statistically significant higher AUROC and AUPRC than MEWS (all P < 0.001). Both models showed decreasing prediction ability as time elapse, but there was a trend that the gap of AUROC values between two model increases gradually (P < 0.001). Three MEWS thresholds (score >3, >4, and >5) were determined as baselines for comparison, ML mode consistently showed improved or equally performance in sensitivity, PPV, NPV, but not in specific. Conclusion Stacking ML methods improve predicted in-hospital mortality than MEWS in adult non-traumatic ED patients, especially in the prediction of delayed mortality.

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Tangkulpanich, Panvilai, Noraset Uppariputtanggoon, and Kasamon Aramvanitch. "The Performances of Multiple Scoring Systems to Predict Patients Required Immediate Life-Saving Intervention in Emergency Department." Ramathibodi Medical Journal 42, no. 3 (2019): 1–11. http://dx.doi.org/10.33165/rmj.2019.42.3.138690.

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Background: Crowding in emergency room is the major problem especially in the resuscitation room. Many patients require immediate life-saving interventions (LSI). Whereas, many different scoring systems such as national early warning score (NEWS), worthing physiological scoring system (WPS), modified early warning score (MEWS), and rapid emergency medicine score (REMS) have been developed for assessing patients at risk. Objective: To evaluate the effectiveness of 4 scoring systems performance in predicting LSI use in emergency room and reenter to the resuscitation room within 48 hours. Methods: Data were collected by a retrospective cross-sectional study of patients treated in the resuscitation room for 2 months period, at Ramathibodi Hospital. The number of patients who received LSI and reentry to resuscitation room were studied, compared by selected scoring systems. Results: Total 839 patients entered resuscitation room, while 331 (39.45%) patients received LSI. The first three groups at risk were metabolic diseases, gastrointestinal systems, and infections, respectively. The most effective scoring system in predicting patients required LSI was MEWS, the discrimination of this system was significantly better than NEWS (AUC, 0.69 vs 0.65; 95% CI, 0.65 - 0.72; P = .01). Eighty-six patients (13.89%) from 619 patients reentered to the resuscitation room. Moreover, NEWS was the most effective in predicting patients who had a risk of reenter (AUC, 0.72; 95% CI, 0.66 - 0.78; P < .001). Conclusions: MEWS is the most effective scoring system for patient assessment of LSI utilization. However, NEWS is the one suitable for predicting reenter tendency.

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Caramello, Valeria, Valentina Beux, Alessandro Vincenzo De Salve, Alessandra Macciotta, Fulvio Ricceri, and Adriana Boccuzzi. "Comparison of different prognostic scores for risk stratification in septic patients arriving to the Emergency Department." Italian Journal of Medicine 14, no. 2 (2020): 79–87. http://dx.doi.org/10.4081/itjm.2020.1232.

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We evaluated the prognostic performance of systemic inflammatory response syndrome (SIRS), sequential organ failure assessment (SOFA), quick-SOFA (qSOFA), modified early warning score (MEWS), lactates and procalcitonin in septic patients. Prospective study on adults with sepsis in the Emergency Department (ED). Area under the Receiver operator characteristic curve (AUC) was calculated to assess how scores predict mortality at 30 and 60 days (d) and upon admission to Intensive care unit (ICU). Among 469 patients, mortality was associated with higher SOFA, qSOFA, MEWS and lactates level. ICU admission was associated with higher SOFA, procalcitonin and MEWS. Prognostic performance for mortality were: SOFA AUC 30 d 0.76 (0.69-0.81); 60 d 0.74 (0.68-0.79); qSOFA AUC 30 d 0.72 (0.66-0.79); 60 d 0.73 (0.67-0.78) and lactates AUC 30 d 0.71 (0.60-0.82); 60d 0.65 (0.54- 0.73). For the outcome ICU admission, procalcitonin had the highest AUC [0.66 (0.56-0.64], followed by SOFA [0.61 (0.54-0.69)] and MEWS [0.60 (0.53-0.67)]. SOFA, qSOFA and lactates assessment after arrival in the ED have a good performance in detecting patients at risk of mortality for sepsis. Procalcitonin is useful to select patients that will need ICU admission.

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Jayasundera, Romesh, Mark Neilly, Toby Smith, and Phyo Myint. "Are Early Warning Scores Useful Predictors for Mortality and Morbidity in Hospitalised Acutely Unwell Older Patients? A Systematic Review." Journal of Clinical Medicine 7, no. 10 (2018): 309. http://dx.doi.org/10.3390/jcm7100309.

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Background: Early warning scores (EWSs) are used to identify deteriorating patients for appropriate interventions. We performed a systematic review to examine the usefulness of EWSs in predicting inpatient mortality and morbidity (transfer to higher-level care and length of hospital stay) in older people admitted to acute medical units with sepsis, acute cardiovascular events, or pneumonia. Methods: A systematic review of published and unpublished databases was conducted. Cochrane′s tool for assessing Risk of Bias in Non-Randomised Studies—of Interventions (ROBINS-I) was used to appraise the evidence. A narrative synthesis was performed due to substantial heterogeneity. RESULTS: Five studies (n = 12,057) were eligible from 1033 citations. There was an overall “moderate” risk of bias for all studies. The predictive ability of EWSs regarding mortality was reported in one study (n = 274), suggesting EWSs were better at predicting survival, (negative predictive value >90% for all scores). Three studies (n = 1819) demonstrated a significant association between increasing modified EWSs (MEWSs) and increased risk of mortality. Hazards ratios for a composite death/intensive care (ICU) admission with MEWSs ≥5 were significant in one study (p = 0.003). Two studies (n = 1421) demonstrated that a MEWS ≥6 was associated with 21 times higher probability of mortality (95% Confidence Interval (CI): 2.71–170.57) compared with a MEWS ≤1. A MEWS of ≥5 was associated with 22 times higher probability of mortality (95% CI: 10.45–49.16). Conclusion: Increasing EWSs are strongly associated with mortality and ICU admission in older acutely unwell patients. Future research should be targeted at better understanding the usefulness of high and increasing EWSs for specific acute illnesses in older adults.

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Suppiah, Aravind, Deep J. Malde, Tameem Arab, et al. "Modified early warning score (MEWS): A user friendly and sensitive predictor of poor outcome in acute pancreatitis." Pancreatology 12, no. 3 (2012): e11-e12. http://dx.doi.org/10.1016/j.pan.2012.03.028.

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Graham, C. A., K. M. Choi, C. W. Ki, et al. "Evaluation and Validation of the Use of Modified Early Warning Score (MEWS) in Emergency Department Observation Ward." Academic Emergency Medicine 14, no. 5 Supplement 1 (2007): S199—S200. http://dx.doi.org/10.1197/j.aem.2007.03.1279.

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Thomson, Jane, Yasir Tashkandi, Pedro Ison, et al. "Rescuing the deteriorating patient: The development and evaluation of the Electronic Modified Early Warning Score (e-MEWS)." Journal of Infection and Public Health 8, no. 4 (2015): 400–401. http://dx.doi.org/10.1016/j.jiph.2015.04.013.

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Dunson, William A., Emily Erickson, Chad Freckleton, et al. "Leveraging the electronic medical record (EMR) to improve sepsis care in cancer outpatients." Journal of Clinical Oncology 36, no. 30_suppl (2018): 319. http://dx.doi.org/10.1200/jco.2018.36.30_suppl.319.

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319 Background: Sepsis is a life-threatening organ dysfunction caused by a dysregulated response to infection and a major healthcare problem in cancer patients. Patients with cancer are at increased risk of morbidity and mortality from sepsis. Approaches like the modified Early Warning Score (mEWS) could offer an opportunity to identify patients at risk for sepsis earlier and to prompt a timely evaluation. However, available evidence for cancer outpatient settings remains scarce. The aim of this presentation is to describe first results of the mEWS implementation at Huntsman Cancer Hospital (HCC) outpatient clinics. The question, whether patients with sepsis can be detected using this approach will be answered. Methods: In 2015, the University of Utah Healthcare implemented mEWS as prediction tool for sepsis. The automated calculation of mEWS is based on real-time data from the EMR. For this analysis, we extracted a cancer outpatient population from a 15-month time frame (from December 2016 to February 2018) within the EHR. We selected patients with a mEWS > 4, grouped these patients according to the process of care after mEWS scoring (e.g., admitted to ICU) and analyzed subgroup based upon mEWS score, discharge disposition and sepsis diagnosis. Results: Within the analyzed time frame 502 cancer outpatients had a mEWS score of 4 or higher. 88 of these patients (17.5%) were diagnosed with sepsis after mEWS screening. Out of the patients with sepsis, 22 were admitted to ICU, 63 were admitted to a medical floor and 3 were treated at the Huntsman Acute Care Clinic. Out of the 414 without a diagnosis of sepsis, 13 patients were admitted to ICU, 72 patients were admitted to a medical floor (in each case for other reasons then sepsis) and 329 patients were sent to home. Conclusions: Sepsis is a serious problem in cancer outpatient care. In our analysis, one in six patients with a mEWS score of 4 and higher were diagnosed with sepsis. This analysis has shown that the implementation of a real-time, EMR based scoring system like mEWS can support the early detection and treatment of sepsis in this population.

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Kim, Jeongmin, Myunghun Chae, Hyuk-Jae Chang, Young-Ah Kim, and Eunjeong Park. "Predicting Cardiac Arrest and Respiratory Failure Using Feasible Artificial Intelligence with Simple Trajectories of Patient Data." Journal of Clinical Medicine 8, no. 9 (2019): 1336. http://dx.doi.org/10.3390/jcm8091336.

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We introduce a Feasible Artificial Intelligence with Simple Trajectories for Predicting Adverse Catastrophic Events (FAST-PACE) solution for preparing immediate intervention in emergency situations. FAST-PACE utilizes a concise set of collected features to construct an artificial intelligence model that predicts the onset of cardiac arrest or acute respiratory failure from 1 h to 6 h prior to its occurrence. Data from the trajectory of 29,181 patients in intensive care units of two hospitals includes periodic vital signs, a history of treatment, current health status, and recent surgery. It excludes the results of laboratory data to construct a feasible application in wards, out-hospital emergency care, emergency transport, or other clinical situations where instant medical decisions are required with restricted patient data. These results are superior to previous warning scores including the Modified Early Warning Score (MEWS) and the National Early Warning Score (NEWS). The primary outcome was the feasibility of an artificial intelligence (AI) model predicting adverse events 1 h to 6 h prior to occurrence without lab data; the area under the receiver operating characteristic curve of this model was 0.886 for cardiac arrest and 0.869 for respiratory failure 6 h before occurrence. The secondary outcome was the superior prediction performance to MEWS (net reclassification improvement of 0.507 for predicting cardiac arrest and 0.341 for predicting respiratory failure) and NEWS (net reclassification improvement of 0.412 for predicting cardiac arrest and 0.215 for predicting respiratory failure) 6 h before occurrence. This study suggests that AI consisting of simple vital signs and a brief interview could predict a cardiac arrest or acute respiratory failure 6 h earlier.

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Araújo, Maria Eduarda da Silva, Luzia Cibele de Souza Maximiano, Carmem Josaura de Lima Oliveira, Johny Carlos de Queiroz, Andressa Maria Flausino Chaves Pereira, and Alcivan Nunes Vieira. "Perfil de gravidade clínica de pacientes admitidos em Unidade de Terapia Intensiva." Research, Society and Development 10, no. 3 (2021): e58410313759. http://dx.doi.org/10.33448/rsd-v10i3.13759.

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Objetivo: avaliar a gravidade clínica do paciente admitido em UTI aplicando o Modified Early Warning Score. Método: estudo transversal, analítico, quantitativo; foi realizado na UTI de um hospital de referência regional. Os dados foram coletados nos prontuários dos pacientes usando um instrumento focando: motivo da admissão na UTI; doença de base, comorbidades; complicações clínicas e intervenções realizadas na UTI. A amostra foi composta por 265 prontuários considerando um nível de significância de 5% e um erro amostral relativo de 8%. Resultados: prevaleceram as faixas etárias de 41-50 (13%) e 71-80 anos (18%); quanto ao motivo de admissão identificou-se: agravos traumáticos (30%), pneumonia (12%), Acidente Vascular Encefálico (11%) e o Acidente Vascular Encefálico Hemorrágico (10%). A avaliação da gravidade através do MEWS identificou: valores entre 1 e 12 com média de 5,2; maior taxa de mortalidade associada ao MEWS classificado entre 4 a 6. Entre pacientes que usaram VMI, para 40,3% o MEWS ficou entre 4-6. A maior permanência na UTI foi registrada em pacientes com MEWS de 1-4. Conclusão: pontuações mais elevadas no MEWS estão associadas a uma maior gravidade clínica, bem como maior necessidade assistencial, permitindo assim o estabelecimento de prioridades na assistência.

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Patel, Amar, Saad Hassan, Abid Ullah, Tahir Hamid, and Hannah Kirk. "Early triaging using the Modified Early Warning Score (MEWS) and dedicated emergency teams leads to improved clinical outcomes in acute emergencies." Clinical Medicine 15, Suppl 3 (2015): s3. http://dx.doi.org/10.7861/clinmedicine.15-3-s3.

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Jemal, Hanen, Zied Kechaou, and Mounir Ben Ayed. "Enhanced Decision Support Systems in Intensive Care Unit Based on Intuitionistic Fuzzy Sets." Advances in Fuzzy Systems 2017 (2017): 1–8. http://dx.doi.org/10.1155/2017/7371634.

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In areas of medical diagnosis and decision-making, several uncertainty and ambiguity shrouded situations are most often imposed. In this regard, one may well assume that intuitionistic fuzzy sets (IFS) should stand as a potent technique useful for demystifying associated with the real healthcare decision-making situations. To this end, we are developing a prototype model helpful for detecting the patients risk degree in Intensive Care Unit (ICU). Based on the intuitionistic fuzzy sets, dubbed Medical Intuitionistic Fuzzy Expert Decision Support System (MIFEDSS), the shown work has its origins in the Modified Early Warning Score (MEWS) standard. It is worth noting that the proposed prototype effectiveness validation is associated through a real case study test at the Polyclinic ESSALEMA cited in Sfax, Tunisia. This paper does actually provide some practical initial results concerning the system as carried out in real life situations. Indeed, the proposed system turns out to prove that the MIFEDSS does actually display an imposing capability for an established handily ICU related uncertainty issues. The performance of the prototypes is compared with the MEWS standard which exposed that the IFS application appears to perform highly better in deferring accuracy than the expert MEWS score with higher degrees of sensitivity and specificity being recorded.

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