Relevant bibliographies by topics / (Modified) Early Warning Scoring (MEWS/EWS)

Academic literature on the topic '(Modified) Early Warning Scoring (MEWS/EWS)'

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Published: 10 December 2022
Last updated: 19 February 2023

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Journal articles on the topic "(Modified) Early Warning Scoring (MEWS/EWS)"

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Chang, Su-Han, Chiao-Hsuan Hsieh, Yi-Ming Weng, Ming-Shun Hsieh, Zhong Ning Leonard Goh, Hsien-Yi Chen, Tung Chang, 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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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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Wu, Kuan-Han, Fu-Jen Cheng, Hsiang-Ling Tai, Jui-Cheng Wang, Yii-Ting Huang, Chih-Min Su, and Yun-Nan Chang. "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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Kumala Fajar Apsari, Ratih. "Deteksi Pasien Obstetrik Kritis dengan Maternal Early Warning System." Jurnal Anestesi Obstetri Indonesia 2, no. 1 (April 15, 2020): 63–70. http://dx.doi.org/10.47507/obstetri.v2i1.35.

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Adaptasi fisiologis yang terjadi pada ibu hamil dapat menyamarkan tanda-tanda penyakit maternal berat. Ini mempersulit identifikasi kolaps maternal yang akan terjadi. Penggunaan early warning system (EWS) yang dimodifikasi untuk penggunaan pada pasien ibu hamil dan postpartum akan membantu dalam identifikasi, treatment dini, dan penanganan pasien yang memiliki, atau akan mengalami, penyakit kritis. Maternal Early Warning System (MEWS) seharusnya mengidentifikasi pasien yang berisiko untuk mengalami perburukan pada saat intervensi dini dapat mencegah perburukan ke morbiditas berat MEWS telah digunakan secara ekstensif dalam praktek obstetrik, tetapi sistem yang digunakan sangat bervariasi. Parameter-parameter yang sering dimasukkan dalam MEWS antara lain denyut jantung, tingkat pernapasan, tekanan darah, dan tingkat kesadaran. Dari berbagai MEWS yang telah dikembangkan, ada tiga MEWS utama, yaitu (1) modified early obstetric warning system (MEOWS), (2) Maternal Early Warning Criteria (MEWC), dan (3) Maternal Early Warning Trigger (MEWT) tool. Hingga kini masih belum diketahui sistem MEWS apa yang terbaik, dan setiap rumah sakit mungkin memerlukan penyesuaian dalam parameter MEWS. Literatur yang ada menunjukkan kemungkinan manfaat dan mendukung penggunaan MEWS. Implementasi dan penggunaan MEWT telah dikaitkan dengan penurunan morbiditas maternal komposit dan morbiditas maternal berat. Akan tetapi, respon apa yang optimal untuk setting tertentu agar memperbaiki pelayanan maternal setelah tanda peringatan muncul hingga kini masih belum jelas. Detection of Critically Ill Obstetric Patients with Maternal Early Warning System Abstract Physiological adaptations that develop in pregnant women may obscure signs of severe maternal diseases. These causes difficulties in identifying the impending maternal collapse. An early warning system (EWS) modified for pregnant and postpartum women may assist in identification, early treatment, and management of patients who already or will develop critical illness. Maternal Early Warning System MEWS has been extensively used in obstetric practices; however, the systems used in preactice are varied. The most considered parameters for MEWS are heart rate, respiratory rate, blood pressure, and level of consciousness. From many MEWS developed, three primary MEWS existed, (1) modified early obstetric warning system (MEOWS), (2) Maternal Early Warning Criteria (MEWC), dan (3) Maternal Early Warning Trigger (MEWT) tool. There is still no consensus regarding which MEWS is superior, and different hospitals may require adjustments in MEWS parameters. The existing literatures suggested the potential benefit of MEWS and supported MEWS in clinical practice. Implementation and adoption of MEWS had been associated with reduced composite maternal morbidities and severe maternal morbidities. However, the optimal response for certain settings to improve maternal services after warning system has been activated is still lacking.
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Durantez-Fernández, Carlos, Begoña Polonio-López, José L. Martín-Conty, Clara Maestre-Miquel, Antonio Viñuela, Raúl López-Izquierdo, Laura Mordillo-Mateos, et al. "Comparison of Nine Early Warning Scores for Identification of Short-Term Mortality in Acute Neurological Disease in Emergency Department." Journal of Personalized Medicine 12, no. 4 (April 14, 2022): 630. http://dx.doi.org/10.3390/jpm12040630.

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(1) Background: The aim was screening the performance of nine Early Warning Scores (EWS), to identify patients at high-risk of premature impairment and to detect intensive care unit (ICU) admissions, as well as to track the 2-, 7-, 14-, and 28-day mortality in a cohort of patients diagnosed with an acute neurological condition. (2) Methods: We conducted a prospective, longitudinal, observational study, calculating the EWS [Modified Early Warning Score (MEWS), National Early Warning Score (NEWS), VitalPAC Early Warning Score (ViEWS), Modified Rapid Emergency Medicine Score (MREMS), Early Warning Score (EWS), Hamilton Early Warning Score (HEWS), Standardised Early Warning Score (SEWS), WHO Prognostic Scored System (WPSS), and Rapid Acute Physiology Score (RAPS)] upon the arrival of patients to the emergency department. (3) Results: In all, 1160 patients were included: 808 patients were hospitalized, 199 cases (17%) required ICU care, and 6% of patients died (64 cases) within 2 days, which rose to 16% (183 cases) within 28 days. The highest area under the curve for predicting the need for ICU admissions was obtained by RAPS and MEWS. For predicting mortality, MREMS obtained the best scores for 2- and 28-day mortality. (4) Conclusions: This is the first study to explore whether several EWS accurately identify the risk of ICU admissions and mortality, at different time points, in patients with acute neurological disorders. Every score analyzed obtained good results, but it is suggested that the use of RAPS, MEWS, and MREMS should be preferred in the acute setting, for patients with neurological impairment.
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Guan, Gigi, Crystal Man Ying Lee, Stephen Begg, Angela Crombie, and George Mnatzaganian. "The use of early warning system scores in prehospital and emergency department settings to predict clinical deterioration: A systematic review and meta-analysis." PLOS ONE 17, no. 3 (March 17, 2022): e0265559. http://dx.doi.org/10.1371/journal.pone.0265559.

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Background It is unclear which Early Warning System (EWS) score best predicts in-hospital deterioration of patients when applied in the Emergency Department (ED) or prehospital setting. Methods This systematic review (SR) and meta-analysis assessed the predictive abilities of five commonly used EWS scores (National Early Warning Score (NEWS) and its updated version NEWS2, Modified Early Warning Score (MEWS), Rapid Acute Physiological Score (RAPS), and Cardiac Arrest Risk Triage (CART)). Outcomes of interest included admission to intensive care unit (ICU), and 3-to-30-day mortality following hospital admission. Using DerSimonian and Laird random-effects models, pooled estimates were calculated according to the EWS score cut-off points, outcomes, and study setting. Risk of bias was evaluated using the Newcastle-Ottawa scale. Meta-regressions investigated between-study heterogeneity. Funnel plots tested for publication bias. The SR is registered in PROSPERO (CRD42020191254). Results Overall, 11,565 articles were identified, of which 20 were included. In the ED setting, MEWS, and NEWS at cut-off points of 3, 4, or 6 had similar pooled diagnostic odds ratios (DOR) to predict 30-day mortality, ranging from 4.05 (95% Confidence Interval (CI) 2.35–6.99) to 6.48 (95% CI 1.83–22.89), p = 0.757. MEWS at a cut-off point ≥3 had a similar DOR when predicting ICU admission (5.54 (95% CI 2.02–15.21)). MEWS ≥5 and NEWS ≥7 had DORs of 3.05 (95% CI 2.00–4.65) and 4.74 (95% CI 4.08–5.50), respectively, when predicting 30-day mortality in patients presenting with sepsis in the ED. In the prehospital setting, the EWS scores significantly predicted 3-day mortality but failed to predict 30-day mortality. Conclusion EWS scores’ predictability of clinical deterioration is improved when the score is applied to patients treated in the hospital setting. However, the high thresholds used and the failure of the scores to predict 30-day mortality make them less suited for use in the prehospital setting.
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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 (February 11, 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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Stolić, Radojica, Dragica Bukumirić, Milena Jovanović, Tomislav Nikolić, Tatjana Labudović, Vekoslav Mitrović, Kristina Bulatović, et al. "A new scoring system for Covid-19 in patients on hemodialysis: Modified Early Warning score." Praxis medica 50, no. 1-2 (2021): 1–6. http://dx.doi.org/10.5937/pramed2102001s.

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Introduction. At the very beginning of the Corona virus epidemic there was not enough data on whether hemodialysis patients have a higher risk for Corona virus infection and which factors may affect the severity of clinical picture. Objective. The aim of the study was to determine the significance of the Modified Early Warning Assessment (MEWS) score for the assessment of coronavirus disease exacerbation. Methods. The research was conducted in COVID dialysis, as a retrospective, descriptive-analytical study, at the University Clinical Center Kragujevac, Serbia, which was organized ad-hoc for treatment of SARS-Cov-2 infection positive patients, which are transfered from Center for Hemodialysis "Ćuprija". They were evaluated routine laboratory findings, demographic and gender structure, arterial blood pressure, presence of comorbidities and residual diuresis, duration of dialysis, radiological evaluation of lungs, determination of MEWS score were the parameters that were monitored. The results were monitored on admission and and in the end of treatment. Results. A statistically significant difference was registered in serum lactate dehydrogenase concentration (486 ± 107.62 vs. 423.7 ± 92.4 U/L); p = 0.022 and absolute monocyte count (0.46 ± 0.15 vs. 0.67 ± 0.34 x 103; p = 0.008). The significant increase in MEWS score was also found (b = 0.017; p = 0.030). There was a positive correlation between increase of MEWS score and age (b = 0.027; p = 0.002) and arterial hypertension as a concomitant comorbidity (b = 0.700; p = 0.033). Conclusion. In the observed period, there was a significant increase in the degree of MEWS score of dialysis patients who had SARS-Cov-2 infection.
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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 (October 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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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 (May 15, 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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Dissertations / Theses on the topic "(Modified) Early Warning Scoring (MEWS/EWS)"

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(9829427), Andrea Reid. "Understanding registered nurses' practice utilising a (modified) early warning scoring system in Australia: A grounded theory study." Thesis, 2014. https://figshare.com/articles/thesis/Building_energy_conservation_and_indoor_air_quality_assessment_in_a_subtropical_climate/20346684.

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 Background: The Medical Emergency Team (MET) expanded the role of the traditional cardiac arrest team with the intent to encourage rapid assessment of and response to deterioration of the patient before a cardiopulmonary arrest occurred on the hospital ward. The (Modified) Early Warning Scoring (MEWS/EWS) system was introduced to supplement the MET as a secondary means of supporting the ward nurse to be able to undertake an early identification of the deteriorating patient. Nurses play a vital role in accurately completing this tool. Previous studies have neither explained, nor explored nurses' understanding of using early warning scoring systems nor the importance and relevance of doing so. 

Aim: This dissertation reports on a study aimed at discovering Registered Nurses' understandings of using (Modified) Early Warning Scoring (MEWS/EWS) systems in Australian hospitals. 

Research Design A Grounded Theory approach was used to explore Registered Nurses' understanding of the MEWS/EWS system. The constant comparative method of data analysis was untaken to develop a substantive theory to explain this process. A sample of 14 Registered Nurses from Australian hospitals provided the data from which a substantive theory emerged. 

Findings The study identified the central category of shared understanding. Shared understanding was central to Registered Nurses using a MEWS/EWS system designed to "track" signs of deterioration and "trigger" a rapid response. This shared understanding requires a common agreement between health professions and healthcare facilities on the benefit of the system. When the shared understanding was absent, Registered Nurses were circumnavigating the system to achieve a desired response, which was to essentially achieve a positive outcome for the patient. They circumnavigated the process by calling the medical emergency team (MET) to ultimately keep the patient safe and to ensure the patient was seen. 

Conclusion In unveiling the substantive theory to prevent clinical deterioration and optimise patient outcomes the multidisciplinary team require a shared understanding of the MEWS/EWS system it became apparent that when the central issue of a shared understanding was diminished or missing, efficient use of the Track and Trigger systems (TTS) could be compromised. The study contributes to the body of knowledge about MEWS/EWS systems but in an area not previously addressed, furthering insight into the factors that affect nurses when utilising the MEWS/EWS systems. This research has the potential to shape research on MEWS/EWS systems use in the future. 

  

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