scholarly journals Do medical students recognise the deteriorating patient by analysing their vital signs? A monocentric observational study based on the National Early Warning Score 2

BMJ Open ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. e044354
Author(s):  
David Alexander Christian Messerer ◽  
Michael Fauler ◽  
Astrid Horneffer ◽  
Achim Schneider ◽  
Oliver Keis ◽  
...  
Keyword(s):  
Medical Students ◽  
Clinical Response ◽  
Early Warning ◽  
Vital Signs ◽  
Early Warning Score ◽  
Professional Activity ◽  
Monitoring Frequency ◽  
National Early Warning Score ◽  
Deteriorating Patient ◽  
Current Risk

ObjectiveAssessment of the expertise of medical students in evaluating vital signs and their implications for the current risk of a patient, an appropriate monitoring frequency, and a proper clinical response.Methods251 second-year and 267 fifth-year medical students in a curriculum consisting of 6 years of medical school at Ulm University, Germany, were interviewed in a paper-based questionnaire. The students were asked to rate their proficiency in interpreting vital signs and to give pathological thresholds of vital signs. Based on the National Early Warning Score 2 (NEWS2), nine vital signs of fictional patients were created and students were asked to comment on their clinical risk, to set an appropriate monitoring frequency as well as a clinical response.ResultsInterviewing medical students regarding each vital sign individually, the students indicated a pathological threshold in accordance with the NEWS2 for respiratory rate, temperature, and heart rate. By contrast, inappropriate pathological limits were given regarding oxygen saturation and systolic blood pressure. Translating the vital signs into nine fictional patients, fifth-year medical students overall chose an appropriate response in 78% (67%−78%, median±IQR). In detail, fifth-year students successfully identified patients at very high or low risk and allocated them accordingly. However, cases on the edge were often stratified inappropriately. For example, a fictional case with vital signs indicating a surging sepsis was frequently underappreciated (48.5%) and allocated to an insufficient clinical response by fifth-year students.ConclusionsRecognising the healthy as well as the deteriorating patient is a key ability for future physicians. NEWS2-based education might be a valuable tool to assess and give feedback on student’s knowledge in this vital professional activity.

scholarly journals Impact of the level of sickness on higher mortality in emergency medical admissions to hospital at weekends

2017 ◽  
Vol 22 (4) ◽  
pp. 236-242 ◽  
Author(s):  
Mohammed Mohammed ◽  
Muhammad Faisal ◽  
Donald Richardson ◽  
Robin Howes ◽  
Kevin Beatson ◽  
...  
Keyword(s):  
Early Warning ◽  
Odds Ratio ◽  
Vital Signs ◽  
Early Warning Score ◽  
Emergency Admissions ◽  
Clinical Assessments ◽  
Admission Time ◽  
Emergency Medical ◽  
Acute Hospitals ◽  
National Early Warning Score

Objective Routine administrative data have been used to show that patients admitted to hospitals over the weekend appear to have a higher mortality compared to weekday admissions. Such data do not take the severity of sickness of a patient on admission into account. Our aim was to incorporate a standardized vital signs physiological-based measure of sickness known as the National Early Warning Score to investigate if weekend admissions are: sicker as measured by their index National Early Warning Score; have an increased mortality; and experience longer delays in the recording of their index National Early Warning Score. Methods We extracted details of all adult emergency medical admissions during 2014 from hospital databases and linked these with electronic National Early Warning Score data in four acute hospitals. We analysed 47,117 emergency admissions after excluding 1657 records, where National Early Warning Score was missing or the first (index) National Early Warning Score was recorded outside ±24 h of the admission time. Results Emergency medical admissions at the weekend had higher index National Early Warning Score (weekend: 2.53 vs. weekday: 2.30, p < 0.001) with a higher mortality (weekend: 706/11,332 6.23% vs. weekday: 2039/35,785 5.70%; odds ratio = 1.10, 95% CI 1.01 to 1.20, p = 0.04) which was no longer seen after adjusting for the index National Early Warning Score (odds ratio = 0.99, 95% CI 0.90 to 1.09, p = 0.87). Index National Early Warning Score was recorded sooner (−0.45 h, 95% CI −0.52 to −0.38, p < 0.001) for weekend admissions. Conclusions Emergency medical admissions at the weekend with electronic National Early Warning Score recorded within 24 h are sicker, have earlier clinical assessments, and after adjusting for the severity of their sickness, do not appear to have a higher mortality compared to weekday admissions. A larger definitive study to confirm these findings is needed.

scholarly journals Factors affecting the clinical response to National Early Warning score triggers

Critical Care ◽  
2014 ◽  
Vol 18 (Suppl 1) ◽  
pp. P45 ◽  
Author(s):  
I Kolic ◽  
S McCartney ◽  
S Crane ◽  
Z Perkins ◽  
A Taylor
Keyword(s):  
Clinical Response ◽  
Early Warning ◽  
Early Warning Score ◽  
Factors Affecting ◽  
National Early Warning Score

scholarly journals Comparison of the National Early Warning Score (NEWS) and the Modified Early Warning Score (MEWS) for predicting admission and in-hospital mortality in elderly patients in the pre-hospital setting and in the emergency department

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e6947 ◽  
Author(s):  
Toshiya Mitsunaga ◽  
Izumu Hasegawa ◽  
Masahiko Uzura ◽  
Kenji Okuno ◽  
Kei Otani ◽  
...  
Keyword(s):  
Elderly Patients ◽  
Hospital Mortality ◽  
Early Warning ◽  
Pressure Pulse ◽  
Vital Signs ◽  
Early Warning Score ◽  
Single Centre ◽  
Peripheral Oxygen Saturation ◽  
Significant Difference ◽  
National Early Warning Score

The aim of this study is to evaluate the usefulness of the pre-hospital National Early Warning Score (pNEWS) and the pre-hospital Modified Early Warning Score (pMEWS) for predicting admission and in-hospital mortality in elderly patients presenting to the emergency department (ED). We also compare the value of the pNEWS with that of the ED NEWS (eNEWS) and ED MEWS (eMEWS) for predicting admission and in-hospital mortality. This retrospective, single-centre observational study was carried out in the ED of Jikei University Kashiwa Hospital, in Chiba, Japan, from 1st April 2017 to 31st March 2018. All patients aged 65 years or older were included in this study. The pNEWS/eNEWS were derived from seven common physiological vital signs: respiratory rate, peripheral oxygen saturation, the presence of inhaled oxygen parameters, body temperature, systolic blood pressure, pulse rate and Alert, responds to Voice, responds to Pain, Unresponsive (AVPU) score, whereas the pMEWS/eMEWS were derived from six common physiological vital signs: respiratory rate, peripheral oxygen saturation, body temperature, systolic blood pressure, pulse rate and AVPU score. Discrimination was assessed by plotting the receiver operating characteristic (ROC) curve and calculating the area under the ROC curve (AUC). The median pNEWS, pMEWS, eNEWS and eMEWS were significantly higher at admission than at discharge (p < 0.001). The median pNEWS, pMEWS, eNEWS and eMEWS of non-survivors were significantly higher than those of the survivors (p < 0.001). The AUC for predicting admission was 0.559 for the pNEWS and 0.547 for the pMEWS. There was no significant difference between the AUCs of the pNEWS and the pMEWS for predicting admission (p = 0.102). The AUCs for predicting in-hospital mortality were 0.678 for the pNEWS and 0.652 for the pMEWS. There was no significant difference between the AUCs of the pNEWS and the pMEWS for predicting in-hospital mortality (p = 0.081). The AUC for predicting admission was 0.628 for the eNEWS and 0.591 for the eMEWS. The AUC of the eNEWS was significantly greater than that of the eMEWS for predicting admission (p < 0.001). The AUC for predicting in-hospital mortality was 0.789 for the eNEWS and 0.720 for the eMEWS. The AUC of the eNEWS was significantly greater than that of the eMEWS for predicting in-hospital mortality (p < 0.001). For admission and in-hospital mortality, the AUC of the eNEWS was significantly greater than that of the pNEWS (p < 0.001, p < 0.001), and the AUC of the eMEWS was significantly greater than that of the pMEWS (p < 0.01, p < 0.05). Our single-centre study has demonstrated the low utility of the pNEWS and the pMEWS as predictors of admission and in-hospital mortality in elderly patients, whereas the eNEWS and the eMEWS predicted admission and in-hospital mortality more accurately. Evidence from multicentre studies is needed before introducing pre-hospital versions of risk-scoring systems.

scholarly journals Abbreviated National Early Warning Score predicts the need for hospital admission and in-hospital mortality in elderly patients

2018 ◽  
Vol 14 (3) ◽  
Author(s):  
Toshiya Mitsunaga ◽  
Masahiko Hujita ◽  
Izumu Hasegawa ◽  
Kei Otani ◽  
Kenji Okuno ◽  
...  
Keyword(s):  
Elderly Patients ◽  
Hospital Mortality ◽  
Early Warning ◽  
Roc Analysis ◽  
Pressure Pulse ◽  
Vital Signs ◽  
Early Warning Score ◽  
Operating Characteristics ◽  
Peripheral Oxygen Saturation ◽  
National Early Warning Score

The aim of this study was to evaluate the value of the Abbreviated National Early Warning Score (aNEWS) for predicting admissions and in-hospital mortality in elderly patients present to Emergency Department (ED). This retrospective, single-centred observational study was carried out in the ED of Minamitama Hospital, in Tokyo, Japan from 1 April 2018 to 30 April 2018. All of the patients aged 65 and older were included in this study. The aNEWS is based on six common physiological vital signs, including peripheral oxygen saturation, the presence of inhaled oxygen parameters, body temperature, systolic blood pressure, pulse rate, and the Alert, responds to Voice, responds to Pain, Unresponsive score. The scores range from 0 and 3 for each parameter. The aNEWS ranged from a score of 0 to a maximum of 17. The receiver operating characteristics (ROC) analysis was used to evaluate the predictive value of the aNEWS for admission and in-hospital mortality. The median aNEWS of patients admitted to the hospital was significantly higher than that of patients discharged from the ED (P<0.001). The median aNEWS of survivors was significantly higher than that of non-survivors (P<0.001). The Areas under the ROC Curve (AUC) for predicting admission was 0.773 [95% CI 0.7142 to 0.8317, P<0.001] for the aNEWS. The AUC for predicting in-hospital mortality was 0.791 [95% CI 0.604 to 0.978, P<0.001] for the aNEWS. Our single-centred study has demonstrated the utility of the aNEWS as a predictor of patient admission and in-hospital mortality in elderly patients.

scholarly journals ChroniSense National Early Warning Score Study (CHESS): a wearable wrist device to measure vital signs in hospitalised patients—protocol and study design

BMJ Open ◽  
2019 ◽  
Vol 9 (9) ◽  
pp. e028219
Author(s):  
Michelle Helena Van Velthoven ◽  
Felicia Adjei ◽  
Dimitris Vavoulis ◽  
Glenn Wells ◽  
David Brindley ◽  
...  
Keyword(s):  
Early Warning ◽  
Vital Sign ◽  
Clinical Decision Making ◽  
Vital Signs ◽  
Early Warning Score ◽  
Individual Parameter ◽  
Standard Clinical Practice ◽  
Reference Number ◽  
Hospitalised Patients ◽  
National Early Warning Score

IntroductionThe National Early Warning Score is used as standard clinical practice in the UK as a track and trigger system to monitor hospitalised patients. Currently, nurses are tasked to take routine vital signs measurements and manually record these on a clinical chart. Wearable devices could provide an easier, reliable, more convenient and cost-effective method of monitoring. Our aim is to evaluate the clinical validity of Polso (ChroniSense Medical, Yokneam Illit, Israel), a wrist-based device, to provide National Early Warning Scores.Methods and analysisWe will compare Polso National Early Warning Score measurements to the currently used manual measurements in a UK Teaching District General Hospital. Patients aged 18 years or above who require recordings of observations of vital signs at least every 6 hours will be enrolled after consenting. The sample size for the study was calculated to be 300 participants based on the assumption that the final dataset will include four pairs of measurements per-patient and per-vital sign, resulting in a total of 1200 pairs of data points per vital sign. The primary outcome is the agreement on the individual parameter scores and values of the National Early Warning Score: (1) respiratory rate, (2) oxygen saturation, (3) body temperature, (4) systolic blood pressure and (5) heart rate. Secondary outcomes are the agreement on the aggregate National Early Warning Score. The incidence of adverse events will be recorded. The measurements by the device will not be used for the clinical decision-making in this study.Ethics and disseminationWe obtained ethical approval, reference number 18/LO/0123 from London—Hampstead Research Ethics Committee, through the Integrated Research Application System, (reference number: 235 034. The study received no objection from the Medicine and Health Regulatory Authority, reference number: CI/20018/005 and has National Institute for Health Research portfolio adoption status CPMS number: 32 532.Trial registration numberNCT03448861; Pre-results.

scholarly journals Distribution of the National Early Warning Score (NEWS) in care home residents

2019 ◽  
Vol 49 (1) ◽  
pp. 141-145 ◽  
Author(s):  
Robert Oliver Barker ◽  
Rachel Stocker ◽  
Siân Russell ◽  
Anthony Roberts ◽  
Andrew Kingston ◽  
...  
Keyword(s):  
Older Adults ◽  
Early Warning ◽  
Care Home ◽  
Descriptive Analysis ◽  
Vital Signs ◽  
Acute Illness ◽  
Care Homes ◽  
Early Warning Score ◽  
Care Home Resident ◽  
National Early Warning Score

Abstract Background the National Early Warning Score (NEWS) is a tool based on vital signs that aims to standardise detection of, and response to, clinical deterioration in adults. NEWS has been adopted in hospitals but not adapted for other settings. This study aimed to explore the feasibility of measuring the NEWS in care homes and describe the distribution of NEWS readings amongst care home residents. Methods descriptive analysis of all NEWS readings recorded in a 30-month period (2016–19) across 46 care homes in one Clinical Commissioning Group in England. Comparisons were made between measurements taken as a routine reading and those prompted by concern about acute illness. Results a total of 19,604 NEWS were recorded from 2,424 older adults (≥65 years; mean age 85). Median NEWS was 2. Two thirds (66%) of residents had a low NEWS (≤2), and 28% had a score of 0. Of the total NEWS readings, 6,277 (32%) were known to be routine readings and 2,256 (12%) were measured because of staff concerns. Median NEWS was 1 for routine and 2 for concern recordings. Overall, only 12% of NEWS were high (≥5), but a higher proportion were elevated when there were concerns about acute illness (18%), compared with routine recordings (7%). Conclusions use of NEWS in care homes appears to be feasible. The majority of NEWS were not elevated, and the distribution of scores is consistent with other out-of-hospital settings. Further work is required to know if NEWS is triggering the most appropriate response and improving care home resident outcomes.

Development of A Pharmaceutical Early Warning Scoring Model for Cardiac Arrest Using Deep Learning: Retrospective Cohort Study (Preprint)

2020 ◽  
Author(s):  
Hsiao-Ko Chang ◽  
Hui-Chih Wang ◽  
Chih-Fen Huang ◽  
Feipei Lai
Keyword(s):  
Time Series ◽  
Cardiac Arrest ◽  
Early Warning ◽  
Time Series Data ◽  
Predictive Accuracy ◽  
Vital Signs ◽  
Sliding Window ◽  
Early Warning Score ◽  
Series Data ◽  
Dynamic Time

BACKGROUND In most of Taiwan’s medical institutions, congestion is a serious problem for emergency departments. Due to a lack of beds, patients spend more time in emergency retention zones, which make it difficult to detect cardiac arrest (CA). OBJECTIVE We seek to develop a pharmaceutical early warning model to predict cardiac arrest in emergency departments via drug classification and medical expert suggestion. METHODS We propose a new early warning score model for detecting cardiac arrest via pharmaceutical classification and by using a sliding window; we apply learning-based algorithms to time-series data for a Pharmaceutical Early Warning Scoring Model (PEWSM). By treating pharmaceutical features as a dynamic time-series factor for cardiopulmonary resuscitation (CPR) patients, we increase sensitivity, reduce false alarm rates and mortality, and increase the model’s accuracy. To evaluate the proposed model we use the area under the receiver operating characteristic curve (AUROC). RESULTS Four important findings are as follows: (1) We identify the most important drug predictors: bits, and replenishers and regulators of water and electrolytes. The best AUROC of bits is 85%; that of replenishers and regulators of water and electrolytes is 86%. These two features are the most influential of the drug features in the task. (2) We verify feature selection, in which accounting for drugs improve the accuracy: In Task 1, the best AUROC of vital signs is 77%, and that of all features is 86%. In Task 2, the best AUROC of all features is 85%, which demonstrates that thus accounting for the drugs significantly affects prediction. (3) We use a better model: For traditional machine learning, this study adds a new AI technology: the long short-term memory (LSTM) model with the best time-series accuracy, comparable to the traditional random forest (RF) model; the two AUROC measures are 85%. (4) We determine whether the event can be predicted beforehand: The best classifier is still an RF model, in which the observational starting time is 4 hours before the CPR event. Although the accuracy is impaired, the predictive accuracy still reaches 70%. Therefore, we believe that CPR events can be predicted four hours before the event. CONCLUSIONS This paper uses a sliding window to account for dynamic time-series data consisting of the patient’s vital signs and drug injections. In a comparison with NEWS, we improve predictive accuracy via feature selection, which includes drugs as features. In addition, LSTM yields better performance with time-series data. The proposed PEWSM, which offers 4-hour predictions, is better than the National Early Warning Score (NEWS) in the literature. This also confirms that the doctor’s heuristic rules are consistent with the results found by machine learning algorithms.

scholarly journals Experiences of a National Early Warning Score (NEWS) intervention in care homes during the COVID-19 pandemic: a qualitative interview study

BMJ Open ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. e045469
Author(s):  
Rachel Stocker ◽  
Siân Russell ◽  
Jennifer Liddle ◽  
Robert O Barker ◽  
Adam Remmer ◽  
...  
Keyword(s):  
Early Warning ◽  
Healthcare Professionals ◽  
Care Home ◽  
Qualitative Interview ◽  
Interview Study ◽  
Care Homes ◽  
Early Warning Score ◽  
Service Utilisation ◽  
Qualitative Interview Study ◽  
National Early Warning Score

BackgroundThe COVID-19 pandemic has taken a heavy toll on the care home sector, with residents accounting for up to half of all deaths in Europe. The response to acute illness in care homes plays a particularly important role in the care of residents during a pandemic. Digital recording of a National Early Warning Score (NEWS), which involves the measurement of physical observations, started in care homes in one area of England in 2016. Implementation of a NEWS intervention (including equipment, training and support) was accelerated early in the pandemic, despite limited evidence for its use in the care home setting.ObjectivesTo understand how a NEWS intervention has been used in care homes in one area of North-East England during the COVID-19 pandemic, and how it has influenced resident care, from the perspective of stakeholders involved in care delivery and commissioning.MethodsA qualitative interview study with care home (n=10) and National Health Service (n=7) staff. Data were analysed using thematic analysis.ResultsUse of the NEWS intervention in care homes in this area accelerated during the COVID-19 pandemic. Stakeholders felt that NEWS, and its associated education and support package, improved the response of care homes and healthcare professionals to deterioration in residents’ health during the pandemic. Healthcare professionals valued the ability to remotely monitor resident observations, which facilitated triage and treatment decisions. Care home staff felt empowered by NEWS, providing a common clinical language to communicate concerns with external services, acting as an adjunct to staff intuition of resident deterioration.ConclusionsThe NEWS intervention formed an important part of the care home response to COVID-19 in the study area. Positive staff perceptions now need to be supplemented with data on the impact on resident health and well-being, workload, and service utilisation, during the pandemic and beyond.

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