scholarly journals Continuous monitoring in COVID-19 care; a retrospective study in time of crisis

JAMIA Open ◽  
2021 ◽  
Author(s):  
Roy de Ree ◽  
Jorn Willemsen ◽  
Gilbert te Grotenhuis ◽  
Rick de Ree ◽  
Joé Kolkert ◽  
...  
Keyword(s):  
Adverse Events ◽  
Respiratory Rate ◽  
Nursing Staff ◽  
Early Warning ◽  
Wireless Sensors ◽  
Continuous Monitoring ◽  
Vital Signs ◽  
Early Warning Score ◽  
Monitoring Systems ◽  
Patients At Risk

Abstract Background A new monitoring system was implemented to support nursing staff and physicians on the COVID-19 ward. This system was designed to remotely monitor vital signs, to calculate an automated Early Warning Score (aEWS) and to help identify patients at risk of deterioration. Methods Hospitalized patients who tested positive for SARS-CoV-2 were connected to two wireless sensors measuring vital signs. Patients were divided into two groups based on the occurrence of adverse events during hospitalization. Heart and respiratory rate were monitored continuously and an automated EWS was calculated every 5 minutes. Data were compared between groups. Results Prior to the occurrence of adverse events, significantly higher median heart and respiration rate and significantly lower median SPO2 values were observed. Mean and median automated EWS were significantly higher in patients with an adverse event. Conclusion Continuous monitoring systems might help to detect clinical deterioration in COVID-19 patients at an earlier stage. Lay Summary A new monitoring system was implemented to support nursing staff and physicians on the COVID-19 ward. This system was designed to remotely monitor vital signs, like respiratory rate, heart rate and the oxygen level in the blood. These parameters were used to calculate an automated early warning score which helps to identify patients at risk of deterioration. Hospitalized patients who tested positive for SARS-CoV-2 were connected to two wireless sensors. Heart and respiratory rate were monitored continuously and an automated EWS was calculated every 5 minutes. Data were compared between patients at the COVID-19 ward and patients who were transported to the ICU or died. COVID patients at the ICU or those who died had significantly higher median heart and respiration rate and significantly lower median oxygen levels. These findings showed that continuous monitoring systems might help to detect clinical deterioration in COVID-19 patients at an earlier stage.

scholarly journals Examining the utility of the Hamilton early warning scores (HEWS) at triage: Retrospective pilot study in a Canadian emergency department

CJEM ◽  
2017 ◽  
Vol 20 (2) ◽  
pp. 266-274 ◽  
Author(s):  
Steven Skitch ◽  
Benjamin Tam ◽  
Michael Xu ◽  
Laura McInnis ◽  
Anthony Vu ◽  
...  
Keyword(s):  
At Risk ◽  
Emergency Department ◽  
Early Warning ◽  
Vital Signs ◽  
Roc Curves ◽  
Early Warning Score ◽  
Critical Event ◽  
Discriminative Ability ◽  
Early Warning Scores ◽  
Patients At Risk

ABSTRACTObjectivesEarly warning scores use vital signs to identify patients at risk of critical illness. The current study examines the Hamilton Early Warning Score (HEWS) at emergency department (ED) triage among patients who experienced a critical event during their hospitalization. HEWS was also evaluated as a predictor of sepsis.MethodsThe study population included admissions to two hospitals over a 6-month period. Cases experienced a critical event defined by unplanned intensive care unit admission, cardiopulmonary resuscitation, or death. Controls were randomly selected from the database in a 2-to-1 ratio to match cases on the burden of comorbid illness. Receiver operating characteristic (ROC) curves were used to evaluate HEWS as a predictor of the likelihood of critical deterioration and sepsis.ResultsThe sample included 845 patients, of whom 270 experienced a critical event; 89 patients were excluded because of missing vitals. An ROC analysis indicated that HEWS at ED triage had poor discriminative ability for predicting the likelihood of experiencing a critical event 0.62 (95% CI 0.58-0.66). HEWS had a fair discriminative ability for meeting criteria for sepsis 0.77 (95% CI 0.72-0.82) and good discriminative ability for predicting the occurrence of a critical event among septic patients 0.82 (95% CI 0.75-0.90).ConclusionThis study indicates that HEWS at ED triage has limited utility for identifying patients at risk of experiencing a critical event. However, HEWS may allow earlier identification of septic patients. Prospective studies are needed to further delineate the utility of the HEWS to identify septic patients in the ED.

scholarly journals Pediatric Early Warning Score Systems, nurse’s perspective – a focus group study

2019 ◽  
Vol 2 (3) ◽  
pp. 38
Author(s):  
Claus Sixtus Jensen
Keyword(s):  
Focus Group ◽  
Early Warning ◽  
Clinical Judgment ◽  
Vital Signs ◽  
Early Warning Score ◽  
Focus Group Discussions ◽  
Focus Group Study ◽  
Group Discussions ◽  
Patients At Risk ◽  
Nurses Perceptions

Background: Pediatric early warning score (PEWS) systems are used to monitor pediatric patients’ vital signs and facilitate the treatment of patients at risk of deteriorating. The aim of this study was to gain knowledge about nurses’ experiences with PEWS and to highlight factors facilitating and impeding the use of PEWS tools in clinical practice we aim to obtain knowledge about nurses’ experiences with PEWS. Methods: An exploratory qualitative design was chosen using focus group discussions to gain a deeper understanding of nurses’ experiences with PEWS. A total of five focus group discussions were conducted at three hospitals, and the analyses performed were inspired by Kvale and Brinckman. Results: Seven themes were identified, including i) lack of interdisciplinary awareness, ii) clinical judgment and PEWS—a multi-faceted approach, iii) PEWS supports a professional language, iv) monitoring equipment—a challenge, v) PEWS helps to visualize the need for escalating care, vi) an inflexible and challenging tool, and vii) supportive tools enhance the nurses’ experiences of PEWS positively. Conclusions: Our findings suggest that attention should be given to nurses’ perceptions of how both clinical judgment and PEWS should be seen as essential in providing nurses with information about the patients’ conditions. If not, the risk of failing to recognize patients’ deteriorating conditions will remain. From the nurses’ perspective, medical doctors seemed unaware of their role in using PEWS.

scholarly journals Adjusting Early Warning Score by clinical assessment: a study protocol for a Danish cluster-randomised, multicentre study of an Individual Early Warning Score (I-EWS)

BMJ Open ◽  
2020 ◽  
Vol 10 (1) ◽  
pp. e033676
Author(s):  
Pernille B Nielsen ◽  
Martin Schultz ◽  
Caroline Sophie Langkjaer ◽  
Anne Marie Kodal ◽  
Niels Egholm Pedersen ◽  
...  
Keyword(s):  
Multicentre Study ◽  
Nursing Staff ◽  
Clinical Assessment ◽  
Early Warning ◽  
Vital Signs ◽  
Early Warning Score ◽  
Prognostic Information ◽  
Use Of Resources ◽  
Cluster Randomised ◽  
All Cause Mortality

IntroductionTrack and trigger systems (TTSs) based on vital signs are implemented in hospitals worldwide to identify patients with clinical deterioration. TTSs may provide prognostic information but do not actively include clinical assessment, and their impact on severe adverse events remain uncertain. The demand for prospective, multicentre studies to demonstrate the effectiveness of TTSs has grown the last decade. Individual Early Warning Score (I-EWS) is a newly developed TTS with an aggregated score based on vital signs that can be adjusted according to the clinical assessment of the patient. The objective is to compare I-EWS with the existing National Early Warning Score (NEWS) algorithm regarding clinical outcomes and use of resources.Method and analysisIn a prospective, multicentre, cluster-randomised, crossover, non-inferiority study. Eight hospitals are randomised to use either NEWS in combination with the Capital Region of Denmark NEWS Override System (CROS) or implement I-EWS for 6.5 months, followed by a crossover. Based on their clinical assessment, the nursing staff can adjust the aggregated score with a maximum of −4 or +6 points. We expect to include 150 000 unique patients. The primary endpoint is all-cause mortality at 30 days. Coprimary endpoint is the average number of times per day a patient is NEWS/I-EWS-scored, and secondary outcomes are all-cause mortality at 48 hours and at 7 days as well as length of stay.Ethics and disseminationThe study was presented for the Regional Ethics committee who decided that no formal approval was needed according to Danish law (J.no. 1701733). The I-EWS study is a large prospective, randomised multicentre study that investigates the effect of integrating a clinical assessment performed by the nursing staff in a TTS, in a head-to-head comparison with the internationally used NEWS with the opportunity to use CROS.Trial registration numberNCT03690128.

scholarly journals P120: Exploring the utility of the Hamilton early warning score at triage: pilot study in a Canadian emergency department

CJEM ◽  
2016 ◽  
Vol 18 (S1) ◽  
pp. S118-S118
Author(s):  
S. Skitch ◽  
L. McInnis ◽  
A. Vu ◽  
B. Tam ◽  
M. Xu ◽  
...  
Keyword(s):  
At Risk ◽  
Emergency Department ◽  
Early Warning ◽  
Tertiary Care ◽  
Vital Signs ◽  
Early Warning Score ◽  
Critical Event ◽  
Likelihood Ratios ◽  
Discriminative Ability ◽  
Patients At Risk

Introduction: Early warning scores (EWS) use vital signs to identify patients at risk of critical events as defined by unplanned intensive care unit (ICU) admission, cardiopulmonary resuscitation (CPR), or death. Systems that combine an EWS with a ICU outreach team can improve hospital survival and cardiac arrest rates. Although initially developed for use in ward patients, evidence suggests that EWS are useful in emergency department (ED) patients and may aid in the earlier identification of sepsis. The Hamilton Early Warning Score (HEWS) was recently developed as part of quality improvement process in our health system. The current study examined HEWS at ED triage among a cohort of patients who experienced a critical event during their hospitalization. HEWS were also evaluated as a predictor of sepsis. Methods: Patient were selected from a database of patients admitted to a medical or surgical ward at two tertiary care hospitals over a six-month period. Cases were patients who experienced a critical event during admission and were admitted via the ED. Controls were randomly selected from the database in a two-to-one ratio using an algorithm to match cases based upon burden of comorbid illness. Receiver operator curves (ROC) and likelihood ratios were used to evaluate HEWS at ED triage as a predictor of likelihood of critical deterioration and sepsis. Results: The sample included 845 patients of whom 267 experienced a critical event. The median time to occurrence of critical event from admission was 124 hours. ROC analysis indicated that HEWS at ED triage had poor discriminative ability for predicting likelihood of experiencing a critical event 0.63 [95%CI: 0.58-0.67]. HEWS had fair discriminative ability for predicting likelihood of meeting criteria for sepsis 0.75 [95%CI: 0.71-0.80], and good discriminative ability for predicting likelihood of experiencing a critical event among patients meeting criteria for sepsis 0.80 [95%CI: 0.74-0.86]. Conclusion: This retrospective study indicates that HEWS at ED triage has limited utility for identifying patients at risk of experiencing a critical event. This may be because deterioration commonly occurred days after admission. However, HEWS may have utility as tool for aiding earlier identification of critically ill septic patients. Prospective studies are needed to further delineate the utility of the HEWS in the ED.

scholarly journals Frequency of alterations in qSOFA, SIRS, MEWS and NEWS scores during the emergency department stay in infectious patients: a prospective study

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Gideon H. P. Latten ◽  
Judith Polak ◽  
Audrey H. H. Merry ◽  
Jean W. M. Muris ◽  
Jan C. Ter Maaten ◽  
...  
Keyword(s):  
Emergency Department ◽  
Respiratory Rate ◽  
Early Warning ◽  
Vital Sign ◽  
Vital Signs ◽  
Early Warning Score ◽  
Suspected Infection ◽  
Prospective Multicentre Study ◽  
Clinical Rules ◽  
Clinical Rule

Abstract Background For emergency department (ED) patients with suspected infection, a vital sign-based clinical rule is often calculated shortly after the patient arrives. The clinical rule score (normal or abnormal) provides information about diagnosis and/or prognosis. Since vital signs vary over time, the clinical rule scores can change as well. In this prospective multicentre study, we investigate how often the scores of four frequently used clinical rules change during the ED stay of patients with suspected infection. Methods Adult (≥ 18 years) patients with suspected infection were prospectively included in three Dutch EDs between March 2016 and December 2019. Vital signs were measured in 30-min intervals and the quick Sequential Organ Failure Assessment (qSOFA) score, the Systemic Inflammatory Response Syndrome (SIRS) criteria, the Modified Early Warning Score and the National Early Warning Score (NEWS) score were calculated. Using the established cut-off points, we analysed how often alterations in clinical rule scores occurred (i.e. switched from normal to abnormal or vice versa). In addition, we investigated which vital signs caused most alterations. Results We included 1433 patients, of whom a clinical rule score changed once or more in 637 (44.5%) patients. In 6.7–17.5% (depending on the clinical rule) of patients with an initial negative clinical rule score, a positive score occurred later during ED stay. In over half (54.3–65.0%) of patients with an initial positive clinical rule score, the score became negative later on. The respiratory rate caused most (51.2%) alterations. Conclusion After ED arrival, alterations in qSOFA, SIRS, MEWS and/or NEWS score are present in almost half of patients with suspected infection. The most contributing vital sign to these alterations was the respiratory rate. One in 6–15 patients displayed an abnormal clinical rule score after a normal initial score. Clinicians should be aware of the frequency of these alterations in clinical rule scores, as clinical rules are widely used for diagnosis and/or prognosis and the optimal moment of assessing them is unknown.

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.

Glucose as an additional parameter to National Early Warning Score (NEWS) in prehospital setting enhances identification of patients at risk of death: an observational cohort study

2020 ◽  
pp. emermed-2018-208309
Author(s):  
Hanna Vihonen ◽  
Mitja Lääperi ◽  
Markku Kuisma ◽  
Jussi Pirneskoski ◽  
Jouni Nurmi
Keyword(s):  
At Risk ◽  
Blood Glucose ◽  
Regression Model ◽  
Early Warning ◽  
Prehospital Setting ◽  
Early Warning Score ◽  
Calibration Model ◽  
Risk Of Death ◽  
Patients At Risk ◽  
National Early Warning Score

BackgroundTo determine if prehospital blood glucose could be added to National Early Warning Score (NEWS) for improved identification of risk of short-term mortality.MethodsRetrospective observational study (2008–2015) of adult patients seen by emergency medical services in Helsinki metropolitan area for whom all variables for calculation of NEWS and a blood glucose value were available. Survival of 24 hours and 30 days were determined. The NEWS parameters and glucose were tested by multivariate logistic regression model. Based on ORs we formed NEWSgluc model with hypoglycaemia (≤3.0 mmol/L) 3, normoglycaemia 0 and hyperglycaemia (≥11.1 mmol/L) 1 points. The scores from NEWS and NEWSgluc were compared using discrimination (area under the curve), calibration (Hosmer-Lemeshow test), likelihood ratio tests and reclassification (continuous net reclassification index (cNRI)).ResultsData of 27 141 patients were included in the study. Multivariable regression model for NEWSgluc parameters revealed a strong association with glucose disturbances and 24-hour and 30-day mortality. Likelihood ratios (LRs) for mortality at 24 hours using a cut-off point of 15 were for NEWSgluc: LR+ 17.78 and LR− 0.96 and for NEWS: LR+ 13.50 and LR− 0.92. Results were similar at 30 days. Risks per score point estimation and calibration model showed glucose added benefit to NEWS at 24 hours and at 30 days. Although areas under the curve were similar, reclassification test (cNRI) showed overall improvement of classification of survivors and non-survivors at 24 days and 30 days with NEWSgluc.ConclusionsIncluding glucose in NEWS in the prehospital setting seems to improve identification of patients at risk of death.

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.

Evaluating the Use of a Modified Early Warning Score in Predicting Serious Adverse Events in Iranian Hospitalized Patients: A Prognostic Study

2020 ◽  
Vol 46 (1) ◽  
pp. 72-82 ◽  
Author(s):  
Maryam Maftoohian ◽  
Abdolghader Assarroudi ◽  
Jacqueline J. Stewart ◽  
Mostafa Dastani ◽  
Mohammad Hassan Rakhshani ◽  
...  
Keyword(s):  
Adverse Events ◽  
Early Warning ◽  
Hospitalized Patients ◽  
Early Warning Score ◽  
Serious Adverse Events
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