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Early warning scores serve as valuable tools for predicting adverse events in patients. This study aimed to compare the diagnostic performance of National Early Warning Score, Hamilton Early Warning Score, Standardized Early Warning Score, and Triage Early Warning Score in forecasting intubation and mortality among patients with coronavirus disease 2019. This predictive correlation study included 370 patients admitted to the emergency department of 22 Bahman Hospital in Neyshabur, Iran, from December 2021 to March 2022. The aforementioned scores were assessed daily upon patient admission and throughout a 1-month hospitalization period, alongside intubation and mortality occurrences. Data analysis used SPSS 26 and MEDCALC 20.0.13 software. We adhered to the Standards for Reporting of Diagnostic Accuracy Studies guidelines to ensure the accurate reporting of our study. The patients' mean age was 65.03 ± 18.47 years, with 209 (56.5%) being male. Both Standardized Early Warning Score and Hamilton Early Warning Score demonstrated high diagnostic performance, with area under the curve values of 0.92 and 0.95, respectively. For Standardized Early Warning Score, the positive likelihood ratio was 10.81 for intubation and 17.90 for mortality, whereas for Hamilton Early Warning Score, the positive likelihood ratio was 7.88 for intubation and 10.40 for mortality. The negative likelihood ratio values were 0.23 and 0.17 for Standardized Early Warning Score and 0.21 and 0.18 for Hamilton Early Warning Score, respectively, for the 24-hour period preceding intubation events and mortality. Findings suggest that Standardized Early Warning Score, followed by Hamilton Early Warning Score, has superior diagnostic performance in predicting intubation and mortality in patients with coronavirus disease 2019 within 24 hours before these outcomes. Therefore, serial assessments of Hamilton Early Warning Score or Standardized Early Warning Score may be valuable tools for health care providers in identifying high-risk patients with coronavirus disease 2019 who require intubation or are at increased risk of mortality. [ABSTRACT FROM AUTHOR]

Objectives: This study aimed to summarize the results of coronavirus disease 2019 (COVID-19) risk assessments and to examine the associations between risk levels and various indicators, including COVID-19 incidence, risk perception, community mobility, and government policy. Methods: The results of the risk assessment and the indicators utilized were summarized. From November 2021 to May 2022, the COVID-19 risk level was evaluated on a weekly basis, and its correlation with these indicators was analyzed. Data were obtained from press releases by the Korea Disease Control and Prevention Agency, regular surveys conducted by Hankook Research, and information available on the Google and Oxford websites. Results: Weekly risk assessments were conducted for 30 weeks, using different indices depending on the phases. Correlation analysis revealed the strongest positive correlation between risk level and risk perception (r =0.841). The risk level from "1-week lead" demonstrated a strong positive correlation with the time-varying reproduction number (Rt). Similarly, the risk level from "week lagged value" showed a strong positive correlation with the number of severe cases in the hospital. Conclusion: At the time of risk assessment, the Rt precedes the risk level, while severe cases in hospitals follow. Therefore, the assessed risk level functioned as an early warning system. Risk perception demonstrated the strongest correlation with the risk level, suggesting consistency throughout the assessment period. Contextual indicators (e.g., risk perception) that consider time lags and implementation scales, could improve the evaluation of future risk assessment results, particularly when there are challenges in reflecting specific situations in coordinated emergency response. [ABSTRACT FROM AUTHOR]

To make a cross-cultural adaptation of the National Early Warning Score 2 (NEWS 2) from English to Angolan Portuguese. A methodological research of cross-cultural adaptation was conducted, involving sequential stages of forward translation, translation synthesis, back-translation, and the application of the Delphi Panel methodology for analyzing semantic, idiomatic, experiential, and conceptual equivalence between the translated and the original versions. This process culminated in the development of a pre-final version, which subsequently underwent testing in a cohort of nurses (n = 37). The Intraclass Correlation Coefficient was calculated to assess inter-rater reliability of ratings. Cronbach's alpha was used for evaluating the internal consistency and reliability within the items of the NEWS 2 score. The cross-cultural adaptation process allowed us to prepare the final version of this tool. The data collected during the testing phase facilitated the examination of inter-rater reliability of ratings and the internal consistency and reliability within the items of the NEWS2 score. The Intraclass Correlation Coefficient observed at this step was 0.992. The Cronbach's alpha was 0.993. The cross-cultural adaptation of the NEWS 2 scoring system to Angolan Portuguese was successful, providing healthcare professionals in Angola with the means to effectively use the tool. [ABSTRACT FROM AUTHOR]

In the context of the COVID-19 pandemic, the early and accurate identification of patients at risk of deterioration was crucial in overcrowded and resource-limited emergency departments. This study conducts an external validation for the evaluation of the performance of the National Early Warning Score 2 (NEWS2), the S/F ratio, and the ROX index at ED admission in a large cohort of COVID-19 patients from Colombia, South America, assessing the net clinical benefit with decision curve analysis. A prospective cohort study was conducted on 6907 adult patients with confirmed COVID-19 admitted to a tertiary care ED in Colombia. The study evaluated the diagnostic performance of NEWS2, S/F ratio, and ROX index scores at ED admission using the area under the receiver operating characteristic curve (AUROC) for discrimination, calibration, and decision curve analysis for the prediction of intensive care unit admission, invasive mechanical ventilation, and in-hospital mortality. We included 6907 patients who presented to the ED with confirmed SARS-CoV-2 infection from March 2020 to November 2021. Mean age was 51 (35–65) years and 50.4% of patients were males. The rate of intensive care unit admission was 28%, and in-hospital death was 9.8%. All three scores have good discriminatory performance for the three outcomes based on the AUROC. S/F ratio showed miscalibration at low predicted probabilities and decision curve analysis indicated that the NEWS2 score provided a greater net benefit compared to other scores across at a 10% threshold to decide ED admission at a high-level of care facility. The NEWS2, S/F ratio, and ROX index at ED admission have good discriminatory performances in COVID-19 patients for the prediction of adverse outcomes, but the NEWS2 score has a higher net benefit underscoring its clinical utility in optimizing patient management and resource allocation in emergency settings. [ABSTRACT FROM AUTHOR]

Background: Pulmonary embolism (PE) is an important cause of mortality and morbidity in the geriatric population. We aimed to compare the ability of the pulmonary embolism severity index (PESI), rapid emergency medicine score (REMS), and hypotension, oxygen saturation, low temperature, electrocardiogram change, and loss of independence (HOTEL) to predict prognosis and intensive care requirement in geriatric patient with PE. Results: The median age of 132 patients was 77 (71–82) years. PESI was higher in the non-survivor group [132 (113–172)] (P =0.001). The median REMS was 8 (7–10), and it was higher in the non-survivor group [10 (7.5–12.0)] (p = 0.005). The median HOTEL score was 1 (0–2) in the whole cohort and 2 (1–3) in the non-survivor group, indicating significant difference compared to the survivor group (P = 0.001). The area under the curve (AUC) values of HOTEL, REMS, and PESI were determined as 0.72, 0.65, and 0.71, respectively. For the prediction of intensive care requirement, the AUC values of HOTEL, REMS, and PESI were 0.76, 0.75, and 0.76, respectively, with no significant difference in pairwise comparisons (PESI vs. REMS: p = 0.520, HOTEL vs. PESI: P = 0.526, REMS vs. HOTEL: P = 0.669, overall test: P = 0.96, DeLong's test). The risk ratios of HOTEL and PESI were parallel to each other [5.31 (95% confidence interval (CI): 2.53–11.13) and 5.34 (95% CI: 2.36–12.08), respectively]. Conclusion: HOTEL and REMS were as successful as PESI in predicting short-term mortality and intensive care requirement in geriatric patients with PE. These scores are also more practical since they have fewer parameters than PESI. [ABSTRACT FROM AUTHOR]

The aim of this study is to determine the effect of nursing guide application (NGA) on patient outcomes in patients followed up according to the modified early warning score (MEWS) in the postoperative period. A randomized controlled clinical trial. The sample of the study consisted of 252 patients who underwent surgical intervention under general anesthesia in a university hospital between July 29, 2022, and October 31, 2022. Results showed that the development of complications was less in the study group (SG) compared to the control group (CG) during anesthesia (P =.027), in the postanesthesia care unit (PACU) (P =.017), and in the clinic (P =.001). It was found that the duration of stay in PACU in the CG was significantly shorter than in the study group (P <.001), and as the duration of stay in PACU in CG decreased, the MEWS increased (r = −0.201, P =.024). We found that there were fewer patients transferred to the intensive care unit (ICU) after PACU (P =.007), the MEWS was lower, and the number of nursing interventions applied to patients was higher (P <.05). In patients followed up according to MEWS, NGA had a positive effect on preventing the development of complications and shortening the intervention time for complications, decreasing ICU admission, decreasing MEWS and increasing the number of nursing interventions. Based on the results, it may be recommended to use MEWS+NGA in the early postoperative period as it positively affects patient outcomes. [ABSTRACT FROM AUTHOR]

Each year, 245,000 people in the UK develop sepsis, with most cases arising in primary care (Rudd et al, 2020). Currently, around 20% of people who develop sepsis do not survive (Burki, 2018), and approximately 40% of survivors have cognitive or functional impairment (Prescott and Angus, 2018). In an effort to save lives and improve outcomes, the National Institute for Health and Care Excellence (NICE), in common with other international guidelines, has recommended that sepsis is treated within an hour with broad-spectrum antibiotics (Academy of Medical Royal Colleges, 2022). On the 31 January 2024, NICE updated its NG51 guideline for the UK, which was originally published in 2016. The update includes recommendations on recognition and early assessment, initial treatment, escalating care, finding the source of infection, early monitoring, and information and support. This article updates readers on changes to the NICE guidance and how they affect clinical practice. [ABSTRACT FROM AUTHOR]

Copyright of Ciencia, Cuidado e Saude is the property of Universidade Estadual de Maringa and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: Early warning scores (EWS) are routinely used in hospitals to assess a patient's risk of deterioration. EWS are traditionally recorded on paper observation charts but are increasingly recorded digitally. In either case, evidence for the clinical effectiveness of such scores is mixed, and previous studies have not considered whether EWS leads to changes in how deteriorating patients are managed. Objective: This study aims to examine whether the introduction of a digital EWS system was associated with more frequent observation of patients with abnormal vital signs, a precursor to earlier clinical intervention. Methods: We conducted a 2-armed stepped-wedge study from February 2015 to December 2016, over 4 hospitals in 1 UK hospital trust. In the control arm, vital signs were recorded using paper observation charts. In the intervention arm, a digital EWS system was used. The primary outcome measure was time to next observation (TTNO), defined as the time between a patient's first elevated EWS (EWS ≥3) and subsequent observations set. Secondary outcomes were time to death in the hospital, length of stay, and time to unplanned intensive care unit admission. Differences between the 2 arms were analyzed using a mixed-effects Cox model. The usability of the system was assessed using the system usability score survey. Results: We included 12,802 admissions, 1084 in the paper (control) arm and 11,718 in the digital EWS (intervention) arm. The system usability score was 77.6, indicating good usability. The median TTNO in the control and intervention arms were 128 (IQR 73-218) minutes and 131 (IQR 73-223) minutes, respectively. The corresponding hazard ratio for TTNO was 0.99 (95% CI 0.91-1.07; P =.73). Conclusions: We demonstrated strong clinical engagement with the system. We found no difference in any of the predefined patient outcomes, suggesting that the introduction of a highly usable electronic system can be achieved without impacting clinical care. Our findings contrast with previous claims that digital EWS systems are associated with improvement in clinical outcomes. Future research should investigate how digital EWS systems can be integrated with new clinical pathways adjusting staff behaviors to improve patient outcomes. [ABSTRACT FROM AUTHOR]

Copyright of Revista Ciencias de la Salud is the property of Colegio Mayor de Nuestra Senora del Rosario and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: During the coronavirus disease 2019 (COVID-19) pandemic, early warning scores (EWS) have been used to help emergency physicians with triage. This study aimed to evaluate the threemost used EWSs: Rapid Emergency Medicine Score (REMS), Modified Early Warning Score (MEWS), and National EarlyWarning Score (NEWS), based on the in-hospital mortality of geriatric patients with COVID-19. Methods: This retrospective, single-center study included geriatric patients hospitalized for COVID-19 from May 2021 to July 2021 at the MacKay Memorial Hospital. Patients who (i) presented with out- of-hospital cardiac arrest (OHCA), (ii) were transferred fromother hospitals, and (iii) hadmissing demographic data were excluded. The area under the receiver operating characteristic curve (AUC) was calculated to predict the in-hospital mortality rate associated with each EWS. Results: The study included 135 patients, of whom24 (17.8%) died. Themedian age of the included patients was 74.44 years, and 53% of them were men. Of the selected EWSs, MEWS (AUC = 0.761) exhibited the highest prognostic value, with a cutoff value of 3.5. Furthermore, NEWS (AUC = 0.758) and REMS (AUC = 0.736) exhibited good prognostic value. Conclusion: We validated the three most used EWSs, and MEWS performed well in predicting the in-hospital mortality of geriatric patients with COVID-19 using basic parameters. [ABSTRACT FROM AUTHOR]

A delay in detecting acute hypertensive crisis in postpartum mothers can exacerbate complications in the mother. Neonatal nurses are uniquely qualified to identify postpartum warning signs in mothers while they are in the NICU with their infants. Few research studies have explored the use of neonatal nurse screenings for acute hypertensive crisis in postpartum mothers. NICU nurses screening mothers for postpartum depression has yielded success in improving outcomes, and this model could be translated into screening for acute hypertensive crisis. Further education should be implemented for NICU nurses that include a review of adult blood pressure monitoring, early warning signs, and symptoms of preeclampsia that the mother should report. This article discusses the importance of the neonatal nurse's role in identifying early warning signs of maternal postpartum hypertensive crisis. [ABSTRACT FROM AUTHOR]

Objective: Acute exacerbations of COPD (AECOPD) are common causes of hospitalization. Various scoring systems have been proposed to classify the risk of clinical deterioration or mortality in hospitalized patients with AECOPD. We sought to investigate whether clinical deterioration and mortality scores at admission can predict adverse events occurring during hospitalization and after discharge of patients with AECOPD. Methods: We performed a retrospective study of patients admitted with AECOPD. The National Early Warning Score 2 (NEWS2), the NEWS288-92%, the Dyspnea, Eosinopenia, Consolidation, Acidemia, and atrial Fibrillation (DECAF) score, and the modified DECAF (mDECAF) score were calculated at admission. We assessed the sensitivity, specificity, and overall performance of the scores for the following outcomes: in-hospital mortality; need for invasive mechanical ventilation or noninvasive ventilation (NIV); long hospital stays; hospital readmissions; and future AECOPD. Results: We included 119 patients admitted with AECOPD. The median age was 75 years, and 87.9% were male. The NEWS288-92% was associated with an 8.9% reduction in the number of individuals classified as requiring close, continuous observation, without an increased risk of death in the group of individuals classified as being low-risk patients. The NEWS288-92% and NEWS2 scores were found to be adequate in predicting the need for acute NIV and longer hospital stays. The DECAF and mDECAF scores were found to be better at predicting in-hospital mortality than the NEWS2 and NEWS288-92%. Conclusions: The NEWS288-92% safely reduces the need for clinical monitoring in patients with AECOPD when compared with the NEWS2. The NEWS2 and NEWS288-92% appear to be good predictors of the length of hospital stay and need for NIV, but they do not replace the DECAF and mDECAF scores as predictors of mortality. [ABSTRACT FROM AUTHOR]

Background: Necrotizing enterocolitis (NEC) risk has been shown to arise from multiple sources and risk awareness may be supported using bedside tools. Purpose: The purpose of this research was to examine the extent to which GutCheckNEC was associated with scores for clinical deterioration, severity of illness, and clinical outcome, and further to examine how scores might improve NEC prediction. Methods: A retrospective, correlational case-control study with infant data from 3 affiliated neonatal intensive care units was conducted. Results: Of 132 infants (44 cases, 88 controls), most were 28 weeks of gestation at birth and less (74%). Median age at NEC onset was 18 days (range: 6-34 days), with two-thirds diagnosed before 21 days. At 68 hours of life, higher GutCheckNEC scores were associated with NEC requiring surgery or resulting in death (relative risk ratio [RRR] = 1.06, P =.036), associations that persisted at 24 hours prior to diagnosis (RRR = 1.05, P =.046), and at the time of diagnosis (RRR = 1.05, P =.022) but showed no associations for medical NEC. GutCheckNEC scores were significantly correlated with pediatric early warning scores (PEWS) (r > 0.30; P <.005) and SNAPPE-II scores (r > 0.44, P <.0001). Increasing numbers of clinical signs and symptoms were positively associated with GutCheckNEC and PEWS at the time of diagnosis (r = 0.19, P =.026; and r = 0.25, P =.005, respectively). Implications for Practice and Research: GutCheckNEC provides structure to streamline assessment and communication about NEC risk. Yet, it is not intended to be diagnostic. Research is needed on how GutCheckNEC impacts timely recognition and treatment. [ABSTRACT FROM AUTHOR]

With the development of the times, online courses have become more and more popular, and learning early warning models have become increasingly widely used. Learning early warning models can monitor students' online behavior, thereby achieving the effect of enabling students to consciously learn. However, the learning early warning model is still not perfect. Therefore, this article focused on the application of multimodal information analysis in learning early warning models, aiming to further improve the learning early warning model through multimodal information analysis. This article tested the classroom test scores of students using a learning early warning system using multimodal information analysis and those not using a learning early warning system using multimodal information analysis through experiments. It was found that the scores of students using multimodal information analysis were concentrated between 70 and 90 points, while the scores of students not using multimodal information analysis were concentrated between 60 and 70 points. From the results of this experimental data, it can be seen that students with multimodal information analysis have better scores in learning early warning models, which indicates that multimodal information analysis is conducive to the improvement of learning early warning models. [ABSTRACT FROM AUTHOR]

The SAAD Digest CPD questions 2023 - the answers provides answers to multiple-choice questions related to various topics in dental care. The questions cover subjects such as the impact of misophonia on dental care, COVID-19 vaccination and dental sedation, pain and anxiety management in pregnant dental patients, and the use of dexmedetomidine as an alternative medication in children with autism. The document also includes information on the use of Amsed for conscious sedation in adults with learning disabilities, referrals for treatment with additional pharmacological support in children, and complications and outcomes associated with midazolam conscious sedation. The summary provides a brief overview of the topics covered in the document, allowing library patrons to determine if they want to explore the full text further. [Extracted from the article]

A number of risks exist in commercial housing, and it is critical for the government, the real estate industry, and consumers to establish an objective early warning indicator system for commercial housing risks and to conduct research regarding its measurement and early warning. In this paper, we examine the commodity housing market and construct a risk index for the commodity housing market at three levels: market level, the real estate industry and the national economy. Using the Bootstrap aggregating-grey wolf optimizer-support vector machine (Bagging-GWO-SVM) model after synthesizing the risk index by applying the CRITIC objective weighting method, the commercial housing market can be monitored for risks and early warnings. Based on the empirical study, the following conclusions have been drawn: (1) The commodity housing market risk index accurately reflect the actual risk situation in Tianjin; (2) Based on comparisons with other models, the Bagging-GWO-SVM model provides higher accuracy in early warning. A final set of suggestions is presented based on the empirical study. [ABSTRACT FROM AUTHOR]

Background: Cardiac arrests are often preceded by several hours of physiological deterioration that may go undetected. Local Problem: Cardiac arrests frequently occurred on medical-surgical units without prior rapid response team intervention. Methods: A pre/postintervention design was used to evaluate a protocol to guide the use of the Modified Early Warning Score (MEWS) by medical-surgical nurses to escalate the care of deteriorating adult patients. Interventions: Following staff education, the MEWS protocol was implemented across 8 medical-surgical units. Results: There was a significant increase in patients experiencing a rapid response prior to a cardiac arrest after implementing the MEWS protocol (P <.0001). Conclusion: Implementing a consistent review of MEWS values allows medical-surgical nurses to initiate assistance from a rapid response team that may prevent an inpatient cardiac arrest. [ABSTRACT FROM AUTHOR]

Use of the revised National Early Warning Score (NEWS) 2, a tool used to measure acute deterioration in hospital, is mandatory in acute NHS hospitals and ambulance services. Community staff who wish to escalate acutely unwell people to ambulance or acute services need to be able to use NEWS. This article outlines the uses and limitations of NEWS and how it can aid identification and escalation of people who are acutely unwell in community settings, including those with suspected sepsis. [ABSTRACT FROM AUTHOR]

Early recognition of clinical deterioration plays a pivotal role in a Rapid Response System (RRS), and it has been a crucial step in reducing inpatient morbidity and mortality. Traditional Early Warning Scores (EWS) and Deep Early Warning Scores (DEWS) for identifying patients at risk are still limited because of the challenges of imbalanced multivariate temporal data. Typical issues leading to their limitations are low sensitivity, high late alarm rate, and lack of interpretability; this hinders the system's deployment in clinical settings. This study develops an EWS based on Temporal Variational Autoencoder (TVAE) and a window interval learning framework, which uses the latent space features generated from the input multivariate temporal features, to learn the temporal dependence distribution between the target labels (clinical deterioration probability). Implementing the target information in the Fully Connected Network (FCN) with a loss function assists in addressing the imbalance problem and improving the performance of the time series classification task. The proposed method is validated on an in-house clinical dataset collected from Chonnam National University Hospitals (CNUH) and a public dataset from the University of Virginia (UV). Extensive trials with diverse validation methods and study cases demonstrate that our system outperforms existing methods, showcasing remarkable performance across usual criteria for classification models, typically as the Area Under The Receiver Operating Characteristic Curve (AUROC) and the Area Under The Precision-Recall Curve (AUPRC). TVAE exhibits a notable decrease in late alarm issues across two datasets, presenting stable performance even with a limited number of data samples. [Display omitted] • Predicting a patient's deterioration is an urgent problem for healthcare system. • Medical data characteristics pose challenges for deep learning applications. • Proposed approach boosts early recognition, enhancing patient care. • Extensive trials confirm superior performance over other methods. • Ongoing integration into hospital systems for practical clinical application and enhanced care. [ABSTRACT FROM AUTHOR]

• Heart rate variability (HRV) provides non-invasive and continuous monitoring for early detection of deterioration in septic patients by reflecting the sympathovagal imbalance. • We developed HRV based machine learning models to predict sepsis and septic shock 120 mins in advance for patients with suspected sepsis. • Our model outperformed the conventional scoring systems (delta SOFA, NEWS, MEWS) in predicting clinical deterioration in patients with suspected sepsis, and was externally validated on the Medical Information Mart for Intensive Care III (MIMIC-III) database. To develop and compare heart rate variability (HRV) based machine learning algorithms for septic shock and sepsis prediction against established metrics validated on the Medical Information Mart for Intensive Care III (MIMIC-III) database for early detection of septic patient deterioration. We developed HRV-based prediction models in a prospective cohort study in an emergency department (ED). Adult patients with a clinical diagnosis of infection and suspected sepsis were recruited in our ED between April 2016 and September 2017. Different machine learning algorithms were trained to continuously predict septic shock onset 120 min ahead on the included patients using HRV obtained in five-minute intervals. We further applied transfer learning among patients with Sepsis-3 in the MIMIC- III database. We recruited and included 38 and 755 patients with a total recording time of 360 and 19,321 patient hours from our ED and the MIMIC-III database, respectively. The extreme gradient boosting (XGBoost) model outperformed other machine learning models and conventional models including the delta SOFA score, National Early Warning Score (NEWS), and Modified Early Warning Score (MEWS) in predicting septic shock (AUROC: 0.94; 95% CI: 0.91–0.96) during internal validation. After transfer learning, the XGBoost model had an AUROC of 0.91 (95% CI: 0.90–0.91) to predict septic shock in patients with Sepsis-3 in the MIMIC-III database. HRV-based XGBoost models provide a promising non-invasive tool for early septic shock prediction and patient deterioration due to infection, potentially enhancing patient management strategies. [ABSTRACT FROM AUTHOR]

Background: Wearable devices could be used to continuously monitor vital signs in patients who are hospitalized, but they require validation. Objective: This study aimed to evaluate the clinical validity of the prototype of a semiautomated wearable wrist device (ChroniSense Polso) to measure vital signs and provide National Early Warning Scores (NEWSs). Methods: Vital signs and NEWSs measured using the wearable device were compared with standard, nurse-lead manual measurements. We enrolled adult patients (aged ≥18 years) who required vital sign measurements at least every 6 hours in a UK teaching district general hospital. Wearable device measurements were not used for clinical decision-making. The primary outcome was the agreement on the individual National Early Warning parameter scores and vital sign measurements: respiratory rate, oxygen saturation, body temperature, systolic blood pressure, and heart rate. Secondary outcomes were the agreement on the total NEWS, incidence of adverse events, and user acceptance. To compare the wearable device measurements with the standard measurements, we analyzed vital sign measurements by limits of agreement (Bland-Altman analysis) and conducted κ agreement analyses for NEWSs. A user experience survey was conducted with questions about comfort of the wrist device, safety, preference, and use. Results: We included 132 participants in the study, with a mean age of 62 (SD 15.81) years; most of them were men (102/132, 77.3%). The highest weighted κ values were found for heart rate (0.69, 95% CI 0.57-0.81 for all 385 measurements) and systolic blood pressure (0.39, 95% CI 0.30-0.47 for all 339 measurements). Weighted κ values were low for respiration rate (0.03, 95% CI −0.001 to 0.05 for all 445 measurements), temperature (0, 95% CI 0-0 for all 231 measurements), and oxygen saturation (−0.11, 95% CI −0.20 to −0.02 for all 187 measurements). Weighted κ using Cicchetti-Allison weights showed κ of 0.20 (95% CI 0.03-0.38) when using all 56 total NEWSs. The user acceptance survey found that approximately half (45/91, 49%) of the participants found it comfortable to wear the device and liked its appearance. Most (85/92, 92%) of them said that they would wear the device during their next hospital visit, and many (74/92, 80%) said that they would recommend it to others. Conclusions: This study shows the promising use of a prototype wearable device to measure vital signs in a hospital setting. Agreement between the standard measurements and wearable device measurements was acceptable for systolic blood pressure and heart rate, but needed to be improved for respiration rate, temperature, and oxygen saturation. Future studies need to improve the clinical validity of this wearable device. Large studies are required to assess clinical outcomes and cost-effectiveness of wearable devices for vital sign measurement. International Registered Report Identifier (IRRID): RR2-10.1136/bmjopen-2018-028219 [ABSTRACT FROM AUTHOR]

The shift toward remote patient monitoring methods to detect clinical deterioration requires testing of wearable devices in real-life clinical settings. This study aimed to develop a remote early warning scoring (REWS) system based on continuous measurements using a wearable device, and compare its diagnostic performance for the detection of deterioration to the diagnostic performance of the conventional modified early warning score (MEWS). The study population of this prospective, single center trial consisted of patients who underwent major abdominal cancer surgery and were monitored using routine in-hospital spotcheck measurements of the vital parameters. Heart and respiratory rates were measured continuously using a wireless accelerometer patch (HealthDot). The prediction by MEWS of deterioration toward a complication graded Clavien-Dindo of 2 or higher was compared to the REWS derived from continuous measurements by the wearable patch. A total of 103 patients and 1909 spot-check measurements were included in the analysis. Postoperative deterioration was observed in 29 patients. For both EWS systems, the sensitivity (MEWS: 0.20 95% CI: [0.13–0.29], REWS: 0.20 95% CI: [0.13–0.29]) and specificity (MEWS: 0.96 95% CI: [0.95–0.97], REWS: 0.96 95% CI: [0.95–0.97]) were assessed. The diagnostic value of the REWS method, based on continuous measurements of the heart and respiratory rates, is comparable to that of the MEWS in patients following major abdominal cancer surgery. The wearable patch could detect the same amount of deteriorations, without requiring manual spot check measurements. [ABSTRACT FROM AUTHOR]

OBJECTIVE: COVID-19 patients have been shown to be hypercoagulable, increasing the risk for thromboembolic events. The kinetics of the blood coagulation process were monitored daily throughout hospitalization in COVID-19 positive patients. PATIENTS AND METHODS: Thromboelastography (TEG) was used to assess blood coagulation in 48 adult patients hospitalized for COVID-19 in this prospective cohort study. Clinical risk was assessed via National Early Warning Scores (NEWS) for each day of hospitalization. RESULTS: During hospitalization, 98% of patients had one or more procoagulable TEG result. Thromboelastography results remained prothrombotic upon discharge in 80% of patients. NEWS significantly decreased by discharge compared to the peak scores. CONCLUSIONS: Overall, patients were discharged from the hospital with significant clinical improvement, but without abnormal TEG results returning to a normal range. All patients in our study survived and few had thromboembolic events, so if and for how long these patients remain at risk for future complications warrants further investigation. [ABSTRACT FROM AUTHOR]

Copyright of Cukurova Medical Journal / Çukurova Üniversitesi Tip Fakültesi Dergisi is the property of Cukurova University, Faculty of Medicine and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Cukurova Medical Journal / Çukurova Üniversitesi Tip Fakültesi Dergisi is the property of Cukurova University, Faculty of Medicine and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

• This is the first study to provide accurate septic shock onset prediction using only 5 min of patient's vital signals which makes the proposed models the fastest to provide insights to clinicians. • The proposed models rely only on vital signals unlike other literature models which include lab tests and patient history which might take time to collect. Our models eliminate that dependency on such data. Sepsis is a major public health emergency and one of the leading causes of morbidity and mortality in critically ill patients. For each hour treatment is delayed, shock-related mortality increases, so early diagnosis and intervention is of utmost importance. However, earlier recognition of shock requires active monitoring, which may be delayed due to subclinical manifestations of the disease at the early phase of onset. Machine learning systems can increase timely detection of shock onset by exploiting complex interactions among continuous physiological waveforms. We use a dataset consisting of high-resolution physiological waveforms from intensive care unit (ICU) of a tertiary hospital system. We investigate the use of mean arterial blood pressure (MAP), pulse arrival time (PAT), heart rate variability (HRV), and heart rate (HR) for the early prediction of shock onset. Using only five minutes of the aforementioned vital signals from 239 ICU patients, our developed models can accurately predict septic shock onset 6 to 36 h prior to clinical recognition with area under the receiver operating characteristic (AUROC) of 0.84 and 0.8 respectively. This work lays foundations for a robust, efficient, accurate and early prediction of septic shock onset which may help clinicians in their decision-making processes. This study introduces machine learning models that provide fast and accurate predictions of septic shock onset times up to 36 h in advance. BP, PAT and HR dynamics can independently predict septic shock onset with a look-back period of only 5 mins. [ABSTRACT FROM AUTHOR]

Copyright of Medicina (Buenos Aires) is the property of Medicina (Buenos Aires) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The document is a correction notice for a study titled "Early Prediction of Cardiac Arrest in the Intensive Care Unit Using Explainable Machine Learning: Retrospective Study." The correction addresses errors in Figures 4 and 5 related to model performance and external validation. The study was conducted by authors from various institutions in South Korea and will be updated online with the corrections. [Extracted from the article]

Copyright of Revista Colombiana de Obstetricia y Ginecologia is the property of Federacion Colombiana de Asociaciones de Obstetricia y Ginecologia and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: Inpatient nurses identified the need to recognize clinical deterioration earlier, including rapid response team (RRT) activations and transfers to the intensive care unit. Surveys identified the need for better interdisciplinary communication. Local Problem: A system was needed to detect early clinical deterioration with structured responses promoting multidisciplinary collaboration. Methods: An early warning score (EWS) identified patients at risk. The system ensured timely and accurate actions were taken when scores reached 3 or above. Interventions: Collaborative, graded responses to EWSs and nurse-led rounds promoted communication and timely interventions. Results: Mortality decreased (-27%) as did multiple RRT activations on a single patient (-15%). Nurses are aware of early vital sign changes (+45%) and resident responsiveness has improved. There has been an increase in nurse/resident communication satisfaction (+31%). Conclusions: The system implemented reinforces the importance of patient assessment, collaboration among the multidisciplinary team, and promotes early interventions. [ABSTRACT FROM AUTHOR]

• Following the introduction of the EWS in the ED, identification of the most serious patients (i.e. MTS 1) remained stable, however, staff were more likely to place other patients in a higher risk category. • Post EWS implementation, patients allocated an MTS of 2–5 waited significantly longer to see a clinician and overall spent a longer period of time in the ED. • Once introduced, staff were consistent in how they approached the allocation of MTS in conjunction with the EWS. • The effective and sustained combined use of the MTS and EWS in the ED requires resources in terms of increased bed capacity and experienced clinical staff. The combined use of the Manchester Triage System (MTS) with the Early Warning Score (EWS) may be useful in ensuring both appropriate prioritisation and continued monitoring in the Emergency Department (ED) leading to early intervention for deteriorating patients thus improving patient outcomes especially in overcrowded EDs. Determine the effect of the EWS and MTS on accuracy of the MTS and ED waiting times. A retrospective cohort chart review of all adult patients who presented to the ED in one large hospital in Ireland (n = 10,048) at three time points between 1st September 2015-30th September 2016; 3 months prior to EWS introduction, implementation month and 9 months post-implementation. Patients were significantly more likely to be categorised as an MTS category 2 (rather than 3–5) after the EWS was introduced (p < 0.001). Waiting times between triage and clinician review (p < 0.05) increased as did total time in the ED (p > 0.001). A similar finding was observed for patients with an MTS of 3–5. Although positive in terms of patient outcomes, the effective and sustained combined use of the MTS and EWS requires increased bed capacity and experienced clinical staff to ensure that the ED journey time reduced rather than increased. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The purpose of this study was to identify and compare barriers and enablers to the implementation of the Children's Hospital Early Warning Score (CHEWS) on a pediatric inpatient unit pre- and post-implementation. A qualitative descriptive design, guided by the Theoretical Domains Framework, was used to conduct semi-structured focus groups and individual interviews with nurses on a pediatric inpatient unit to identify barriers and enablers in the pre- and post- CHEWS implementation phases. Data were analyzed using a directed content analysis approach followed by inductive thematic analysis. Two pre-implementation focus groups (N = 15) and 8 post-implementation individual interviews with nurses were conducted. We identified pre- and post- CHEWS implementation barriers related to clinical decision making, interprofessional relationships, the unit context, and negative emotions, and enablers related to quality of care and patient safety. The identified barriers and enablers to implementation were categorized within 13 TDF domains. Our findings illustrate a range of barriers and enablers to CHEWS implementation during the pre- and post-implementation phases. Tailored strategies are needed to overcome barriers related to nurses' perceptions of CHEWS impeding clinical decision-making and interprofessional collaboration. By addressing the identified barriers, we can leverage nurses' motivations for using CHEWS to improve the quality of patient care and enhance patient safety. The barriers and enablers identified in this study can be used to select implementation strategies to support the use of early warning systems in pediatric nursing practice. • Early warning systems detect signs of clinical deterioration in patients. • Multi-level barriers to the implementation of an early warning system exist. • Barriers related to nurses' clinical decision-making when using CHEWS were identified. • Challenges with interprofessional collaboration were identified at the interpersonal level. • Tailored strategies are needed to facilitate the use of early warning scores in practice. [ABSTRACT FROM AUTHOR]

In large acute medical wards treating heterogenous and complex patients, intensity of patient care should be graduated according to clinical severity. We conducted a retrospective observational study on all unselected admissions (8838) to the internal medicine ward of the Santa Chiara Hospital of Trento from 2012 to 2017. During 2012 and 2013, a standard organizational model (SMC) was in place, while an organizational model for intensity of medical care (IMC) was introduced in 2014. In SMC, patient admission was performed according to bed availability only. In IMC, patients were allocated to three different ward settings (high, medium and post-acute care) based on the stratification of clinical instability. The National Early Warning Score (NEWS) was used for the stratification, together with the clinical judgment. The implementation of the IMC model led to a decrease of mortality and urgent transfers for clinical deterioration to Intensive Care Unit and to an increase of admissions from Intensive Care Unit and from regional spoke hospitals. Redesigning delivery processes based on IMC can play a pivotal role in improving patient outcomes and bed management. [ABSTRACT FROM AUTHOR]

The modified early warning score (MEWS) is used to detect clinical deterioration of hospitalized patients. We aimed to investigate the predictive value of MEWS and derived quick Sequential Organ Failure Assessment (qSOFA) scores for intensive care unit admission in patients with a hematologic malignancy admitted to the ward. Retrospective, observational study in two Dutch university hospitals. Data from adult patients with a hematologic malignancy, admitted to the ward over a 2-year period, were extracted from electronic patient files. Intensive care admission. We included 395 patients with 736 hospital admissions; 2% (n = 15) of admissions resulted in admission to the intensive care unit. A higher MEWS (OR 1.5; 95 %CI 1.3–1.80) and qSOFA (OR 4.4; 95 %CI 2.1–9.3) were associated with admission. Using restricted cubic splines, a rise in the probability of admission for a MEWS ≥ 6 was observed. The AUC of MEWS for predicting admission was 0.830, the AUC of qSOFA was 0.752. MEWS was indicative for intensive care unit admission two days before admission. MEWS was a sensitive predictor of ICU admission in patients with a hematologic malignancy, superior to qSOFA. Future studies should confirm cut-off values and identify potential additional characteristics, to further enhance identification of critically ill hemato-oncology patients. The Modified Early Warning Score (MEWS) can be used as a tool for healthcare providers to monitor clinical deterioration and predict the need for intensive care unit admission in patients with a hematologic malignancy. Yet, consistent application and potential reevaluation of current thresholds is crucial. This will enable bedside nurses to more effectively identify patients needing adjunctive care, facilitating timely interventions and improved outcome. [ABSTRACT FROM AUTHOR]

Abstract Background Early Warning Scores were introduced into acute hospitals in 2000. 99% of acute hospitals employ a EWS to monitor deteriorating patients with 97.9% of these linked to a referral protocol. Despite this high level of adoption, there has been little improvement in the recognition and response to deteriorating patients over the last decade. Objective To explore the patterns of compliance with Early Warning Track and Trigger Tools. Design A narrative review. Data sources Electronic databases (Medline, CIHAHL, EmBase, the Cochrane library, the Centre for Reviews and Dissemination (CRD) and PROSPERO) were searched from 1 January 2000 to 5 July 2018. Titles, abstracts and full text papers were screened (two independent reviewers) against inclusion criteria and seven papers were included in the review. Data were extracted by one reviewer and checked by a second reviewer using a bespoke data collection sheet. Review methods All papers were quantitative in design but demonstrated clinical and methodological heterogeneity therefore a meta-analysis was not possible. A qualitative approach was undertaken to synthesise findings using a framework analysis and narrative synthesis. Themes were identified, named, defined and reported according to outcome measure. Results 7/27 papers representing over 3000 patients and 963,000 data points were included in the analysis. Reported studies were conducted in the United Kingdom (n = 4), Denmark (n = 2) and Amsterdam (n = 1). Three key themes were identified, early warning score calculation accuracy, monitoring frequency and clinical response. This review identifies poor compliance with the Early Warning Score (EWS) protocol in all three themes. There is significant scoring inaccuracy with omitted EWS, missing elements of the EWS and incorrectly calculated EWS. Adherence to monitoring frequency is poor with a higher EWS being associated with reduced compliance with the escalation protocol. There is inadequate compliance with the escalation element of the EWS protocol with concerning extended delays to clinical review. There is evidence of worsening clinical response with increasing EWS. Although significant improvement is demonstrated in clinical response with the use of electronic EWS protocols, non-compliance still occurs at all EWS stages. Conclusion Compliance with EWS is poor but the cause is unidentified. Outcomes can only improve if staff complete the EWS fully, calculate the score accurately, monitor according to protocol and escalate according to clinical response. Social, environmental and professional behaviours that affect effective use of track and trigger tools should be explored to improve our understanding of suboptimal management of the deteriorating patient. [ABSTRACT FROM AUTHOR]

Background: Limited data exist describing supportive care management, laboratory abnormalities and outcomes in patients with Ebola virus disease (EVD) in West Africa. We report data which constitute the first description of the provision of enhanced EVD case management protocols in a West African setting.Methods: Demographic, clinical and laboratory data were collected by retrospective review of clinical and laboratory records of patients with confirmed EVD admitted between 5 November 2014 and 30 June 2015.Results: A total of 44 EVD patients were admitted (median age 37 years (range 17-63), 32/44 healthcare workers), and excluding those evacuated, the case fatality rate was 49% (95% CI 33%-65%). No pregnant women were admitted. At admission 9/44 had stage 1 disease (fever and constitutional symptoms only), 12/44 had stage 2 disease (presence of diarrhoea and/or vomiting) and 23/44 had stage 3 disease (presence of diarrhoea and/or vomiting with organ failure), with case fatality rates of 11% (95% CI 1%-58%), 27% (95% CI 6%-61%), and 70% (95% CI 47%-87%) respectively (p = 0.009). Haemorrhage occurred in 17/41 (41%) patients. The majority (21/40) of patients had hypokalaemia with hyperkalaemia occurring in 12/40 patients. Acute kidney injury (AKI) occurred in 20/40 patients, with 14/20 (70%, 95% CI 46%-88%) dying, compared to 5/20 (25%, 95% CI 9%-49%) dying who did not have AKI (p = 0.01). Ebola virus (EBOV) PCR cycle threshold value at baseline was mean 20.3 (SD 4.3) in fatal cases and 24.8 (SD 5.5) in survivors (p = 0.007). Mean national early warning score (NEWS) at admission was 5.5 (SD 4.4) in fatal cases and 3.0 (SD 1.9) in survivors (p = 0.02). Central venous catheters were placed in 37/41 patients and intravenous fluid administered to 40/41 patients (median duration of 5 days). Faecal management systems were inserted in 21/41 patients, urinary catheters placed in 27/41 and blood component therapy administered to 20/41 patients.Conclusions: EVD is commonly associated life-threatening electrolyte imbalance and organ dysfunction. We believe that the enhanced levels of protocolized care, scale and range of medical interventions we report, offer a blueprint for the future management of EVD in resource-limited settings. [ABSTRACT FROM AUTHOR]

Objective systematic monitoring has recently been implemented widely in non-obstetric departments. In the UK, Early Warning Score (EWS) systems specifically designed for the obstetric population (OEWS) are used. No information on the use of OEWS in Scandinavia has been reported. Consequently, we wanted to investigate the use of vital signs and attitude towards systematic monitoring of parturients in Denmark, Norway and Sweden. Design electronic questionnaires sent to heads of midwifery. The heads of midwifery referred two clinically active midwives. All in-hospital obstetric departments in Scandinavia were invited to participate. Findings heads of midwifery from 76 departments (68%), and 125 clinical midwives (82%) responded. Ten per cent of midwives reported use of OEWS. Reported implementation barriers to OEWS included lack of evidence and suspected impact on the parturient due to frequent interruptions. fifty-four per cent of clinical midwives reported a systolic blood pressure threshold of 90–139 mmHg, while 33% reported a threshold of>160 mmHg. Ninety-three per cent stated a low threshold for maternal heart rate<60 bpm whereas 10% reported an upper threshold heart rate ≥ 150 bpm. Forty-seven per cent reported call for assistance thresholds for maternal heart rate at 60–110 bpm. Key conclusions OEWS is not implemented in Scandinavian obstetric departments and reported thresholds of vital signs varied considerably. Major barriers for implementation in Scandinavia include midwives’ concern of interruptions for the parturient and increased workload, and unclear benefit from use of OEWS. Local departments should provide midwives with unambiguous thresholds for vital signs in parturients either through local guidelines or via OEWS. [ABSTRACT FROM AUTHOR]

Objective Early warning scores, such as the Children's Hospital Early Warning Score (CHEWS), are used by hospitals to identify patients at risk for critical deterioration and trigger clinicians to intervene and prevent further deterioration. This study's objectives were to validate the CHEWS and to compare the CHEWS to the previously validated Brighton Pediatric Early Warning Score (PEWS) for early detection of critical deterioration in hospitalized, non-cardiac patients at a pediatric hospital. Design and Methods A retrospective cohort study reviewed medical and surgical patients at a quaternary academic pediatric hospital. CHEWS scores and abstracted PEWS scores were obtained on cases (n = 360) and a randomly selected comparison sample (n = 776). Specificity, sensitivity, area under the receiver-operating characteristic curves (AUROC) and early warning times were calculated for both scoring tools. Results The AUROC for CHEWS was 0.902 compared to 0.798 for PEWS ( p < 0.001). Sensitivity for scores ≥ 3 was 91.4% for CHEWS and 73.6% for PEWS with specificity of 67.8% for CHEWS and 88.5% for PEWS. Sensitivity for scores ≥ 5 was 75.6% for CHEWS and 38.9% for PEWS with specificity of 88.5% for CHEWS and 93.9% for PEWS. The early warning time from critical score (≥ 5) to critical deterioration was 3.8 h for CHEWS versus 0.6 h for PEWS ( p < 0.001). Conclusion The CHEWS system demonstrated higher discrimination, higher sensitivity and longer early warning time than the PEWS for identifying children at risk for critical deterioration. [ABSTRACT FROM AUTHOR]

Background: Patients in general medical-surgical wards who experience unplanned transfer to the intensive care unit (ICU) show evidence of physiologic derangement 6-24h prior to their deterioration. With increasing availability of electronic medical records (EMRs), automated early warning scores (EWSs) are becoming feasible.Objective: To describe the development and performance of an automated EWS based on EMR data.Materials and Methods: We used a discrete-time logistic regression model to obtain an hourly risk score to predict unplanned transfer to the ICU within the next 12h. The model was based on hospitalization episodes from all adult patients (18years) admitted to 21 Kaiser Permanente Northern California (KPNC) hospitals from 1/1/2010 to 12/31/2013. Eligible patients met these entry criteria: initial hospitalization occurred at a KPNC hospital; the hospitalization was not for childbirth; and the EMR had been operational at the hospital for at least 3months. We evaluated the performance of this risk score, called Advanced Alert Monitor (AAM) and compared it against two other EWSs (eCART and NEWS) in terms of their sensitivity, specificity, negative predictive value, positive predictive value, and area under the receiver operator characteristic curve (c statistic).Results: A total of 649,418 hospitalization episodes involving 374,838 patients met inclusion criteria, with 19,153 of the episodes experiencing at least one outcome. The analysis data set had 48,723,248 hourly observations. Predictors included physiologic data (laboratory tests and vital signs); neurological status; severity of illness and longitudinal comorbidity indices; care directives; and health services indicators (e.g. elapsed length of stay). AAM showed better performance compared to NEWS and eCART in all the metrics and prediction intervals. The AAM AUC was 0.82 compared to 0.79 and 0.76 for eCART and NEWS, respectively. Using a threshold that generated 1 alert per day in a unit with a patient census of 35, the sensitivity of AAM was 49% (95% CI: 47.6-50.3%) compared to the sensitivities of eCART and NEWS scores of 44% (42.3-45.1) and 40% (38.2-40.9), respectively. For all three scores, about half of alerts occurred within 12h of the event, and almost two thirds within 24h of the event.Conclusion: The AAM score is an example of a score that takes advantage of multiple data streams now available in modern EMRs. It highlights the ability to harness complex algorithms to maximize signal extraction. The main challenge in the future is to develop detection approaches for patients in whom data are sparser because their baseline risk is lower. [ABSTRACT FROM AUTHOR]

Objective: We examined whether an early warning score (EWS) could predict inpatient complications in surgical patients. Background: Abnormal vitals often precede in-hospital mortality. The EWS calculated using vital signs has been developed to identify patients at risk for mortality. Methods: Inpatient general surgery procedures with National Surgical Quality Improvement Project data from 2013 to 2014 were matched with enterprise data on vital signs and neurologic status to calculate the EWS for each postoperative vital set measured on the ward. Outcomes of major complications, unplanned intensive care unit transfer, and medical emergency team activation were classified using the Clavien-Dindo system as grade I to V. Relationship with EWS and timing of complication was assessed using Kruskal-Wallis test and linear regression accounting for clustering with generalized estimating equation. Results: Among 552 patients admitted to the ward postsurgery, 68 (12.3%) developed at least one grade I to III complication and 37 (6.7%) developed a grade IV/V complication. The mean maximum EWS was significantly higher preceding grade IV/V complications (10.1) compared with grade I to III complications (6.4) or across the hospital stay in patients without complications (5.4; P < 0.01). EWS significantly increased in the 3 days preceding grade IV/V complications (P < 0.001) and declined in patients without complications in the 3 days before discharge (P<0.001). A threshold EWS of 8 predicted occurrence of grade IV/V complications with 81% sensitivity and 84% specificity. Conclusions: Critical postoperative complications can be preceded by rising EWS. Interventional studies are needed to evaluate whether EWS can reduce the severity of postoperative complications and mortality for surgical patients through early identification and intervention. [ABSTRACT FROM AUTHOR]

Aim: The aim of this study was to evaluate adherence to an intervention optimizing in-hospital monitoring practice, by introducing early warning scoring (EWS) of vital parameters. Background: Interventions comprising EWS systems reduce in-hospital mortality, but evaluation of adherence to such interventions is required to correctly interpret interventional outcome. Method: Adherence was evaluated with a mixed-methods approach. Quantitative data, obtained pre-interventionally (2009) and postinterventionally (2010 and 2011), were used to calculate and compare time intervals between scorings of vital parameters. Semi-structured interviews were used to evaluate the implementation process. Results: We found significant reductions in time intervals between measurements of vital parameters in 2011 compared to 2009. Scorings of vital parameters were repeated within 8 hours in 71-77% of patients scoring total modified EWS levels of 0,2 or 4. The theme Motivation by clinical relevance and meaningfulness was identified as crucial to the implementation process. Conclusion: High adherence to an intervention may be strongly related to nurses' perceived clinical relevance of the intervention. [ABSTRACT FROM AUTHOR]

The hospital internal medicine (IM) needs to adapt to the socio-demographic changes occurred during the last thirty years: patients currently show an increased overall complexity owing to the increase in the average age of the patients admitted, to more several and severe comorbidities, and a higher concentration in our wards of most severe cases. Our departments have to change in order to pursue a more efficient organization and to offer care to users modulated according to their needs and conditions. The Intensity of Care in Internal Medicine Group of the Federation of Associations of Hospital Doctors on Internal Medicine - Lazio carried out a population-based study in eight Internal Medicine wards of the region with the aim of characterizing the patients there admitted, using the modified early warning score (mEWS), monitoring and evaluating the outcomes of hospitalization. This has allowed us to determine the cut-off of the score indicating a greater statistical probability of a fatal outcome corresponding to 3, contrary to what originally reported by Subbe et al. in 2001. According to our results into the Departments of IM should be provided an area of high care, where monitor and stabilize the patients admitted with a mEWS score ≥ 3, before transferring them to the wards of lower intensity of care. This organizational model of the high care of medical patients has the benefit of offer the technical and professional assistance appropriate to the level of clinical risk, with more intensive care to more critical stages of illness. [ABSTRACT FROM AUTHOR]

Objectives: to evaluate accuracy, sensitivity, specificity and inter-rater agreement of AVPU (Alert, Voice, Pain, Unresponsive) when used by non-specialist nursing staff assessing consciousness, and to investigate users' views. Methods: Video-recorded simulations of assessments of consciousness were developed and verified by an expert panel. Participants scored simulations using AVPU and completed questionnaires eliciting views on the scale. AVPU scores were compared with functional levels agreed by the panel. Setting: A large urban teaching hospital. Results: Fifty-one participants scored 255 simulations. Overall accuracy was 82.4% (95% CI = 77.7-87.1%), sensitivity 0.94 (95% CI = 0.90-0.98), specificity 0.74 (95% CI = 0.66-0.82) and inter-rater agreement (un-weighted kappa) 0.782. Accuracy was low for simulations depicting an orientated patient whose eyes open to speech (49% correct) and a confused patient with spontaneous eye opening (61.5% correct). Sensitivity and agreement for levels corresponding to ''Alert'' and ''Voice'' were 0.81 (95% CI = 0.69-0.93) and kappa = 0.506. Participants expressed uncertainty about aspects of AVPU's use. Conclusions: AVPU had low rates of accuracy, sensitivity and agreement in distinguishing between ''Alert'' and ''Voice'', and low specificity overall, suggesting it may be unsuitable for early warning scoring. Participants expressed doubts about the use of AVPU. [ABSTRACT FROM AUTHOR]

Abstract: The outcome of cardiac arrest in hospitalized infants and children is poor. However, cardiac arrest is often predictable based on many hours of hypoxaemia, hypotension and associated symptoms and signs (heart rate, respiratory rate, respiratory effort, neurological change) and staff concern. If intensive expert medical and nursing interventions are provided quickly before cardiac arrest, some deaths on wards outside the intensive care environment are preventable. Over the past decade, the introduction of rapid response and early warning systems in some large paediatric hospitals has reduced the incidence of unexpected cardiac arrest by some 40% and death by 20%. These systems enable any staff member (or parent) to summon urgent expert assistance to the patient’s bedside without the need to consult senior staff members. Introduction of a system is a culture change necessitating institutional adoption, extensive education in recognition of the seriously-ill patient, and abolition of hierarchical barriers to obtain rapid assistance. [Copyright &y& Elsevier]

Summary: The purpose of this study was to determine if routine clinical assessment could reliably predict in-hospital death in patients admitted with acute exacerbation of COPD (AECOPD). Methods: In a case-crossover study the case records of AECOPD related deaths were reviewed. Clinical and laboratory variables including performance status (WHO-PS) and a composite physiological score (early warning score, EWS) at initial clinical assessment on final admission (FA) and penultimate admission (PA) for AECOPD were compared. Results: Sixty patients included in study, female 60%, mean age (SD) 75 (8.7) years. 98% had ≥2 admissions for AECOPD. On univariate analysis variables associated with death were: Charlson score, WHO-PS, EWS, pH<7.35, Urea and CRP. On multivariate analysis predictors of mortality were: WHO-PS (OR 95% CI: 4.9 (1.06–22.61); p =0.04) and EWS (OR 95% CI: 3.39 (1.56–7.41); p =0.002). ROC analysis of relationship between combined WHO-PS/EWS score and death gave AUC 0.86; a total score≥6 had sensitivity 78% and specificity 86.2% and on multivariate analysis OR (95% CI) for death was 19.3 (4.3–86.2); p <0.0005. Conclusion: In-hospital deaths from AECOPD may be predicted by assessment of WHO-PS and EWS on admission to hospital. [ABSTRACT FROM AUTHOR]