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Introduction: Few scoring systems are used in the emergency department to identify critically ill patients and anticipate patients' deterioration such as National Early Warning Score (NEWS). This study aimed to evaluate NEWS in patients with acute stroke and its relationship with treatment and type of stroke and patient outcome.Methods: In this prospective cross-sectional descriptive-analytical study, all patients over 18 years of age with a diagnosis of ischemic stroke, who presented through the emergency department, were involved. The variables of interest were collected; the NEWs score was calculated for each patient.Results: In assessing NEWS and its relationship with outcome based on the ROC curve, the area under the curve was equal to 0.417. Considering the high intensity of NEWS above 7, sensitivity, specificity, positive predictive value, negative predictive value, PLR, and NLR were 16.67%, 98.77%, 83.33%, 74.45%, 13.5, 0.84 respectively. In assessing NEWS and its relationship with stroke type on the ROC curve, the (AUC) was equal to 0.526. Considering the high intensity of NEWS above 7, sensitivity, specificity, positive predictive value, negative predictive value, PLR, and NLR were 8.33%, 94.95%, 16.67%, 88.53%, 1.65, and 0.97 respectively.Conclusion: In terms of outcome, NEWS seems to have acceptable specificity and positive and negative predictive values. Regarding the type of stroke, NEWS has an acceptable specificity but it only has a negative predictive value about the non-hemorrhagic type of stroke. This means that if the NEWS number is LOW, the probability is that the type of stroke is ischemic and the patient outcome is good.

Background Various rapid response systems have been developed to detect clinical deterioration in patients. Few studies have evaluated single-parameter systems in children compared to scoring systems. Therefore, in this study we evaluated a single-parameter system called the acute response system (ARS). Methods This retrospective study was performed at a tertiary children’s hospital. Patients under 18 years old admitted from January 2012 to August 2023 were enrolled. ARS parameters such as systolic blood pressure, heart rate, respiratory rate, oxygen saturation, and whether the ARS was activated were collected. We divided patients into two groups according to activation status and then compared the occurrence of critical events (cardiopulmonary resuscitation or unexpected intensive care unit admission). We evaluated the ability of ARS to predict critical events and calculated compliance. We also analyzed the correlation between each parameter that activates ARS and critical events. Results The critical events prediction performance of ARS has a specificity of 98.5%, a sensitivity of 24.0%, a negative predictive value of 99.6%, and a positive predictive value of 8.1%. The compliance rate was 15.6%. Statistically significant increases in the risk of critical events were observed for all abnormal criteria except low heart rate. There was no significant difference in the incidence of critical events. Conclusions ARS, a single parameter system, had good specificity and negative predictive value for predicting critical events; however, sensitivity and positive predictive value were not good, and medical staff compliance was poor.

Abstract Background Retrospective studies have demonstrated that the deep learning-based cardiac arrest risk management system (DeepCARS™) is superior to the conventional methods in predicting in-hospital cardiac arrest (IHCA). This prospective study aimed to investigate the predictive accuracy of the DeepCARS™ for IHCA or unplanned intensive care unit transfer (UIT) among general ward patients, compared with that of conventional methods in real-world practice. Methods This prospective, multicenter cohort study was conducted at four teaching hospitals in South Korea. All adult patients admitted to general wards during the 3-month study period were included. The primary outcome was predictive accuracy for the occurrence of IHCA or UIT within 24 h of the alarm being triggered. Area under the receiver operating characteristic curve (AUROC) values were used to compare the DeepCARS™ with the modified early warning score (MEWS), national early warning Score (NEWS), and single-parameter track-and-trigger systems. Results Among 55,083 patients, the incidence rates of IHCA and UIT were 0.90 and 6.44 per 1,000 admissions, respectively. In terms of the composite outcome, the AUROC for the DeepCARS™ was superior to those for the MEWS and NEWS (0.869 vs. 0.756/0.767). At the same sensitivity level of the cutoff values, the mean alarm counts per day per 1,000 beds were significantly reduced for the DeepCARS™, and the rate of appropriate alarms was higher when using the DeepCARS™ than when using conventional systems. Conclusion The DeepCARS™ predicts IHCA and UIT more accurately and efficiently than conventional methods. Thus, the DeepCARS™ may be an effective screening tool for detecting clinical deterioration in real-world clinical practice. Trial registration This study was registered at ClinicalTrials.gov ( NCT04951973 ) on June 30, 2021.

Background: The early identification of sepsis presenting a high risk of deterioration is a daily challenge to optimise patient pathway. This is all the most crucial in the prehospital setting to optimize triage and admission into the appropriate unit: emergency department (ED) or intensive care unit (ICU). We report the association between the prehospital National Early Warning Score 2 (NEWS-2) and in-hospital, 30 and 90-day mortality of SS patients cared for in the pre-hospital setting by a mobile ICU (MICU). Methods: Septic shock (SS) patients cared for by a MICU between 2016, April 6th and 2021 December 31st were included in this retrospective cohort study. The NEWS-2 is based on 6 physiological variables (blood pressure, heart rate, respiratory rate, temperature, oxygen saturation prior oxygen supplementation, and level of consciousness) and ranges from 0 to 20. The Inverse Probability Treatment Weighting (IPTW) propensity method was applied to assess the association with in-hospital, 30 and 90-day mortality. A NEWS-2 ≥ 7 threshold was chosen for increased clinical deterioration risk definition and usefulness in clinical practice based on previous reports. Results: Data from 530 SS patients requiring MICU intervention in the pre-hospital setting were analysed. The mean age was 69 ± 15 years and presumed origin of sepsis was pulmonary (43%), digestive (25%) or urinary (17%) infection. In-hospital mortality rate was 33%, 30 and 90-day mortality were respectively 31% and 35%. A prehospital NEWS-2 ≥ 7 is associated with an increase in-hospital, 30 and 90-day mortality with respective RRa = 2.34 [1.39–3.95], 2.08 [1.33–3.25] and 2.22 [1.38–3.59]. Calibration statistic values for in-hospital mortality, 30-day and 90-day mortality were 0.54; 0.55 and 0.53 respectively. Conclusion: A prehospital NEWS-2 ≥ 7 is associated with an increase in in-hospital, 30 and 90-day mortality of septic shock patients cared for by a MICU in the prehospital setting. Prospective studies are needed to confirm the usefulness of NEWS-2 to improve the prehospital triage and orientation to the adequate facility of sepsis. [ABSTRACT FROM AUTHOR]

Background: Vital sign monitoring is considered an essential aspect of clinical care in hospitals. In general wards, this relies on intermittent manual assessments performed by clinical staff at intervals of up to 12 h. In recent years, continuous monitoring of vital signs has been introduced to the clinic, with improved patient outcomes being one of several potential benefits. The aim of this study was to determine the workload difference between continuous monitoring and manual monitoring of vital signs as part of the National Early Warning Score (NEWS). Methods: Three wireless sensors continuously monitored blood pressure, heart rate, respiratory rate, and peripheral oxygen saturation in 20 patients admitted to the general hospital ward. The duration needed for equipment set‐up and maintenance for continuous monitoring in a 24‐h period was recorded and compared with the time spent on manual assessments and documentation of vital signs performed by clinical staff according to the NEWS. Results: The time used for continuous monitoring was 6.0 (IQR 3.2; 7.2) min per patient per day vs. 14 (9.7; 32) min per patient per day for the NEWS. Median difference in duration for monitoring of vital signs was 9.9 (95% CI 5.6; 21) min per patient per day between NEWS and continuous monitoring (p <.001). Time used for continuous monitoring in isolated patients was 6.6 (4.6; 12) min per patient per day as compared with 22 (9.7; 94) min per patient per day for NEWS. Conclusion: The use of continuous monitoring was associated with a significant reduction in workload in terms of time for monitoring as compared with manual assessment of vital signs. [ABSTRACT FROM AUTHOR]

Sepsis is a common cause of maternal mortality and morbidity. Early detection and rapid management are essential. In this study, we evaluate the compliance with the implemented maternity-specific Early Warning Score (EWS), Rapid Response Team (RRT) protocol and the Surviving Sepsis Campaign (SSC) Hour-1 Bundle in a tertiary hospital in the Netherlands. We performed a retrospective patient chart review from July 2019 to June 2020 at the Leiden University Medical Centre. We included women who received therapeutic antibiotics and were admitted for at least 24 hours. We included 240 women: ten were admitted twice and one woman three times, comprising 252 admissions. A clinical diagnosis of sepsis was made in 22 women. The EWS was used in 29% (n = 73/252) of admissions. Recommendations on the follow-up of the EWS were carried out in 53% (n = 46/87). Compliance with the RRT protocol was highest for assessment by a medical doctor within 30 minutes (n = 98/117, 84%) and lowest for RRT involvement (n = 7/23, 30%). In women with sepsis, compliance with the SSC Bundle was highest for acquiring blood cultures (n = 19/22, 85%), while only 64% (n = 14/22) received antibiotics within 60 minutes of the sepsis diagnosis. The adherence to the maternity-specific EWS and the SSC Hour-1 bundle was insufficient, even within this tertiary setting in a high-income country. [ABSTRACT FROM AUTHOR]

Purpose: This study aimed to describe the 24-hour cycle of wearable sensor-obtained heart rate in patients with deterioration-free recovery and to compare it with patients experiencing postoperative deterioration. Methods: A prospective observational trial was performed in patients following bariatric or major abdominal cancer surgery. A wireless accelerometer patch (Healthdot) continuously measured postoperative heart rate, both in the hospital and after discharge, for a period of 14 days. The circadian pattern, or diurnal rhythm, in the wearable sensor-obtained heart rate was described using peak, nadir and peak-nadir excursions. Results: The study population consisted of 137 bariatric and 100 major abdominal cancer surgery patients. In the latter group, 39 experienced postoperative deterioration. Both surgery types showed disrupted diurnal rhythm on the first postoperative days. Thereafter, the bariatric group had significantly lower peak heart rates (days 4, 7–12, 14), lower nadir heart rates (days 3–14) and larger peak-nadir excursions (days 2, 4–14). In cancer surgery patients, significantly higher nadir (days 2–5) and peak heart rates (days 2–3) were observed prior to deterioration. Conclusions: The postoperative diurnal rhythm of heart rate is disturbed by different types of surgery. Both groups showed recovery of diurnal rhythm but in patients following cancer surgery, both peak and nadir heart rates were higher than in the bariatric surgery group. Especially nadir heart rate was identified as a potential prognostic marker for deterioration after cancer surgery. [ABSTRACT FROM AUTHOR]

Aim: The aim of the study was to assess the suitability of an online education package to prepare health professionals to use a new paediatric early warning system. Design: Quasi‐experimental mixed methods using co‐production. Methods: Participants completed the Package and participated in up to four clinical scenarios. Data were collected using self‐report surveys, and during clinical scenarios; escalation of care, documentation, family involvement, communication handovers were assessed, and recorded debriefings were thematically analysed. Data were integrated using tabulated joint displays. Results: Eleven nurses and three doctors were recruited from three mixed adult and paediatric hospitals. Following completion of the Package and clinical scenarios 13/14 (93%) participants agreed preparedness and confidence to use the ESCALATION System had increased. For 53% handovers, the communication framework was followed, for 79% charts, documentation was complete. Participants engaged with the parent (actor) for 97% scenario interactions. The Package was effective and participation in clinical scenarios appeared to enhance learning. Patient or public contribution: Consumers participated in the steering group overseeing the study and in the expert panel who reviewed the education package and clinical scenarios. [ABSTRACT FROM AUTHOR]

Background: The ability to predict the prognosis of a disease and anticipate death is valuable for patients and families especially in an acute care setting for chronically ill patient. Multiple scoring systems are used to measure disease progression and predict hospital mortality in patients with life-threatening illnesses, taking into account acute conditions, catastrophic events, and slow decline. Aim: Our primary aim is to assess palliative performance score (PPS), early warning score (EWS) and local rumah sakit Dr Hasan Sadikin (RSHS) score to predict 14 days in-hospital mortality. Methods: This was a single-center prospective cohort study from November 2022 to April 2023. Patients with World Health Organization category of terminal illnesses were scored using PPS, EWS and RSHS score and were followed up for 14 days in hospital. Multivariate analysis were conducted and The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines were used. Results: A multivariable model was calculated using Cox regression. The final model results indicate that EWS (HR: 2.9, 95% CI: 1.1– 7.7) and a decrease in consciousness (HR: 3.6, 95% CI: 1.2– 10.22) were statistically significant in predicting mortality. Discussions: Most patient in the cohort that died had cancer and were admitted in the previous 6 months. Relying solely on single prediction may not provide enough accuracy, within a 14-day timeframe. Therefore, the results of multivariate analysis were not statistically significant due to Several factors contribute to the complexity of this prediction challenge. As a multifaceted disease with varying stages, treatments, and outcomes, cancer presents a diverse landscape of patient experiences. Conclusion: EWS and decreased consciousness are significant predictors of in-hospital mortality. It is crucial in clinical setting to use multiple indicators to predict death and improve patient care. [ABSTRACT FROM AUTHOR]

Background: Early identification of a patient with infection who may develop sepsis is of utmost importance. Unfortunately, this remains elusive because no single clinical measure or test can reflect complex pathophysiological changes in patients with sepsis. However, multiple clinical and laboratory parameters indicate impending sepsis and organ dysfunction. Screening tools using these parameters can help identify the condition, such as SIRS, quick SOFA (qSOFA), National Early Warning Score (NEWS), or Modified Early Warning Score (MEWS). We aim to externally validate qSOFA, SIRS, and NEWS/NEWS2/MEWS for in-hospital mortality among adult patients with suspected infection who presenting to the emergency department. Methods and analysis: PASSEM study is an international prospective external validation cohort study. For 9 months, each participating center will recruit consecutive adult patients who visited the emergency departments with suspected infection and are planned for hospitalization. We will collect patients' demographics, vital signs measured in the triage, initial white blood cell count, and variables required to calculate Charlson Comorbidities Index; and follow patients for 90 days since their inclusion in the study. The primary outcome will be 30-days in-hospital mortality. The secondary outcome will be intensive care unit (ICU) admission, prolonged stay in the ICU (i.e., ≥72 hours), and 30- as well as 90-days all-cause mortality. The study started in December 2021 and planned to enroll 2851 patients to reach 200 in-hospital death. The sample size is adaptive and will be adjusted based on prespecified consecutive interim analyses. Discussion: PASSEM study will be the first international multicenter prospective cohort study that designated to externally validate qSOFA score, SIRS criteria, and EWSs for in-hospital mortality among adult patients with suspected infection presenting to the ED in the Middle East region. Study registration: The study is registered at ClinicalTrials.gov (NCT05172479). [ABSTRACT FROM AUTHOR]

Background: The current situation of the unprecedented COVID-19 pandemic leverages Artificial Intelligence (AI) as an innovative tool for addressing the evolving clinical challenges. An example is utilizing Machine Learning (ML) models—a subfield of AI that take advantage of observational data/Electronic Health Records (EHRs) to support clinical decision-making for COVID-19 cases. This study aimed to evaluate the clinical characteristics and risk factors for COVID-19 patients in the United Arab Emirates utilizing EHRs and ML for survival analysis models. Methods: We tested various ML models for survival analysis in this work we trained those models using a different subset of features extracted by several feature selection methods. Finally, the best model was evaluated and interpreted using goodness-of-fit based on calibration curves,Partial Dependence Plots and concordance index. Results: The risk of severe disease increases with elevated levels of C-reactive protein, ferritin, lactate dehydrogenase, Modified Early Warning Score, respiratory rate and troponin. The risk also increases with hypokalemia, oxygen desaturation and lower estimated glomerular filtration rate and hypocalcemia and lymphopenia. Conclusion: Analyzing clinical data using AI models can provide vital information for clinician to measure the risk of morbidity and mortality of COVID-19 patients. Further validation is crucial to implement the model in real clinical settings. [ABSTRACT FROM AUTHOR]

(1) Background: Early identification of severe coronavirus disease 2019 (COVID-19) pneumonia at the initial phase of hospitalization is very crucial. To address this, we validated and updated the National Early Warning Score 2 (NEWS2) for this purpose. (2) Methods: We conducted a study on adult patients with COVID-19 infection in Chiang Mai, Thailand, between May 2021 and October 2021. (3) Results: From a total of 725 COVID-19 adult patients, 350 (48.3%) patients suffered severe COVID-19 pneumonia. In determining severe COVID-19 pneumonia, NEWS2 and NEWS2 + Age + BMI (NEWS2 Plus) showed the C-statistic values of 0.798 (95% CI, 0.767–0.830) and 0.821 (95% CI, 0.791–0.850), respectively. The C-statistic values of NEWS2 Plus were significantly improved compared to those of NEWS2 alone (p = 0.012). Utilizing a cut-off point of five, NEWS2 Plus exhibited better sensitivity and negative predictive value than the traditional NEWS2, with values of 99.7% vs. 83.7% and 98.9% vs. 80.7%, respectively. (4) Conclusions: The incorporation of age and BMI into the traditional NEWS2 score enhanced the efficacy of determining severe COVID-19 pneumonia. Physicians can rely on NEWS2 Plus (NEWS2 + Age + BMI) as a more effective decision-making tool for triaging COVID-19 patients during early hospitalization. [ABSTRACT FROM AUTHOR]

Background: Early detection of clinical deterioration among hospitalized patients is a clinical priority for patient safety and quality of care. Current automated approaches for identifying these patients perform poorly at identifying imminent events. Objective: Develop a machine learning algorithm using pager messages sent between clinical team members to predict imminent clinical deterioration. Design: We conducted a large observational study using long short-term memory machine learning models on the content and frequency of clinical pages. Participants: We included all hospitalizations between January 1, 2018 and December 31, 2020 at Vanderbilt University Medical Center that included at least one page message to physicians. Exclusion criteria included patients receiving palliative care, hospitalizations with a planned intensive care stay, and hospitalizations in the top 2% longest length of stay. Main Measures: Model classification performance to identify in-hospital cardiac arrest, transfer to intensive care, or Rapid Response activation in the next 3-, 6-, and 12-hours. We compared model performance against three common early warning scores: Modified Early Warning Score, National Early Warning Score, and the Epic Deterioration Index. Key Results: There were 87,783 patients (mean [SD] age 54.0 [18.8] years; 45,835 [52.2%] women) who experienced 136,778 hospitalizations. 6214 hospitalized patients experienced a deterioration event. The machine learning model accurately identified 62% of deterioration events within 3-hours prior to the event and 47% of events within 12-hours. Across each time horizon, the model surpassed performance of the best early warning score including area under the receiver operating characteristic curve at 6-hours (0.856 vs. 0.781), sensitivity at 6-hours (0.590 vs. 0.505), specificity at 6-hours (0.900 vs. 0.878), and F-score at 6-hours (0.291 vs. 0.220). Conclusions: Machine learning applied to the content and frequency of clinical pages improves prediction of imminent deterioration. Using clinical pages to monitor patient acuity supports improved detection of imminent deterioration without requiring changes to clinical workflow or nursing documentation. [ABSTRACT FROM AUTHOR]

The evaluation of acute poisoning is challenging due to varied toxic substances and clinical presentations. The new-Poisoning Mortality Score was recently developed to assess patients with acute poisoning and showed good performance in predicting in-hospital mortality. The objective of this study is to externally validate the performance of the new-Poisoning Mortality Score and to compare it with the Modified Early Warning Score. This retrospective analysis used data from the 2019–2020 Injury Surveillance Cohort, established by the Korea Center for Disease Control and Prevention, to perform external validation of the new-Poisoning Mortality Score. The statistical performances of the new-Poisoning Mortality and Modified Early Warning Scores were assessed and compared in terms of discrimination and calibration. Discrimination analysis involved metrics such as sensitivity, specificity, accuracy, and the area under the receiver operating characteristic curve. For calibration analysis, the Hosmer-Lemeshow goodness-of-fit test was utilized and calibration curves for each score were generated to elucidate the relationship between observed and predicted mortalities. This study analysed 16,570 patients with acute poisoning. Significant differences were observed between survivors and those who died in-hospital, including age, sex, and vital signs. The new-Poisoning Mortality Score showed better performance over the Modified Early Warning Score in predicting in-hospital mortality, in terms of the area under the receiver operating characteristic curve (0.947 versus 0.800), sensitivity (0.863 versus 0.667), specificity (0.912 versus 0.817), and accuracy (0.911 versus 0.814). When evaluated through calibration curves, the new-Poisoning Mortality Score showed better concordance between predicted and observed mortalities. In subgroup analyses, the score system consistently showed strong performance, excelling particularly in substances with high mortality indices and remaining superior in all substances as a group. Our study has helped to validate the new-Poisoning Mortality Score as an effective tool for predicting in-hospital mortality in patients with acute poisoning in the emergency department. The score system demonstrated superior performance over the Modified Early Warning Score in various metrics. Our findings suggest that the new-Poisoning Mortality Score can contribute to the enhancement of clinical decision-making and patient management. [ABSTRACT FROM AUTHOR]

Background: Ursodeoxycholic acid (UDCA) has been recently proposed as a modulator of angiotensin‐converting enzyme 2 (ACE2) receptor expression, with potential effects on COVID‐19. Aim and Study Design: We retrospectively evaluated the clinical course and outcome of subjects taking UDCA admitted to the hospital for COVID‐19 compared with matched infected subjects. Differences regarding the severity and outcome of the disease between treated and non‐treated subjects were assessed. The Kaplan–Meier survival analysis and log‐rank test were used to evaluate the effect of UDCA on all‐cause intra‐hospital mortality. Results: Among 6444 subjects with confirmed COVID‐19 admitted to the emergency department (ED) from 1 March 2020 to 31 December 2022, 109 subjects were taking UDCA. After matching 629 subjects were included in the study: 521 in the no UDCA group and 108 in the UDCA group. In our matched cohort, 144 subjects (22.9%) died, 118 (22.6%) in the no‐UDCA group and 26 (24.1%) in the UDCA group. The Kaplan–Meier analysis showed no significant difference in survival between groups. In univariate regression analysis, the presence of pneumonia, National Early Warning Score (NEWS) score, and Charlson Comorbidity Index (CCI) were significant independent predictors of death. At multivariate Cox regression analysis, age, NEWS, pneumonia and CCI index were confirmed significant independent predictors of death. UDCA treatment was not a predictor of survival both in univariate and multivariate regressions. Conclusions: UDCA treatment does not appear to have significant effects on the outcome of COVID‐19. Specially designed prospective studies are needed to evaluate efficacy in preventing infection and severe disease. [ABSTRACT FROM AUTHOR]

The present study aimed to clarify the practical implications of implementing a risk pre-warning nursing model combined with early nasojejunal enteral nutrition in patients with severe stroke. One hundred patients with severe stroke treated at the Affiliated Hospital of Nantong University, Nantong City, China between January 2022 and June 2023 were recruited. The control group received early enteral nutrition support and conventional nursing, whereas the experimental group was subjected to a risk pre-warning nursing model. After the intervention, the serum albumin, prealbumin, and total protein levels were higher in the experimental group than in the control group. However, the experimental group demonstrated shorter bowel sound recovery, anal exhaust, and anal defecation times. The incidence of complications was lower in the experimental group (4.0%) than in the control group (18.0%). The experimental group exhibited a reduction in intensive care unit hospitalization time, total hospitalization time, and expenses than the control group. The National Institute of Health stroke scale, self-rating depression scale, and self-rating anxiety scale scores were lower in the experimental group than in the control group. In conclusion, early nasojejunal nutrition with risk pre-warning nursing model can improve nutritional status and gastrointestinal function, regulate neurological function, alleviate negative emotions, reduce complications, and shorten the hospital stay of patients with severe stroke. [ABSTRACT FROM AUTHOR]

The 'quick Sepsis Related Organ Failure Assessment' (qSOFA), 'Systemic Inflammatory Response Syndrome' (SIRS), and 'National Early Warning Score' 2 (NEWS2) scores are yet to be comparatively validated in ward-based cardiac surgical patients despite widespread routine use in clinical practice. We sought to assess the predictive validity of NEWS, SIRS, and qSOFA in identifying postoperative, ward-level cardiac surgical patients at risk of poor short-term mortality. All adult patients who underwent cardiac surgery at a single tertiary center between November 2014 and October 2017 were identified. Data for bedside observations, hematological results, and microbiology requests were obtained from electronic health records. Survival data were acquired from a national registry. The primary outcome was the discriminatory ability, measured by the area under the receiver operating characteristic (AUROC), of each score for in-hospital mortality. One thousand five hundred forty three (male n = 1101, 71%) patients were included. Overall in-hospital mortality was 2.4%. There was no significant difference in discriminatory ability of NEWS (AUROC 0.5060), SIRS (AUROC 0.4874), and qSOFA (AUROC 0.5139) for in-hospital mortality (P = 0.881). Sensitivity for this outcome was ubiquitously low (13.51-40.54%). Current illness-severity scores show a low discriminatory ability for in-hospital mortality in ward-based cardiac surgical patients. Caution should be used in the application of these prognostic screening tools for early detection of poor outcomes in this population. [ABSTRACT FROM AUTHOR]

To describe the epidemiological and clinical profile of pediatric patients admitted to a secondary hospital who were transferred to the intensive care unit, as well as to report the final outcome after 30 days of transfer to the ICU. This was a retrospective descriptive study conducted by the medical, nursing, and general hospital nursing coordinations, a pediatrician, and an academic nursing student in a pediatric ward. The participant sample included patients admitted to a pediatric ward who were transferred to the intensive care unit from January to December 2023, in a secondary hospital in Ceará. Data were collected from physical medical records, electronic medical records, and ICU transfer management spreadsheets. The information was recorded through Google Forms, generating a database stored in a Microsoft Office Excel spreadsheet. The variables were categorized for better data analysis, and absolute and relative frequencies were calculated and presented in the form of tables and figures. There were a total of 89 transfers from the pediatric clinical bed ward to the pediatric ICU, 69.7% of whom were males and 30.3% were females. Regarding the age group, 53.9% of the transfers corresponded to children up to 2 years of age. We observed that 32.6% of the transfers to the pediatric ICU were performed within 24 hours of admission to the ward and 13.5% were transferred between 24 hours and 48 hours of admission. The outcome within 30 days of ICU transfer showed a favorable outcome, corresponding to 93.3% of the patients. The present study collects epidemiological data from a pediatric unit, favoring the knowledge of its profile for managers and employees. [ABSTRACT FROM AUTHOR]

The pediatric early warning score (PEWS) is a tool used to predict clinical deterioration. Referenced vital sign parameters are based on expert opinion but heart rate and respiratory rate percentiles in hospitalized children have been published. This retrospective case-control study of unplanned intensive care unit (ICU) transfers compares evidence-based vital signs (EBVS) effect on PEWS sensitivity and specificity, determines the impact of age categories on PEWS deterioration prediction, and evaluates whether EBVS PEWS is associated with need for invasive ICU supports. EBVS PEWS improved sensitivity (43%-71% vs 30%-63%) for unplanned transfers with slightly decreased specificity (88%-98% vs 93%-99%). Logistic regression analysis and odds ratios (ORs) demonstrated EBVS PEWS was associated with increased risk for ICU-specific supports (OR = 1.16, 95% confidence interval [CI] = 1.0-1.34, P =.0498). Evidence-based vital signs can improve PEWS sensitivity to identify unplanned ICU transfers and identify patients requiring ICU-specific interventions. [ABSTRACT FROM AUTHOR]

Measuring the physiological parameters and their variations for 24 h provides a significantly visible pattern for patient health monitoring. The life-threatening event can be identified by determining the abnormalities in physiological parameters. These parameters play a vital role in the accurate calculation of early warning score (EWS). Therefore, in this paper, an automated and internet of things (IoT)-based EWS calculation has been presented for timely detection and diagnosis of the abnormality associated with the physiological parameters of the patient. It will be useful in avoiding life-threatening events. At present, the EWS is calculated by the conventional method, where the different physiological parameters are monitored by medical staff or nurses in a particular time interval. The conventional scoring system is laborious, time-consuming, and prone to human error. Thus, the presented automatic and IoT-based EWS system for patient monitoring has been successfully implemented. The presented system can continuously calculate EWS by measuring and recording the physiological parameter in real-time. A laboratory prototype has been configured and validated for the EWS calculation and observation in the hospital and home environment. [ABSTRACT FROM AUTHOR]

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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]

Background Risk prediction tools for acutely ill children have been developed in highand low-income settings, but few are validated or incorporated into clinical guidelines. We aimed to assess the performance of existing paediatric early warning scores for use in low- and middle-income countries using clinical data from a recent large multi-country study in Africa and South-Asia. Methods We used data (children across three nutritional strata) from the Childhood Acute Illness and Nutrition (CHAIN) Network cohort study (n= 3101). We assessed 10 scores where similar predictor variables were available in the CHAIN cohort. We evaluated performance using the area under the receiver operating curve (AUC) (primary outcome), sensitivity, specificity, positive and negative predictive value, and positive and negative likelihood ratio (secondary outcomes). Results Most scores showed poor discrimination, and all scores had low sensitivity. The paediatric early death index for Africa (AUC = 0.80; 95% confidence interval (CI) = 0.77-0.83), respiratory index of severity in children (AUC= 0.77; 95% CI = 0.74-0.81), and respiratory index of severity in children in Malawi (AUC=0.78; 95% CI = 0.75-0.82) showed acceptable/ good overall discrimination. Among children without wasting, most scores had acceptable/good performance, some even excellent. Poor discrimination was found for most scores among children with moderate and severe wasting or kwashiorkor. Conclusions All scores demonstrated lower validation performance than originally reported. Among children without wasting, most risk prediction scores performed acceptably whilst in malnourished children they performed poorly. There is a need for a malnutrition specific score. Further research is needed on specific actions in responding to scores. Integration into future guidelines will require acknowledging staffing, resources and workflows. [ABSTRACT FROM AUTHOR]

OBJECTIVE: To identify the level of knowledge and attitudes towards Early Warning Scores (EWS) in detecting deteriorating haemodialysis patients among Registered Nurses (RNs) in private hospitals. METHODOLOGY: A quantitative design using a cross-sectional study was conducted. The respondents were 157 registered nurses working at haemodialysis services centres from five selected KPJ Group of Hospitals and were utilizing EWS. The sample size was calculated using a published formula based on 260 haemodialysis registered nurses. The data was collected using a self-administered questionnaire. Descriptive analysis was used for all variables collected. Statistical analysis was performed using the Social Packages for the Social Sciences (SPSS) software version 20. RESULTS: The findings showed that there is a significant relationship (95% significance level) between the level of knowledge (median value of 33.0 and standard deviation of 1.28) and the attitudes (median value of 33.0 and standard deviation of 7.11) from the constructs. CONCLUSION: Knowledge of EWS is vital for these nurses to recognize subtle changes that indicate any early deterioration in patients' conditions and their attitudes in perceiving the importance of offering positive haemodialysis services to their patients. The findings also suggest that the education level of RNs and years of experience in matters of positive haemodialysis services also provide an intuitive understanding of the best way to employ EWS. [ABSTRACT FROM AUTHOR]

Objective: To assess Pediatric Alert Score (EPA) performance in screening cases of sepsis in a hospital context. Methods: This is a diagnostic test study guided by the Standards for the Reporting of Diagnostic Accuracy Studies (STARD) recommendations. The sample consisted of 190 children and adolescents admitted to a hospital in the countryside of Bahia, Brazil. Data collection was carried out in the database of an umbrella project in medical records and the hospital's records system. Processing and analysis were performed in SPSS® version 25.0 for Windows and MedCalc® version 20.00. EPA performance in sepsis screening when compared to the reference standard criteria was measured through sensitivity, specificity, predictive values and ROC curve. Results: Among the participants, 53.2% were male, with a mean age of 4.39 years (SD: 4.28) and a median of 3 years (IQR: 1 – 8). The prevalence of sepsis identified by the reference standard was 10% and by EPA (23.1%). The sensitivity, specificity and positive and negative predictive values of EPA in sepsis screening were 73.7%, 82.5%, 31.8% and 96.6%, respectively. The area under the ROC curve was 0.794. Conclusion: The study presents evidence on EPA performance in sepsis screening, demonstrating good accuracy in discriminating pediatric patients with and without sepsis in the studied sample. [ABSTRACT FROM AUTHOR]

Background: Acute febrile illness (AFI) is the most common presentation in the pediatric emergency room, and bedside risk assessment scores are very useful to identify those at risk. This study aimed to evaluate the predictive validity of quick Sequential Organ Failure Assessment (qSOFA), quick Pediatric Logistic Organ Dysfunction-2 (qPELOD-2), Liverpool qSOFA (LqSOFA), and Pediatric Early Warning Score (PEWS) to predict the outcome of patients with AFI admitted to the pediatric intensive care unit (PICU). Subjects and Methods: This prospective observational study included children under the age of 18 years admitted to PICU. A thorough history and examination was performed in the ER, and the qSOFA, the qPELOD-2, the LqSOFA, and the PEWS scores were calculated. The primary outcome was inhospital mortality. The capacity of the scores to predict outcome was evaluated for calibration (using Hosmer–Lemeshow adaptation of the Chi-square test) and discrimination (using receiver operating characteristic [ROC] curve). The scores were compared for any significant difference using z-statistics. Results: The study included 239 patients with the most common diagnosis of dengue fever. The overall mortality rate in the study was 8.4%. On the calibration of the models, all the scores showed a good fit to predict mortality. On discrimination by ROC curve, the LqSOFA score and PEWS had the best area under the curve for ROC curve (AUC-ROC) (0.913), followed by the qSOFA score (0.859). On comparing the AUC-ROC curve, no statistically significant difference was found between the scoring systems to predict mortality. Conclusions: Bedside risk stratification scores are a simple and convenient tool to identify patients at risk for mortality and assess prognosis. No single assessment tool was found superior to others. [ABSTRACT FROM AUTHOR]

Background: Pediatric scores such as the Pediatric Early Warning Score (PEWS) are based on parameters available at the bedside. The aim of this study was to assess the utility of PEWS to determine the need for critical care support within the next 24–48 h. this study aimed to see if PEWS could predict a suitable level of care, namely ward, high-dependency unit (HDU), or pediatric intensive care unit (PICU). Subjects and Methods: It was a prospective observational study and a convenient sample method was used with children of age groups from 1 month to 18 years, coming to the pediatrics department being the subject. We correlated the level of care at admission and also after 48 h with PEWS at the time of admission of children already intubated, children on inotropes at the time of admission, children with surgical illness, and children admitted only for procedure/procedural sedation were excluded from this study. The Brighton PEWS was used to calculate PEWS. Results: A total of 953 patients were enrolled in this study. In this study, the likelihood of admission to PICU correlated well with PEWS above 6 with a positive predictive value of 56% and a negative predictive value of 99.43%. Conclusions: The admission PEWS can be used as an effective tool for deciding the level of care area. Score <3 admission PEWS can be kept at the ward, while >3 score at HDU/PICU where frequent periodic monitoring should be done. [ABSTRACT FROM AUTHOR]

Introduction: The WHO has now declared COVID-19 as endemic and it may be prudent to identify high-risk patients requiring reverse transcriptase-polymerase chain reaction (RT-PCR). During the pandemic, RT-PCR testing and reporting were running around-the-clock. We attempted to validate this scoring system and predict high probable in the obstetric subpopulation based on a modified early warning scoring system (EWSS) score. Materials and Methods: Data were collected from case sheets of pregnant women who were admitted to the obstetrics and gynecology department, according to the EWSS protocol. All the criteria mentioned in the EWSS score were tabulated in an Excel sheet. A modified list of signs, symptoms, and investigations was correlated with RT-PCR. This model obtained was validated with appropriate statistical tests. Patients who had undergone lower-segment cesarean section had hypertension (HTN), and diabetes as comorbidities and were included in the scoring system. Results: The odds ratio of the patient being positive was 3.56 with diabetes mellitus and 0.93 with HTN, most presented with minor symptoms such as expectoration, sore throat, dyspnea, and anosmia and these had odds ratio of 7.03, 12.68, 4.24, and 2.45, respectively, but the confidence interval was very wide. In laboratory investigations, C-reactive protein (CRP) and lactate dehydrogenase (LDH) elevations were found commonly and the odds ratio was 16.09 and 8.78, respectively. Conclusion: We concluded that if a pregnant woman presents with a sore throat, expectoration, dyspnea, or anosmia and presents with raised CRP and LDH with diabetes as a comorbidity there is a very high probability that the patient may have COVID-19 and needs to be tested or isolated. [ABSTRACT FROM AUTHOR]

The purpose of this study was to analyse the risk factors for sepsis in patients with trauma and develop a new scoring system for predicting sepsis in patients with trauma based on these risk factors. This will provide a simple and effective early warning method for the rapid and accurate detection and evaluation of the probability of sepsis in patients with trauma to assist in planning timely clinical interventions. We undertook a retrospective analysis of the clinical data of 216 patients with trauma who were admitted to the emergency intensive care unit of the emergency medicine department of the Hebei Medical University Third Hospital, China, between November 2017 and October 2022. We conducted a preliminary screening of the relevant factors using univariate logistic regression analysis and included those factors with a p value of <0.075 in the multivariate logistic regression analysis, from which the risk factors were screened and assigned, and obtained a total score, which was the sepsis early warning score. The incidence of sepsis in patients in the intensive care unit with trauma was 36.9%, and the mortality rate due to sepsis was 19.4%. We found statistically significant differences in several factors for patients with sepsis. The risk factors for sepsis in patients with trauma were the activated partial thromboplastin time, the New Injury Severity Score, growth differentiation factor‐15 levels, shock, mechanical ventilation and the Acute Physiology and Chronic Health Evaluation II score. The area under the receiver operating characteristic curve of the sepsis early warning score for predicting sepsis in patients with trauma was 0.725. When the cutoff value of the early warning score was set at 5.0 points, the sensitivity was 69.9% and the specificity was 60.3%. The incidence of sepsis in patients with trauma can be reduced by closely monitoring patients' hemodynamics, implementing adequate fluid resuscitation promptly and by early removal of the catheter to minimize the duration of unnecessary invasive mechanical ventilation. In this study, we found that the use of the sepsis early warning score helped in a more accurate and effective evaluation of the prognosis of patients with trauma. [ABSTRACT FROM AUTHOR]

Whether the National Early Warning Score 2 (NEWS2) can effectively discriminate the severe/critical state of patients with coronavirus disease 2019 (COVID-19) at the prehospital stage remains unknown. We aimed to assess the performance of NEWS2 in rapidly discriminating severe/critical COVID-19 and its relationship with prehospital medical services. Six illness severity scores of 414 patients were calculated at the prehospital stage. Receiver operating characteristic curves were generated to explore the ability of these scores to discriminate severe/critical patients from mild/moderate patients. A logistic regression analysis was conducted to evaluate independent predictors associated with severe/critical state. The age, numbers of comorbidities, prehospital care workload, consumption of medical human resources, and illness severity scores of severe/critical patients were higher than those of mild/moderate patients (p < 0.05). When NEWS2 scores >2, the sensitivity, specificity, positive predictive value, and negative predictive value were 93.5%, 90.7%, 74.1%, and 98.0%, respectively. The C-statistic of NEWS2 (0.963) was higher than that of quick Sequential Organ Failure Assessment (0.680, p < 0.001), CRB-65 (0.879, p < 0.001), Rapid Acute Physiology Score (0.692, p < 0.001), and Rapid Emergency Medicine Score (0.879, p < 0.001). NEWS2 was positively correlated with the numbers of prehospital treatment measures (r = 0.732, p < 0.001), numbers of medical staff (r = 0.615, p < 0.001), and total transport time (r = 0.595, p < 0.001). Age ≥65 years (OR = 5.43, p = 0.016), hypertension (OR = 5.39, p < 0.001), active malignancy (OR = 5.94, p = 0.005), and NEWS2 scores >2 (OR = 124.88, p < 0.001) were independent predictors to discriminate severe/critical patients. Oxygen saturation (SpO2) (OR =1.87, p < 0.001) was the unique independent predictor to discriminate false positive patients from true positive patients. Prehospital NEWS2 can accurately and rapidly discriminate severe/critical COVID-19 during the Omicron variant wave. High levels of NEWS2 indicate an increase in prehospital care workload and consumption of medical human resources. [ABSTRACT FROM AUTHOR]

Background: In the last decade, Ibrutinib has become the standard of care in the treatment of several lymphoproliferative diseases such as chronic lymphocytic leukemia (CLL) and several non-Hodgkin lymphoma. Beyond Bruton tyrosine kinase inhibition, Ibrutinib shows broad immunomodulatory effects that may promote the occurrence of infectious complications, including opportunistic infections. The infectious burden has been shown to vary by disease status, neutropenia, and prior therapy but data focusing on severe infections requiring intensive care unit (ICU) admission remain scarce. We sought to investigate features and outcomes of severe infections in a multicenter cohort of 69 patients receiving ibrutinib admitted to 10 French intensive care units (ICU) from 1 January 2015 to 31 December 2020. Results: Median time from ibrutinib initiation was 6.6 [3–18] months. Invasive fungal infections (IFI) accounted for 19% (n = 13/69) of severe infections, including 9 (69%; n = 9/13) invasive aspergillosis, 3 (23%; n = 3/13) Pneumocystis pneumonia, and 1 (8%; n = 1/13) cryptococcosis. Most common organ injury was acute respiratory failure (ARF) (71%; n = 49/69) and 41% (n = 28/69) of patients required mechanical ventilation. Twenty (29%; n = 20/69) patients died in the ICU while day-90 mortality reached 55% (n = 35/64). In comparison with survivors, decedents displayed more severe organ dysfunctions (SOFA 7 [5–11] vs. 4 [3–7], p = 0.004) and were more likely to undergo mechanical ventilation (68% vs. 31%, p = 0.010). Sixty-three ibrutinib-treated patients were matched based on age and underlying malignancy with 63 controls receiving conventional chemotherapy from an historic cohort. Despite a higher median number of prior chemotherapy lines (2 [1–2] vs. 0 [0–2]; p < 0.001) and higher rates of fungal [21% vs. 8%, p = 0.001] and viral [17% vs. 5%, p = 0.027] infections in patients receiving ibrutinib, ICU (27% vs. 38%, p = 0.254) and day-90 mortality (52% vs. 48%, p = 0.785) were similar between the two groups. Conclusion: In ibrutinib-treated patients, severe infections requiring ICU admission were associated with a dismal prognosis, mostly impacted by initial organ failures. Opportunistic agents should be systematically screened by ICU clinicians in this immunocompromised population. [ABSTRACT FROM AUTHOR]

For normal functioning of human organ systems, homeostasis is required. Disruption of normal homeostasis indicates the status of health and provides an early warning score in critical care. Wearable devices noninvasively measure vital signs. Among these wearables, the pressure sensors play a pivotal role in measuring heart rate etc. Resistance pressure sensor (RPS) can be integrated into wearable devices. Conductive elastomers and porous materials are developed to enhance RPS characteristics to improve measuring capability of vital signs. This review highlights the best materials and geometries, fabrication techniques, output data readers and laboratory experimental setups used for vital signs monitor. [ABSTRACT FROM AUTHOR]

Easy-to-use bedside risk assessment is crucial for patients with COVID-19 in the overcrowded emergency department (ED). The aim of this study was to explore the prognostic ability of ratio of percutaneous oxygen saturation (SpO 2) to fraction of inspired oxygen (FiO 2) (S/F); ratio of SpO 2 /FiO 2 to respiratory rate (ROX); National Early Warning Score (NEWS); quick Sequential Organ Failure Assessment (qSOFA); and confusion, respiratory rate, blood pressure, and age ≥ 65 years (CRB-65) in patients with COVID-19 presenting with dyspnea to the ED. In this retrospective observational study, clinical and demographic details of patients with COVID-19 were obtained at ED admission. S/F, ROX, NEWS, CRB-65, and qSOFA scores were calculated at the time of ED arrival. Accuracy of these five indices to predict the need for invasive mechanical ventilation (IMV) within 48 h, intensive care unit (ICU) admission, and early (7-day) mortality were determined using receiver operating characteristic curves. A total of 375 patients were included in this study. Fifty patients (13.3%) required IMV within 48 h and 58 patients (15.5%) were transferred to the ICU. Seven-day mortality was 6.7% and 28-day mortality was 18.1%. Among all five scores determined from patient data on ED admission, ROX, S/F, and NEWS presented greater discriminatory performance than CRB-65 and qSOFA in predicting IMV within 48 h, ICU admission, and early mortality. Emergency physicians can effectively use S/F, ROX, and NEWS scores for rapid risk stratification of patients with COVID-19 infection. Moreover, from the perspective of simplicity and ease of calculation, we recommend the use of the S/F ratio. [ABSTRACT FROM AUTHOR]

Purpose: The Ramathibodi Rapid Response System (RRRS), implemented in March 2017, aims to identify and respond to patients with deteriorating conditions outside the ICU. It employs the Ramathibodi early warning score and clinical signs to monitor all admitted patients, providing expert physician monitoring and early treatment for stabilization and appropriate care triage. This study assesses the RRRS's effectiveness in reducing in-hospital mortality and CPR events outside the ICU.Patients and Methods: We conducted a retrospective observational study from March 2014 to February 2020 in a tertiary care hospital's general wards. We included adult patients experiencing unplanned ICU admission, sudden cardiac arrest, or unexpected death. The study compared in-hospital mortality and CPR incidence outside the ICU between pre- and post-RRRS implementation groups. The associations between RRRS implementation and in-hospital mortality and the incidence of CPR outside the ICU were assessed using multiple logistic regression analyses.Results: We evaluated 17,741 admissions, with 9168 before RRRS implementation (1 March 2014 to 28 February 2017) and 8573 after RRRS implementation (1 March 2017 to 29 February 2020). The implementation of RRRS was associated with a significant reduction in in-hospital mortality, which decreased from 30.0% to 20.8% (odds ratio, 0.62; 95% confidence interval [CI], 0.57 to 0.66; P< 0.0001). Even after adjusting for age, sex, and comorbidities, the reduction in in-hospital mortality remained significant (adjusted odds ratio, 0.58; 95% CI, 0.54 to 0.63; P< 0.0001). The incidence of CPR outside the ICU also decreased from 1.8% to 1.1% (adjusted odds ratio, 0.6; 95% CI, 0.46 to 0.77; P< 0.0001). Additionally, the rate of ICU transfer increased from 85.4% to 92.1% (risk difference, 6.7; 95% CI, 7.6 to 5.8; P< 0.0001) after implementing the RRRS.Conclusion: Implementing the RRRS is associated with a reduction in in-hospital mortality and the incidence of CPR outside the ICU. [ABSTRACT FROM AUTHOR]

The role of antiviral treatment in coronavirus disease 2019 hospitalized patients is controversial. To address this question, we analyzed simultaneously nasopharyngeal viral load and the National Early Warning Score 2 (NEWS‐2) using an effect compartment model to relate viral dynamics and the evolution of clinical severity. The model is applied to 664 hospitalized patients included in the DisCoVeRy trial (NCT04315948; EudraCT 2020‐000936‐23) randomly assigned to either standard of care (SoC) or SoC + remdesivir. Then we use the model to simulate the impact of antiviral treatments on the time to clinical improvement, defined by a NEWS‐2 score lower than 3 (in patients with NEWS‐2 <7 at hospitalization) or 5 (in patients with NEWS‐2 ≥7 at hospitalization), distinguishing between patients with low or high viral load at hospitalization. The model can fit well the different observed patients trajectories, showing that clinical evolution is associated with viral dynamics, albeit with large interindividual variability. Remdesivir antiviral activity was 22% and 78% in patients with low or high viral loads, respectively, which is not sufficient to generate a meaningful effect on NEWS‐2. However, simulations predicted that antiviral activity greater than 99% could reduce by 2 days the time to clinical improvement in patients with high viral load, irrespective of the NEWS‐2 score at hospitalization, whereas no meaningful effect was predicted in patients with low viral loads. Our results demonstrate that time to clinical improvement is associated with time to viral clearance and that highly effective antiviral drugs could hasten clinical improvement in hospitalized patients with high viral loads. [ABSTRACT FROM AUTHOR]

Introduction: Understanding pulmonary function at various phases after coronavirus disease 2019 (COVID-19) infection is critical for determining the exact pathophysiological mechanism of COVID-19. Research Question: What is the correlation between spirometry indices and clinical indicators in COVID-19 patients over a 6-week follow-up? Objectives: 1) To assess deterioration or improvement in spirometry parameters including forced vital capacity (FVC), forced expiratory volume in one second (FEV1), and ratio FEV1/FVC in COVID-19 patients. 2) To study the correlation between FVC, FEV1, and FEV1/FVC with oxygen saturation and clinical findings. Materials and Methods: A prospective observational study was conducted for a 6-week period among 25, COVID-19 patients who were either asymptomatic or mildly symptomatic. Each patient received a home-use-connected spirometer—SpiroPRO®, a pulse oximeter, and a thermometer from Briota Technologies Pvt Ltd. (BRIOTA). Patients and healthcare professionals were given training for performing spirometry twice a day as well as access to mobile apps was provided. Spirometry indices, patient symptoms, and vital statistics were used to calculate the VIEW™ score using machine learning algorithms. Result: The Bland–Altman plots showed that FEV1 reduced slightly up to 21–28 days and comes back to normal around 42 days. VIEW™ score increased up to day 21 and then decreased toward day 42. An increase in VIEW™ score increases the risk of COVID-19 complications. VIEW™ score and FEV1 showed a significant correlation. Conclusion: Home-based spirometry acts as an effective tool for COVID-19 patients to predict lung complications and also promote self-monitoring thereby reducing the burden on the health system. [ABSTRACT FROM AUTHOR]

• Performance of admission pathways for medical patients are not routinely reported. • We evaluated clinical quality indicators specific to acute internal medicine services. • Quality indicators were associated with time of patient arrival to hospital. • Higher performance was seen within same day emergency care services. • Performance in all clinical quality indicators was lower than in previous years. Urgent and emergency care services face increasing pressure, impacting patient care. We evaluated the performance of acute medicine services, assessing clinical quality indicators for unplanned medical admissions to acute hospital services. 152 acute UK hospital services accepting unplanned admissions to acute and general internal medicine completed a day-of-care survey incorporating organisational structure questionnaire and patient-level data over a pre-defined 24-hour period in June 2022. Clinical quality indicators were: Early Warning Score (EWS) measurement within 30 min of hospital arrival; clinician assessment within 4 h; assessment by consultant physician within 6 h (daytime) or 14 h (night-time). Results were compared with 2019, 2020, 2021. 7293 sequential patients were included (and compared with 19,817 patients across 2019–2021). In 2022, 69% of patients (95%CI 67.7–69.9%) had an EWS documented within 30 min. 79% of patients (95%CI 77.8–79.7%) were reviewed by a clinical decision maker within 4 h of hospital arrival. Patients assessed in Same Day Emergency Care services were more likely to meet this target than those assessed in Acute Medical Units or Emergency Departments (OR 2.4, 95%CI 2.02–2.87, p <0.001). Overall, 50% of patients received consultant physician review within the target time (3065/6161, 95%CI 48.5–51.0%); performance varied with time of arrival and location of initial assessment. Performance against all three clinical quality indicators was lower than 2019, 2020 and 2021 (p <0.001 for all). Performance against all quality indicators within acute medicine services is deteriorating. However, performance in Same Day Emergency Care Units is greater than in Acute Medical Units or Emergency Departments. [ABSTRACT FROM AUTHOR]

Copyright of Balikesir Health Sciences Journal / Balıkesir Sağlık Bilimleri Dergisi is the property of Balikesir Health Sciences Journal (BAUN Health Sci J) 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.)

Introduction: Emergencies are a form of health service in emergency or urgent situations that require immediate action from medical personnel working to overcome potential risks and dangers to life. Various forms of emergency services require nurses in hospitals to save time in the process of providing nursing care. One form of emergency service in hospitals is the Early Warning Score (EWS). The use of technology in developing the Early Warning Score such as application mobile can certainly help in improving the quality of emergency services in hospitals, so it can minimize the severity of patients' conditions in the emergency phase. Method: The method in this research is quantitative descriptive research, in this case, the Androidbased mobile Early Warning Score application. This research was conducted to measure the level of user satisfaction where there are 3 dimensions in measuring the level of satisfaction with application use: quality of application information, quality of application use, and impact of application use. Results: The results of the research show that the satisfaction level of the Early Warning Score mobile application at Pontianak Hospital obtained a total score of 419 or 50,60% satisfied, and very satisfied with a total score of 217 or 26.21%. Conclusion: The Early Warning Score mobile application is suitable for use by nursing staff as a medium for improving excellent nursing services. [ABSTRACT FROM AUTHOR]

Aims: The National Early Warning Score (NEWS) is a scoring system that predicts increased mortality and morbidity in critical diseases. The National Early Warning Score + Lactate (NEWS + L) score was created by adding lactate values to this scoring system. In our study, we aimed to determine the value of the NEWS + L score in predicting clinical deterioration in patients presenting with acute decompensated heart failure (chronic heart failure). Methods and results: In this observational, cross‐sectional study, patients with decompensated heart failure who were admitted to the emergency department between 1 October 2020 and 31 December 2020 were included. Patients were divided into two groups: those with and without poor prognostic outcomes. The main outcomes were in‐hospital mortality, discharge after treatment in the emergency department, admission to the ward, and admission to the intensive care unit. We analysed a total of 141 applications from 130 patients. The mean age was 72.6 ± 11.8 years, and 50.8% were female. Poor prognostic outcomes were observed in 92 (65%) patients. There was no difference between the patients with and without poor prognostic outcomes in terms of mean age, gender, and comorbidities, except for atrial fibrillation. There was a statistically significant difference between the patients without and with poor prognosis outcomes in terms of NEWS {3 [interquartile range (IQR): 0–5] and 6 [IQR: 3–8]} and NEWS + L scores [4.7 (IQR: 2.3–7.2) and 8.0 (IQR: 5.2–10.4)] (P < 0.001). The area under the curve values for predicting poor prognosis were calculated as 0.719 for NEWS, 0.734 for NEWS + L, and 0.601 for lactate values. The rate of poor prognostic outcomes was higher (79%) in patients with moderate and high NEWS scores. Patients with Q1 NEWS + L scores had a lower rate of poor prognostic outcomes, while patients with Q2, Q3, and Q4 scores of NEWS + L had a higher rate of poor prognostic outcomes. Conclusions: The NEWS score and the addition of the lactate value to this score, the NEWS + L score, were higher in patients with poor prognostic outcomes who presented with decompensated heart failure in our emergency department. NEWS + L slightly outperformed the NEWS score in predicting prognosis. The NEWS + L score shows promise as a prognostic indicator for patients with decompensated heart failure presenting to the emergency department. [ABSTRACT FROM AUTHOR]

Purpose: Identification of patients at risk of complicated or more severe COVID-19 is of pivotal importance, since these patients might require monitoring, antiviral treatment, and hospitalization. In this study, we prospectively evaluated the SACOV-19 score for its ability to predict complicated or more severe COVID-19. Methods: In this prospective multicenter study, we included 124 adult patients with acute COVID-19 in three German hospitals, who were diagnosed in an early, uncomplicated stage of COVID-19 within 72 h of inclusion. We determined the SACOV-19 score at baseline and performed a follow-up at 30 days. Results: The SACOV-19 score's AUC was 0.816. At a cutoff of > 3, it predicted deterioration to complicated or more severe COVID-19 with a sensitivity of 94% and a specificity of 55%. It performed significantly better in predicting complicated COVID-19 than the random tree-based SACOV-19 predictive model, the CURB-65, 4C mortality, or qCSI scores. Conclusion: The SACOV-19 score is a feasible tool to aid decision making in acute COVID-19. [ABSTRACT FROM AUTHOR]

What’s happening in nursing across the globe [ABSTRACT FROM AUTHOR]

The article focuses on the challenges in monitoring and managing acute aortic dissection (AAD) in patients, particularly the elderly, during emergency care. Topics include the use of the National Early Warning Score (NEWS) to track patient deterioration, the impact of comorbidities like hypertension and diabetes on AAD outcomes, and the importance of early detection in preventing preventable deaths due to inadequate clinical monitoring.

BackgroundVital signs measurements on the ward are performed intermittently. This could lead to failure to rapidly detect patients with deteriorating vital signs and worsens long-term outcome. The aim of this study was to test the hypothesis that continuous wireless monitoring of vital signs on the postsurgical ward improves patient outcome.MethodsIn this prospective, multicenter, stepped-wedge cluster randomized study, patients in the control group received standard monitoring. The intervention group received continuous wireless monitoring of heart rate, respiratory rate and temperature on top of standard care. Automated alerts indicating vital signs deviation from baseline were sent to ward nurses, triggering the calculation of a full early warning score followed. The primary outcome was the occurrence of new disability three months after surgery.ResultsThe study was terminated early (at 57% inclusion) due to COVID-19 restrictions. Therefore, only descriptive statistics are presented. A total of 747 patients were enrolled in this study and eligible for statistical analyses, 517 patients in the control group and 230 patients in the intervention group, the latter only from one hospital. New disability at three months after surgery occurred in 43.7% in the control group and in 39.1% in the intervention group (absolute difference 4.6%).ConclusionThis is the largest randomized controlled trial investigating continuous wireless monitoring in postoperative patients. While patients in the intervention group seemed to experience less (new) disability than patients in the control group, results remain inconclusive with regard to postoperative patient outcome due to premature study termination.Clinical trial registrationClinicalTrials.gov, ID: NCT02957825.

Early Warning Score (EWS) digunakan untuk menilai perburukan kondisi pasien di rawat inap, namun pelaksanaan EWS belum optimal. Perawat memegang peranan penting dalam pelaksanaan EWS di rawat inap sehingga perlu digali bagaimana pelaksanaannya selama ini yang sudah dilakukan. Tujuan penelitian ini adalah untuk mengetahui bagaimana pengalaman perawat dalam penerapan EWS. Penelitian ini berfokus pada penerapan EWS yang merupakan modifikasi rumah sakit yang ada di daerah Jawa Barat dan pelaksanannya di ruang rawat inap. Desain penelitian adalah kualitatif dengan pendekatan fenomenologi. Pengambilan sampel dilakukan dengan tehnik purposive sampling dimana partisipan adalah perawat berjumlah 5 orang. Triangulasi yang dilakukan adalah triangulasi sumber, teknik pengumpulan data, dan waktu. Instrumen penelitian ini adalah peneliti sendiri. Pengumpulan menggunakan wawancara mendalam dengan bantuan alat buku catatan, alat tulis dan rekaman wawancara. Analisis data menggunakan tehnik Giorgi. Hasil penelitian menemukan 7 tema, yaitu 1) Faktor penyebab diterapkannya EWS 2) sosialisasi EWS, 3) Dokumentasi EWS, 4) Manfaat penerapan EWS, 5) ketersediaan formulir EWS, 6) pemahaman EWS, 7) Tim Code Blue. Penerapan EWS yang baik bisa dilakukan jika ada sosialiasi dan pelatihan terutama perawat baru. Pemahaman dalam pengisian maupun tindak lanjut EWS bisa terjadi jika didasari oleh informasi yang sama. Dokumentasi EWS yang baik bisa terjadi jika lingkungan kerja mendukung dan pimpinan memberikan feedback serta monitoring berkelanjutan

Introduction: Despite widespread implementation of the Early Warning Score (EWS) in hospitals, its effect on patient outcomes remains mostly unknown. We aimed to evaluate associations between the initial EWS and in-hospital mortality, intensive care unit (ICU) admission, and hospital length of stay (LOS).  Methods: We performed a retrospective cohort study of adult patients admitted to a general hospital ward between July 1, 2014–December 31, 2017. Data were obtained from electronic health records (EHR). The primary outcome was in-hospital mortality. Secondary outcomes were ICU admission and hospital LOS. We categorized patients into three risk groups (low, medium or high risk of clinical deterioration) based on EWS. Descriptive analyses were used. Results: After applying inclusion and exclusion criteria, we included 53,180 patients for analysis. We found that the initial (low- vs high-risk) EWS was associated with an increased in-hospital mortality (1.5% vs 25.3%, P