National Early Warning Score (NEWS) at ICU discharge can predict early clinical deterioration after ICU transfer

Intrahospital Handovers before and after the Implementation of ISBAR Communication: A Quality Improvement Study on ICU Nurses' Handovers to General Medical Ward Nurses

BACKGROUND

Research finds a lack of structure as well as varying and incomplete content in intrahospital handovers. This study aimed to improve intrahospital handovers by implementing structured ISBAR communication (identification, situation, background, assessment and recommendation).

METHODS

This quality improvement study was conducted observing 25 handovers given by nurses from the intensive care unit to nurses from general medical wards at baseline and after the implementation of the ISBAR communication tool. The 26-item ISBAR scoring tool was used to audit the handovers. In addition, the structure of the ISBAR communication and time spent on the handovers were observed.

RESULTS

There were no significant improvements from baseline to post-intervention regarding adherence to the ISBAR communication scoring tool. The structure of the handovers improved from baseline to post-intervention (p = 0.047). The time spent on handovers declined from baseline to post-intervention, although not significantly.

CONCLUSIONS

The items in the ISBAR communication scoring tool can act as a guide for details that need to be reported during intrahospital handovers to strengthen patient safety. Future research calls for studies measuring satisfaction among nurses regarding using different handover tools and studies using multifaceted training interventions.

Feasibility study of the use of a wearable vital sign patch in an intensive care unit setting

Multiple studies and review papers have concluded that early warning systems have a positive effect on clinical outcomes, patient safety and clinical performances. Despite the substantial evidence affirming the efficacy of EWS applications, persistent barriers hinder their seamless integration into clinical practice. Notably, EWS, such as the National Early Warning Score, simplify multifaceted clinical conditions into singular numerical indices, thereby risking the oversight of critical clinical indicators and nuanced fluctuations in patients' health status. Furthermore, the optimal deployment of EWS within clinical contexts remains elusive. Manual assessment of EWS parameters exacts a significant temporal toll on healthcare personnel. Addressing these impediments necessitates innovative approaches. In this regard, wearable medical technologies emerge as promising solutions capable of continual monitoring of hospitalized patients' vital signs. To overcome the barriers of the use of early warning scores, wearable medical technology has the potential to continuously monitor vital signs of hospitalised patients. However, a fundamental inquiry arises regarding the comparability of their reliability to the current used golden standards. This inquiry underscores the imperative for rigorous evaluation and validation of wearable medical technologies to ascertain their efficacy in augmenting extant clinical practices. This prospective, single-center study aimed to evaluate the accuracy of heart rate and respiratory rate measurements obtained from the Vivalink Cardiac patch in comparison to the ECG-based monitoring system utilized at AZ Maria Middelares Hospital in Ghent. Specifically, the study focused on assessing the concordance between the data obtained from the Vivalink Cardiac patch and the established ECG-based monitoring system among a cohort of ten post-surgical intensive care unit (ICU) patients. Of these patients, five were undergoing mechanical ventilation post-surgery, while the remaining five were not. The study proceeded by initially comparing the data recorded by the Vivalink Cardiac patch with that of the ECG-based monitoring system. Subsequently, the data obtained from both the Vivalink Cardiac patch and the ECG-based monitoring system were juxtaposed with the information derived from the ventilation machine, thereby providing a comprehensive analysis of the patch's performance in monitoring vital signs within the ICU setting. For heart rate, the Vivalink Cardiac patch was on average within a 5% error range of the ECG-based monitoring system during 85.11±10.81% of the measured time. For respiratory rate this was during 40.55±17.28% of the measured time. Spearman's correlation coefficient showed a very high correlation of ρ = 0.9 8 for heart rate and a moderate correlation of ρ = 0.66 for respiratory rate. In comparison with the ventilated respiratory rate (ventilation machine) the Vivalink and ECG-based monitoring system both had a moderate correlation of ρ = 0.68 . A very high correlation was found between the heart rate measured by the Vivalink Cardiac patch and that of the ECG-based monitoring system of the hospital. Concerning respiratory rate the correlation between the data from the Vivalink Cardiac patch, the ECG-based monitoring system and the ventilation machine was found to be moderate.

Follow-up of perfusion index and inferior vena cava collapsibility index in fluid therapy in prerenal acute renal failure

Introduction

Acute renal failure (ARF), which may occur as a result of hypovolemia, is frequently diagnosed in emergency departments. It is essential to determine these patients' volume status and fluid requirement. The aim of this study was to examine the change in the inferior vena cava (IVC) collapsibility index and perfusion index (PI) in order to evaluate fluid deficit, volume status, and response to fluid therapy in patients with prerenal ARF who presented with signs of hypovolemia.

Materials and methods

The study sample included 104 patients diagnosed with prerenal ARF due to hypovolemia in our emergency department. After obtaining informed consent from the patients, intravenous (IV) fluid therapy (20 cc/kg IV infusion of 0.9% sodium chloride solution for 30 min) was initiated. The PI and IVC collapsibility index were measured before and after the treatment.

Results

Of the patients included in this study, 56.7% were women. The mean age was 76.06 years. Of the patients, 46.2% had a history of multiple diseases. Avoidant/restrictive food intake disorder was the most common complaint (28.8%). The mean PI of the patients was 2.20 at admission, which increased to 3.27 after treatment. The mean IVC collapsibility index was 38.39 at admission, which decreased to 29.36 after treatment. There was a significant and negative correlation between the PI and IVC collapsibility index of the patients.

Conclusions

Early diagnosis and treatment of ARF in emergency departments are critical. Serial measurements of the IVC collapsibility index and PI are helpful in monitoring patients' response to fluid therapy.

Development of a Discharge Criteria Checklist for COVID-19 Patients From the Intensive Care Unit

This study aims to develop and validate a checklist of discharge readiness criteria for COVID-19 patients from the intensive care unit (ICU). We conducted a Delphi design study. The degree of agreement among 7 experts had been evaluated using the content validity index (CVI) through a 4-point Likert scale. The instrument was validated with 17 items. All the experts rated all items as very relevant which scored the item-CVI 1, which validates all checklist items. Using the mean of all items, the scale-CVI was calculated, and it was 1. This meant validation of the checklist as a whole. With regard to the overall checklist evaluation, the mean expert proportion of the instrument was 1, and the S-CVI/UA was 1. This discharge criteria checklist improves transition of care for COVID-19 patients and can help nurses, doctors, and academics to discharge COVID-19 patients from the ICU safely.

Incidence and potential risk factors for remdesivir-associated bradycardia in hospitalized patients with COVID-19: A retrospective cohort study

Background: Remdesivir is widely used for the management of COVID-19 and several studies have reported bradycardia as a potential side effect associated with this agent. The aim of the present study was to evaluate the incidence rate, severity, and potential risk factors of remdesivir-associated bradycardia. Methods: We performed a retrospective cohort study among hospitalized adult patients with COVID-19 who were treated with remdesivir from March 2020 to October 2021. Our primary outcome of interest was the incidence rate and severity of bradycardia after remdesivir administration. We defined mild bradycardia as a heart rate of 51-59 beats per minute, moderate bradycardia as a heart rate of 41-50 beats per minute, and severe bradycardia as a heart rate of ≤40 beats per minute. We also performed univariable and multivariable regression analyses to determine potential bradycardia risk factors. Baseline characteristics were reported as means with standard deviations or medians with interquartile ranges (IQRs). All the statistical tests are shown as odds ratios (ORs) with 95% confidence intervals (CIs). Results: In total, 1,635 patients were included in this study. The median age with IQR was 68 (57-79) years and 51.7% of the patients were male. In total, 606 (37.1%) patients developed bradycardia. Among them, 437 patients (26.7%) developed mild bradycardia, 158 patients (9.7%) moderate bradycardia, while 11 patients (0.7%) experienced severe bradycardia. In our adjusted multivariate logistic regression, the odds of bradycardia development after remdesivir administration were higher among patients with age ≥65 years (OR 1.76, 95% CI: 1.04-2.99, p = 0.04), those with hypertension (OR 1.37, 95% CI: 1.07-1.75, p = 0.01), and obesity (OR 1.32, 95% CI: 1.02-1.68, p = 0.03). Conclusion: More than 1 out of 3 patients (37%) who received remdesivir for COVID-19 developed bradycardia with the majority of these patients developing mild or moderate bradycardia that is usually a benign manifestation not needing treatment in most cases. Age ≥65 years, hypertension, and obesity were potential risk factors for remdesivir-associated bradycardia among hospitalized COVID-19 patients. Clinicians should be aware of this adverse event and consider close clinical monitoring for patients at high risk for this adverse event.

Internal Validation of the Predictive Performance of Models Based on Three ED and ICU Scoring Systems to Predict Inhospital Mortality for Intensive Care Patients Referred from the Emergency Department

Background.A variety of scoring systems have been introduced for use in both the emergency department (ED) such as WPS, REMS, and MEWS and the intensive care unit (ICU) such as APACHE II, SAPS II, and SOFA for risk stratification and mortality prediction. However, the performance of these models in the ICU remains unclear and we aimed to evaluate and compare their performance in the ICU. Methods. This multicenter retrospective cohort study was conducted on severely ill patients admitted to the ICU directly from the ED in seven tertiary hospitals in Iran from August 2018 to August 2020. We evaluated all models in terms of discrimination (AUROC), the balance between positive predictive value and sensitivity (AUPRC), calibration (Hosmer-Lemeshow test and calibration plots), and overall performance using the Brier score (BS). The endpoint was considered inhospital mortality. Results. Among the 3,455 patients included in the study, 54.4% of individuals were male ( $N=\mathrm{1,879}$ ) and 26.5% deceased ( $N=916$ ). The BS for the WPS, REMS, MEWS, APACHE II, SAPS II, and SOFA were 0.178, 0.165, 0.183, 0.157, 0.170, and 0.182, respectively. The AUROC of these models were 0.728 (0.71-0.75), 0.761 (0.74-0.78), 0.682 (0.66-0.70), 0.810 (0.79-0.83), 0.767 (0.75-0.79), and 0.785 (0.77-0.80), respectively. The AUPRC was 0.517 (0.50-0.53) for WPS, 0.547 (0.53-0.56) for REMS, 0.445 (0.42-0.46) for MEWS, 0.630 (0.61-0.65) for APACHE II, 0.559 (0.54-0.58) for SAPS II, and 0.564 (0.54-0.57) for SOFA. All models except the MEWS and SOFA had good calibration. The most accurate model belonged to APACHE II with lowest BS. Conclusion. The APACHE II outperformed all the ED and ICU models and was found to be the most appropriate model in predicting inhospital mortality of patients in the ICU in terms of discrimination, calibration, and accuracy of predicted probability. Except for MEWS, the rest of the models had fair discrimination and partially good calibration. Interestingly, although the REMS is less complicated than the SAPS II, both models exhibited similar performance. Clinicians can utilize the REMS as part of a larger clinical assessment to manage patients more effectively.

Evaluating the Efficacy of the National Early Warning Score in Predicting the Mortality of Stroke Patients Admitted to Intensive Care Units

Background

National Early Warning Score (NEWS) is a tool used to identify patients at risk. Scores are based on initial clinical observations, including heart rate, respiration rate, systolic blood pressure, oxygen saturation, level of consciousness, body temperature, and oxygen support. To date, few studies have been conducted on NEWS evaluation worldwide, and no study has been conducted in Iran.

Objectives

This study aims to evaluate the efficacy of the NEWS in predicting the mortality of stroke patients admitted to intensive care units (ICU).

Methods

The present cross-sectional study included 90 patients with a definitive diagnosis of cerebrovascular accident (CVA) based on symptoms and para-clinical evidence. At the beginning of admission to the ICU and up to first 24 hours of admission, all NEWS parameters were measured and evaluated.

Results

There was a significant relationship between systolic blood pressure, respiratory support, heart rate, and level of consciousness with patients’ discharge status. Also, there was no significant relationship between age, sex, respiratory rate, SPO2, and fever with discharge status. In addition, there was a significant relationship between clinical risk based on NEWS scoring system and patients’ status.

Conclusions

Our results showed a significant relationship between clinical risk based on NEWS scoring and patients’ discharge status so that there was a significant increase in mortality in patients with higher NEWS.

Temperature Profile and Adverse Outcomes After Discharge From the Intensive Care Unit

BACKGROUND

A predictive model that uses the rhythmicity of core body temperature (CBT) could be an easily accessible clinical tool to ultimately improve outcomes among critically ill patients.

OBJECTIVES

To assess the relation between the 24-hour CBT profile (CBT-24) before intensive care unit (ICU) discharge and clinical events in the step-down unit within 7 days of ICU discharge.

METHODS

This retrospective cohort study in a tertiary ICU at a single center included adult patients requiring acute invasive ventilation for more than 48 hours and assessed major clinical adverse events (MCAEs) and rapid response system activations (RRSAs) within 7 days of ICU discharge (MCAE-7 and RRSA-7, respectively).

RESULTS

The 291 enrolled patients had a median mechanical ventilation duration of 139 hours (IQR, 50-862 hours) and at admission had a median Acute Physiology and Chronic Health Evaluation II score of 22 (IQR, 7-42). At least 1 MCAE or RRSA occurred in 64% and 22% of patients, respectively. Independent predictors of an MCAE-7 were absence of CBT-24 rhythmicity (odds ratio, 1.78 [95% CI, 1.07-2.98]; P = .03), Sequential Organ Failure Assessment score at ICU discharge (1.10 [1.00-1.21]; P = .05), male sex (1.72 [1.04-2.86]; P = .04), age (1.02 [1.00-1.04]; P = .02), and Charlson Comorbidity Index (0.87 [0.76-0.99]; P = .03). Age (1.03 [1.01-1.05]; P = .006), sepsis at ICU admission (2.02 [1.13-3.63]; P = .02), and Charlson Comorbidity Index (1.18 [1.02-1.36]; P = .02) were independent predictors of an RRSA-7.

CONCLUSIONS

Use of CBT-24 rhythmicity can assist in stratifying a patient's risk of subsequent deterioration during general care within 7 days of ICU discharge.

If early warning systems are used, would it be possible to estimate early clinical deterioration risk and prevent readmission to intensive care?

Background

Although the intensive care unit (ICU) admission criteria are specified clearly, it is difficult to make the decision of discharge from ICU.

Aims

The purpose of this study is to test whether or not early warning scores will allow us to estimate early clinical deterioration within 24 hours and predict readmission to intensive care. A total of 1330 patients were included in the retrospective study.

Patients and Methods

All the patients' age, gender, ICU hospitalization reasons and Acute Physiological and Chronic Health Evaluation (APACHE II) scores were recorded. National Early Warning Score (NEWS) and VitalpacTM early warning score (VIEWS) scores were calculated using the physiological and neurological examination records. Discharge NEWS and VIEWS values of the patients who were readmitted to intensive care 24 hours after discharge were compared with the patients who were not readmitted to intensive care. The statistical analysis was performed using the IBM SPSS version 21 package software.

Results

Age average of all the patients was 64.3 ± 20.8 years. The number of the patients who were readmitted to intensive care was 118 (8.87%). When examining the factors that affect early clinical deterioration, it was found that advanced age, high APACHE II scores, higher NEWS and VIEWS scores, lower DAP values and the patient's transfer from the ward were significantly predictive (P < 0.05).

Conclusions

In this study, high NEWS and VIEWS are strong scoring systems that can be used in estimating early clinical deterioration risk and are easy-to-use and less time consuming.

Using NEWS2 to triage newly admitted patients with COVID-19

BACKGROUND

The coronavirus disease 2019 (COVID-19) pandemic has spread globally and caused a major worldwide health crisis. Patients who are affected more seriously by COVID-19 usually deteriorate rapidly and need further intensive care.

AIMS AND OBJECTIVES

We aimed to assess the performance of the National Early Warning Score 2 (NEWS2) as a risk stratification tool to discriminate newly admitted patients with COVID-19 at risk of serious events.

DESIGN

We conducted a retrospective single-centre case-control study on 200 unselected patients consecutively admitted in March 2020 in a public general hospital in Wuhan, China.

METHODS

The following serious events were considered: mortality, unplanned intensive care unit (ICU) admission, and non-invasive ventilation treatment. Receiver operating characteristic (ROC) analysis and logistic regression analysis were used to quantify the association between outcomes and NEWS2.

RESULTS

There were 12 patients (6.0%) who had serious events, where 7 patients (3.5%) experienced unplanned ICU admissions. The area under the ROC curve (AUROC) and cut-off of NEWS2 for the composite outcome were 0.83 and 3, respectively. For patients with NEWS2 ≥ 4, the odds of being at risk for serious events was 16.4 (AUROC = 0.74), while for patients with NEWS2 ≥ 7, the odds of being at risk for serious events was 18.2 (AUROC = 0.71).

CONCLUSIONS

NEWS2 has an appropriate ability to triage newly admitted patients with COVID-19 into three levels of risk: low risk (NEWS2 = 0-3), medium risk (NEWS2 = 4-6), and high risk (NEWS2 ≥ 7).

RELEVANCE TO CLINICAL PRACTICE

Using NEWS2 may help nurses in early identification of at-risk COVID-19 patients and clinical nursing decision-making. Using NEWS2 to triage new patients with COVID-19 may help nurses provide more appropriate level of care and medical resources allocation for patients safety.

New Early Warning Score: EMS Off-Label Use in Out-of-Hospital Patients

Background: The National Early Warning Score (NEWS) is an assessment scale of in-hospital patients’ conditions. The purpose of this study was to assess the appropriateness of a potential off-label use of NEWS by the emergency medical system (EMS) to facilitate the identification of critical patients and to trigger appropriate care in the pre-hospital setting. Methods: A single centre, longitudinal, prospective study was carried out between July and August 2020 in the EMS service of Bologna. Home patients with age ≥ 18 years old were included in the study. The exclusion criterion was the impossibility to collect all the parameters needed to measure NEWS. Results: A total of 654 patients were enrolled in the study. The recorded NEWS values increased along with the severity of dispatch priority code, the EMS return code, the emergency department triage code, and with patients’ age (r = 0.135; p = 0.001). The aggregated value of NEWS was associated with an increased risk of hospitalization (OR = 1.30 (1.17; 1.34); p < 0.0001). Conclusion: This study showed that the use of NEWS in the urgent and emergency care services can help patient assessment while not affecting EMS crew operation and might assist decision making in terms of severity-code assignment and resources utilization.

Risk factors for intensive care unit readmission after lung transplantation: a retrospective cohort study

Background

Lung transplantation (LT) is an accepted therapeutic modality for end-stage lung disease patients. Intensive care unit (ICU) readmission is a risk factor for mortality after LT, for which consistent risk factors have not been elucidated. Thus, we investigated the risk factors for ICU readmission during index hospitalization after LT, particularly regarding the posttransplant condition of LT patients.

Methods

In this retrospective study, we investigated all adult patients undergoing LT between October 2012 and August 2017 at our institution. We collected perioperative data from electronic medical records such as demographics, comorbidities, laboratory findings, ICU readmission, and in-hospital mortality.

Results

We analyzed data for 130 patients. Thirty-two patients (24.6%) were readmitted to the ICU 47 times during index hospitalization. At the initial ICU discharge, the Sequential Organ Failure Assessment (SOFA) score (odds ratio [OR], 1.464; 95% confidence interval [CI], 1.083−1.978; P=0.013) and pH (OR, 0.884; 95% CI, 0.813−0.962; P=0.004; when the pH value increases by 0.01) were related to ICU readmission using multivariable regression analysis and were still significant after adjusting for confounding factors. Thirteen patients (10%) died during the hospitalization period, and the number of ICU readmissions was a significant risk factor for in-hospital mortality. The most common causes of ICU readmission and in-hospital mortality were infection-related.

Conclusions

The SOFA score and pH were associated with increased risk of ICU readmission. Early postoperative management of these factors and thorough posttransplantation infection control can reduce ICU readmission and improve the prognosis of LT patients.

Transition of care at discharge from the Intensive Care Unit: a scoping review

OBJECTIVE

to map the available evidence on the components of the transition of care, practices, strategies, and tools used in the discharge from the Intensive Care Unit (ICU) to the Inpatient Unit (IU) and its impact on the outcomes of adult patients.

METHOD

a scoping review using search strategies in six relevant health databases.

RESULTS

37 articles were included, in which 30 practices, strategies or tools were identified for organizing and executing the transfer process, with positive or negative impacts, related to factors intrinsic to the Intensive Care Unit and the Inpatient Unit and cross-sectional factors regarding the staff. The analysis of hospital readmission and mortality outcomes was prevalent in the included studies, in which trends and potential protective actions for a successful care transition are found; however, they still lack more robust evidence and consensus in the literature.

CONCLUSION

transition of care components and practices were identified, in addition to factors intrinsic to the patient, associated with worse outcomes after discharge from the Intensive Care Unit. Discharges at night or on weekends were associated with increased rates of readmission and mortality; however, the association of other practices with the patient's outcome is still inconclusive.

Modified Early Warning Score as a predictor of intensive care unit readmission within 48 hours: a retrospective observational study

OBJECTIVE

To evaluate the hypothesis that the Modified Early Warning Score (MEWS) at the time of intensive care unit discharge is associated with readmission and to identify the MEWS that most reliably predicts intensive care unit readmission within 48 hours of discharge.

METHODS

This was a retrospective observational study of the MEWSs of discharged patients from the intensive care unit. We compared the demographics, severity scores, critical illness characteristics, and MEWSs of readmitted and non-readmitted patients, identified factors associated with readmission in a logistic regression model, constructed a Receiver Operating Characteristic (ROC) curve of the MEWS in predicting the probability of readmission, and presented the optimum criterion with the highest sensitivity and specificity.

RESULTS

The readmission rate was 2.6%, and the MEWS was a significant predictor of readmission, along with intensive care unit length of stay > 10 days and tracheostomy. The ROC curve of the MEWS in predicting the readmission probability had an AUC of 0.82, and a MEWS > 6 carried a sensitivity of 0.78 (95%CI 0.66 - 0.9) and specificity of 0.9 (95%CI 0.87 - 0.93).

CONCLUSION

The MEWS is associated with intensive care unit readmission, and a score > 6 has excellent accuracy as a prognostic predictor.

Impact of Intensive Care Unit Readmissions on Patient Outcomes and the Evaluation of the National Early Warning Score to Prevent Readmissions: Literature Review

Background

Intensive care unit (ICU) readmissions have been shown to increase a patient’s in-hospital mortality and length of stay (LOS). Despite this, no methods have been set in place to prevent readmissions from occurring.

Objective

The aim of this literature review was to evaluate the impact of ICU readmission on patient outcomes and to evaluate the effect of using a risk stratification tool, the National Early Warning Score (NEWS), on ICU readmissions.

Methods

A database search was performed on PubMed, Cumulative Index of Nursing and Allied Health Literature, Google Scholar, and ProQuest. In the initial search, 2028 articles were retrieved; after inclusion and exclusion criteria were applied, 12 articles were ultimately used in this literature review.

Results

This literature review found that patients readmitted to the ICU have an increased mortality rate and LOS at the hospital. The sample sizes in the reviewed studies ranged from 158 to 745,187 patients. Readmissions were most commonly associated with respiratory issues about 18% to 59% of the time. The NEWS has been shown to detect early clinical deterioration in a patient within 24 hours of transfer, with a 95% CI of 0.89 to 0.94 (P<.001), a sensitivity of 93.6% , and a specificity of 82.2%.

Conclusions

ICU readmissions are associated with worse patient outcomes, including hospital mortality and increased LOS. Without the use of an objective screening tool, the provider has been solely responsible for the decision of patient transfer. Assessment with the NEWS could be helpful in decreasing the frequency of inappropriate transfers and ultimately ICU readmission.

Can the prehospital National Early Warning Score 2 identify patients at risk of in-hospital early mortality? A prospective, multicenter cohort study

BACKGROUND

The National Early Warning Score 2 (NEWS2) scores can help identify clinical deterioration.

OBJECTIVE

To assess the predictive capacity of the NEWS2 at prehospital level for the detection of early mortality in the hospital.

METHODS

Prospective multicenter cohort study, in which we compiled a database of observed vital signs between March 1, 2018 and May 30, 2019. We collected demographic data, vital signs (respiration rate, oxygen saturation, supplemental oxygen, temperature, systolic blood pressure, heart rate and level of consciousness), prehospital diagnosis and hospital mortality data. We calculated the AUROC of the NEWS2 for early mortality.

RESULTS

We included a total of 2335 participants. Median age was 69 years (IQR 54-81 years). The AUC for mortality within one day was 0.862 (95%CI:0.78-0.93), within two days 0.885 (95%CI:0.84-0.92) and within seven days 0.835 (95%CI:0.79-0.87) (in all cases, p<0.001).

CONCLUSIONS

The NEWS2 performed at prehospital level is a bedside tool for predicting early hospital mortality.

Role of Biomarkers in the Prediction of Serious Adverse Events after Syncope in Prehospital Assessment: A Multi-Center Observational Study

Syncope is defined as the nontraumatic, transient loss of awareness of rapid onset, short duration and with complete spontaneous recovery, and accounts for 1%–3% of all visits to the emergency department. The objective of this study was to evaluate the predictive capacity of the National Early Warning Score 2 (NEWS2) and prehospital lactate (pLA), individually and combined, at the prehospital level to detect patients with syncope at risk of early mortality (within 48 h) in the hospital environment. A prospective, multicenter cohort study without intervention was carried out on syncope patients aged over 18 who were given advanced life support and taken to the hospital. Our study included a total of 361 cases. Early mortality affected 21 patients (5.8%). The combined score formed by the NEWS2 and the pLA (NEWS2-L) obtained an AUC of 0.948 (95% CI: 0.88–1) and an odds ratio of 86.25 (95% CI: 11.36–645.57), which is significantly higher than that obtained by the NEWS2 or pLA in isolation (p = 0.018). The NEWS2-L can help stratify the risk in patients with syncope treated in the prehospital setting, with only the standard measurement of physiological parameters and pLA.

Use of National Early Warning Score for observation for increased risk for clinical deterioration during post-ICU care at a surgical ward

Purpose

Patients transferred from an intensive care unit (ICU) to a general ward are at risk for clinical deterioration. The aim of the study was to determine if an increase in National Early Warning Score (NEWS) value predicted worse outcomes in surgical ward patients previously treated in the ICU.

Patients and methods

A retrospective observational study was conducted in a cohort of gastrointestinal surgery patients after transfer from an ICU/high dependency unit (HDU). NEWS values were collected throughout the ward admission. Clinical deterioration was defined by ICU readmission or death. The ability of NEWS to predict clinical deterioration was determined using a linear mixed effect model.

Results

We included 124 patients, age 65.9±14.5, 60% males with an ICU Simplified Acute Physiology Score II 33.8±12.7. No patients died unexpectedly at the ward and 20 were readmitted to an ICU/HDU. The NEWS values increased by a mean of 0.15 points per hour (intercept 3.7, P<0.001) before ICU/HDU readmission according to the linear mixed effect model. NEWS at transfer from ICU was the only factor that predicted readmission (OR 1.32; 95% CI 1.01–1.72; P=0.04) at the time of admission to the ward.

Conclusion

Clinical deterioration of surgical patients was preceded by an increase in NEWS.

Post-intensive care unit respiratory failure in older patients liberated from intensive care unit and ventilator: The predictive value of the National Early Warning Score on intensive care unit discharge

AIM

The older adult population is continuously growing worldwide and there is increasing use of medical recourse in older patients, especially for those requiring intensive care unit (ICU) care and mechanical ventilation (MV). The present study aimed to investigate the burden and predictors of post-ICU respiratory failure in older ICU patients weaned from MV.

METHODS

In the present retrospective study, older ICU patients aged ≥60 years, who were successfully weaned from MV and discharged to the general ward from the ICU of Taipei Veterans General Hospital, Taipei, Taiwan, in 2011, were included. Biomarkers on ICU discharge, as well as the National Early Warning Score (NEWS) were recorded and calculated. The outcome measure was post-ICU respiratory failure before day 14 (PIRF-14) requiring reinstitution of MV. Logistical regression was used to assess the predictors for PIRF-14.

RESULTS

Of 272 patients included, 23 (8.5%) developed PIRF-14. The post-ICU in-hospital mortality rates were 47.8% and 6.8% in patients with and without PIRF-14 (adjusted OR 12.597, 95% CI 4.368-36.331). In a multivariate analysis, the levels of NEWS and hemoglobin on ICU discharge were independent predictors for PIRF-14 (adjusted OR 1.273, 95% CI 1.076-1.507 and 0.645, 95% CI 0.474-0.879). In particular, patients with a NEWS of ≥10 and subsequent PIRF-14 had a 15-fold increased risk of mortality as compared with those without both factors (adjusted OR 15.418, 95% CI 4.344-54.720).

CONCLUSIONS

PIRF-14 is associated with high mortality in older ICU patients, and NEWS is a significant predictor for PIRF-14, which could be used to early identify patients at risk of post-ICU respiratory failure in the specific population. Geriatr Gerontol Int 2019; 19: 317-322.

A comparison of the ability of the National Early Warning Score and the National Early Warning Score 2 to identify patients at risk of in-hospital mortality: A multi-centre database study

Aims

To compare the ability of the National Early Warning Score (NEWS) and the National Early Warning Score 2 (NEWS2) to identify patients at risk of in-hospital mortality and other adverse outcomes.

Methods

We undertook a multi-centre retrospective observational study at five acute hospitals from two UK NHS Trusts. Data were obtained from completed adult admissions who were not fit enough to be discharged alive on the day of admission. Diagnostic coding and oxygen prescriptions were used to identify patients with type II respiratory failure (T2RF). The primary outcome was in-hospital mortality within 24 h of a vital signs observation. Secondary outcomes included unanticipated intensive care unit admission or cardiac arrest within 24 h of a vital signs observation. Discrimination was assessed using the c-statistic.

Results

Among 251,266 adult admissions, 48,898 were identified to be at risk of T2RF by diagnostic coding. In this group, NEWS2 showed statistically significant lower discrimination (c-statistic, 95% CI) for identifying in-hospital mortality within 24 h (0.860, 0.857–0.864) than NEWS (0.881, 0.878-0.884). For 1394 admissions with documented T2RF, discrimination was similar for both systems: NEWS2 (0.841, 0.827-0.855), NEWS (0.862, 0.848–0.875). For all secondary endpoints, NEWS2 showed no improvements in discrimination.

Conclusions

NEWS2 modifications to NEWS do not improve discrimination of adverse outcomes in patients with documented T2RF and decrease discrimination in patients at risk of T2RF. Further evaluation of the relationship between SpO₂ values, oxygen therapy and risk should be investigated further before wide-scale adoption of NEWS2.

Evaluation of the efficacy of the National Early Warning Score in predicting in-hospital mortality via the risk stratification

PURPOSE

To investigate the efficacy of the National Early Warning Score (NEWS) in predicting in-hospital mortality.

MATERIALS AND METHODS

This was a retrospective observational study and the electronic medical records of the patients were reviewed based on NEWS at the time of admission.

RESULTS

The performance of NEWS was effective in predicting hospital mortality (area under the curve: 0.765; 95% confidence interval: 0.659-0.846). Based on the Kaplan Meier survival curves, the survival time of patients who are at high risk according to NEWS was significantly shorter than that of patients who are at low risk (p < 0.001). Results of the multivariate Cox proportional hazards regression analysis showed that the hazard ratios of patients who are at medium and high risk based on NEWS were 2.6 and 4.7, respectively (p < 0.001). In addition, our study showed that the combination model that used other factors, such as age and diagnosis, was more effective than NEWS alone in predicting hospital mortality (NEWS: 0.765; combination model: 0.861; p < 0.005).

CONCLUSIONS

NEWS is a simple and useful bedside tool for predicting in-hospital mortality. In addition, the rapid response team must consider other clinical factors as well as screening tools to improve clinical outcomes.