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Woolfe Loftus N, Navales V, Bowden T. Using the NEWS2 and ABCDE assessment to identify early signs of clinical deterioration. Nurs Stand 2024; 39:40-45. [PMID: 38523526 DOI: 10.7748/ns.2024.e12188] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/06/2023] [Indexed: 03/26/2024]
Abstract
Nurses may encounter deteriorating patients in their clinical practice, so they require an understanding of the early physiological signs of deterioration and a structured approach to patient assessment. This enables appropriate management and a timely response to the most life-threatening issues identified, such as a compromised airway. This article describes how nurses can use early warning scores and a structured patient assessment, using the ABCDE (airway, breathing, circulation, disability, exposure) framework, to identify early signs of deterioration and facilitate the timely escalation of patient care where necessary.
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Affiliation(s)
- Nicholas Woolfe Loftus
- Adult Critical Care Unit, St Bartholomew's Hospital, London, and NIHR predoctoral clinical academic fellow, City, University of London, London, England
| | - Vanna Navales
- Adult Critical Care Unit, St Bartholomew's Hospital, London, England
| | - Tracey Bowden
- School of Health and Psychosocial Sciences, City, University of London, London, England
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Briggs J, Kostakis I, Meredith P, Dall'ora C, Darbyshire J, Gerry S, Griffiths P, Hope J, Jones J, Kovacs C, Lawrence R, Prytherch D, Watkinson P, Redfern O. Safer and more efficient vital signs monitoring protocols to identify the deteriorating patients in the general hospital ward: an observational study. Health Soc Care Deliv Res 2024; 12:1-143. [PMID: 38551079 DOI: 10.3310/hytr4612] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/02/2024]
Abstract
Background The frequency at which patients should have their vital signs (e.g. blood pressure, pulse, oxygen saturation) measured on hospital wards is currently unknown. Current National Health Service monitoring protocols are based on expert opinion but supported by little empirical evidence. The challenge is finding the balance between insufficient monitoring (risking missing early signs of deterioration and delays in treatment) and over-observation of stable patients (wasting resources needed in other aspects of care). Objective Provide an evidence-based approach to creating monitoring protocols based on a patient's risk of deterioration and link these to nursing workload and economic impact. Design Our study consisted of two parts: (1) an observational study of nursing staff to ascertain the time to perform vital sign observations; and (2) a retrospective study of historic data on patient admissions exploring the relationships between National Early Warning Score and risk of outcome over time. These were underpinned by opinions and experiences from stakeholders. Setting and participants Observational study: observed nursing staff on 16 randomly selected adult general wards at four acute National Health Service hospitals. Retrospective study: extracted, linked and analysed routinely collected data from two large National Health Service acute trusts; data from over 400,000 patient admissions and 9,000,000 vital sign observations. Results Observational study found a variety of practices, with two hospitals having registered nurses take the majority of vital sign observations and two favouring healthcare assistants or student nurses. However, whoever took the observations spent roughly the same length of time. The average was 5:01 minutes per observation over a 'round', including time to locate and prepare the equipment and travel to the patient area. Retrospective study created survival models predicting the risk of outcomes over time since the patient was last observed. For low-risk patients, there was little difference in risk between 4 hours and 24 hours post observation. Conclusions We explored several different scenarios with our stakeholders (clinicians and patients), based on how 'risk' could be managed in different ways. Vital sign observations are often done more frequently than necessary from a bald assessment of the patient's risk, and we show that a maximum threshold of risk could theoretically be achieved with less resource. Existing resources could therefore be redeployed within a changed protocol to achieve better outcomes for some patients without compromising the safety of the rest. Our work supports the approach of the current monitoring protocol, whereby patients' National Early Warning Score 2 guides observation frequency. Existing practice is to observe higher-risk patients more frequently and our findings have shown that this is objectively justified. It is worth noting that important nurse-patient interactions take place during vital sign monitoring and should not be eliminated under new monitoring processes. Our study contributes to the existing evidence on how vital sign observations should be scheduled. However, ultimately, it is for the relevant professionals to decide how our work should be used. Study registration This study is registered as ISRCTN10863045. Funding This award was funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme (NIHR award ref: 17/05/03) and is published in full in Health and Social Care Delivery Research; Vol. 12, No. 6. See the NIHR Funding and Awards website for further award information.
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Affiliation(s)
- Jim Briggs
- Centre for Healthcare Modelling and Informatics, University of Portsmouth, Portsmouth, UK
| | - Ina Kostakis
- Centre for Healthcare Modelling and Informatics, University of Portsmouth, Portsmouth, UK
| | - Paul Meredith
- Research Department, Portsmouth Hospitals University NHS Trust, Portsmouth, UK
| | | | - Julie Darbyshire
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Stephen Gerry
- Centre for Statistics in Medicine, University of Oxford, Oxford, UK
| | | | - Jo Hope
- Health Sciences, University of Southampton, Southampton, UK
| | - Jeremy Jones
- Health Sciences, University of Southampton, Southampton, UK
| | - Caroline Kovacs
- Centre for Healthcare Modelling and Informatics, University of Portsmouth, Portsmouth, UK
| | | | - David Prytherch
- Centre for Healthcare Modelling and Informatics, University of Portsmouth, Portsmouth, UK
| | - Peter Watkinson
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Oliver Redfern
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
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Ruppert MM, Loftus TJ, Small C, Li H, Ozrazgat-Baslanti T, Balch J, Holmes R, Tighe PJ, Upchurch GR Jr, Efron PA, Rashidi P, Bihorac A. Predictive Modeling for Readmission to Intensive Care: A Systematic Review. Crit Care Explor 2023; 5:e0848. [PMID: 36699252 DOI: 10.1097/CCE.0000000000000848] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023] Open
Abstract
To evaluate the methodologic rigor and predictive performance of models predicting ICU readmission; to understand the characteristics of ideal prediction models; and to elucidate relationships between appropriate triage decisions and patient outcomes. DATA SOURCES PubMed, Web of Science, Cochrane, and Embase. STUDY SELECTION Primary literature that reported the development or validation of ICU readmission prediction models within from 2010 to 2021. DATA EXTRACTION Relevant study information was extracted independently by two authors using the Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies checklist. Bias was evaluated using the Prediction model Risk Of Bias ASsessment Tool. Data sources, modeling methodology, definition of outcomes, performance, and risk of bias were critically evaluated to elucidate relevant relationships. DATA SYNTHESIS Thirty-three articles describing models were included. Six studies had a high overall risk of bias due to improper inclusion criteria or omission of critical analysis details. Four other studies had an unclear overall risk of bias due to lack of detail describing the analysis. Overall, the most common (50% of studies) source of bias was the filtering of candidate predictors via univariate analysis. The poorest performing models used existing clinical risk or acuity scores such as Acute Physiologic Assessment and Chronic Health Evaluation II, Sequential Organ Failure Assessment, or Stability and Workload Index for Transfer as the sole predictor. The higher-performing ICU readmission prediction models used homogenous patient populations, specifically defined outcomes, and routinely collected predictors that were analyzed over time. CONCLUSIONS Models predicting ICU readmission can achieve performance advantages by using longitudinal time series modeling, homogenous patient populations, and predictor variables tailored to those populations.
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Danielis M, Iob R, Achil I, Palese A. Family Visiting Restrictions and Postoperative Clinical Outcomes: A Retrospective Analysis. Nurs Rep 2022; 12:583-588. [PMID: 35997465 PMCID: PMC9397009 DOI: 10.3390/nursrep12030057] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Revised: 08/02/2022] [Accepted: 08/09/2022] [Indexed: 11/16/2022] Open
Abstract
In the last two years, all hospitals have adopted restricted visitation policies due to the coronavirus disease 2019. The objective of this study was to assess the consequences of hospital visitation restrictions on the most common outcome measures on adult patients who underwent surgery. A retrospective study design was conducted according to the STrengthening the Reporting of OBservational studies in Epidemiology statements in 2021. Forty patients exposed to a no-visitors policy and forty unexposed patients (1:1) were enrolled. Patients who were not allowed to receive family visits were more likely to report disorientation/agitation episodes (n = 25, 62.5% vs. n = 12, 30.0%; p < 0.01), spend more sleepless nights (n = 10, 25.0% vs. n = 1, 2.5%; p < 0.01), be restrained (n = 8, 20.0% vs. n = 1, 2.5%; p = 0.02), incur device-removal incidents (n = 14, 35.0% vs. n = 5, 12.5%; p = 0.01) compared to unexposed patients. Conversely, pain episodes were significantly more frequent in the unexposed group (n = 7.1, SD = 7.9 vs. n = 2.4, SD = 2.8; p < 0.01), and there was lower clinical deterioration risk (NEWS of 0−4 average 19.5, SD = 12.2 evaluations vs. 12.3, SD = 8.6; p < 0.01) compared to exposed patients. According to the results, family visiting restrictions should be measured against their possible advantages in order to prevent negative outcomes for surgical patients and to improve the quality of care.
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Mahmoodpoor A, Sanaie S, Saghaleini SH, Ostadi Z, Hosseini MS, Sheshgelani N, Vahedian-Azimi A, Samim A, Rahimi-Bashar F. Prognostic value of National Early Warning Score and Modified Early Warning Score on intensive care unit readmission and mortality: A prospective observational study. Front Med (Lausanne) 2022; 9:938005. [PMID: 35991649 PMCID: PMC9386480 DOI: 10.3389/fmed.2022.938005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Accepted: 07/19/2022] [Indexed: 12/03/2022] Open
Abstract
Background Modified Early Warning Score (MEWS) and National Early Warning Score (NEWS) are widely used in predicting the mortality and intensive care unit (ICU) admission of critically ill patients. This study was conducted to evaluate and compare the prognostic value of NEWS and MEWS for predicting ICU readmission, mortality, and related outcomes in critically ill patients at the time of ICU discharge. Methods This multicenter, prospective, observational study was conducted over a year, from April 2019 to March 2020, in the general ICUs of two university-affiliated hospitals in Northwest Iran. MEWS and NEWS were compared based on the patients’ outcomes (including mortality, ICU readmission, time to readmission, discharge type, mechanical ventilation (MV), MV duration, and multiple organ failure after readmission) using the univariable and multivariable binary logistic regression. The receiver operating characteristic (ROC) curve was used to determine the outcome predictability of MEWS and NEWS. Results A total of 410 ICU patients were enrolled in this study. According to multivariable logistic regression analysis, both MEWS and NEWS were predictors of ICU readmission, time to readmission, MV status after readmission, MV duration, and multiple organ failure after readmission. The area under the ROC curve (AUC) for predicting mortality was 0.91 (95% CI = 0.88–0.94, P < 0.0001) for the NEWS and 0.88 (95% CI = 0.84–0.91, P < 0.0001) for the MEWS. There was no significant difference between the AUC of the NEWS and the MEWS for predicting mortality (P = 0.082). However, for ICU readmission (0.84 vs. 0.71), time to readmission (0.82 vs. 0.67), MV after readmission (0.83 vs. 0.72), MV duration (0.81 vs. 0.67), and multiple organ failure (0.833 vs. 0.710), the AUCs of MEWS were significantly greater (P < 0.001). Conclusion National Early Warning Score and MEWS values of >4 demonstrated high sensitivity and specificity in identifying the risk of mortality for the patients’ discharge from ICU. However, we found that the MEWS showed superiority over the NEWS score in predicting other outcomes. Eventually, MEWS could be considered an efficient prediction score for morbidity and mortality of critically ill patients.
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Affiliation(s)
- Ata Mahmoodpoor
- Research Center for Integrative Medicine in Aging, Aging Research Institute, Tabriz University of Medical Sciences, Tabriz, Iran
- *Correspondence: Ata Mahmoodpoor,
| | - Sarvin Sanaie
- Research Center for Integrative Medicine in Aging, Aging Research Institute, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Seied Hadi Saghaleini
- Department of Anesthesiology and Intensive Care, Faculty of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Zohreh Ostadi
- Department of Anesthesiology and Intensive Care, Faculty of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran
| | | | - Naeeme Sheshgelani
- Student Research Committee, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Amir Vahedian-Azimi
- Trauma Research Center, Nursing Faculty, Baqiyatallah University of Medical Sciences, Tehran, Iran
| | - Abbas Samim
- Chemical Injuries Research Center, Systems Biology and Poisonings Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran
| | - Farshid Rahimi-Bashar
- Anesthesia and Critical Care Department, Hamadan University of Medical Sciences, Hamadan, Iran
- Farshid Rahimi-Bashar,
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Smith D, Cartwright M, Dyson J, Hartin J, Aitken LM. Selecting intervention content to target barriers and enablers of recognition and response to deteriorating patients: an online nominal group study. BMC Health Serv Res 2022; 22:766. [PMID: 35689227 PMCID: PMC9186287 DOI: 10.1186/s12913-022-08128-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2022] [Accepted: 05/23/2022] [Indexed: 12/02/2022] Open
Abstract
Background Patients who deteriorate in hospital wards without appropriate recognition and/or response are at risk of increased morbidity and mortality. Track-and-trigger tools have been implemented internationally prompting healthcare practitioners (typically nursing staff) to recognise physiological changes (e.g. changes in blood pressure, heart rate) consistent with patient deterioration, and then to contact a practitioner with expertise in management of acute/critical illness. Despite some evidence these tools improve patient outcomes, their translation into clinical practice is inconsistent internationally. To drive greater guideline adherence in the use of the National Early Warning Score tool (a track-and-trigger tool used widely in the United Kingdom and parts of Europe), a theoretically informed implementation intervention was developed (targeting nursing staff) using the Theoretical Domains Framework (TDF) version 2 and a taxonomy of Behaviour Change Techniques (BCTs). Methods A three-stage process was followed: 1. TDF domains representing important barriers and enablers to target behaviours derived from earlier published empirical work were mapped to appropriate BCTs; 2. BCTs were shortlisted using consensus approaches within the research team; 3. shortlisted BCTs were presented to relevant stakeholders in two online group discussions where nominal group techniques were applied. Nominal group participants were healthcare leaders, senior clinicians, and ward-based nursing staff. Stakeholders individually generated concrete strategies for operationalising shortlisted BCTs (‘applications’) and privately ranked them according to acceptability and feasibility. Ranking data were used to drive decision-making about intervention content. Results Fifty BCTs (mapped in stage 1) were shortlisted to 14 (stage 2) and presented to stakeholders in nominal groups (stage 3) alongside example applications. Informed by ranking data from nominal groups, the intervention was populated with 12 BCTs that will be delivered face-to-face, to individuals and groups of nursing staff, through 18 applications. Conclusions A description of a theory-based behaviour change intervention is reported, populated with BCTs and applications generated and/or prioritised by stakeholders using replicable consensus methods. The feasibility of the proposed intervention should be tested in a clinical setting and the content of the intervention elaborated further to permit replication and evaluation. Supplementary Information The online version contains supplementary material available at 10.1186/s12913-022-08128-6.
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Affiliation(s)
- Duncan Smith
- School of Health Sciences, City, University of London, Northampton Square, London, EC1V 0HB, UK. .,Patient Emergency Response & Resuscitation Team (PERRT), University College London Hospitals NHS Foundation Trust, Euston Road, London, NW1 2BU, UK.
| | - Martin Cartwright
- School of Health Sciences, City, University of London, Northampton Square, London, EC1V 0HB, UK
| | - Judith Dyson
- Reader in Implementation Science, Birmingham City University, Westbourne Road, Edgbaston, Birmingham, B15 3TN, UK
| | - Jillian Hartin
- Patient Emergency Response & Resuscitation Team (PERRT), University College London Hospitals NHS Foundation Trust, Euston Road, London, NW1 2BU, UK
| | - Leanne M Aitken
- School of Health Sciences, City, University of London, Northampton Square, London, EC1V 0HB, UK.,School of Nursing and Midwifery, Griffith University, Nathan, QLD, 4111, Australia
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Gaughan MR, Jungquist CR. Patient Deterioration on General Care Units: A Concept Analysis. ANS Adv Nurs Sci 2022; 45:E56-68. [PMID: 34879020 DOI: 10.1097/ANS.0000000000000396] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
Patient deterioration is a phenomenon that occurs from the inability to recognize it or respond to a change in condition. Despite the published reports on recognizing a deteriorating patient on general care floors, a gap remains in the ability of nurses to describe the concept, affecting patient outcomes. Walker and Avant's approach was applied to analyze patient deterioration. The aim of this article was to explore and clarify the meaning of patient deterioration and identify attributes, antecedents, and consequences. The defining attributes were compared to early warning scores. An operational definition was developed and its value to nurses established.
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Jorge J, Villarroel M, Tomlinson H, Gibson O, Darbyshire JL, Ede J, Harford M, Young JD, Tarassenko L, Watkinson P. Non-contact physiological monitoring of post-operative patients in the intensive care unit. NPJ Digit Med 2022; 5:4. [PMID: 35027658 DOI: 10.1038/s41746-021-00543-z] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2021] [Accepted: 11/28/2021] [Indexed: 11/08/2022] Open
Abstract
Prolonged non-contact camera-based monitoring in critically ill patients presents unique challenges, but may facilitate safe recovery. A study was designed to evaluate the feasibility of introducing a non-contact video camera monitoring system into an acute clinical setting. We assessed the accuracy and robustness of the video camera-derived estimates of the vital signs against the electronically-recorded reference values in both day and night environments. We demonstrated non-contact monitoring of heart rate and respiratory rate for extended periods of time in 15 post-operative patients. Across day and night, heart rate was estimated for up to 53.2% (103.0 h) of the total valid camera data with a mean absolute error (MAE) of 2.5 beats/min in comparison to two reference sensors. We obtained respiratory rate estimates for 63.1% (119.8 h) of the total valid camera data with a MAE of 2.4 breaths/min against the reference value computed from the chest impedance pneumogram. Non-contact estimates detected relevant changes in the vital-sign values between routine clinical observations. Pivotal respiratory events in a post-operative patient could be identified from the analysis of video-derived respiratory information. Continuous vital-sign monitoring supported by non-contact video camera estimates could be used to track early signs of physiological deterioration during post-operative care.
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Boots R, Mead G, Rawashdeh O, Bellapart J, Townsend S, Paratz J, Garner N, Clement P, Oddy D. Temperature Profile and Adverse Outcomes After Discharge From the Intensive Care Unit. Am J Crit Care 2022; 31:e1-e9. [PMID: 34972850 DOI: 10.4037/ajcc2022223] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/01/2022]
Abstract
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.
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Affiliation(s)
- Rob Boots
- Rob Boots is an associate professor, Thoracic Medicine, Royal Brisbane and Women’s Hospital, and Faculty of Medicine, The University of Queensland, Herston, Queensland, Australia
| | - Gabrielle Mead
- Gabrielle Mead is an honors student, School of Biomedical Sciences, Faculty of Medicine, The University of Queensland
| | - Oliver Rawashdeh
- Oliver Rawashdeh is a senior lecturer,, School of Biomedical Sciences, Faculty of Medicine, The University of Queensland
| | - Judith Bellapart
- Judith Bellapart is a senior specialist, Department of Intensive Care Medicine, Royal Brisbane and Women’s Hospital, and Burns, Trauma and Critical Care, The University of Queensland
| | - Shane Townsend
- Shane Townsend is director, Intensive Care Services, Royal Brisbane and Women’s Hospital
| | - Jenny Paratz
- Jenny Paratz is an associate professor and a senior research fellow, Burns, Trauma and Critical Care Research Centre, The University of Queensland School of Medicine
| | - Nicholas Garner
- Nicholas Garner is a PhD student, School of Biomedical Sciences, Faculty of Medicine, The University of Queensland
| | - Pierre Clement
- Pierre Clement is the clinical information systems manager, Department of Intensive Care Services, Royal Brisbane and Women’s Hospital
| | - David Oddy
- David Oddy is the clinical data manager, Department of Intensive Care Services, Royal Brisbane and Women’s Hospital
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Kupeli I, Subasi F. If early warning systems are used, would it be possible to estimate early clinical deterioration risk and prevent readmission to intensive care? Niger J Clin Pract 2021; 24:1773-1778. [PMID: 34889784 DOI: 10.4103/njcp.njcp_682_19] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
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.
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Affiliation(s)
- I Kupeli
- Department of Anesthesiology And Reanimation, Biruni University Faculty of Medicine, Istanbul, Turkey
| | - F Subasi
- Department of Anesthesiology And Reanimation, Mengücek Gazi Training And Research Hospital, Erzincan, Turkey
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Chang MC, Kim TU, Park D. National early warning score on admission as risk factor for invasive mechanical ventilation in COVID-19 patients: A STROBE-compliant study. Medicine (Baltimore) 2021; 100:e25917. [PMID: 34106657 PMCID: PMC8133259 DOI: 10.1097/md.0000000000025917] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/06/2021] [Accepted: 04/20/2021] [Indexed: 12/15/2022] Open
Abstract
The coronavirus disease (COVID-19) has become a global pandemic. Invasive mechanical ventilation is recommended for the management of patients with COVID-19 who have severe respiratory symptoms. However, various complications can develop after its use. The efficient and appropriate management of patients requires the identification of factors associated with an aggravation of COVID-19 respiratory symptoms to a degree where invasive mechanical ventilation becomes necessary, thereby enabling clinicians to prevent such ventilation. This retrospective study included 138 inpatients with COVID-19 at a tertiary hospital. We evaluated the differences in the demographic and clinical data between 27 patients who required invasive mechanical ventilation and 111 patients who did not. Multivariate logistic regression analysis indicated that the duration of fever, national early warning score (NEWS), and lactate dehydrogenase (LDH) levels on admission were significantly associated with invasive mechanical ventilation in this cohort. The optimal cut-off values were: fever duration ≥1 day (sensitivity 100.0%, specificity 54.95%), NEWS ≥7 (sensitivity 72.73%, specificity 92.52%), and LDH >810 mg/dL (sensitivity 56.0%, specificity 90.29%). These findings can assist in the early identification of patients who will require invasive mechanical ventilation. Further studies in larger patient populations are recommended to validate our findings.
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Affiliation(s)
- Min Cheol Chang
- Department of Physical Medicine and Rehabilitation, College of Medicine, Yeungnam University, Daegu
| | - Tae Uk Kim
- Department of Physical Medicine and Rehabilitation, College of Medicine, Dankook University, Cheonan
| | - Donghwi Park
- Department of Physical Medicine and Rehabilitation, Ulsan University Hospital, University of Ulsan College of Medicine, Ulsan, Republic of Korea
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Smith D, Cartwright M, Dyson J, Hartin J, Aitken LM. Patterns of behaviour in nursing staff actioning the afferent limb of the rapid response system (RRS): A focused ethnography. J Adv Nurs 2020; 76:3548-3562. [PMID: 32996620 DOI: 10.1111/jan.14551] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2020] [Revised: 07/09/2020] [Accepted: 07/29/2020] [Indexed: 12/17/2022]
Abstract
AIM To improve understanding of afferent limb behaviour in acute hospital ward settings, to define and specify who needs to do what differently and to report what afferent limb behaviours should be targeted in a subsequent multi-phase, theory-based, intervention development process. DESIGN Focused ethnography was used including direct observation of nursing staff enacting afferent limb behaviours and review of vital signs charts. METHODS An observation guide focused observation on "key moments" of the afferent limb. Descriptions of observations from between 7 January 2019-18 December 2019 were recorded in a field journal alongside reflexive notes. Vital signs and early warning scores from charts were reviewed and recorded. Field notes were analysed using structured content analysis. Observed behaviour was compared with expected (policy-specified) behaviour. RESULTS Observation was conducted for 300 hr. Four hundred and ninety-nine items of data (e.g., an episode of observation or a set of vital signs) were collected. Two hundred and eighty-nine (58%) items of data were associated with expected (i.e. policy-specified) afferent limb behaviour; 210 (42%) items of data were associated with unexpected afferent limb behaviour (i.e. alternative behaviour or no behaviour). Ten specific behaviours were identified where the behaviour observed deviated (negatively) from policy or where no action was taken when it should have been. One further behaviour was seen to expedite the assessment of a deteriorating patient by an appropriate responder and was therefore considered a positive deviance. CONCLUSION Afferent limb failure has been described as a problem of inconsistent staff behaviour. Eleven potential target behaviours for change are reported and specified using a published framework. IMPACT Clear specification of target behaviour will allow further enquiry into the determinants of these behaviours and the development of a theory-based intervention that is more likely to result in behaviour change and can be tested empirically in future research.
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Affiliation(s)
- Duncan Smith
- School of Health Sciences, City University of London, London, UK.,University College London Hospitals NHS Foundation Trust, London, UK
| | | | - Judith Dyson
- School of Health Sciences, City University of London, London, UK
| | - Jillian Hartin
- University College London Hospitals NHS Foundation Trust, London, UK
| | - Leanne M Aitken
- School of Health Sciences, City University of London, London, UK.,School of Nursing and Midwifery, Griffith University, Nathan, QLD, Australia
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Balshi AN, Huwait BM, Noor ASN, Alharthy AM, Madi AF, Ramadan OE, Balahmar A, Mhawish HA, Marasigan BR, Alcazar AM, Rana MA, Aletreby WT. Modified Early Warning Score as a predictor of intensive care unit readmission within 48 hours: a retrospective observational study. Rev Bras Ter Intensiva 2020; 32:301-307. [PMID: 32667433 PMCID: PMC7405753 DOI: 10.5935/0103-507x.20200047] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2019] [Accepted: 02/17/2020] [Indexed: 12/23/2022] Open
Abstract
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.
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Affiliation(s)
- Ahmed Naji Balshi
- Critical Care Department, King Saud Medical City, Riyadh, Saudi Arabia
| | | | | | | | - Ahmed Fouad Madi
- Critical Care Department, King Saud Medical City, Riyadh, Saudi Arabia
| | | | - Abdullah Balahmar
- Critical Care Department, King Saud Medical City, Riyadh, Saudi Arabia
| | - Huda A Mhawish
- Critical Care Department, King Saud Medical City, Riyadh, Saudi Arabia
| | | | | | - Muhammad Asim Rana
- Internal Medicine and Critical Care Department, Bahria Town International Hospital, Lahore, Pakistan
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