A model-based cost-utility analysis of an automated notification system for deteriorating patients on general wards.

BACKGROUND: Delayed response to clinical deterioration of hospital inpatients is common. Deployment of an electronic automated advisory vital signs monitoring and notification system to signal clinical deterioration is associated with significant improvements in clinical outcomes but there is no evidence on the cost-effectiveness compared with routine monitoring, in the National Health Service (NHS) in the United Kingdom (UK). METHODS: A decision analytic model was developed to estimate the cost-effectiveness of an electronic automated advisory notification system versus standard care, in adults admitted to a district general hospital. Analyses considered: (1) the cost-effectiveness of the technology based on secondary analysis of patient level data of 3787 inpatients in a before-and-after study; and (2) the cost-utility (cost per quality-adjusted life-year (QALY)) over a lifetime horizon, extrapolated using published data. Analysis was conducted from the perspective of the NHS. Uncertainty in the model was assessed using a range of sensitivity analyses. RESULTS: The study population had a mean age of 68 years, 48% male, with a median inpatient stay of 6 days. Expected life expectancy at discharge was assumed to be 17.74 years. (1) Cost-effectiveness analysis: The automated notification system was more effective (-0.027 reduction in mean events per patient) and provided a cost saving of -£12.17 (-182.07 to 154.80) per patient admission. (2) Cost-utility analysis: Over a lifetime horizon the automated notification system was dominant, demonstrating a positive incremental QALY gain (0.0287 QALYs, equivalent to ~10 days of perfect health) and a cost saving of £55.35. At a threshold of £20,000 per QALY, the probability of automated monitoring being cost-effective in the NHS was 81%. Increased use of cableless sensors may reduce cost-savings, however, the intervention remains cost-effective at 100% usage (ICER: £3,107/QALY). Stratified cost-effectiveness analysis by age, National Early Warning Score (NEWS) on admission, and primary diagnosis indicated the automated notification system was cost-effective for most strategies and that use representative of the patient population studied was the most cost-saving strategy. CONCLUSION: Automated notification system for adult patients admitted to general wards appears to be a cost-effective use in the NHS; adopting this technology could be good use of scarce resources with significance for patient safety.

Cardiac herniation post left upper lobectomy and thymectomy: a case report.

BACKGROUND: Cardiac herniation occurs when there is a residual pericardial defect post thoracic surgery and is recognised as a rare but fatal complication. It confers a high mortality and requires immediate surgical correction upon recognition. We present a case of cardiac herniation occurring post thymectomy and left upper lobectomy. CASE PRESENTATION: Initial presentation: A 48-year-old male, hypertensive smoker presented with progressive breathlessness and was found to have a left upper zone mass confirmed on CT biopsy as carcinoid of unclear origin. PET-CT revealed avidity in a left anterior mediastinal area, left upper lobe (LUL) lung mass, mediastinal lymph nodes, and a right thymic satellite nodule. Intraoperatively: Access via left thoracotomy and sternotomy. The LUL tumour involved the left thymic lobe (LTL), left superior pulmonary vein (LSPV), left phrenic nerve and intervening mediastinal fat and pericardium, which were resected en-masse. The satellite nodule in the right thymic lobe (RTL) was adjacent to the junction between the left innominate vein and superior vena cava (SVC). The pericardium was resected from the SVC to the left atrial appendage. Clinical deterioration: Initially the patient was doing well clinically on day 1, however there was sudden bradycardia, hypotension, clamminess, and oligoanuria, with raised central venous pressures and troponins. ECG: no capture in leads V1-2, but positive deflections seen on posterior leads. Echo: no acoustic windows, but good windows seen posteriorly. CXR: left mediastinal shift. Redo operation: After initial resuscitation and stabilisation on the intensive care unit, on day 2 a redo-sternotomy revealed cardiac herniation into the left thoracic cavity with the left ventricular apex pointing towards the spine, and inferior caval kinking. After reduction and repair of the pericardial defect with a fenestrated GoreTex patch, the patient recovered well with complete resolution of the ECG and CXR. CONCLUSION: Cardiac herniation can even occur following sub-pneumonectomy lung resections and should be considered as a differential when faced with a sudden clinical deterioration, warranting early surgical correction.

Effectiveness of an Artificial Intelligence-Enabled Intervention for Detecting Clinical Deterioration.

Importance: Inpatient clinical deterioration is associated with substantial morbidity and mortality but may be easily missed by clinicians. Early warning scores have been developed to alert clinicians to patients at high risk of clinical deterioration, but there is limited evidence for their effectiveness. Objective: To evaluate the effectiveness of an artificial intelligence deterioration model-enabled intervention to reduce the risk of escalations in care among hospitalized patients using a study design that facilitates stronger causal inference. Design, Setting, and Participants: This cohort study used a regression discontinuity design that controlled for confounding and was based on Epic Deterioration Index (EDI; Epic Systems Corporation) prediction model scores. Compared with other observational research, the regression discontinuity design facilitates causal analysis. Hospitalized adults were included from 4 general internal medicine units in 1 academic hospital from January 17, 2021, through November 16, 2022. Exposure: An artificial intelligence deterioration model-enabled intervention, consisting of alerts based on an EDI score threshold with an associated collaborative workflow among nurses and physicians. Main Outcomes and Measures: The primary outcome was escalations in care, including rapid response team activation, transfer to the intensive care unit, or cardiopulmonary arrest during hospitalization. Results: During the study, 9938 patients were admitted to 1 of the 4 units, with 963 patients (median [IQR] age, 76.1 [64.2-86.2] years; 498 males [52.3%]) included within the primary regression discontinuity analysis. The median (IQR) Elixhauser Comorbidity Index score in the primary analysis cohort was 10 (0-24). The intervention was associated with a -10.4-percentage point (95% CI, -20.1 to -0.8 percentage points; P = .03) absolute risk reduction in the primary outcome for patients at the EDI score threshold. There was no evidence of a discontinuity in measured confounders at the EDI score threshold. Conclusions and Relevance: Using a regression discontinuity design, this cohort study found that the implementation of an artificial intelligence deterioration model-enabled intervention was associated with a significantly decreased risk of escalations in care among inpatients. These results provide evidence for the effectiveness of this intervention and support its further expansion and testing in other care settings.

Using the NEWS2 and ABCDE assessment to identify early signs of clinical deterioration.

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.

British societies guideline on the management of emergencies in implantable left ventricular assist device recipients in transplant centres.

An implantable left ventricular assist device (LVAD) is indicated as a bridge to transplantation or recovery in the United Kingdom (UK). The mechanism of action of the LVAD results in a unique state of haemodynamic stability with diminished arterial pulsatility. The clinical assessment of an LVAD recipient can be challenging because non-invasive blood pressure, pulse and oxygen saturation measurements may be hard to obtain. As a result of this unusual situation and complex interplay between the device and the native circulation, resuscitation of LVAD recipients requires bespoke guidelines. Through collaboration with key UK stakeholders, we assessed the current evidence base and developed guidelines for the recognition of clinical deterioration, inadequate circulation and time-critical interventions. Such guidelines, intended for use in transplant centres, are designed to be deployed by those providing immediate care of LVAD patients under conditions of precipitous clinical deterioration. In summary, the Joint British Societies and Transplant Centres LVAD Working Group present the UK guideline on management of emergencies in implantable LVAD recipients for use in advanced heart failure centres. These recommendations have been made with a UK resuscitation focus but are widely applicable to professionals regularly managing patients with implantable LVADs.

Waitlist Outcomes in Candidates With Rare Causes of Heart Failure After Implementation of the 2018 French Heart Allocation Scheme.

BACKGROUND: In 2018, an algorithm-based allocation system for heart transplantation (HT) was implemented in France. Its effect on access to HT of patients with rare causes of heart failure (HF) has not been assessed. METHODS: In this national study, including adults listed for HT between 2018 and 2020, we analyzed waitlist and posttransplant outcomes of candidates with rare causes of HF (restrictive cardiomyopathy [RCM], hypertrophic cardiomyopathy, and congenital heart disease). The primary end point was death on the waitlist or delisting for clinical deterioration. Secondary end points included access to HT and posttransplant mortality. The cumulative incidence of waitlist mortality estimated with competing risk analysis and incidence of transplantation were compared between diagnosis groups. The association of HF cause with outcomes was determined by Fine-Gray or Cox models. RESULTS: Overall, 1604 candidates were listed for HT. At 1 year postlisting, 175 patients met the primary end point and 1040 underwent HT. Candidates listed for rare causes of HF significantly differed in baseline characteristics and had more frequent score exceptions compared with other cardiomyopathies (31.3%, 32.0%, 36.4%, and 16.7% for patients with hypertrophic cardiomyopathy, RCM, congenital heart disease, and other cardiomyopathies). The cumulative incidence of death on the waitlist and probability of HT were similar between diagnosis groups (P=0.17 and 0.40, respectively). The adjusted risk of death or delisting for clinical deterioration did not significantly differ between candidates with rare and common causes of HF (subdistribution hazard ratio (HR): hypertrophic cardiomyopathy, 0.51 [95% CI, 0.19-1.38]; P=0.18; RCM, 1.04 [95% CI, 0.42-2.58]; P=0.94; congenital heart disease, 1.82 [95% CI, 0.78-4.26]; P=0.17). Similarly, the access to HT did not significantly differ between causes of HF (hypertrophic cardiomyopathy: HR, 1.18 [95% CI, 0.92-1.51]; P=0.19; RCM: HR, 1.19 [95% CI, 0.90-1.58]; P=0.23; congenital heart disease: HR, 0.76 [95% CI, 0.53-1.09]; P=0.14). RCM was an independent risk factor for 1-year posttransplant mortality (HR, 2.12 [95% CI, 1.06-4.24]; P=0.03). CONCLUSIONS: Our study shows equitable waitlist outcomes among HT candidates whatever the indication for transplantation with the new French allocation scheme.

Identification of Predictors for Clinical Deterioration in Patients With COVID-19 via Electronic Nursing Records: Retrospective Observational Study.

BACKGROUND: Few studies have used standardized nursing records with Systematized Nomenclature of Medicine-Clinical Terms (SNOMED CT) to identify predictors of clinical deterioration. OBJECTIVE: This study aims to standardize the nursing documentation records of patients with COVID-19 using SNOMED CT and identify predictive factors of clinical deterioration in patients with COVID-19 via standardized nursing records. METHODS: In this study, 57,558 nursing statements from 226 patients with COVID-19 were analyzed. Among these, 45,852 statements were from 207 patients in the stable (control) group and 11,706 from 19 patients in the exacerbated (case) group who were transferred to the intensive care unit within 7 days. The data were collected between December 2019 and June 2022. These nursing statements were standardized using the SNOMED CT International Edition released on November 30, 2022. The 260 unique nursing statements that accounted for the top 90% of 57,558 statements were selected as the mapping source and mapped into SNOMED CT concepts based on their meaning by 2 experts with more than 5 years of SNOMED CT mapping experience. To identify the main features of nursing statements associated with the exacerbation of patient condition, random forest algorithms were used, and optimal hyperparameters were selected for nursing problems or outcomes and nursing procedure-related statements. Additionally, logistic regression analysis was conducted to identify features that determine clinical deterioration in patients with COVID-19. RESULTS: All nursing statements were semantically mapped to SNOMED CT concepts for "clinical finding," "situation with explicit context," and "procedure" hierarchies. The interrater reliability of the mapping results was 87.7%. The most important features calculated by random forest were "oxygen saturation below reference range," "dyspnea," "tachypnea," and "cough" in "clinical finding," and "oxygen therapy," "pulse oximetry monitoring," "temperature taking," "notification of physician," and "education about isolation for infection control" in "procedure." Among these, "dyspnea" and "inadequate food diet" in "clinical finding" increased clinical deterioration risk (dyspnea: odds ratio [OR] 5.99, 95% CI 2.25-20.29; inadequate food diet: OR 10.0, 95% CI 2.71-40.84), and "oxygen therapy" and "notification of physician" in "procedure" also increased the risk of clinical deterioration in patients with COVID-19 (oxygen therapy: OR 1.89, 95% CI 1.25-3.05; notification of physician: OR 1.72, 95% CI 1.02-2.97). CONCLUSIONS: The study used SNOMED CT to express and standardize nursing statements. Further, it revealed the importance of standardized nursing records as predictive variables for clinical deterioration in patients.

Study protocol of a national multicentre prospective evaluation study assessing the validity and impact of the Dutch Paediatric Early Warning Score (PEWS) in the Netherlands.

INTRODUCTION: Early recognition of clinical deterioration and timely intervention are important to improve morbidity and mortality in paediatric care. The Paediatric Early Warning Score (PEWS) is a scoring system aiming to identify hospitalised children at risk for deterioration. Currently, there is a large heterogeneity of PEWS systems in the Netherlands, with a considerable number remaining unvalidated or self-designed. Therefore, a consensus-based Dutch PEWS has been developed in a national study using the Core Outcome Measures in Effectiveness Trials initiative. The Dutch PEWS is a uniform system that integrates a core set of vital parameters together with pre-existing risk factors and uses risk stratification to proactively follow-up on patients at risk (so-called 'watcher patients'). This study aims to validate the Dutch PEWS and to determine its impact on improving patient safety in various hospital settings. METHODS AND ANALYSIS: This national study will be a large multicentre evaluation study, in which the Dutch PEWS will be implemented and evaluated in 12 hospitals in the Netherlands. In this study, a mixed methods methodology will be used and evaluated on predefined outcome measures. To examine the validity of the Dutch PEWS, statistical analyses will be undertaken on quantitative data retrieved from electronic health records. Surveys among physicians and nurses; semistructured interviews with healthcare providers and parents; and daily evaluation forms are being conducted to determine the impact of the Dutch PEWS. The study is being conducted from December 2020 to June 2024.

Predictors of clinical deterioration and intensive care unit admission in trauma patients transferred from northern Quebec to a level 1 trauma centre: a retrospective cohort study.

BACKGROUND: Trauma care in Nunavik, Quebec, is highly challenging. Geographic distances and delays in transport can translate into precarious patient transfers to tertiary trauma care centres. The objective of this study was to identify predictors of clinical deterioration during transport and eventual intensive care unit (ICU) admission for trauma patients transferred from Nunavik to a tertiary trauma care centre. METHODS: This is a retrospective cohort study using the Montreal General Hospital (MGH) trauma registry. All adult trauma patients transferred from Nunavik and admitted to the MGH from 2010 to 2019 were included. Main outcomes of interest were hemodynamic and neurologic deterioration during transport and ICU admission. RESULTS: In total, 704 patients were transferred from Nunavik and admitted to the MGH during the study period. The median age was 33 (interquartile range [IQR] 23-47) years and the median Injury Severity Score was 10 (IQR 5-17). On multiple regression analysis, transport time from site of injury to the MGH (odds ratio [OR] 1.04, 95% confidence interval [CI] 1.01-1.06), thoracic injuries (OR 1.75, 95% CI 1.03-2.99), and head and neck injuries (OR 3.76, 95% CI 2.10-6.76) predicted clinical deterioration during transfer. Injury Severity Score (OR 1.04, 95% CI 1.01-1.08), abnormal local Glasgow Coma Scale score (OR 2.57, 95% CI 1.34-4.95), clinical deterioration during transfer (OR 4.22, 95% CI 1.99-8.93), traumatic brain injury (OR 2.44, 95% CI 1.05-5.68), and transfusion requirement at the MGH (OR 4.63, 95% CI 2.35-9.09) were independent predictors of ICU admission. CONCLUSION: Our study identified several predictors of clinical deterioration during transfer and eventual ICU admission for trauma patients transferred from Nunavik. These factors could be used to refine triage criteria in Nunavik for more timely evacuation and higher level care during transport.

Martha's rule: applying a behaviour change framework to understand the potential of complementary roles of clinicians and patients in improving safety of patients deteriorating in hospital.

AIMS/BACKGROUND: Martha's rule stipulates the right of patients and their families to escalate care as a way to improve safety while in hospital. This article analyses the possible impact of the proposed policy through the lens of a behaviour change framework and explores new opportunities presented by the implementation of Martha's rule.. METHODS: A descriptive analysis was undertaken of interactions between patients, family, friends and clinicians during clinical deterioration in hospital. The capability-opportunity-motivation behaviour change framework was applied to understand reasons for failure to respond to deterioration. RESULTS: Care of deteriorating patients requires recording of vital signs, recognition of abnormalities, reporting through escalation and response by a competent clinician. Regarding the care of patients who deteriorate in hospital, healthcare professionals have capability and motivation to provide safe, high-quality care, but often lack the physical and social opportunity to report or respond through lack of time and peer pressure. Patients and family members have motivation and might have time to support safety systems. Martha's rule or similar arrangements allow healthcare organisations to create opportunities for patients and families to report and escalate care to experts in critical care when they recognise deterioration. CONCLUSIONS: The capability-opportunity-motivation behaviour change framework provides insights into the causes of failure to rescue in deteriorating patients and an argument for opportunities through escalation by patients and families through Martha's rule. This might reduce the number of system failures and enable safer care.

Transforming nursing assessment in acute hospitals: A cluster randomised controlled trial of an evidence-based nursing core assessment (the ENCORE trial).

BACKGROUND: Patient safety is threatened when early signs of clinical deterioration are missed or not acted upon. This research began as a clinical-academic partnership established around a shared concern of nursing physical assessment practices on general wards and delayed recognition of clinical deterioration. The outcome was the development of a complex intervention facilitated at the ward level for proactive nursing surveillance. METHODS: The evidence-based nursing core assessment (ENCORE) trial was a pragmatic cluster-randomised controlled trial. We hypothesised that ward intervention would reduce the incidence of patient rescue events (medical emergency team activations) and serious adverse events. We randomised 29 general wards in a 1:2 allocation, across 5 Australian hospitals to intervention (n = 10) and usual care wards (n = 19). Skilled facilitation over 12 months enabled practitioner-led, ward-level practice change for proactive nursing surveillance. The primary outcome was the rate of medical emergency team activations and secondary outcomes were unplanned intensive care unit admissions, on-ward resuscitations, and unexpected deaths. Outcomes were prospectively collected for 6 months following the initial 6 months of implementation. Analysis was at the patient level using generalised linear mixed models to account for clustering by ward. RESULTS: We analysed 29,385 patient admissions to intervention (n = 11,792) and control (n = 17,593) wards. Adjusted models for overall effects suggested the intervention increased the rate of medical emergency team activations (adjusted incidence rate ratio 1.314; 95 % confidence interval 0.975, 1.773), although the confidence interval was compatible with a marginal decrease to a substantial increase in rate. Confidence intervals for secondary outcomes included a range of plausible effects from benefit to harm. However, considerable heterogeneity was observed in intervention effects by patient comorbidity. Among patients with few comorbid conditions in the intervention arm there was a lower medical emergency team activation rate and decreased odds of unexpected death. Among patients with multimorbidity in the intervention arm there were higher rates of medical emergency team activation and intensive care unit admissions. CONCLUSION: Trial outcomes have refined our assumptions about the impact of the ENCORE intervention. The intervention appears to have protective effects for patients with low complexity where frontline teams can respond locally. It also appears to have redistributed medical emergency team activations and unplanned intensive care unit admissions, mobilising higher rates of rescue for patients with multimorbidity. TRIAL REGISTRATION NUMBER: ACTRN12618001903279 (Date of registration: 22/11/2018; First participant recruited: 01/02/2019).

Risk factors and predicting nomogram for the clinical deterioration of non-severe community-acquired pneumonia.

BACKGROUND: Currently, there remains insufficient focus on non-severe community-acquired pneumonia (CAP) patients who are at risk of clinical deterioration, and there is also a dearth of research on the related risk factors. Early recognition of hospitalized patients at risk of clinical deterioration will be beneficial for their clinical management. METHOD: A retrospective study was conducted in The First Affiliated Hospital of Wenzhou Medical University, China, spanning from January 1, 2018 to April 30, 2022, and involving a total of 1,632 non-severe CAP patients. Based on whether their condition worsened within 72 h of admission, patients were divided into a clinical deterioration group and a non-clinical deterioration group. Additionally, all patients were randomly assigned to a training set containing 75% of patients and a validation set containing 25% of patients. In the training set, risk factors for clinical deterioration in patients with non-severe CAP were identified by using LASSO regression analysis and multivariate logistic regression analysis. A nomogram was developed based on identified risk factors. The effectiveness of the nomogram in both the training and validation sets was assessed using Receiver Operating Characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). RESULTS: Age, body mass index (BMI), body temperature, cardiovascular comorbidity, respiratory rate, LDH level, lymphocyte count and D-dimer level were identified as risk factors associated with the clinical deterioration of non-severe CAP within 72 h of admission. The area under curve (AUC) value of the nomogram was 0.78 (95% CI: 0.74-0.82) in the training set and 0.75 (95% CI: 0.67-0.83) in the validation set. Furthermore, the calibration curves for both the training and validation sets indicated that the predicted probability of clinical deterioration aligned with the actual probability. Additionally, DCA revealed clinical utility for the nomogram at a specific threshold probability. CONCLUSION: The study successfully identified the risk factors linked to the clinical deterioration of non-severe CAP and constructed a nomogram for predicting the probability of deterioration. The nomogram demonstrated favorable predictive performance and has the potential to aid in the early identification and management of non-severe CAP patients at elevated risk of deterioration.

Validation of oxygen saturations measured in the community by emergency medical services as a marker of clinical deterioration in patients with confirmed COVID-19: a retrospective cohort study.

OBJECTIVES: To evaluate oxygen saturation and vital signs measured in the community by emergency medical services (EMS) as clinical markers of COVID-19-positive patient deterioration. DESIGN: A retrospective data analysis. SETTING: Patients were conveyed by EMS to two hospitals in Hampshire, UK, between 1 March 2020 and 31 July 2020. PARTICIPANTS: A total of 1080 patients aged ≥18 years with a COVID-19 diagnosis were conveyed by EMS to the hospital. PRIMARY AND SECONDARY OUTCOME MEASURES: The primary study outcome was admission to the intensive care unit (ICU) within 30 days of conveyance, with a secondary outcome representing mortality within 30 days of conveyance. Receiver operating characteristic (ROC) analysis was performed to evaluate, in a retrospective fashion, the efficacy of different variables in predicting patient outcomes. RESULTS: Vital signs measured by EMS staff at the first point of contact in the community correlated with patient 30-day ICU admission and mortality. Oxygen saturation was comparably predictive of 30-day ICU admission (area under ROC (AUROC) 0.753; 95% CI 0.668 to 0.826) to the National Early Warning Score 2 (AUROC 0.731; 95% CI 0.655 to 0.800), followed by temperature (AUROC 0.720; 95% CI 0.640 to 0.793) and respiration rate (AUROC 0.672; 95% CI 0.586 to 0.756). CONCLUSIONS: Initial oxygen saturation measurements (on air) for confirmed COVID-19 patients conveyed by EMS correlated with short-term patient outcomes, demonstrating an AUROC of 0.753 (95% CI 0.668 to 0.826) in predicting 30-day ICU admission. We found that the threshold of 93% oxygen saturation is prognostic of adverse events and of value for clinician decision-making with sensitivity (74.2% CI 0.642 to 0.840) and specificity (70.6% CI 0.678 to 0.734).

Society of Critical Care Medicine Guidelines on Recognizing and Responding to Clinical Deterioration Outside the ICU: 2023.

RATIONALE: Clinical deterioration of patients hospitalized outside the ICU is a source of potentially reversible morbidity and mortality. To address this, some acute care hospitals have implemented systems aimed at detecting and responding to such patients. OBJECTIVES: To provide evidence-based recommendations for hospital clinicians and administrators to optimize recognition and response to clinical deterioration in non-ICU patients. PANEL DESIGN: The 25-member panel included representatives from medicine, nursing, respiratory therapy, pharmacy, patient/family partners, and clinician-methodologists with expertise in developing evidence-based Clinical Practice Guidelines. METHODS: We generated actionable questions using the Population, Intervention, Control, and Outcomes (PICO) format and performed a systematic review of the literature to identify and synthesize the best available evidence. We used the Grading of Recommendations Assessment, Development, and Evaluation Approach to determine certainty in the evidence and to formulate recommendations and good practice statements (GPSs). RESULTS: The panel issued 10 statements on recognizing and responding to non-ICU patients with critical illness. Healthcare personnel and institutions should ensure that all vital sign acquisition is timely and accurate (GPS). We make no recommendation on the use of continuous vital sign monitoring among unselected patients. We suggest focused education for bedside clinicians in signs of clinical deterioration, and we also suggest that patient/family/care partners' concerns be included in decisions to obtain additional opinions and help (both conditional recommendations). We recommend hospital-wide deployment of a rapid response team or medical emergency team (RRT/MET) with explicit activation criteria (strong recommendation). We make no recommendation about RRT/MET professional composition or inclusion of palliative care members on the responding team but suggest that the skill set of responders should include eliciting patients' goals of care (conditional recommendation). Finally, quality improvement processes should be part of a rapid response system. CONCLUSIONS: The panel provided guidance to inform clinicians and administrators on effective processes to improve the care of patients at-risk for developing critical illness outside the ICU.

Executive Summary: Society of Critical Care Medicine Guidelines on Recognizing and Responding to Clinical Deterioration Outside the ICU.

RATIONALE: Clinical deterioration of patients hospitalized outside the ICU is a source of potentially reversible morbidity and mortality. To address this, some acute care facilities have implemented systems aimed at detecting and responding to such patients. OBJECTIVES: To provide evidence-based recommendations for hospital clinicians and administrators to optimize recognition and response to clinical deterioration in non-ICU patients. PANEL DESIGN: The 25-member panel included representatives from medicine, nursing, respiratory therapy, pharmacy, patient/family partners, and clinician-methodologists with expertise in developing evidence-based clinical practice guidelines. METHODS: We generated actionable questions using the Population, Intervention, Control, and Outcomes format and performed a systematic review of the literature to identify and synthesize the best available evidence. We used the Grading of Recommendations Assessment, Development, and Evaluation approach to determine certainty in the evidence and to formulate recommendations and good practice statements (GPSs). RESULTS: The panel issued 10 statements on recognizing and responding to non-ICU patients with critical illness. Healthcare personnel and institutions should ensure that all vital sign acquisition is timely and accurate (GPS). We make no recommendation on the use of continuous vital sign monitoring among "unselected" patients due to the absence of data regarding the benefit and the potential harms of false positive alarms, the risk of alarm fatigue, and cost. We suggest focused education for bedside clinicians in signs of clinical deterioration, and we also suggest that patient/family/care partners' concerns be included in decisions to obtain additional opinions and help (both conditional recommendations). We recommend hospital-wide deployment of a rapid response team or medical emergency team (RRT/MET) with explicit activation criteria (strong recommendation). We make no recommendation about RRT/MET professional composition or inclusion of palliative care members on the responding team but suggest that the skill set of responders should include eliciting patients' goals of care (conditional recommendation). Finally, quality improvement processes should be part of a rapid response system (GPS). CONCLUSIONS: The panel provided guidance to inform clinicians and administrators on effective processes to improve the care of patients at-risk for developing critical illness outside the ICU.

Prognostic Role of Tricuspid Annular Plane Systolic Excursion to Systolic Pulmonary Artery Pressure Ratio for the Identification of Early Clinical Deterioration in Intermediate-High-Risk Pulmonary Embolism Patients.

The ratio of tricuspid annular plane systolic excursion (TAPSE) to echocardiographically measured systolic pulmonary artery pressure (PASP) has been proposed as a surrogate of RV-arterial coupling. In this analysis, we assess the prognostic role of TAPSE/PASP for early clinical deterioration and short-term mortality in an often clinically challenging population of intermediate-high-risk patients with pulmonary embolism (PE). A post hoc analysis of intermediate-high-risk patients with PE enrolled in the Italian Pulmonary Embolism Registry (ClinicalTrials.gov: NCT01604538) was performed. All patients underwent transthoracic echocardiography at admission. The primary and secondary outcomes were clinical deterioration within 48 hours from admission and 30-day all-cause mortality, respectively. In 422 intermediate-high-risk patients with PE (mean age 71.2 ± 5.3 years, 238 men), 37 (8.7%) experienced clinical deterioration within 48 hours of admission. The 30-day mortality rate was 6.6% (n = 28). The receiver operating characteristic analysis established 0.33 as the optimal cut-off value for the TAPSE/PASP in predicting 48-hour clinical deterioration (area under the curve 0.79 ± 0.1). The sensitivity, specificity, positive predictive value, and negative predictive value were 81%, 88.5%, 40.5%, and 97.9%, respectively. The multivariate Cox regression analysis showed that a TAPSE/PASP ≤0.33 was an independent predictor of 48-hour clinical deterioration (hazard ratio 2.06, 95% confidence interval 1.98 to 2.11, p <0.0001) and 30-day mortality (hazard ratio 2.28, 95% confidence interval 2.25 to 2.33, p <0.001). TAPSE/PASP shows promise as a noninvasive prognostic predictor to identify intermediate-high-risk patients with PE at a higher risk of early clinical deterioration and short-term mortality.

Night-time detection and response in relation to deteriorating inpatients: A scoping review.

BACKGROUND: Although detection and response to clinical deterioration have been studied, the range and nature of studies focused on night-time clinical setting remain unclear. AIM: This study aimed to identify and map existing research and findings concerning night-time detection and response to deteriorating inpatients in usual care or research settings. STUDY DESIGN: A scoping review method was used. PubMed, CINAHL, Web of Science, and Ichushi-Web databases were systematically searched. We included studies focusing on night-time detection and response to clinical deterioration. RESULTS: Twenty-eight studies were included. These studies were organized into five categories: night-time medical emergency team or rapid response team (MET/RRT) response, night-time observation using the early warning score (EWS), available resources for physicians' practice, continuous monitoring of specific parameters, and screening for night-time clinical deterioration. The first three categories were related to interventional measures in usual care settings, and relevant findings mainly demonstrated the actual situation and challenges of night-time practice. The final two categories were related to the interventions in the research settings and included innovative interventions to identify at-risk or deteriorating patients. CONCLUSIONS: Systematic interventional measures, such as MET/RRT and EWS, could have been sub-optimally performed at night. Innovations in monitoring technologies or implementation of predictive models could be helpful in improving the detection of night-time deterioration. RELEVANCE TO CLINICAL PRACTICE: This review provides a compilation of current evidence regarding night-time practice concerning patient deterioration. However, a lack of understanding exists on specific and effective practices regarding timely action for deteriorating patients at night.

Effect of Preoperative Home-Based Exercise Training on Quality of Life After Lung Cancer Surgery: A Multicenter Randomized Controlled Trial.

BACKGROUND: Preoperative exercise training is recommended for improvement of clinical outcomes after lung cancer (LC) surgery. However, its effectiveness in preventing postoperative decline in quality of life (QoL) remains unknown. This study investigated the effect of preoperative home-based exercise training (PHET) on QoL after LC surgery. METHODS: Patients awaiting LC resection were randomized to PHET or a control group (CG). The PHET program combined aerobic and resistance exercise, with weekly telephone supervision. Primary outcome was QoL-assessed with the European Organization for Research and Treatment of Cancer (EORTC) Quality of Life Questionnaire C30 (QLQ-C30) at baseline, before surgery, and 1 month after surgery. The secondary outcomes were hospital length of stay and physical performance. The main analysis included a factorial repeated-measures analysis of variance. Additionally, the proportion of patients experiencing clinical deterioration from baseline to post-surgery was assessed. RESULTS: The study included 41 patients (68.1 ± 9.3 years; 68.3% male) in the intention-to-treat analysis (20 PHET patients, 21 CG patients). A significant group × time interaction was observed for global QoL (p = 0.004). Between-group differences in global QoL were statistically and clinically significant before surgery (mean difference [MD], 13.5 points; 95% confidence interval [CI], 2.4-24.6; p = 0.019) and after surgery (MD, 12.4 points; 95% CI, 1.3-23.4; p = 0.029), favoring PHET. Clinical deterioration of global QoL was reported by 71.4% of the CG patients compared with 30 % of the PHET patients (p = 0.003). Between-group differences in favor of PHET were found in pain and appetite loss as well as in physical, emotional and role functions after surgery (p < 0.05). Compared with CG, PHET was superior in improving preoperative five-times sit-to-stand and postoperative exercise capacity (p < 0.05). No between-group differences in other secondary outcomes were observed. CONCLUSION: The study showed that PHET can effectively prevent the decline in QoL after LC surgery.

Systematic review and longitudinal analysis of implementing Artificial Intelligence to predict clinical deterioration in adult hospitals: what is known and what remains uncertain.

OBJECTIVE: To identify factors influencing implementation of machine learning algorithms (MLAs) that predict clinical deterioration in hospitalized adult patients and relate these to a validated implementation framework. MATERIALS AND METHODS: A systematic review of studies of implemented or trialed real-time clinical deterioration prediction MLAs was undertaken, which identified: how MLA implementation was measured; impact of MLAs on clinical processes and patient outcomes; and barriers, enablers and uncertainties within the implementation process. Review findings were then mapped to the SALIENT end-to-end implementation framework to identify the implementation stages at which these factors applied. RESULTS: Thirty-seven articles relating to 14 groups of MLAs were identified, each trialing or implementing a bespoke algorithm. One hundred and seven distinct implementation evaluation metrics were identified. Four groups reported decreased hospital mortality, 1 significantly. We identified 24 barriers, 40 enablers, and 14 uncertainties and mapped these to the 5 stages of the SALIENT implementation framework. DISCUSSION: Algorithm performance across implementation stages decreased between in silico and trial stages. Silent plus pilot trial inclusion was associated with decreased mortality, as was the use of logistic regression algorithms that used less than 39 variables. Mitigation of alert fatigue via alert suppression and threshold configuration was commonly employed across groups. CONCLUSIONS: : There is evidence that real-world implementation of clinical deterioration prediction MLAs may improve clinical outcomes. Various factors identified as influencing success or failure of implementation can be mapped to different stages of implementation, thereby providing useful and practical guidance for implementers.

Early predictors of clinical deterioration in intermediate-high risk pulmonary embolism: clinical needs, research imperatives, and pathways forward.

A subset of intermediate-high risk pulmonary embolism (PE) patients will suffer clinical deterioration in the early hours following the acute event. Current evidence-based guidelines for the management of acute PE have provided limited direction for identification of which intermediate-high risk PE patients will go on to develop haemodynamic decompensation. Furthermore, a paucity of data further hampers guideline recommendations regarding the optimal approach and duration of intensive monitoring, best methods to assess the early response to anticoagulation, and the ideal window for reperfusion therapy, if decompensation threatens. The aim of the present article is to identify the current unmet needs related to the early identification of intermediate-high risk PE patients at higher risk of clinical deterioration and mortality during the early hours after the acute cardiovascular event and suggest some potential strategies to further explore gaps in the literature.