Does earlier detection of critically ill patients on surgical wards lead to better outcomes?

Predicting patient decompensation from continuous physiologic monitoring in the emergency department

Anticipation of clinical decompensation is essential for effective emergency and critical care. In this study, we develop a multimodal machine learning approach to predict the onset of new vital sign abnormalities (tachycardia, hypotension, hypoxia) in ED patients with normal initial vital signs. Our method combines standard triage data (vital signs, demographics, chief complaint) with features derived from a brief period of continuous physiologic monitoring, extracted via both conventional signal processing and transformer-based deep learning on ECG and PPG waveforms. We study 19,847 adult ED visits, divided into training (75%), validation (12.5%), and a chronologically sequential held-out test set (12.5%). The best-performing models use a combination of engineered and transformer-derived features, predicting in a 90-minute window new tachycardia with AUROC of 0.836 (95% CI, 0.800-0.870), new hypotension with AUROC 0.802 (95% CI, 0.747-0.856), and new hypoxia with AUROC 0.713 (95% CI, 0.680-0.745), in all cases significantly outperforming models using only standard triage data. Salient features include vital sign trends, PPG perfusion index, and ECG waveforms. This approach could improve the triage of apparently stable patients and be applied continuously for the prediction of near-term clinical deterioration.

Association of Postoperative Undertriage to Hospital Wards With Mortality and Morbidity

IMPORTANCE

Undertriaging patients who are at increased risk for postoperative complications after surgical procedures to low-acuity hospital wards (ie, floors) rather than highly vigilant intensive care units (ICUs) may be associated with risk of unrecognized decompensation and worse patient outcomes, but evidence for these associations is lacking.

OBJECTIVE

To test the hypothesis that postoperative undertriage is associated with increased mortality and morbidity compared with risk-matched ICU admission.

DESIGN, SETTING, AND PARTICIPANTS

This longitudinal cross-sectional study was conducted using data from the University of Florida Integrated Data Repository on admissions to a university hospital. Included patients were individuals aged 18 years or older who were admitted after a surgical procedure from June 1, 2014, to August 20, 2020. Data were analyzed from April through August 2021.

EXPOSURES

Ward admissions were considered undertriaged if their estimated risk for hospital mortality or prolonged ICU stay (ie, ≥48 hours) was in the top quartile among all inpatient surgical procedures according to a validated machine-learning model using preoperative and intraoperative electronic health record features available at surgical procedure end time. A nearest neighbors algorithm was used to identify a risk-matched control group of ICU admissions.

MAIN OUTCOMES AND MEASURES

The primary outcomes of hospital mortality and morbidity were compared among appropriately triaged ward admissions, undertriaged wards admissions, and a risk-matched control group of ICU admissions.

RESULTS

Among 12 348 postoperative ward admissions, 11 042 admissions (89.4%) were appropriately triaged (5927 [53.7%] women; median [IQR] age, 59 [44-70] years) and 1306 admissions (10.6%) were undertriaged and matched with a control group of 2452 ICU admissions. The undertriaged group, compared with the control group, had increased median [IQR] age (64 [54-74] years vs 62 [50-73] years; P = .001) and increased proportions of women (649 [49.7%] women vs 1080 [44.0%] women; P < .001) and admitted patients with do not resuscitate orders before first surgical procedure (53 admissions [4.1%] vs 27 admissions [1.1%]); P < .001); 207 admissions that were undertriaged (15.8%) had subsequent ICU admission. In the validation cohort, hospital mortality and prolonged ICU stay estimations had areas under the receiver operating characteristic curve of 0.92 (95% CI, 0.91-0.93) and 0.92 (95% CI, 0.92-0.92), respectively. The undertriaged group, compared with the control group, had similar incidence of prolonged mechanical ventilation (32 admissions [2.5%] vs 53 admissions [2.2%]; P = .60), decreased median (IQR) total costs for admission ($26 900 [$18 400-$42 300] vs $32 700 [$22 700-$48 500]; P < .001), increased median (IQR) hospital length of stay (8.1 [5.1-13.6] days vs 6.0 [3.3-9.3] days, P < .001), and increased incidence of hospital mortality (19 admissions [1.5%] vs 17 admissions [0.7%]; P = .04), discharge to hospice (23 admissions [1.8%] vs 14 admissions [0.6%]; P < .001), unplanned intubation (45 admissions [3.4%] vs 49 admissions [2.0%]; P = .01), and acute kidney injury (341 admissions [26.1%] vs 477 admissions [19.5%]; P < .001).

CONCLUSIONS AND RELEVANCE

This study found that admitted patients at increased risk for postoperative complications who were undertriaged to hospital wards had increased mortality and morbidity compared with a risk-matched control group of admissions to ICUs. Postoperative undertriage was identifiable using automated preoperative and intraoperative data as features in real-time machine-learning models.

Severe Hypoalbuminemia at Admission Is Strongly Associated with Worse Prognosis in Older Adults with SARS-CoV-2 Infection

Serum albumin levels have been associated with prognosis in several conditions among older adults. The aim of this study is to assess the prognostic value in mortality of serum albumin in older adults with SARS-CoV-2 infection. Methods. Cohort observational study with consecutive older-adults (≥65 years old), with confirmed SARS-CoV-2 infection admitted to a university hospital between March–May 2020. A logistic regression model was fitted to assess the impact of albumin levels on in-hospital mortality adjusted by potential confounders. Results. Among a total of 840 patients admitted to the hospital, 405 (48%) were older adults with a total of 92 deaths (23%) among them. Those who died were older, had more comorbidities, higher inflammation status and lower levels of serum albumin at admission [3.10 g/dL (0.51) vs. 3.45 g/dL (0.45); p < 0.01. Serum albumin levels at admission were negatively correlated with inflammatory markers such as C-Reactive protein (Pearson Coeff −0.4634; p < 0.001) or IL-6 (Pearson’s Coeff −0.244; p = 0.006) at admission but also to other clinical outcomes such time to clinical stability (Pearson’s Coeff −0.259; p < 0.001). Severe hypoalbuminemia associated with increased risk of mortality was defined as ≤3 g/dL at admission according to the AUC/ROC analysis (0.72 95% CI 0.63–0.81) In a multivariate logistic regression model adjusting by age, inflammation, comorbidities and severity at admission severe hypoalbuminemia was a strong predictor of in-hospital mortality (OR 2.18 95% CI 1.03–4.62; p = 0.039). Conclusion. Severe hypoalbuminemia with ≤3 g/dL is an independent risk factor for mortality among older adults with SARS-CoV-2 infection. There is a consistent correlation between albumin levels and inflammatory biomarkers. Further studies are needed to determine whether the supplementation of albumin as coadjuvant treatment will have a positive impact on the prognosis of this infection.

Prevalence and Prognostic Value of Myocardial Injury in the Initial Presentation of SARS-CoV-2 Infection among Older Adults

Myocardial involvement during SARS-CoV-2 infection has been reported in many prior publications. We aim to study the prevalence and the clinical implications of acute myocardial injury (MIN) during SARS-CoV-2 infection, particularly in older patients. The method includes a longitudinal observational study with all consecutive adult patients admitted to a COVID-19 unit between March-April 2020. Those aged ≥65 were considered as older adult group. MIN was defined as at least 1 high-sensitive troponin (hs-TnT) concentration above the 99th percentile upper reference limit with different sex-cutoff. Results. Among the 634 patients admitted during the period of observation, 365 (58%) had evidence of MIN, and, of them, 224 (61%) were older adults. Among older adults, MIN was associated with longer time to recovery compared to those without MIN (13 days (IQR 6-21) versus 9 days (IQR 5-17); p < 0.001, respectively. In-hospital mortality was significantly higher in older adults with MIN at admission versus those without it (71 (31%) versus 11 (12%); p < 0.001). In a logistic regression model adjusting by age, sex, severity, and Charlson Comorbidity Index, the OR for in-hospital mortality was 2.1 (95% CI: 1.02-4.42; p = 0.043) among those older adults with MIN at admission. Older adults with acute myocardial injury had greater time to clinical recovery, as well as higher odds of in-hospital mortality.

Emergency Department Length of Stay and Mortality in Critically Injured Patients

OBJECTIVE

Multicenter data from 2 decades ago demonstrated that critically ill and injured patients spending more than 6 hours in the emergency department (ED) before transfer to the intensive care unit (ICU) had higher mortality rates. A contemporary analysis of ED length of stay in critically injured patients at American College of Surgeons' Trauma Quality Improvement Program (ACS-TQIP) centers was performed to test whether prolonged ED length of stay is still associated with mortality.

METHODS

This was an observational cohort study of critically injured patients admitted directly to ICU from the ED in ACS-TQIP centers from 2010-2015. Spending more than 6 hours in the ED was defined as prolonged ED length of stay. Patients with prolonged ED length of stay were matched to those with non-prolonged ED length of stay and mortality was compared.

MAIN RESULTS

A total of 113,097 patients were directly admitted from the ED to the ICU following injury. The median ED length of stay was 167 minutes. Prolonged ED length of stay occurred in 15,279 (13.5%) of patients. Women accounted for 29.4% of patients with prolonged ED length of stay but only 25.8% of patients with non-prolonged ED length of stay, P < 0.0001. Mortality rates were similar after matching-4.5% among patients with prolonged ED length of stay versus 4.2% among matched controls. Multivariable logistic regression of the matched cohorts demonstrated prolonged ED length of stay was not associated with mortality. However, women had higher adjusted mortality compared to men Odds Ratio = 1.41, 95% Confidence Interval 1.28 -1.61, P < 0.0001.

CONCLUSION

Prolonged ED length of stay is no longer associated with mortality among critically injured patients. Women are more likely to have prolonged ED length of stay and mortality.

Opportunities for machine learning to improve surgical ward safety

BACKGROUND

Delayed recognition of decompensation and failure-to-rescue on surgical wards are major sources of preventable harm. This review assimilates and critically evaluates available evidence and identifies opportunities to improve surgical ward safety.

DATA SOURCES

Fifty-eight articles from Cochrane Library, EMBASE, and PubMed databases were included.

CONCLUSIONS

Only 15-20% of patients suffering ward arrest survive. In most cases, subtle signs of instability often occur prior to critical illness and arrest, and underlying pathology is reversible. Coarse risk assessments lead to under-triage of high-risk patients to wards, where surveillance for complications depends on time-consuming manual review of health records, infrequent patient assessments, prediction models that lack accuracy and autonomy, and biased, error-prone decision-making. Streaming electronic heath record data, wearable continuous monitors, and recent advances in deep learning and reinforcement learning can promote efficient and accurate risk assessments, earlier recognition of instability, and better decisions regarding diagnosis and treatment of reversible underlying pathology.

Implementation of an automated early warning scoring system in a surgical ward: Practical use and effects on patient outcomes

Introduction

Early warning scores (EWS) are being increasingly embedded in hospitals over the world due to their promise to reduce adverse events and improve the outcomes of clinical patients.

The aim of this study was to evaluate the clinical use of an automated modified EWS (MEWS) for patients after surgery.

Methods

This study conducted retrospective before-and-after comparative analysis of non-automated and automated MEWS for patients admitted to the surgical high-dependency unit in a tertiary hospital. Operational outcomes included number of recorded assessments of the individual MEWS elements, number of complete MEWS assessments, as well as adherence rate to related protocols. Clinical outcomes included hospital length of stay, in-hospital and 28-day mortality, and ICU readmission rate.

Results

Recordings in the electronic medical record from the control period contained 7929 assessments of MEWS elements and were performed in 320 patients. Recordings from the intervention period contained 8781 assessments of MEWS elements in 273 patients, of which 3418 were performed with the automated EWS system. During the control period, 199 (2.5%) complete MEWS were recorded versus 3991 (45.5%) during intervention period. With the automated MEWS systems, the percentage of missing assessments and the time until the next assessment for patients with a MEWS of ≥2 decreased significantly. The protocol adherence improved from 1.1% during the control period to 25.4% when the automated MEWS system was involved. There were no significant differences in clinical outcomes.

Conclusion

Implementation of an automated EWS system on a surgical high dependency unit improves the number of complete MEWS assessments, registered vital signs, and adherence to the EWS hospital protocol. However, this positive effect did not translate into a significant decrease in mortality, hospital length of stay, or ICU readmissions. Future research and development on automated EWS systems should focus on data management and technology interoperability.

Statistical Modeling and Aggregate-Weighted Scoring Systems in Prediction of Mortality and ICU Transfer: A Systematic Review

BACKGROUND

The clinical deterioration of patientsin general hospital wards is an important safety issue. Aggregate-weighted early warning systems (EWSs) may not detect risk until patients present with acute decline.

PURPOSE

We aimed to compare the prognostic test accuracy and clinical workloads generated by EWSs using statistical modeling (multivariable regression or machine learning) versus aggregate-weighted tools.

DATA SOURCES

We searched PubMed and CINAHL using terms that described clinical deterioration and use of an advanced EWS.

STUDY SELECTION

The outcome was clinical deterioration (intensive care unit transfer or death) of adult patients on general hospital wards. We included studies published from January 1, 2012 to September 15, 2018.

DATA EXTRACTION

Following 2015 PRIMSA systematic review protocol guidelines; 2015 TRIPOD criteria for predictive model evaluation; and the Cochrane Collaboration guidelines, we reported model performance, adjusted positive predictive value (PPV), and conducted simulations of workup-to-detection ratios.

DATA SYNTHESIS

Of 285 articles, six studies reported the model performance of advanced EWSs, and five were of high quality. All EWSs using statistical modeling identified at-risk patients with greater precision than aggregate-weighted EWSs (mean AUC 0.80 vs 0.73). EWSs using statistical modeling generated 4.9 alerts to find one true positive case versus 7.1 alerts in aggregate-weighted EWSs; a nearly 50% relative workload increase for aggregate-weighted EWSs.

CONCLUSIONS

Compared with aggregate-weighted tools, EWSs using statistical modeling consistently demonstrated superior prognostic performance and generated less workload to identify and treat one true positive case. A standardized approach to reporting EWS model performance is needed, including outcome definitions, pretest probability, observed and adjusted PPV, and workup-to-detection ratio.

Barriers and facilitators related to the implementation of a physiological track and trigger system: A systematic review of the qualitative evidence

Purpose

To identify the barriers to, and facilitators of, the implementation of physiological track and trigger systems (PTTSs), perceived by healthcare workers, through a systematic review of the extant qualitative literature.

Data sources

Searches were performed in PUBMED, CINAHL, PsycInfo, Embase and Web of Science. The reference lists of included studies were also screened.

Study selection

The electronic searches yielded 2727 papers. After removing duplicates, and further screening, a total of 10 papers were determined to meet the inclusion criteria and were reviewed.

Data extraction

A deductive content analysis approach was taken to organizing and analysing the data. A framework consisting of two overarching dimensions ('User-related changes required to implement PTTSs effectively' and 'Factors that affect user-related changes'), 5 themes (staff perceptions of PTTSs and patient safety, workflow adjustment, PTTS, implementation process and local context) and 14 sub themes was used to classify the barriers and facilitators to the implementation of PTTSs.

Results of data synthesis

Successful implementation of a PTTS must address the social context in which it is to be implemented by ensuring that the users believe that the system is effective and benefits patient care. The users must feel invested in the PTTS and its use must be supported by training to ensure that all healthcare workers, senior and junior, understand their role in using the system.

Conclusion

PTTSs can improve patient safety and quality of care. However, there is a need for a robust implementation strategy or the benefits of PTTSs will not be realized.

The impact of delayed critical care outreach team activation on in-hospital mortality and other patient outcomes: a historical cohort study

PURPOSE

Early warning scores (EWS) and critical care outreach teams (CCOT) have been developed to respond to decompensating patients. Nevertheless, controversy exists around their effectiveness. The primary objective of this study was to determine if a delay of ≥ 60 min between when a patient was identified as meeting EWS criteria and the CCOT was activated impacted in-hospital mortality.

METHODS

This was a historical cohort study evaluating all new CCOT activations over a four-year study period (1 June 2007 to 31 August 2011) for inpatients ≥ 18 yr of age at two academic tertiary care hospitals in London, Ontario, Canada. Multivariable logistic regression accounting for repeated measures was used to determine the effect of delayed CCOT activation on in-hospital mortality (primary outcome). Differences in outcomes between medical and surgical patients were also examined.

RESULTS

There were 3,133 CCOT activations for 1,684 (53.8%) medical patients and 1,449 (46.2%) surgical patients during the study period. The CCOT was activated < 60 min of a patient meeting EWS criteria in 2,160 (68.9%) cases and ≥ 60 min in 973 (31.1%) cases. Patients with ≥ 60 min delay were more likely be admitted to the intensive care unit (odds ratio [OR], 1.22; 95% confidence interval [CI], 1.07 to 1.47) and to suffer in-hospital mortality (OR, 1.30; 95% CI, 1.08 to 1.56). Irrespective of delay, surgical patients were less likely to experience in-hospital mortality than medical patients (OR, 0.46; 95% CI, 0.39 to 0.55).

CONCLUSION

Including the rates of delay in CCOT activation and the admitting service could be an additional step in exploring the conflicting results seen in the current literature assessing the impact of CCOT on patient outcomes.

Is the Modified Early Warning Score (MEWS) superior to clinician judgement in detecting critical illness in the pre-hospital environment?

AIM

Physiological track and trigger scores have an established role in enhancing the detection of critical illness in hospitalized patients. Their potential to identify individuals at risk of clinical deterioration in the pre-hospital environment is unknown. This study compared the predictive accuracy of the Modified Early Warning Score (MEWS) with current clinical practice.

METHODS

A retrospective observational cohort study of consecutive adult (≥16 yrs) emergency department attendances to a single centre over a two-month period. The outcome of interest was the occurrence or not of an adverse event within 24h of admission. Hospital pre-alerting was used as a measure of current critical illness detection and its accuracy compared with MEWS scores calculated from pre-hospital observations.

RESULTS

3504 patients were included in the study. 76 (2.5%) suffered an adverse event within 24 h of admission. Paramedics pre-alerted the hospital in 224 cases (7.3%). Clinical judgement demonstrated a sensitivity of 61.8% (95% CI 51.0-72.8%) with a specificity of 94.1% (95% CI 93.2-94.9%). MEWS was a good predictor of adverse outcomes and hence critical illness detection (AUC 0.799, 95% CI 0.738-0.856). Combination systems of MEWS and clinical judgement may be effective MEWS ≥4+clinical judgement: sensitivity 72.4% (95% CI 62.5-82.7%), specificity 84.8% (95% CI 83.52-86.1%).

CONCLUSIONS

Clinical judgement alone has a low sensitivity for critical illness in the pre-hospital environment. The addition of MEWS improves detection at the expense of reduced specificity. The optimal scoring system to be employed in this setting is yet to be elucidated.

Does the use of a "track and trigger" warning system reduce mortality in trauma patients?

INTRODUCTION

Despite the lack of robust evidence, numerous different "track and trigger" warning systems have been implemented. These have only been validated in an emergency medical admissions setting. The Modified Early Warning Score (MEWS) is the chosen track and trigger system used in the University Hospitals of Leicester trauma unit, but has not been validated in trauma patients. A considerable proportion of all trauma admissions are elderly patients with proximal femoral fractures and significant co-morbidities. Early recognition of physiological deterioration and prompt action could therefore be lifesaving in this patient group.

AIM

To identify whether the implementation of the MEWS system coupled with a critical care outreach service resulted in a reduction in mortality in a busy trauma unit.

METHOD

A retrospective study. The MEWS system was implemented in all trauma and orthopaedic wards at the Leicester Royal Infirmary in the summer of 2005. The numbers of emergency trauma inpatient admissions and deaths from January 2002 to December 2009 were obtained. The diagnosis, primary procedures and cause of death, if known, were noted. Comparisons were made pre- and post-MEWS. Student's t-test was used for statistical analysis.

RESULTS

32,149 patients were admitted (55% male; 45% female). Overall there were 889 deaths (77% female; 33% male, P<0.0001). The in-hospital mortality rate for orthopaedic trauma patients was 2.8% throughout the 7-year study period. 61% of those who died were admitted with proximal femoral fractures. The modal age group with the highest mortality was 81-90 years. Overall, females had a considerably greater mortality rate than males. The mortality rate was lower post-MEWS in males (1.82-1.418%; P=0.214), females (4.871-3.364%; P=0.108) and all patients (3.215-2.294%; P=0.092), but this was not statistically significant.

CONCLUSION

The use of a track and trigger warning system has not led to a statistically significant reduction in mortality in trauma patients. In view of the apparent lack of clinical effectiveness of the MEWS/outreach partnership, the cost effectiveness of this initiative needs to be questioned. Possible reasons for these findings include: failure of the MEWS to be correctly applied, inadequate action once the threshold is triggered, or unsuitability of this tool for this patient population. A better system for identifying and treating elderly, medically unwell trauma patients with co-morbidities needs to be developed.

Risk factors and outcomes of high-dependency patients requiring intensive care unit admission: a nested case-control study

Intermediate-care or high-dependency units can provide a level of care that lies between the intensive care unit (ICU) and general ward, but the patients who are most likely to benefit from such level of care remains uncertain. This nested case-control study assessed the incidence and risk factors of high-dependency patients requiring ICU admission and whether these admissions were associated with a worse outcome when compared to other emergency ICU admissions. Seventy-seven consecutive high-dependency patients requiring ICU admission (cases) were compared with 77 patients who did not require ICU admission (controls) and also 928 emergency ICU admissions from other areas. The incidence of high-dependency patients requiring ICU admission was 6.7% (95% confidence interval 5.3 to 8.2). High-dependency admissions from the ward (odds ratio 4.46, 95% confidence interval 1.55 to 12.78) or emergency department (odds ratio 4.48, 95% confidence interval 1.54 to 13.0) and a need for concurrent non-invasive ventilation, inotrope infusion and acute kidney injury (odds ratio 14.90, 95% confidence interval 3.79 to 58.3) was associated with a higher risk of ICU admission. Hospital mortality of the high-dependency patients requiring ICU admission was not significantly different from other emergency ICU admissions (odds ratio 1.08, 95% confidence interval 0.55 to 2.11). In summary, high-dependency patients requiring ICU admission were uncommon unless they had multi-organ failure and their hospital mortality was not significantly different from other emergency ICU admissions.

Identifying infected emergency department patients admitted to the hospital ward at risk of clinical deterioration and intensive care unit transfer

OBJECTIVES

An important challenge faced by emergency physicians (EPs) is determining which patients should be admitted to an intensive care unit (ICU) and which can be safely admitted to a regular ward. Understanding risk factors leading to undertriage would be useful, but these factors are not well characterized.

METHODS

The authors performed a secondary analysis of two prospective, observational studies of patients admitted to the hospital with clinically suspected infection from an urban university emergency department (ED). Inclusion criteria were as follows: adult ED patient (age 18 years or older), ward admission, and suspected infection. The primary outcome was transfer to an ICU within 48 hours of admission. Using multiple logistic regression, independent predictors of early ICU transfer were identified, and the area under the curve for the model was calculated.

RESULTS

Of 5,365 subjects, 93 (1.7%) were transferred to an ICU within 48 hours. Independent predictors of ICU transfer included respiratory compromise (odds ratio [OR] = 2.5, 95% confidence interval [CI] = 1.4 to 4.3), congestive heart failure (CHF; OR = 2.2, 95% CI = 1.4 to 3.6), peripheral vascular disease (OR = 2.0, 95% CI = 1.1 to 3.7), systolic blood pressure (sBP) < 100 mm Hg (OR = 1.9, 95% CI = 1.2 to 2.9), heart rate > 90 beats/min (OR = 1.8, 95% CI = 1.1 to 2.8), and creatinine > 2.0 (OR = 1.8, 95% CI = 1.1 to 2.8). Cellulitis was associated with a lower likelihood of ICU transfer (OR = 0.33, 95% CI = 0.15 to 0.72). The area under the curve for the model was 0.73, showing moderate discriminatory ability.

CONCLUSIONS

  In this preliminary study, independent predictors of ICU transfer within 48 hours of admission were identified. While somewhat intuitive, physicians should consider these factors when determining patient disposition.

Validation of a physiological track and trigger score to identify developing critical illness in haematology patients

OBJECTIVE

To validate two physiological track and trigger systems; the early warning score (Morgan et al., 1997) and the trust observation chart on a haematology unit. The study aimed to determine whether either of these systems could be used to identify developing critical illness in haematology.

RESEARCH DESIGN

A prospective validation study where all patients' physiological observations were recorded, the level of care they were receiving assessed and after data collection finished, the triggers and EWS calculated.

SETTING

A haematology unit in an inner London hospital.

RESULTS

71 patients took part in the study; 17 of these became critically ill. The sensitivity of both systems compared favourably with other studies. However, specificity was lower. This will mean a number of false negative results within this patient group.

CONCLUSION

The study concluded that the systems are useful adjuncts to identify developing critical illness in haematology patients but cannot be used in isolation due to the high number of false negative results that occur. Any plan to introduce either system should acknowledge the increase in workload that will result.

A 'shock room' for early management of the acutely ill

Our 850-bed, academic, tertiary care hospital uses a four-bed dedicated 'shock room' situated between the Departments of Emergency Medicine and Intensive Care to stabilise all acutely ill patients from outside or inside the hospital before transfer to the intensive care unit or other department. Admitted patients stay a maximum of four hours in the shock room. In this article we describe our experiences using this shock room by detailing the demographic data, including time and source of admission, diagnosis and outcome, for the 2514 patients admitted to the shock room in 2006. The most common reasons for admission were cardiac (33%) and neurological (21%) diagnoses. After diagnosis and initial treatment, 54% of patients were transferred to an intensive care unit or a coronary care unit; 2.5% of patients died in the shock room. The shock room provides a useful area of collaboration between emergency department and intensive care unit staff and enables acutely ill patients to be assessed and treated rapidly to optimise outcomes.

Ambulance alerting to hospital: the need for clearer guidance

BACKGROUND

The decision by paramedics to alert a receiving hospital to the imminent arrival of a critically ill patient is currently based on the crew's clinical judgement.

AIMS

To evaluate the efficiency of current alerting practice and to assess the need for objective guidelines.

METHODS

Data were collected in the Birmingham Heartlands Hospital, Birmingham, UK, over 1 week in February 2005. All alerted patients and all critically ill patients brought to the emergency department over this time period were identified. These two groups were studied to find those patients who were alerted but not critically ill, those who were critically ill but not alerted, and those who were both alerted and critically ill. The presenting conditions were identified and compared between groups.

RESULTS

454 patients were brought by ambulance to the emergency department during the study week. Of the 27 alerted patients, 23 were critically ill, leaving four patients alerted inappropriately. 29 of the 52 critically ill patients had not been alerted by ambulance crews. Most (n = 22) of these patients were adults with medical conditions.

CONCLUSIONS

Ambulance crews do not alert hospitals to critically ill patients adequately. The Modified Early Warning Score should be considered to be the basis of a prehospital tool to aid their decision.

Medical emergency team syndromes and an approach to their management

INTRODUCTION

Most literature on the medical emergency team (MET) relates to its effects on patient outcome. Less information exists on the most common causes of MET calls or on possible approaches to their management.

METHODS

We reviewed the calling criteria and clinical causes of 400 MET calls in a teaching hospital. We propose a set of minimum standards for managing a MET review and developed an approach for managing common problems encountered during MET calls.

RESULTS

The underlying reasons for initiating MET calls were hypoxia (41%), hypotension (28%), altered conscious state (23%), tachycardia (19%), increased respiratory rate (14%) and oliguria (8%). Infection, pulmonary oedema, and arrhythmias featured as prominent causes of all triggers for MET calls. The proposed minimum requirements for managing a MET review included determining the cause of the deterioration, documenting the events surrounding the MET, establishing a medical plan and ongoing medical follow-up, and discussing the case with the intensivist if certain criteria were fulfilled. A systematic approach to managing episodes of MET review was developed based on the acronym 'A to G': ask and assess; begin basic investigations and resuscitation, call for help if needed, discuss, decide, and document, explain aetiology and management, follow-up, and graciously thank staff. This approach was then adapted to provide a management plan for episodes of tachycardia, hypotension, hypoxia and dyspnoea, reduced urinary output, and altered conscious state.

CONCLUSION

A suggested approach permits audit and standardization of the management of MET calls and provides an educational framework for the management of acutely unwell ward patients. Further evaluation and validation of the approach are required.

Excellent anaesthesia needs patient preparation and postoperative support to influence outcome

PURPOSE OF REVIEW

Studies over many years have demonstrated that preoptimization and attention to appropriate perioperative care is associated with a substantial decrease in surgical mortality. This review discusses ways in which patient preparation and perioperative support can minimize surgical mortality and morbidity.

RECENT FINDINGS

Scoring systems continue to be developed in order to classify categories of surgical risk. Objective physiologically based assessments can also identify high-risk groups of patients. Debate continues over the indications for specific interventions such as beta-blockade or statin therapy. There is continuing interest in perioperative optimization of oxygen delivery. A multimodality approach paying attention to a range of possible interventions appears to be beneficial. Audit, training, experience and a sufficient volume of procedures are all factors associated with surgical mortality.

SUMMARY

The provision of a high-quality service throughout the perioperative period is vital for a successful outcome. Patients need to be assessed well before major elective surgery to determine if they fall into a high-risk category. Some patients may benefit from a change in management. Postoperatively, critical-care support should be available backed by level 1 (enhanced ward) care with input from outreach or medical emergency teams 24 hours per day, seven days a week.