Gary B. Smith

European Resuscitation Council Guidelines for Resuscitation 2010 Section 4. Adult advanced life support

Cardiothoracic Anaesthesia, Southampton General Hospital, Southampton, UK Anaesthesia and Intensive Care Medicine, Royal United Hospital, Bath, UK Anaesthesia and Intensive Care Medicine, Southmead Hospital, Bristol, UK Surgical Intensive Care Unit, Oslo University Hospital Ulleval, Oslo, Norway Department of Cardiology, Academic Medical Center, Amsterdam, The Netherlands Critical Care and Resuscitation, University of Warwick, Warwick Medical School, Warwick, UK

European Resuscitation Council Guidelines for Resuscitation 2015: Section 3. Adult advanced life support

Anaesthesia and Intensive Care Medicine, Southmead Hospital, Bristol, UK Anaesthesia and Intensive Care Medicine, Royal United Hospital, Bath, UK School of Clinical Sciences, University of Bristol, UK Department of Anaesthesiology and Intensive Care Medicine, University Hospital of Cologne, Germany Warwick Medical School, University of Warwick, Coventry, UK Heart of England NHS Foundation Trust, Birmingham, UK Department of Anesthesiology, University Medical Center, Johannes Gutenberg-University, Mainz, Germany SAMU de Paris, Department of Anaesthesiology and Intensive Care, Necker University Hospital, Paris, France Anaesthesia, Intensive Care and Emergency Medical Service, Santa Maria degli Angeli Hospital, Pordenone, Italy Department of Anaesthesiology and Intensive Care, Catholic University School of Medicine, Rome, Italy Division of Intensive Care, Department of Anaesthesiology, Intensive Care and Pain Medicine, Helsinki University Hospital and Helsinki University, elsinki, Finland Centre of Postgraduate Medical Research & Education, Bournemouth University, Bournemouth, UK Department of Anaesthesiology, Division of Emergencies and Critical Care, Oslo University Hospital, Oslo, Norway Institute of Clinical Medicine, University of Oslo, Oslo, Norway edical Cardiac Anaesthesia and Cardiac Intensive Care, NIHR Southampton Respiratory Biom outhampton, UK

The ability of the National Early Warning Score (NEWS) to discriminate patients at risk of early cardiac arrest, unanticipated intensive care unit admission, and death

INTRODUCTION Early warning scores (EWS) are recommended as part of the early recognition and response to patient deterioration. The Royal College of Physicians recommends the use of a National Early Warning Score (NEWS) for the routine clinical assessment of all adult patients. METHODS We tested the ability of NEWS to discriminate patients at risk of cardiac arrest, unanticipated intensive care unit (ICU) admission or death within 24h of a NEWS value and compared its performance to that of 33 other EWSs currently in use, using the area under the receiver-operating characteristic (AUROC) curve and a large vital signs database (n=198,755 observation sets) collected from 35,585 consecutive, completed acute medical admissions. RESULTS The AUROCs (95% CI) for NEWS for cardiac arrest, unanticipated ICU admission, death, and any of the outcomes, all within 24h, were 0.722 (0.685-0.759), 0.857 (0.847-0.868), 0.894 (0.887-0.902), and 0.873 (0.866-0.879), respectively. Similarly, the ranges of AUROCs (95% CI) for the other 33 EWSs were 0.611 (0.568-0.654) to 0.710 (0.675-0.745) (cardiac arrest); 0.570 (0.553-0.568) to 0.827 (0.814-0.840) (unanticipated ICU admission); 0.813 (0.802-0.824) to 0.858 (0.849-0.867) (death); and 0.736 (0.727-0.745) to 0.834 (0.826-0.842) (any outcome). CONCLUSIONS NEWS has a greater ability to discriminate patients at risk of the combined outcome of cardiac arrest, unanticipated ICU admission or death within 24h of a NEWS value than 33 other EWSs.

Multicenter study of obstetric admissions to 14 intensive care units in southern England.

ObjectivesTo identify pregnant and postpartum patients admitted to intensive care units (ICUs), the cause for their admission, and the proportion that might be appropriately managed in a high-dependency environment (HDU) by using an existing database. To estimate the goodness-of-fit for the Simplified Acute Physiology Score II, the Acute Physiology and Chronic Health Evaluation (APACHE) II, and the APACHE III scoring systems in the obstetrical population. DesignRetrospective analysis of demographic, diagnostic, treatment, and severity of illness data. SettingFourteen ICUs in Southern England. PatientsPregnant or postpartum (<42 days) admissions between January 1, 1994, and December 31, 1996. InterventionsNone. Measurements and Main Results We identified 210 patients, constituting 1.84% (210 of 11,385) of all ICU admissions and 0.17% (210 of 122,850) of all deliveries. Most admissions followed postpartum complications (hypertensive disease of pregnancy [39.5%] and major hemorrhage [33.3%]). Seven women were transferred to specialist ICUs. There was considerable variation between ICUs with respect to the number and type of interventions required by patients. Some 35.7% of patients stayed in ICU for <2 days and received no specific ICU interventions; these patients might have been safely managed in an HDU. There were seven maternal deaths (3.3%); fetal mortality rate was 20%. The area under the receiver operator characteristic curve and the standardized mortality ratio were 0.92 (confidence interval [CI], 0.85–0.99) and 0.43 for the Simplified Acute Physiology Score II, 0.94 (CI, 0.86–1.0) and 0.24 for APACHE II, and 0.98 (CI, 0.96–1.0) and 0.43 for APACHE III, respectively. ConclusionsExisting databases can both identify critically ill obstetrical patients and provide important information about them. Obstetrical ICU admissions often require minimal intervention and are associated with low mortality rates. Many might be more appropriately managed in an HDU. The commonly used severity of illness scoring systems are good discriminators of outcome from intensive care admission in this group but may overestimate mortality rates. Severity of illness scoring systems may require modification in obstetrical patients to adjust for the normal physiologic responses to pregnancy.

Prediction of outcome from intensive care : A prospective cohort study comparing Acute Physiology and Chronic Health Evaluation II and III prognostic systems in a United Kingdom intensive care unit

OBJECTIVE To evaluate the ability of two prognostic systems to predict hospital mortality in adult intensive care patients. DESIGN Prospective cohort study. SETTING A mixed medical and surgical intensive care unit (ICU) in the United Kingdom. PATIENTS A total of 1,144 patients consecutively admitted to the study. INTERVENTIONS None. MEASUREMENTS AND MAIN RESULTS Acute Physiology and Chronic Health Evaluation (APACHE) II and III prognostic systems were applied to assess probabilities of hospital mortality, which were compared with the actual outcome. The overall goodness-of-fit of both models was assessed. Hospital death rates were higher than those predicted by each system. Risk estimates showed a strong positive correlation between both systems (nonsurvivors r2 = 0.756, p < .0001; survivors r2 = 0.787, p < .0001). Calibration of APACHE II (chi 2 = 98.6, Lemeshow-Hosmer) was superior to that of APACHE III (chi 2 = 129.8, Lemeshow-Hosmer). The total correct classification rate of APACHE III was greater for all decision criteria applied; the best overall total correct classification rate was 80.6% for APACHE III and 77.9% for APACHE II (both for a decision criterion of 40%). The areas under the receiver operating characteristic curves were 0.806 and 0.847 for APACHE II and III, respectively, confirming the better discrimination of APACHE III. When patients were classified by diagnostic categories, risk predictions did not fit uniformly across the spectrum of disease groups. For both models, mortality ratios were highest for trauma patients and lowest for the group with respiratory disease. APACHE II predictions for patients with gastrointestinal disease were significantly better. Risk estimates for surgical admissions were superior with APACHE II (MR = 1.27) compared with APACHE III (MR = 1.56), but were similar for medical patients (1.22 vs. 1.28 for APACHE II and III, respectively). Bias induced by factors reflecting the clinical practice in an individual ICU (e.g., admission criteria, treatment before admission) may have considerable impact on risk estimates. The identification of such factors appears to be a prerequisite for the meaningful interpretation of observed and predicted death rates on the individual ICU level. CONCLUSIONS Both predictive models demonstrated a similar degree of overall goodness-of-fit. APACHE II showed better calibration, but discrimination was better with APACHE III. Hospital mortality was higher than predicted by both models, but was underestimated to a greater degree by APACHE III. Risk estimates by both models showed considerable variation across the disease spectrum of ICU patients. Risk predictions for surgical patients and patients with gastrointestinal disease were better with APACHE II. Factors reflecting the clinical practice of an individual ICU are not accounted for by APACHE II and III. Overall, the performance of APACHE III was not superior to that of its predecessor for a cohort of United Kingdom ICU patients; for certain diagnostic categories, APACHE III performed worse than APACHE II despite an improved system of disease classification.

Chest compression depth and survival in out-of-hospital cardiac arrest

AIM Outcomes from out-of-hospital cardiac arrest (OHCA) may improve if rescuers perform chest compressions (CCs) deeper than the previous recommendation of 38-51mm and consistent with the 2010 AHA Guideline recommendation of at least 51mm. The aim of this study was to assess the relationship between CC depth and OHCA survival. METHODS Prospective analysis of CC depth and outcomes in consecutive adult OHCA of presumed cardiac etiology from two EMS agencies participating in comprehensive CPR quality improvement initiatives. ANALYSIS Multivariable logistic regression to calculate adjusted odds ratios (aORs) for survival to hospital discharge and favorable functional outcome. RESULTS Among 593 OHCAs, 136 patients (22.9%) achieved return of spontaneous circulation, 63 patients (10.6%) survived and 50 had favorable functional outcome (8.4%). Mean CC depth was 49.8±11.0mm and mean CC rate was 113.9±18.1CCmin(-1). Mean depth was significantly deeper in survivors (53.6mm, 95% CI: 50.5-56.7) than non-survivors (48.8mm, 95% CI: 47.6-50.0). Each 5mm increase in mean CC depth significantly increased the odds of survival and survival with favorable functional outcome: aORs were 1.29 (95% CI 1.00-1.65) and 1.30 (95% CI 1.00-1.70) respectively. CONCLUSION Deeper chest compressions were associated with improved survival and functional outcome following OHCA. Our results suggest that adhering to the 2010 AHA Guideline-recommended depth of at least 51mm could improve outcomes for victims of OHCA.

Incidence and outcome of in-hospital cardiac arrest in the United Kingdom National Cardiac Arrest Audit

OBJECTIVE To report the incidence, characteristics and outcome of adult in-hospital cardiac arrest in the United Kingdom (UK) National Cardiac Arrest Audit database. METHODS A prospectively defined analysis of the UK National Cardiac Arrest Audit (NCAA) database. 144 acute hospitals contributed data relating to 22,628 patients aged 16 years or over receiving chest compressions and/or defibrillation and attended by a hospital-based resuscitation team in response to a 2222 call. The main outcome measures were incidence of adult in-hospital cardiac arrest and survival to hospital discharge. RESULTS The overall incidence of adult in-hospital cardiac arrest was 1.6 per 1000 hospital admissions with a median across hospitals of 1.5 (interquartile range 1.2-2.2). Incidence varied seasonally, peaking in winter. Overall unadjusted survival to hospital discharge was 18.4%. The presenting rhythm was shockable (ventricular fibrillation or pulseless ventricular tachycardia) in 16.9% and non-shockable (asystole or pulseless electrical activity) in 72.3%; rates of survival to hospital discharge associated with these rhythms were 49.0% and 10.5%, respectively, but varied substantially across hospitals. CONCLUSIONS These first results from the NCAA database describing the current incidence and outcome of adult in-hospital cardiac arrest in UK hospitals will serve as a benchmark from which to assess the future impact of changes in service delivery, organisation and treatment for in-hospital cardiac arrest.

The Acute Care Undergraduate TEaching (ACUTE) Initiative : consensus development of core competencies in acute care for undergraduates in the United Kingdom

BackgroundThe care of the acutely ill patient in hospital is often sub-optimal. Poor recognition of critical illness combined with a lack of knowledge, failure to appreciate the clinical urgency of a situation, a lack of supervision, failure to seek advice and poor communication have been identified as contributory factors. At present the training of medical students in these important skills is fragmented. The aim of this study was to use consensus techniques to identify the core competencies in the care of acutely ill or arrested adult patients that medical students should possess at the point of graduation.DesignHealthcare professionals were invited to contribute suggestions for competencies to a website as part of a modified Delphi survey. The competency proposals were grouped into themes and rated by a nominal group comprised of physicians, nurses and students from the UK. The nominal group rated the importance of each competency using a 5-point Likert scale.ResultsA total of 359 healthcare professionals contributed 2,629 competency suggestions during the Delphi survey. These were reduced to 88 representative themes covering: airway and oxygenation; breathing and ventilation; circulation; confusion and coma; drugs, therapeutics and protocols; clinical examination; monitoring and investigations; team-working, organisation and communication; patient and societal needs; trauma; equipment; pre-hospital care; infection and inflammation. The nominal group identified 71 essential and 16 optional competencies which students should possess at the point of graduation.ConclusionsWe propose these competencies form a core set for undergraduate training in resuscitation and acute care.

The effect of lead time bias on severity of illness scoring, mortality prediction and standardised mortality ratio in intensive care — a pilot study

The effect of lead time bias on severity of illness scoring, mortality prediction and standardised mortality ratios was examined in a pilot study of 76 intensive care (ICU) patients using APACHE II, APACHE III and SAPS II scoring systems. The inclusion of data collected in the period prior to ICU admission increased severity of illness scores and estimated risk of hospital mortality significantly for all three scoring systems (p < 0.01) by up to 14 points and 42.7% (APACHE II), 50 points and 26.3% (APACHE III) and 23 points and 33.4% (SAPS II), respectively. Standardised mortality ratios fell from 0.99 to 0.79 (APACHE II), 0.96 to 0.84 (APACHE III) and 0.75 to 0.64 (SAPS II), but these changes failed to reach statistical significance. Lead time bias had most effect in medical patients and on emergency admissions, and least effect in patients admitted from the operating theatre. These trends suggest that mortality ratios may not necessarily reflect intensive care unit performance and indicate that a larger study of the effect of lead time bias, case mix, pre‐ICU care or post‐ICU management on standardised mortality ratios is indicated.

Health technology assessment review: Remote monitoring of vital signs - current status and future challenges

Recent developments in communications technologies and associated computing and digital electronics now permit patient data, including routine vital signs, to be surveyed at a distance. Remote monitoring, or telemonitoring, can be regarded as a subdivision of telemedicine - the use of electronic and telecommunications technologies to provide and support health care when distance separates the participants. Depending on environment and purpose, the patient and the carer/system surveying, analysing or interpreting the data could be separated by as little as a few feet or be on different continents. Most telemonitoring systems will incorporate five components: data acquisition using an appropriate sensor; transmission of data from patient to clinician; integration of data with other data describing the state of the patient; synthesis of an appropriate action, or response or escalation in the care of the patient, and associated decision support; and storage of data. Telemonitoring is currently being used in community-based healthcare, at the scene of medical emergencies, by ambulance services and in hospitals. Current challenges in telemonitoring include: the lack of a full range of appropriate sensors, the bulk weight and size of the whole system or its components, battery life, available bandwidth, network coverage, and the costs of data transmission via public networks. Telemonitoring also has the ability to produce a mass of data - but this requires interpretation to be of clinical use and much necessary research work remains to be done.