Unanticipated Intensive Care Unit Admission Research Articles

Prediction of postoperative patient deterioration and unanticipated intensive care unit admission using perioperative factors.

Currently, no evidence-based criteria exist for decision making in the post anesthesia care unit (PACU). This could be valuable for the allocation of postoperative patients to the appropriate level of care and beneficial for patient outcomes such as unanticipated intensive care unit (ICU) admissions. The aim is to assess whether the inclusion of intra- and postoperative factors improves the prediction of postoperative patient deterioration and unanticipated ICU admissions. A retrospective observational cohort study was performed between January 2013 and December 2017 in a tertiary Dutch hospital. All patients undergoing surgery in the study period were selected. Cardiothoracic surgeries, obstetric surgeries, catheterization lab procedures, electroconvulsive therapy, day care procedures, intravenous line interventions and patients under the age of 18 years were excluded. The primary outcome was unanticipated ICU admission. An unanticipated ICU admission complicated the recovery of 223 (0.9%) patients. These patients had higher hospital mortality rates (13.9% versus 0.2%, p<0.001). Multivariable analysis resulted in predictors of unanticipated ICU admissions consisting of age, body mass index, general anesthesia in combination with epidural anesthesia, preoperative score, diabetes, administration of vasopressors, erythrocytes, duration of surgery and post anesthesia care unit stay, and vital parameters such as heart rate and oxygen saturation. The receiver operating characteristic curve of this model resulted in an area under the curve of 0.86 (95% CI 0.83-0.88). The prediction of unanticipated ICU admissions from electronic medical record data improved when the intra- and early postoperative factors were combined with preoperative patient factors. This emphasizes the need for clinical decision support tools in post anesthesia care units with regard to postoperative patient allocation.

Predictive value of a tiered escalation response system: A case control study

ObjectiveRapid response systems designed to detect and respond to clinical deterioration often incorporate a multitiered, escalation response. We sought to determine the ‘predictive strength’ of commonly used triggers, and tiers of escalation, for predicting a rapid response team (RRT) call, unanticipated intensive care unit admission, or cardiac arrest (events). DesignThis was a nested, matched case–control study. SettingThe study setting involved a tertiary referral hospital. ParticipantsCases experienced an event, and controls were matched patients without an event. Outcome measuresSensitivity and specificity and area under the receiver operating characteristic curve (AUC) were measured. Logistic regression determined the set of triggers with the highest AUC. ResultsThere were 321 cases and 321 controls. Nurse triggers occurred in 62%, medical review triggers in 34%, and RRT triggers 20%. Positive predictive value of nurse triggers was 59%, that of medical review triggers was 75%, and that of RRT triggers was 88%. These values were no different when modifications to triggers were considered. The AUC was 0.61 for nurses, 0.67 for medical review, and 0.65 for RRT triggers. With modelling, the AUC was 0.63 for the lowest tier, 0.71 for next highest, and 0.73 for the highest tier. ConclusionFor a three-tiered system, at the lowest tier, specificity of triggers decreases, sensitivity increases, but the discriminatory power is poor. Thus, there is little to be gained by using a rapid response system with more than two tiers. Modifications to triggers reduced the potential number of escalations and did not affect tier discriminatory value.

Tiered escalation response systems in practice: A post hoc analysis examining the workload implications

ObjectiveMany rapid response systems now have multiple tiers of escalation in addition to the traditional single tier of a medical emergency team. Given that the benefit to patient outcomes of this change is unclear, we sought to investigate the workload implications of a multitiered system, including the impact of trigger modification. DesignThe study design incorporated a post hoc analysis using a matched case–control dataset. SettingThe study setting was an acute, adult tertiary referral hospital. ParticipantsCases that had an adverse event (cardiac arrest or unanticipated intensive care unit admission) or a rapid response team (RRT) call participated in the study. Controls were matched by age, gender, ward and time of year, and no adverse event or RRT call. Participants were admitted between May 2014 and April 2015. Main outcome measuresThe main outcome measure were the number of reviews, triggers, and modifications across three tiers of escalation; a nurse review, a multidisciplinary review (MDT—admitting medical team review), and an RRT call. ResultsThere were 321 cases and 321 controls. Overall, there were 1948 nurse triggers, of which 1431 (73.5%) were in cases and 517 (26.5%) in controls, 798 MDT triggers (660 [82.7%] in cases and 138 [17.3%] in controls), and 379 RRT triggers (351 [92.6%] in cases and 28 [7.4%] in controls). Per patient per 24 h, there were 3.03 nurse, 1.24 MDT, and 0.59 RRT triggers. Accounting for modifications, this reduced to 2.17, 0.88, and 0.42, respectively. The proportion of triggers that were modified, so as not to trigger a review, was similar across all the tiers, being 28.6% of nurse, 29.6% of MDT, and 28.2% of RRT triggers. Per patient per 24 h, there were 0.61 nurse reviews, 0.52 MDT reviews, and 0.08 RRT reviews. ConclusionsLower-tier triggers were more prevalent, and modifications were common. Modifications significantly mitigated the escalation workload across all tiers of a multitiered system.

Planning for the Worst: The impact of a comprehensive, risk associated treatment protocol on unanticipated ICU admissions in patients affected by rib fractures

BackgroundThere is no agreed upon triage criteria to identify traumatic rib fracture patients at the highest risk for decline. We developed a comprehensive triage tool that assigns patients to high, moderate, and low risk categories. The primary outcome of our study was to evaluate unplanned intensive care unit (ICU) admissions. MethodsWe conducted a single-center, retrospective review at our level 1 trauma center comparing two cohorts of patients (≥18 years of age) six months before and after implementation of our risk-associated rib fracture protocol. ResultsAfter implementation of the risk-associated rib fracture protocol, the unplanned ICU admission rate decreased from 6.60% (PRE) to 2.60% (POST) (p = 0.014). ConclusionsImplementation of our rib fracture protocol demonstrates that a comprehensive triage tool with a cascading risk associated treatment plan reduces in-hospital clinical decline of patients with traumatic rib fractures, as measured by unplanned ICU admissions.

The predictive power of the National Early Warning Score (NEWS) 2, as compared to NEWS, among patients assessed by a Rapid response team: A prospective multi-centre trial

AimEarly identification of patients at risk of serious adverse events (SAEs) is of vital importance, yet it remains a challenging task. We investigated the predictive power of National Early Warning Score (NEWS) 2, as compared to NEWS, among patients assessed by a Rapid response team (RRT). MethodsProspective, observational cohort study on 898 consecutive patients assessed by the RRTs in 26 Swedish hospitals. For each patient, NEWS and NEWS 2 scores were uniformly calculated by the study team. The associations of NEWS and NEWS 2 scores with unanticipated admissions to Intensive care unit (ICU), mortality and in-hospital cardiac arrests (IHCA) within 24 h, and the composite of these three events were investigated using logistic regression. The predictive power of NEWS and NEWS 2 was assessed using the area under the receiver operating characteristic (AUROC) curves. ResultsThe prognostic accuracy of NEWS/NEWS 2 in predicting mortality was acceptable (AUROC 0.69/0.67). In discriminating the composite outcome and unanticipated ICU admission, both NEWS and NEWS 2 were relatively weak (AUROC 0.62/0.62 and AUROC 0.59/0.60 respectively); for IHCA the performance was poor. There were no differences between NEWS and NEWS 2 as to the predictive power. ConclusionThe prognostic accuracy of NEWS 2 to predict mortality within 24 h was acceptable. However, the prognostic accuracy of NEWS 2 to predict IHCA was poor. NEWS and NEWS 2 performed similar in predicting the risk of SAEs but their performances were not sufficient for use as a risk stratification tool in patients assessed by a RRT.

Torsades de pointes in the PACU after outpatient endoscopy: a case report

BackgroundThis case demonstrates the severe electrolyte derangements that may present after a common therapy such as a bowel preparation for an outpatient procedure and the rare yet potential detrimental outcomes of those abnormalities. It also highlights the implications of long QT syndrome regarding pharmacology and treatment.Case presentationWe present a case of 48 year-old female with severe electrolyte derangements and long QT syndrome (LQTS) leading to Torsades de Pointes (TdP), pulseless ventricular fibrillation, and unsynchronized defibrillation in the post anesthesia care unit (PACU) after uneventful upper and lower endoscopy. This led to an unanticipated intensive care unit admission for aggressive electrolyte repletion, cardiology consultation, and implantable cardioverter defibrillator (ICD) placement.ConclusionsThis is a rare presentation after an outpatient procedure that would have had a detrimental outcome if not promptly diagnosed and treated appropriately. Therefore, we aim to provide further insight into the diagnosis and treatment of severe hypokalemia and long QT syndrome resulting in Torsades de Pointes and ventricular fibrillation.

Efficient Postoperative Disposition Selection in Pediatric Otolaryngology Patients: A Novel Approach.

Pediatric patients undergoing surgery on the aerodigestive tract require a wide range of postoperative airway support that may be difficult predict in the preoperative period. Inaccurate prediction of postoperative resource needs leads to care inefficiencies in the form of unanticipated intensive care unit (ICU) admissions, ICU bed request cancellations, and overutilization of ICU resources. At our hospital, inefficient utilization of pediatric intensive care unit (PICU) resources was negatively impacting safety, access, throughput, and finances. We hypothesized that actionable key drivers of inefficient ICU utilization at our hospital were operative scheduling errors and the lack of predictability of intermediate-risk patients and that improvement methodology could be used in iterative cycles to enhance efficiency of care. Through testing this hypothesis, we aimed to provide a framework for similar efforts at other hospitals. Quality improvement initiative. Plan, Do, Study, Act methodology (PDSA) was utilized to implement two cycles of change aimed at improving level-of-care efficiency at an academic pediatric hospital. In PDSA cycle 1, we aimed to address scheduling errors with surgical order placement restriction, creation of a standardized list of surgeries requiring PICU admission, and implementation of a hard stop for postoperative location in the electronic medical record surgical order. In the PDSA cycle 2, a new model of care, called the Grey Zone model, was designed and implemented where patients at intermediate risk of airway compromise were observed for 2-5 hours in the post-anesthesia care unit. After this observation period, patients were then transferred to the level of care dictated by their current status. Measures assessed in PDSA cycle 1 were unanticipated ICU admissions and ICU bed request cancellations. In addition to continued analysis of these measures, PDSA cycle 2 measures were ICU beds avoided, safety events, and secondary transfers from extended observation to ICU. In PDSA cycle 1, no significant decrease in unanticipated ICU admissions was observed; however, there was an increase in average monthly ICU bed cancellations from 36.1% to 45.6%. In PDSA cycle 2, average monthly unanticipated ICU admissions and cancelled ICU bed requests decreased from 1.3% to 0.42% and 45.6% to 33.8%, respectively. In patients observed in the Grey Zone, 229/245 (93.5%) were transferred to extended observation, avoiding admission to the ICU. Financial analysis demonstrated a charge differential to payers of $1.1 million over the study period with a charge differential opportunity to the hospital of $51,720 for each additional hospital transfer accepted due to increased PICU bed availability. Implementation of the Grey Zone model of care improved efficiency of ICU resource utilization through reducing unanticipated ICU admissions and ICU bed cancellations while simultaneously avoiding overutilization of ICU resources for intermediate-risk patients. This was achieved without compromising safety of patient care, and was financially sound in both fee-for-service and value-based reimbursement models. While such a model may not be applicable in all healthcare settings, it may improve efficiency at other pediatric hospitals with high surgical volume and acuity. N/A Laryngoscope, 131:S1-S10, 2021.

Are Postoperative Clinical Outcomes Influenced by Length of Stay in the Postanesthesia Care Unit?

To compare clinical outcomes of patients who required a prolonged length of stay in the postanesthesia care unit (PACU) with a control group. A single-center purposive-sampled retrospective medical record and database audit. Patients with prolonged PACU stays were compared to a group of patients whose stay was less than median for outcome measures: rapid response team (RRT) activation, cardiac arrest, unanticipated intensive care unit admissions, and survival to discharge. A total of 1,867 patients were included in the analysis (n=931 prolonged stay and n=933 control group). Prolonged stay in PACU was higher among patients who were older, had higher American Society of Anesthesiologist score, and were discharged to wards during the afternoon or late nursing shift. RRT activation after discharge from PACU occurred in more patients in the study group compared with the control group (7% vs 1%, respectively). There were no cardiac arrests recorded in either group within the 24hours after PACU discharge period. Prolonged stay in the PACU for 2 or more hours because of clinical reasons appears to be associated with a higher incidence of clinical deterioration in the ward setting requiring RRT intervention within 24hours after discharge from PACU.

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

AimsTo compare the ability of the National Early Warning Score (NEWS) and the National Early Warning Score 2 (NEWS2) to identify patients at risk of in-hospital mortality and other adverse outcomes. MethodsWe undertook a multi-centre retrospective observational study at five acute hospitals from two UK NHS Trusts. Data were obtained from completed adult admissions who were not fit enough to be discharged alive on the day of admission. Diagnostic coding and oxygen prescriptions were used to identify patients with type II respiratory failure (T2RF). The primary outcome was in-hospital mortality within 24 h of a vital signs observation. Secondary outcomes included unanticipated intensive care unit admission or cardiac arrest within 24 h of a vital signs observation. Discrimination was assessed using the c-statistic. ResultsAmong 251,266 adult admissions, 48,898 were identified to be at risk of T2RF by diagnostic coding. In this group, NEWS2 showed statistically significant lower discrimination (c-statistic, 95% CI) for identifying in-hospital mortality within 24 h (0.860, 0.857–0.864) than NEWS (0.881, 0.878-0.884). For 1394 admissions with documented T2RF, discrimination was similar for both systems: NEWS2 (0.841, 0.827-0.855), NEWS (0.862, 0.848–0.875). For all secondary endpoints, NEWS2 showed no improvements in discrimination. ConclusionsNEWS2 modifications to NEWS do not improve discrimination of adverse outcomes in patients with documented T2RF and decrease discrimination in patients at risk of T2RF. Further evaluation of the relationship between SpO2 values, oxygen therapy and risk should be investigated further before wide-scale adoption of NEWS2.

Predicting in-hospital mortality and unanticipated admissions to the intensive care unit using routinely collected blood tests and vital signs: Development and validation of a multivariable model

AimThe National Early Warning System (NEWS) is based on vital signs; the Laboratory Decision Tree Early Warning Score (LDT-EWS) on laboratory test results. We aimed to develop and validate a new EWS (the LDTEWS:NEWS risk index) by combining the two and evaluating the discrimination of the primary outcome of unanticipated intensive care unit (ICU) admission or in-hospital mortality, within 24 h. MethodsWe studied emergency medical admissions, aged 16 years or over, admitted to Oxford University Hospitals (OUH) and Portsmouth Hospitals (PH). Each admission had vital signs and laboratory tests measured within their hospital stay. We combined LDT-EWS and NEWS values using a linear time-decay weighting function imposed on the most recent blood tests. The LDTEWS:NEWS risk index was developed using data from 5 years of admissions to PH, and validated on a year of data from both PH and OUH. We tested the risk index’s ability to discriminate the primary outcome using the c-statistic. ResultsThe development cohort contained 97,933 admissions (median age = 73 years) of which 4723 (4.8%) resulted inhospital death and 1078 (1.1%) in unanticipated ICU admission. We validated the risk index using data from PH (n = 21,028) and OUH (n = 16,383). The risk index showed a higher discrimination in the validation sets (c-statistic value (95% CI)) (PH, 0.901 (0.898–0.905); OUH, 0.916 (0.911–0.921)), than NEWS alone (PH, 0.877 (0.873–0.882); OUH, 0.898 (0.893–0.904)). ConclusionsThe LDTEWS:NEWS risk index increases the ability to identify patients at risk of deterioration, compared to NEWS alone.

Manual centile-based early warning scores derived from statistical distributions of observational vital-sign data

Aims of studyTo develop and validate a centile-based early warning score using manually-recorded data (mCEWS). To compare mCEWS performance with a centile-based early warning score derived from continuously-acquired data (from bedside monitors, cCEWS), and with other published early warning scores. Materials and methodsWe used an unsupervised approach to investigate the statistical properties of vital signs in an in-hospital patient population and construct an early-warning score from a “development” dataset. We evaluated scoring systems on a separate “validation” dataset. We assessed the ability of scores to discriminate patients at risk of cardiac arrest, unanticipated intensive care unit admission, or death, each within 24 h of a given vital-sign observation, using metrics including the area under the receiver-operating characteristic curve (AUC). ResultsThe development dataset contained 301,644 vital sign observations from 12,153 admissions (median age (IQR): 63 (49–73); 49.2% females) March 2014–September 2015. The validation dataset contained 1,459,422 vital-sign observations from 53,395 admissions (median age (IQR): 68 (48–81), 51.4% females) October 2015–May 2017. The AUC (95% CI) for the mCEWS was 0.868 (0.864–0.872), comparable with the National EWS, 0.867 (0.863–0.871), and other recently proposed scores. The AUC for cCEWS was 0.808 (95% CI, 0.804–0.812). The improvement in performance in comparison to the continuous CEWS was mainly explained by respiratory rate threshold differences. ConclusionsPerformance of an EWS is highly dependent on the database from which itis derived. Our unsupervised statistical approach provides a straightforward, reproducible method to enable the rapid development of candidate EWS systems.

Short National Early Warning Score — Developing a Modified Early Warning Score

IntroductionEarly Warning Score (EWS) systems have been developed for detecting hospital patients clinical deterioration. Many studies show that a National Early Warning Score (NEWS) performs well in discriminating survival from death in acute medical and surgical hospital wards. NEWS is validated for Portugal and is available for use. A simpler EWS system may help to reduce the risk of error, as well as increase clinician compliance with the tool. ObjectivesThe aim of the study was to evaluate whether a simplified NEWS model will improve use and data collection. MethodsWe evaluated the ability of single and aggregated parameters from the NEWS model to detect patients’ clinical deterioration in the 24h prior to an outcome. There were 2 possible outcomes: Survival vs Unanticipated intensive care unit admission or death. We used binary logistic regression models and Receiver Operating Characteristic Curves (ROC) to evaluate the parameters’ performance in discriminating among the outcomes for a sample of patients from 6 Portuguese hospital wards. ResultsNEWS presented an excellent discriminating capability (Area under the Curve of ROC (AUCROC)=0.944). Temperature and systolic blood pressure (SBP) parameters did not contribute significantly to the model. We developed two different models, one without temperature, and the other by removing temperature and SBP (M2). Both models had an excellent discriminating capability (AUCROC: 0.965; 0.903, respectively) and a good predictive power in the optimum threshold of the ROC curve. ConclusionsThe 3 models revealed similar discriminant capabilities. Although the use of SBP is not clearly evident in the identification of clinical deterioration, it is recognized as an important vital sign. We recommend the use of the first new model, as its simplicity may help to improve adherence and use by health care workers.

Clinical deterioration in older adults with delirium during early hospitalisation: a prospective cohort study

ObjectivesTo measure the prevalence and incidence of delirium in older adults as they transition from the emergency department (ED) to the inpatient ward, and to determine the association between delirium...

Can binary early warning scores perform as well as standard early warning scores for discriminating a patient's risk of cardiac arrest, death or unanticipated intensive care unit admission?

IntroductionAlthough the weightings to be summed in an early warning score (EWS) calculation are small, calculation and other errors occur frequently, potentially impacting on hospital efficiency and patient care. Use of a simpler EWS has the potential to reduce errors. MethodsWe truncated 36 published ‘standard’ EWSs so that, for each component, only two scores were possible: 0 when the standard EWS scored 0 and 1 when the standard EWS scored greater than 0. Using 1564,153 vital signs observation sets from 68,576 patient care episodes, we compared the discrimination (measured using the area under the receiver operator characteristic curve—AUROC) of each standard EWS and its truncated ‘binary’ equivalent. ResultsThe binary EWSs had lower AUROCs than the standard EWSs in most cases, although for some the difference was not significant. One system, the binary form of the National Early Warning System (NEWS), had significantly better discrimination than all standard EWSs, except for NEWS. Overall, Binary NEWS at a trigger value of 3 would detect as many adverse outcomes as are detected by NEWS using a trigger of 5, but would require a 15% higher triggering rate. ConclusionsThe performance of Binary NEWS is only exceeded by that of standard NEWS. It may be that Binary NEWS, as a simplified system, can be used with fewer errors. However, its introduction could lead to significant increases in workload for ward and rapid response team staff. The balance between fewer errors and a potentially greater workload needs further investigation.

Serious adverse events in a hospital using early warning score – What went wrong?

AimTo evaluate the performance of a new early warning score (EWS) system by reviewing all serious adverse events in our hospital over a 6-month time period. MethodAll incidents of unexpected death (UD), cardiac arrest (CA) and unanticipated intensive care unit admission(UICU) of adult patients on general wards were reviewed to see if the escalation protocol that is part of the EWS system was followed in the 24h preceding the event, and if not where in the chain of events failure occurred. ResultsWe found 77 UICU and 67 cases of the combined outcome (CO) of CA and UD. At least two full sets of EWS were recorded in 87, 94 and 75% of UICU, CA and UD. Patients were monitored according to the escalation protocol in 13, 31 and 13% of UICU, CA and UD. Nurses escalated care and contacted physicians in 64% and 60% of events of UICU and the corresponding proportions for CO were 58% and 55%. On call physicians provided adequate care in 49% of cases of UICU and 29% of cases of the CO. Senior staff was involved according to protocol in 53% and 36% of cases of UICU and CO, respectively. ConclusionPoor compliance with the escalation protocol was commonly found when serious adverse events occurred but level of care provided by physicians was also a problem in a hospital with implemented early warning system. This information may prove useful in improving performance of EWS systems.

Decision-tree early warning score (DTEWS) validates the design of the National Early Warning Score (NEWS)

Aim of study: To compare the performance of a human-generated, trial and error-optimised early warning score (EWS), i.e., National Early Warning Score (NEWS), with one generated entirely algorithmically using Decision Tree (DT) analysis. Materials and methodsWe used DT analysis to construct a decision-tree EWS (DTEWS) from a database of 198,755 vital signs observation sets collected from 35,585 consecutive, completed acute medical admissions. We evaluated the ability of DTEWS to discriminate patients at risk of cardiac arrest, unanticipated intensive care unit admission or death, each within 24h of a given vital signs observation. We compared the performance of DTEWS and NEWS using the area under the receiver-operating characteristic (AUROC) curve. ResultsThe structures of DTEWS and NEWS were very similar. The AUROC (95% CI) for DTEWS for cardiac arrest, unanticipated ICU admission, death, and any of the outcomes, all within 24h, were 0.708 (0.669–0.747), 0.862 (0.852–0.872), 0.899 (0.892–0.907), and 0.877 (0.870–0.883), respectively. Values for NEWS were 0.722 (0.685–0.759) [cardiac arrest], 0.857 (0.847–0.868) [unanticipated ICU admission}, 0.894 (0.887–0.902) [death], and 0.873 (0.866–0.879) [any outcome]. ConclusionsThe decision-tree technique independently validates the composition and weightings of NEWS. The DT approach quickly provided an almost identical EWS to NEWS, although one that admittedly would benefit from fine-tuning using clinical knowledge. We believe that DT analysis could be used to quickly develop candidate models for disease-specific EWSs, which may be required in future.

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

IntroductionEarly 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. MethodsWe 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. ResultsThe 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). ConclusionsNEWS 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.

Medical reviews before cardiac arrest, medical emergency call or unanticipated intensive care unit admission: their nature and impact on patient outcome

Medical reviews before cardiac arrest, medical emergency call or unanticipated intensive care unit admission: their nature and impact on patient outcome

Major complications of airway management in the UK: results of the Fourth National Audit Project of the Royal College of Anaesthetists and the Difficult Airway Society. Part 1: Anaesthesia

This project was devised to estimate the incidence of major complications of airway management during anaesthesia in the UK and to study these events. Reports of major airway management complications during anaesthesia (death, brain damage, emergency surgical airway, unanticipated intensive care unit admission) were collected from all National Health Service hospitals for 1 yr. An expert panel assessed inclusion criteria, outcome, and airway management. A matched concurrent census estimated a denominator of 2.9 million general anaesthetics annually. Of 184 reports meeting inclusion criteria, 133 related to general anaesthesia: 46 events per million general anaesthetics [95% confidence interval (CI) 38-54] or one per 22,000 (95% CI 1 per 26-18,000). Anaesthesia events led to 16 deaths and three episodes of persistent brain damage: a mortality rate of 5.6 per million general anaesthetics (95% CI 2.8-8.3): one per 180,000 (95% CI 1 per 352-120,000). These estimates assume that all such cases were captured. Rates of death and brain damage for different airway devices (facemask, supraglottic airway, tracheal tube) varied little. Airway management was considered good in 19% of assessable anaesthesia cases. Elements of care were judged poor in three-quarters: in only three deaths was airway management considered exclusively good. Although these data suggest the incidence of death and brain damage from airway management during general anaesthesia is low, statistical analysis of the distribution of reports suggests as few as 25% of relevant incidents may have been reported. It therefore provides an indication of the lower limit for incidence of such complications. The review of airway management indicates that in a majority of cases, there is 'room for improvement'.

Major complications of airway management in the UK: results of the Fourth National Audit Project of the Royal College of Anaesthetists and the Difficult Airway Society. Part 2: intensive care and emergency departments

The Fourth National Audit Project of the Royal College of Anaesthetists and Difficult Airway Society (NAP4) was designed to identify and study serious airway complications occurring during anaesthesia, in intensive care unit (ICU) and the emergency department (ED). Reports of major complications of airway management (death, brain damage, emergency surgical airway, unanticipated ICU admission, prolonged ICU stay) were collected from all National Health Service hospitals over a period of 1 yr. An expert panel reviewed inclusion criteria, outcome, and airway management. A total of 184 events met inclusion criteria: 36 in ICU and 15 in the ED. In ICU, 61% of events led to death or persistent neurological injury, and 31% in the ED. Airway events in ICU and the ED were more likely than those during anaesthesia to occur out-of-hours, be managed by doctors with less anaesthetic experience and lead to permanent harm. Failure to use capnography contributed to 74% of cases of death or persistent neurological injury. At least one in four major airway events in a hospital are likely to occur in ICU or the ED. The outcome of these events is particularly adverse. Analysis of the cases has identified repeated gaps in care that include: poor identification of at-risk patients, poor or incomplete planning, inadequate provision of skilled staff and equipment to manage these events successfully, delayed recognition of events, and failed rescue due to lack of or failure of interpretation of capnography. The project findings suggest avoidable deaths due to airway complications occur in ICU and the ED.