This study examines the outcomes of 11,021 head injury patients admitted to UK ICUs since 1995, and the predictive ability of five risk-adjustment scores for intensive care head injury mortality.
ICNARC is an independent charity and coordinates a national comparative audit of patient outcomes from participating ICUs. In total, 171 UK ICUs contributed data used in this study: 153 in England, 8 in Northern Ireland and 10 in Wales. The CMP is a high quality database and performs well against the Directory of Clinical Databases criteria , comprising data on consecutive admissions from each centre, explicit variable definitions, data collection training for observers and objective variables without scope for inter-observer error.
A limitation of the analysis is that a proportion of admissions, 1,692 patients, did not have a documented GCS/pre-sedation GCS. These patients were, therefore, excluded from the analysis, which may have introduced an element of bias.
Seventy-seven percent of the head injury admissions in this analysis were male, a male to female ratio of 3.3:1. In series of several thousands of head injuries in adults, including patients who did not require intensive care and presented with any GCS, males accounted for 67% to 90% of cases [2, 8, 24–27]. This association is well established and is correlated with the greater sensation seeking behaviour of males . The mean age of adults admitted to the ICUs in this analysis was 44 years. This is moderately higher than other studies that quote mean ages between 28 and 38 years [8, 24–27, 29, 30].
Survivors' length of stay (LOS) in ICU was a median of 3.2 days. Non-survivors only stayed a median of 1.6 days. The design of this analysis is such that we can only speculate upon explanations for this disparity. Firstly, this may be a reflection of limited provision of ICU beds within participating centres. Much has been written about critical care provision in the UK [31–34]. A shortage of units providing intermediate/high dependency care  and intensive care  has been identified and appropriately referred patients may still be refused admission to intensive care because of this . Patients in our study may have been cared for on a ward or in a lower level critical care setting and transferred to the ICU only when they had acutely deteriorated, by which point it may have been too late to sizeably influence their outcome. Similarly, there may have been pressure to discharge patients from the ICU prematurely to make way for others with greater perceived critical care need. This appears to be supported by the higher non-survivors' median hospital LOS of three days; that is, patients with ultimately fatal head injury did not spend all of their admission receiving intensive care. Alternatively, the fact that these patients did not stay on an ICU for their entire admission may have reflected sound medical judgement by which intensive care was channelled away from patients whose outcome would not have been expected to be changed significantly regardless of the level of medical attention they received.
A study of 843 head injury patients in a UK ICU demonstrated similar overall median ICU LOS of three days . Asthma patients, in contrast, only stay a median of 1.5 days in UK ICUs and represented only 1.7% of UK ICU admissions . As well as longer ICU LOS, head injury accounted for 3% of all ICU admissions in our analysis. Therefore, with intensive care costing £1,219 to £1,638 per day , head injury represents a large burden on critical care resources. The survivors tended to stay in hospital for some time, with a median hospital LOS of 24 days. Overall, median LOS was 23 days in a series of 182 head injury patients presenting with a GCS of less than 9 , and 10 days in a series of 843 patients requiring ICU treatment . Asthma and chronic obstructive pulmonary disease median hospital LOS were 8 days  and 16 days , respectively.
It is notable that non-survivors spent only a median of three days in hospital. It appears that if their injury was serious enough to be fatal, they would die early during the admission, within only a couple of days. In contrast, the long hospital LOS of survivors in our study is not surprising. These are highly dependent patients who need almost all activities of daily living performed for them; those requiring initial intubation will require weaning from the respiratory support and their immobility puts them at risk of multiple medical complications, such as venous thromboembolism and pneumonia. Many of these patients will also have associated injuries that will delay their recovery, such as those to the chest, abdominal organs and spine.
Head injury patients in this analysis had a 77% chance of surviving to leave the ICU and a 66.5% chance of surviving to leave hospital. Our in-hospital mortality rate of 33.5% is comparable to previous studies, whose patients were adults and all received intensive care, where the mortality rate was 23% to 39.5% [8, 36, 38, 40]. A mortality of just 14% was described where severe head injury accounted for only 32% of 22,924 patients . Patients in our analysis with a pre-sedation GCS of 3 to 8 had a mortality of 38.5% compared to 44% mortality in a series of severe head injury only . However, this included all hospital admissions whereas our analysis was restricted to those who were accepted for intensive therapy, and so would have included patients whose prognosis was deemed so dire and unmodifiable that they would not have been ICU candidates or who died prior to admission to an ICU.
It is notable that almost 30% of non-survivors in our analysis died after initial discharge from the ICU. This again may represent sound medical judgement in patients deemed to have a dire prognosis that would not improve significantly despite intensive care; however, only 8% of these patients had all active treatment withdrawn during their ICU stay, and only 19% were specified as a discharge for palliative care. Alternatively, it may again represent a lack of ICU provision to patients with great need for it. An estimated figure of 50% of non-survivors after surgery in the UK are never admitted to an ICU . Clearly all of our patients were within an ICU at some point of their admission but it is possible that the length of time they spent there may not have been optimal.
Surgical status showed that approximately 20% of admissions required emergency surgery prior to their arrival in the ICU. However, the nature of the database does not inform us of the type of surgery performed and, although some may have undergone craniotomy, they may alternatively have undergone surgery for extracranial injuries, for example, laparotomy.
Our analysis also compared the performance of five risk prediction models in the prediction of head injury mortality in this population. Risk prediction models can be used to prognosticate but also to allow large-scale audit of outcomes in different centres or at different times. Observational studies of provision and outcomes in critical care often rely on risk prediction models to reduce bias. For these reasons, the models must be robust with as accurate calibration as possible to the particular population. Established models can display a loss of fit when evaluated in different critical care populations . Even more so, this is a potential problem when they are evaluated in a single condition, such as head injury, for which they have not been specifically developed. We compared the models using a spectrum of measures of calibration and discrimination. This followed an approach developed under the guidance of an expert statistical steering committee for a large multicentre comparison of the risk prediction models in all ICU admissions . The use of quantitative measures of model fit (Cox's calibration regression, Brier's score) rather than tests of perfect calibration (Hosmer-Lemeshow) alone allows more reliable comparison of the degree of miscalibration among the models. Although none of the risk prediction models evaluated in this analysis discriminated perfectly between survivors and non-survivors amongst 5,393 head injury patients in intensive care, SAPS II, MPM II and the ICNARC model discriminated better than APACHE II and III and had superior calibration. The performance of the risk prediction models surpassed that of raw GCS alone. This is a reflection of the importance of multiple factors in the prediction of outcome after head injury. Extracranial factors indirectly reflect the scale of secondary brain injury. Not only does the outcome from traumatic brain injury depend on adequate oxygenation and perfusion to facilitate restoration of normal neural architecture and physiology, insufficiency of these causes further neuronal insult. Therefore, incorporating the factors relating to systemic injury and cardiorespiratory function, for example, allows more accurate prediction of outcome.
The ICNARC model performed the best of all with respect to both discrimination and calibration. There may be several reasons for this. Firstly, this comparative analysis was based on an original dataset of 374,594 admissions from the CMP and the ICNARC model was derived using 231,930 of those admissions from the same database. Therefore, this would not be a fair representation of the ICNARC model's performance in head injury in intensive care. The comparative analysis was repeated using the remaining 142,664 admissions (2,563 head injuries), where none had been used to develop the ICNARC model, and it was again demonstrated to perform the best. A criticism that could still be raised is that these patients still have a similar case mix to those used to develop the ICNARC model as they came from the same UK ICUs. It is surprising, therefore, that the APACHE II model we used, which had been recalibrated for UK ICUs, did not perform better. In contrast, SAPS II and MPM II were developed using data from 137 ICUs in 12 countries throughout Europe and North America, the UK being only one of them, but still performed better than the UK-calibrated APACHE model. Thus, case mix can only partially explain the differences in model performance.
The second reason for the superior performance of the ICNARC model, followed by SAPS II and MPM II, may be their choice and weighting of variables relevant to neurological outcome. All of the models incorporate a mixture of the basic physiological factors that cause secondary brain injury, such as systolic blood pressure, hypoxia and temperature. However, they treat the neurological status of the patient differently and in varying depth. APACHE III uses a grid combining variations of eye opening, verbal and motor responses to give an overall score. The categories of each component are a compressed form of those in the Glasgow Coma Scale. SAPS II, on the other hand, uses the full GCS, which has been repeatedly shown to independently predict head injury mortality [6, 8, 26, 43, 44]. Although MPM II uses a cruder assessment of conscious level, that is, 'coma or deep stupor', it also incorporates the presence of intracranial mass effect. Presence of a mass lesion has also been demonstrated to be an independent predictor of head injury mortality [8, 40, 45, 46]. In the case of sedated patients, APACHE II and III assume their GCS to be 15, which in the context of head injury requiring intensive care is clearly an often-false assumption and will underestimate disease severity. In contrast, SAPS II uses pre-sedation GCS as a direct replacement for the GCS in the first 24 hours, and the ICNARC model uses weightings for sedated and paralysed/sedated patients. The combination is much more likely to give a truer neurological assessment and make the ICNARC model a more appropriate tool in predicting head injury mortality.