BackgroundMortality as an endpoint has been the focus of trauma research whereas few studies investigate long-term outcomes in terms of morbidity. An adequate analysis of post-injury morbidity includes several dimensions, for this reason sick leave has been used as a proxy for morbidity in the current study. The aim of this retrospective matched observational cohort study was to investigate sick leave before and after trauma and factors associated with prolonged sick leave.MethodsPatients from a level one trauma centre 2005–2010 were matched in a 1:5 ratio with uninjured controls. By linkage to national registries, sick leave rates were compared. The association between potential risk factors and full-time sick leave at twelve months post injury, the primary end-point, was examined in trauma patients by logistic regression.ResultsFour thousand seven hundred twelve patients and 25,013 controls aged 20–63 were included. Trauma patients had more sick leave both before and after trauma. Age, psychiatric disease, low level of education, serious injury, spinal injury, reduced consciousness at admission, discharge destination other than home, and hospital length of stay >7 days were all associated with the primary end-point. The strongest risk factor was sick leave before trauma; this was also noted in the most seriously injured patients.DiscussionIn this retrospective matched observational cohort study we found a significant long-term morbidity, measured as sick leave, among trauma patients. Compared to controls the difference was maximal early after trauma and sustained throughout the follow up period. In the logistic regression, factors associated with the traumatic injury as well as host factors increased the probability of not returning to work. Full sick leavemonth twelve post injury was strongly associated with pre-injury sick leave but also with age, psychiatric comorbidity, level of education, injury severity, spinal injury, low GCS at admission, length of stay at hospital and discharge to other destination than home.ConclusionsTrauma patients suffer from significant long-term morbidity. The sustained post-trauma morbidity is largely influenced by factors not related to injury per se. These insights enable identification of patients at risk for prolonged sick leave after trauma.
ObjectiveTo better match hospital resources to patients’ needs of trauma care, a protocol for facilitating in-hospital triage decisions was implemented at a Swedish level I trauma centre. In the protocol, physiological parameters, anatomical injuries and mechanism of injury were documented, and used to activate full or limited trauma team response. The aim of this study was to evaluate the efficacy of the criteria-directed protocol to determine in-hospital trauma triage in an emergency department.MethodsLevel of triage and triage rates were compared before and after implementation of the protocol. Overtriage and undertriage were assessed with injury severity score higher than 15 as the cutoff for defining major trauma. Medical records for undertriaged patients were retrospectively reviewed.ResultsIn 2011, 78% of 1408 trauma team activations required full trauma response, with an overtriage rate of 74% and an undertriage rate of 7%. In 2013, after protocol implementation, 58% of 1466 trauma team activations required full trauma response. Overtriage was reduced to 52% and undertriage was increased to 10%. However, there were no preventable deaths in the undertriaged patients.ConclusionA criteria-directed protocol for use in the emergency department was efficient in reducing overtriage rates without risking undertriaged patients’ safety.
BackgroundAssessment of trauma-system performance is important for improving the care of injured patients. The aim of the study was to compare risk-adjusted survival in two Scandinavian Level-I trauma centres.MethodsThis was an observational, retrospective study of prospectively-collected trauma registry data for patients >14 years from Karolinska University Hospital – Solna (KUH), Sweden, and Oslo University Hospital – Ullevål (OUH), Norway, from 2009-2011. Probability of survival (Ps) was calculated according to the Trauma and Injury Severity Score (TRISS) method. Risk-adjusted survival per patient was calculated by assigning every patient a value corresponding to gained or lost fractional life: Each survivor contributed a reward of 1-Ps and each death a penalty of -Ps. The sum of penalties and rewards, corresponding to the difference between expected and actual mortality, was compared between the centres. We present the data as excess survivors per 100 trauma patients.ResultsThere were 4485 admissions at KUH and 3591 at OUH. The proportion of severely injured patients was higher at OUH compared with KUH (Injury Severity Score [ISS] >15: 33.9 % vs. 21.1 %, p <0.001). OUH had a larger proportion of patients >65 years (16.0 % vs. 13.4 %, p <0.001) and greater comorbidity (ASA-PS ≥3: 14.6 % vs. 6.9 %, p <0.001) compared with KUH. The frequency of helicopter transport and presence of prehospital physicians was higher at OUH compared with KUH (27.6 % vs. 15.5 % and 30.5 % vs. 3.7 %, both p <0.001). Secondary admissions were 5.2-fold more common at OUH compared with KUH (p <0.001). There were no differences in 30-day mortality for severely injured patients (ISS >15). Risk-adjusted survival rate was higher at OUH than at KUH for primary (0.59 vs. 0.51) but lower for secondary (1.41 vs. 2.85) admissions (both p <0.001).ConclusionAdjustments for age as a continuous variable and comorbidity should be made when comparing risk-adjusted survival between hospitals, but this is not possible with the TRISS model. A survival prediction model that takes this into account may be a better choice for Scandinavian trauma populations. The current study could not rule out the influence of the system differences between the centres on risk-adjusted survival.
Preventable deaths were commonly caused by clinical judgment errors in the early phases but death occurred late. Ps calculated with NORMIT was more accurate than TRISS in predicting mortality, but both perform poorly in identifying preventable and non-preventable deaths when applying the cut-offs. PR of all trauma death is still the golden standard in preventability analysis.
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