Predicting health status in the first year after trauma.

BACKGROUND: Although mortality rates following major trauma are continuing to decline, a growing number of patients are experiencing long-term disability. The aim of this study was to identify factors associated with health status in the first year following trauma and develop prediction models based on a defined trauma population. METHODS: The Brabant Injury Outcome Surveillance (BIOS) study was a multicentre prospective observational cohort study. Adult patients with traumatic injury were included from August 2015 to November 2016 if admitted to one of the hospitals of the Noord-Brabant region in the Netherlands. Outcome measures were EuroQol Five Dimensions 5D-3L (EQ-5D™ utility and visual analogue scale (VAS)) and Health Utilities Index (HUI) 2 and 3 scores 1 week and 1, 3, 6 and 12 months after injury. Prediction models were developed using linear mixed models, with patient characteristics, preinjury health status, injury severity and frailty as possible predictors. Predictors that were significant (P < 0·050) for one of the outcome measures were included in all models. Performance was assessed using explained variance (R2 ). RESULTS: In total, 4883 patients participated in the BIOS study (50·0 per cent of the total), of whom 3366 completed the preinjury questionnaires. Preinjury health status and frailty were the strongest predictors of health status during follow-up. Age, sex, educational level, severe head or face injury, severe torso injury, injury severity, Functional Capacity Index score, co-morbidity and duration of hospital stay were also relevant in the multivariable models predicting health status. R2 ranged from 35 per cent for EQ-VAS to 48 per cent for HUI 3. CONCLUSION: The most important predictors of health status in the first year after trauma in this population appeared to be preinjury health status and frailty.

Prevalence, recovery patterns and predictors of quality of life and costs after non-fatal injury: the Brabant Injury Outcome Surveillance (BIOS) study.

INTRODUCTION: Trauma is a major public health problem worldwide that leads to high medical and societal costs. Overall, improved understanding of the full spectrum of the societal impact and burden of injury is needed. The main purpose of the Brabant Injury Outcome Surveillance (BIOS) study is to provide insight into prevalence, predictors and recovery patterns of short-term and long-term health-related quality of life (HRQoL) and costs after injury. MATERIALS AND METHODS: This is a prospective, observational, follow-up cohort study in which HRQoL, psychological, social and functional outcome, and costs after trauma will be assessed during 24 months follow-up within injured patients admitted in 1 of 10 hospitals in the county Noord-Brabant, the Netherlands. Data will be collected by self-reported questionnaires at 1 week (including preinjury assessment), and 1, 3, 6, 12 and 24 months after injury. If patients are not capable of filling out the questionnaires, proxies will be asked to participate. Also, information about mechanism and severity of injury, comorbidity and indirect and direct costs will be collected. Mixed models will be used to examine the course of HRQoL, functional and psychological outcome, costs over time and between different groups, and to identify predictors for poor or good outcome. RELEVANCE: This study should make a substantial contribution to the international collaborative effort to assess the societal impact and burden of injuries more accurately. The BIOS results will also be used to develop an outcome prediction model for outcome evaluation including, besides the classic fatal, non-fatal outcome. TRIAL REGISTRATION NUMBER: NCT02508675.

Comparing health status after major trauma across different levels of trauma care.

INTRODUCTION: Mortality due to trauma has reduced the past decades. Trauma network implementations have been an important contributor to this achievement. Besides mortality, patient reported outcome parameters should be included in evaluation of trauma care. While concentrating major trauma care, hospitals are designated with a certain level of trauma care following specific criteria. OBJECTIVE: Comparing health status of major trauma patients after two years across different levels of trauma care in trauma networks. METHODS: Multicentre observational study comprising a secondary longitudinal multilevel analysis on prospective cohorts from two neighbouring trauma regions in the Netherlands. INCLUSION CRITERIA: patient aged ≥ 18 with an ISS > 15 surviving their injuries at least one year after trauma. Health status was measured one and two years after trauma by EQ-5D-5 L, added with a sixth health dimension on cognition. Level I trauma centres were considered as reference in uni- and multivariate analysis. RESULTS: Respondents admitted to a level I trauma centre scored less favourable EQ-US and EQ-VAS in both years (0.81-0.81, 71-75) than respondents admitted to a level II (0.88-0.87, 78-85) or level III (0.89-0.88, 75-80) facility. Level II facilities scored significantly higher EQ-US and EQ-VAS in time for univariate analysis (ß 0.095, 95% CI 0.038-0.153, p = 0.001, and ß 7.887, 95% CI 3.035-12.740, p = 0.002), not in multivariate analysis (ß 0.052, 95% CI -0.010-0.115, p = 0.102, and ß 3.714, 95% CI -1.893-9.321, p = 0.193). Fewer limitations in mobility (OR 0.344, 95% CI 0.156-0.760), self-care (OR 0.219, 95% CI 0.077-0.618), and pain and discomfort (OR 0.421, 95% CI 0.214-0.831) remained significant for level II facilities in multivariate analysis, whereas significant differences with level III facilities disappeared. CONCLUSION: Major trauma patients admitted to level I trauma centres reported a less favourable general health status and more limitations compared to level II and III facilities scoring populations norms one to two years after trauma. Differences on general health status and limitations in specific health domains disappeared in adjusted analysis. Well-coordinated trauma networks offer homogeneous results for all major trauma patients when they are distributed in different centres according to their need of care.

Prognostic factors and quality of life after pelvic fractures. The Brabant Injury Outcome Surveillance (BIOS) study.

INTRODUCTION: Pelvic fractures can have long-term consequences for health-related quality of life (HRQoL). The main purpose of this study is to provide insight into short-term HRQoL in the first year after pelvic injury and to identify short-term prognostic factors of decreased outcome. METHODS: This is a prospective, observational, multicenter, follow-up cohort study in which HRQoL and functional outcomes were assessed during 12-month follow-up of injured adult patients admitted to 1 of 10 hospitals in the county of Noord-Brabant, the Netherlands. The data were collected by self-reported questionnaires at 1 week (including preinjury assessment) and 1, 3, 6 and 12 months after injury. The EuroQoL-5D (EQ-5D), visual analog scale (VAS), Merle d'Aubigné Hip Score (MAHS) and Majeed Pelvic Score (MPS) were used. Multivariable mixed models were used to examine the course of the HRQoL and the prognostic factors for decreased HRQoL and functional outcomes over time. RESULTS: A total of 184 patients with pelvic fractures were identified between September 2015-September 2016; the fractures included 71 Tile A, 44 Tile B and 10 Tile C fractures and 59 acetabular fractures. At the pre-injury, 1 week, and 1, 3, 6 and 12 months after injury time points, the mean EQ-5D Index values were 0.90, 0.26, 0.45, 0.66, 0.77 and 0.80, respectively, and the mean EQ-VAS values were 83, 45, 57, 69, 75 and 75, respectively. At 6 and 12 months after injury, 22 and 25% of the MPS < 65 year group, 38 and 47% of the MPS ≥ 65 year group and 34 and 51% of the MAHS group, respectively, reached the maximum score. Pre-injury score, female gender and high Injury Severity Score (ISS) were important prognostic factors for a decreased HRQoL, and the EQ-5D VAS ß = 0.43 (95% CI: 0.31 - 0.57), -6.66 (95% CI: -10.90 - -0.43) and -7.09 (95% CI: -6.11 - -5.67), respectively. DISCUSSION: Patients with pelvic fractures experience a reduction in their HRQoL. Most patients do not achieve the HRQoL of their pre-injury state within 1 year after trauma. Prognostic factors for decreased HRQoL are a low pre-injury score, high ISS and female gender. We do not recommend using the MAHS and MPS in mid- or long-term follow-up of pelvic fractures because of ceiling effects. Trial registration number NCT02508675.

The prevalence and prognostic factors of psychological distress in older patients with a hip fracture: A longitudinal cohort study.

INTRODUCTION: A hip fracture can be experienced as a traumatic event that can induce psychological distress. The aim of this study is to give more insight into the prevalence of symptoms of psychological distress in older patients following the first year after a hip fracture. In addition, prognostic factors were determined for psychological distress after hip fracture. MATERIALS AND METHODS: This hip fracture cohort data was derived from the Brabant Injury Outcome Surveillance, a multicenter longitudinal prospective cohort study. Hip fracture patients (≥65years) admitted to a hospital between August 2015 and November 2016 were asked to complete a questionnaire at 1 week, and 1, 3, 6 and 12 months. The Hospital Anxiety and Depression Scale (HADS) was used to assess symptoms of anxiety and depression and the Impact of Event Scale (IES) was used to assess symptoms of posttraumatic stress (PTS). Prognostic factors were assessed with multivariable logistic mixed models. RESULTS: In total 570 patients (inclusion rate: 69.7%) were included. The prevalence of psychological distress ranged from 36% at 1 week to 31% at 1 year after hip fracture. Frailty at onset of hip fracture was the most important prognostic factor of symptoms of depression (Odds ratio (OR), 2.74; 95% Confidence interval (CI) 1.41 to 5.34) and anxiety (OR, 2.60; 95% CI 1.15 to 5.85) on average in the year following hip fracture. Frailty was not a prognostic factor of symptoms of PTS (OR, 1.97; 95% CI 0.42 to 9.23). CONCLUSIONS: The prevalence of psychological distress is high in the first year after a hip fracture. Frailty at onset of a hip fracture is the most important prognostic factor of symptoms of depression and anxiety. These findings have important implications for strategies with early identification of frail patients with a hip fracture at high risk of psychological distress.

Medical and productivity costs after trauma.

BACKGROUND: Well-advised priority setting in prevention and treatment of injuries relies on detailed insight into costs of injury. This study aimed to provide a detailed overview of medical and productivity costs due to injury up to two years post-injury and compare these costs across subgroups for injury severity and age. METHODS: A prospective longitudinal cohort study followed all adult (≥18 years) injury patients admitted to a hospital in Noord-Brabant, the Netherlands. Patients filled out questionnaires 1 week, 1, 3, 6, 12 and 24 months after trauma, including items on health care consumption from the medical consumption questionnaire (iMCQ) and productivity loss from the productivity cost questionnaire (PCQ). Furthermore, injury severity was defined by Injury Severity Score (ISS). Data on diagnostics was retrieved from hospital registries. We calculated medical costs, consisting of in-hospital costs and post-hospital medical costs, and productivity costs due to injury up to two years post-injury. RESULTS: Approximately 50% (N = 4883) of registered patients provided informed consent, and 3785 filled out at least one questionnaire. In total, the average costs per patient were €12,190. In-hospital costs, post-hospital medical costs and productivity costs contributed €4810, €5110 and €5830, respectively. Total costs per patient increased with injury severity, from €7030 in ISS1-3 to €23,750 in ISS16+ and were lowest for age category 18-24y (€7980), highest for age category 85 years and over (€15,580), and fluctuated over age groups in between. CONCLUSION: Both medical costs and productivity costs generally increased with injury severity. Furthermore, productivity costs were found to be a large component of total costs of injury in ISS1-8 and are therefore a potentially interesting area with regard to reducing costs.

Validation and reliability of the Abbreviated World Health Organization Quality of Life Instrument (WHOQOL-BREF) in the hospitalized trauma population.

INTRODUCTION: While the number of trauma patients surviving their injury increase, it is important to measure Quality of Life (QoL). The Abbreviated World Health Organization Quality of Life (WHOQOL-BREF) questionnaire can be used to assess QoL. However, its psychometric properties in trauma patients are unknown and therefore, we aimed to investigate the validity and reliability of the WHOQOL-BREF for the hospitalized trauma population. METHODS: Data were derived from the Brabant Injury Outcome Surveillance. Floor and ceiling effects and missing values of the WHOQOL-BREF were examined. Confirmatory factor analysis (CFA) was performed to examine the underlying 4 dimensions (i.e. physical, psychological, social and environmental) of the questionnaire. Cronbach's alpha (CA) was calculated to determine internal consistency. In total, 42 hypotheses were formulated to determine construct validity and 6 hypotheses were created to determine discriminant validity. To determine construct validity, Spearman's correlations were calculated between the WHOQOL-BREF and the EuroQol-five-dimension-3-level questionnaire, the Health Utility Index Mark 2 and 3, the Hospital Anxiety and Depression Scale and the Impact of Event Scale. Discriminant validity between patients with minor injuries (i.e. Injury Severity Score (ISS)≤8) and moderate/severe injuries (i.e. ISS ≥ 9) was examined by conducting Mann-Whitney-U-tests. RESULTS: In total, 202 patients (median 63y) participated in this study with a median of 32 days (interquartile range 29-37) post-trauma. The WHOQOL-BREF showed no problematic floor and ceiling effects. The CFA revealed a moderate model fit. The domains showed good internal consistency, with the exception of the social domain. All individual items and domain scores of the WHOQOL-BREF showed nearly symmetrical distributions since mean scores were close to median scores, except of the 'general health' item. The highest percentage of missing values was found on the 'sexual activity' item (i.e. 19.3%). The WHOQOL-BREF showed moderate construct and discriminant validity since in both cases, 67% of the hypotheses were confirmed. CONCLUSION: The present study provides support for using the WHOQOL-BREF for the hospitalized trauma population since the questionnaire appears to be valid and reliable. The WHOQOL-BREF can be used to assess QoL in a heterogeneous group of hospitalized trauma patients accurately. TRAIL REGISTRATION: ClinicalTrials.gov identifier: NCT02508675.

The effect of socio-economic status on non-fatal outcome after injury: A systematic review.

BACKGROUND: Over the past decades, the number of survivors of injuries has rapidly grown. It has become important to focus more on the determinants of non-fatal outcome. Although socio-economic status (SES) is considered to be a fundamental determinant of health in general, the role of SES as a determinant of non-fatal outcome after injury is largely unknown. METHODS: An online search was conducted in November 2015 using Embase, Medline, Web of Science, Cinahl, Cochrane, Google scholar and PubMed. Studies examining the relation between SES and a physical or psychological outcome measure, or using SES as a confounder in a general trauma population were included. There were no restrictions regarding study design. The 'Quality in Prognostic Studies tool' was used to assess the methodological quality of the included studies. RESULTS: The 24 included studies showed large variations in methodological quality. The number of participants ranged from 56 to 4639, and assessments of the measures ranged from immediately to 6year post-injury. Studies used a large number of variables as indicators of SES. Participant's educational level was used most frequently. The majority of the studies used a multivariable technique to analyse the relation between SES and non-fatal outcome after injury. All studies found a positive association (80% of studies significant, n=19) between increased SES and better non-fatal outcome after injury. CONCLUSION: Although an adequate and valid measure of SES is lacking, the results of this review showed that SES is an important determinant of non-fatal outcome after injury. Future research should focus on the definition and measurement of SES and should further underpin the effect of SES on non-fatal outcome after injury.