Health status after periprosthetic proximal femoral fractures.

Aims: Periprosthetic proximal femoral fractures (PFFs) are a major complication after total hip arthroplasty (THA). Health status after PFF is not specifically investigated. The aim of this study is to evaluate the health status pattern over two years after sustaining a PFF. Methods: A cohort of patients with PFF after THA was derived from the Brabant Injury Outcomes Surveillance (BIOS) study. The BIOS study, a prospective, observational, multicentre follow-up cohort study, was conducted to obtain data by questionnaires pre-injury and at one week, and one, three, six, 12, and 24 months after trauma. Primary outcome measures were the EuroQol five-dimension three-level questionnaire (EQ-5D-3L), the Health Utility Index 2 (HUI2), and the Health Utility Index 3 (HUI3). Secondary outcome measures were general measurements such as duration of hospital stay and mortality. Results: A total of 70 patients with a PFF were included. EQ-5D utility scores were significantly lower on all timepoints except at six months' follow-up compared to pre-injury. EuroQol visual analogue scale (EQ-VAS) scores at one month's follow-up were significantly lower compared to pre-injury. The percentage of reported problems at two years was higher for all dimensions except anxiety/depression when compared to pre-injury. The mean EQ-5D utility score was 0.26 higher in males compared to females (95% confidence interval (CI) 0.01 to 0.42; p = 0.003). The mean EQ-VAS score for males was 8.9 points higher when compared to females over all timepoints (95% CI 1.2 to 16.7; p = 0.027). Mortality was 10% after two years' follow-up. Conclusion: PFF patients are a frail population with substantial functional impairment at baseline. Post-injury, they have a significant and clinically relevant lower health status two years after trauma when compared to pre-injury. Health status improves the most between one and three months after injury. Two years after PFF, more patients experience problems in mobility, self-care, usual activities, and pain/discomfort than pre-injury.

Using PROM(I)S to measure health-related quality of life in patients with a bone fracture: An observational cohort study.

INTRODUCTION: The incidence of patients with fractures is increasing and so is the impact on health care systems and society. To improve patient care, measurement of disabilities and impaired health experiences after traumatic musculoskeletal injuries are important. Next to objective clinical parameters, PROM(I)S can be used to map health domains important to patients. We aimed to objectify different aspects of (health-related) quality of life in fracture patients, including the ability to participate in social roles and activities using PROMIS among other PROMs. METHODS: An observational cohort study was performed in which health-related quality of life in fracture patients was measured. Patients aged 18 year and older either treated conservatively or surgically between November 2020 and June 2022 were included. Participants were followed for a maximum of one year and completed the following PROMs: PROMIS-CAT physical function, PROMIS-CAT pain interference, PROMIS-CAT ability to participate in social roles and activities and LEFS or QDASH. We applied a univariate linear mixed model to evaluate significance of improvement. RESULTS: Seven hundred-forty six patients with a mean age of 54.4 years were included. Mean PROMIS scores were structurally inferior in the lower extremity (LE) fracture group in comparison with the upper extremity (UE) fracture group. For "PROMIS physical function", UE fracture patients performed better and showed physical progression earlier. For "PROMIS pain interference", UE fracture patients experienced fewer limitations, but it took longer to experience improvement in this group. For "PROMIS ability to participate in social roles", significant improvement was only seen in the UE fracture group at one year follow up. CONCLUSION: Upper -and lower extremity fractures can have a significant impact on physical function and social health. Patients with UE fractures tend to have fewer limitations compared to LE fracture patients. Physical function and pain interference is most impaired shortly after the injury in all fracture patients and show significant changes over time, social health improves less over time. Moment of measurement should be based on type of fracture and can differ between individual patients, but when generic measures and outcomes are desirable, PROMIS questionnaires can potentially be used measurement.

Recovery to normal vital functions and acid-base status after a severe trauma in Level I versus Level II Trauma Centres.

PURPOSE: In the Netherlands, approximately 70% of severely injured patients (ISS ≥ 16) are transported directly to a Level I trauma center. This study compared the time needed to return to normal vital parameters and normal acid-base status in severely injured patients and some in-hospital processes in Level I versus Level II trauma centers. METHODS: This retrospective cohort study included all adult severely injured patients or adult trauma patients admitted to the intensive care unit between 2015 and 2020 in a Dutch trauma region. The primary endpoint was time until normal vital parameters and acid-base status. Secondary endpoints were complication rate, hospital length of stay, emergency department length of stay, and time until a computed tomography (CT) scan. RESULTS: A total of 2345 patients were included. Patients admitted to a Level I trauma center had a significantly higher rate of normalization of vital parameters over time (HR 1.51). There was no significant difference in normalization rate of the acid-base status over time (HR 1.10). In Level I trauma centers, time spent at the emergency department and time until the CT scan was significantly shorter (respectively, ß - 38 min and ß - 77 min), and the complication rate was significantly lower (OR 0.35). CONCLUSION: Severely injured patients admitted to a Level I trauma center require less time to normalize their vital functions. Level I centers are better equipped, resulting in better in-hospital processes with shorter time at the emergency department and shorter time until a CT scan.

From numbers to meaningful change: Minimal important change by using PROMIS in a cohort of fracture patients.

INTRODUCTION: use of the Patient-Reported Outcomes measurement Information System (PROMIS®) is slowly increasing in patients with a fracture. Yet, minimal important change of PROMIS in patients with fractures has been addressed in a very limited number of studies. As the minimal important change (MIC) is important to interpret PROMIS-scores, the goal is to estimate the MIC for PROMIS physical function (PF), PROMIS pain interference (PI) and PROMIS ability to participate in social roles and activities (APSRA) in patients with a fracture. Secondly, the smallest detectable change was determined. MATERIALS AND METHODS: A longitudinal cohort study on patients ≥ 18 years receiving surgical or non-surgical care for fractures was conducted. Patients completed PROMIS PF V1.1, PROMIS PI V1.1 and PROMIS APSRA V2.0. For follow-up, patients completed three additional anchor questions evaluating patient-reported improvement on a seven point rating scale. The predictive modeling method was used to estimate the MIC value of all three PROMIS questionnaires. RESULTS: Hundred patients with a mean age of 55.4 ± 12.6 years were included of which sixty (60%) were female. Seventy-two (72%) patients were recovering from a surgical procedure. PROMIS-CAT T-scores of all PROMIS measures showed significant correlations with their anchor questions. The predictive modeling method showed a MIC value of +2.4 (n = 98) for PROMIS PF, -2.9 (n = 96) for PROMIS PI and +3.2 (n = 91) for PROMIS APSRA. CONCLUSION: By using the anchor based predictive modeling method, PROMIS MIC-values for improvement of respectively +2.4 points on a T-score metric for PROMIS-PF, -2.9 for PROMIS-PI and +3.2 for PROMIS APSRA give the impression of being meaningful to patients. These values can be used in clinical practice for managing patient expectations; to inform on treatment results; and to assess if patients experience significant change. This in order to encourage patient centered care.

Comparing Patient-Reported Outcomes Measurement Information System Computer Adaptive Testing With Existing Measures After Operative Interventions for Extremity Fractures.

INTRODUCTION: Patient-Reported Outcomes Measurement Information System (PROMIS) enables the use of computer adaptive testing (CAT). The aim of this prospective cohort study was to compare the most commonly used disease-specific instruments with PROMIS CAT questionnaires in patients with trauma. METHODS: All patients with trauma (ages 18-75) who underwent an operative intervention for an extremity fracture between June 1, 2018, and June 30, 2019, were included. The disease-specific instruments were the Quick Disabilities of the Arm, Shoulder, and Hand for upper extremity fractures and the Lower Extremity Functional Scale (LEFS) for lower extremity fractures. Pearson's correlation (r) between the disease-specific instruments and the PROMIS CAT questionnaires (PROMIS Physical Function, PROMIS Pain Interference, and PROMIS Ability to Participate in Social Roles and Activities) was calculated at week 2, week 6, month 3, and month 6. Construct validity and responsiveness were calculated. RESULTS: A total of 151 patients with an upper extremity fracture and 109 patients with a lower extremity fracture were included. At month 3 and month 6, the correlation was strong between the LEFS and PROMIS Physical Function (r = 0.88 and r = 0.90, respectively), and at month 3, the correlation was strong between the LEFS and PROMIS Social Roles and Activities (r = 0.72). At week 6, month 3, and month 6, there was a strong correlation between the Quick Disabilities of the Arm, Shoulder, and Hand and PROMIS Physical Function (r = 0.74, r = 0.70, and r = 0.76, respectively). CONCLUSIONS: The PROMIS CAT measures are acceptably related to existing non-CAT instruments and may be a useful tool during follow-up after operative interventions for extremity fractures.

Clustering of trauma patients based on longitudinal data and the application of machine learning to predict recovery.

Predicting recovery after trauma is important to provide patients a perspective on their estimated future health, to engage in shared decision making and target interventions to relevant patient groups. In the present study, several unsupervised techniques are employed to cluster patients based on longitudinal recovery profiles. Subsequently, these data-driven clusters were assessed on clinical validity by experts and used as targets in supervised machine learning models. We present a formalised analysis of the obtained clusters that incorporates evaluation of (i) statistical and machine learning metrics, (ii) clusters clinical validity with descriptive statistics and medical expertise. Clusters quality assessment revealed that clusters obtained through a Bayesian method (High Dimensional Supervised Classification and Clustering) and a Deep Gaussian Mixture model, in combination with oversampling and a Random Forest for supervised learning of the cluster assignments provided among the most clinically sensible partitioning of patients. Other methods that obtained higher classification accuracy suffered from cluster solutions with large majority classes or clinically less sensible classes. Models that used just physical or a mix of physical and psychological outcomes proved to be among the most sensible, suggesting that clustering on psychological outcomes alone yields recovery profiles that do not conform to known risk factors.

Trajectories and prognostic factors for recovery after hip fracture: a longitudinal cohort study.

PURPOSE: The aim of this study was to determine recovery trajectories and prognostic factors for poor recovery in frail and non-frail patients after hip fracture. METHODS: Patients with a hip fracture aged 65 years and older admitted to a hospital in the Netherlands from August 2015 to November 2016 were asked to complete questionnaires at one week and one, three, six, 12, and 24 months after injury. The questionnaires included the ICEpop CAPability measure for older people, Health Utility Index, and the Hospital Anxiety Depression Scale. Latent class trajectory analysis was used to determine trajectories of recovery. Patient and injury characteristics for favourable and unfavourable outcome were compared with logistic regression. RESULTS: In total, 696 patients were included of which 367 (53%) patients were frail. Overall, recovery trajectories in frail patients were worse compared to trajectories in non-frail patients. In frail patients, poor recovery was significantly associated with dementia. Lower age was a prognostic factor for good recovery. Immobility, loneliness and weight loss were prognostic for respectively poor capability and symptoms of anxiety and depression. In non-frail patients, recovery after hip fracture was associated with loneliness and the type of hip fracture. CONCLUSION: Although frailty is associated with poor recovery in older patients with hip fracture, a large proportion of frail patients show good recovery. Loneliness determines poor recovery with anxiety and depressive symptoms. TRAIL REGISTRATION: ClinicalTrials.gov identifier: NCT02508675 (July 27, 2015).

Developing mHealth to the Context and Valuation of Injured Patients and Professionals in Hospital Trauma Care: Qualitative and Quantitative Formative Evaluations.

BACKGROUND: Trauma care faces challenges to innovating their services, such as with mobile health (mHealth) app, to improve the quality of care and patients' health experience. Systematic needs inquiries and collaborations with professional and patient end users are highly recommended to develop and prepare future implementations of such innovations. OBJECTIVE: This study aimed to develop a trauma mHealth app for patient information and support in accordance with the Center for eHealth Research and Disease Management road map and describe experiences of unmet information and support needs among injured patients with trauma, barriers to and facilitators of the provision of information and support among trauma care professionals, and drivers of value of an mHealth app in patients with trauma and trauma care professionals. METHODS: Formative evaluations were conducted using quantitative and qualitative methods. Ten semistructured interviews with patients with trauma and a focus group with 4 trauma care professionals were conducted for contextual inquiry and value specification. User requirements and value drivers were applied in prototyping. Furthermore, a complementary quantitative discrete choice experiment (DCE) was conducted with 109 Dutch trauma surgeons, which enabled triangulation on value specification results. In the DCE, preferences were stated for hypothetical mHealth products with various attributes. Panel data from the DCE were analyzed using conditional and mixed logit models. RESULTS: Patients disclosed a need for more psychosocial support and easy access to more extensive information on their injury, its consequences, and future prospects. Health care professionals designated workload as an essential issue; a digital solution should not require additional time. The conditional logit model of DCE results suggested that access to patient app data through electronic medical record integration (odds ratio [OR] 3.3, 95% CI 2.55-4.34; P<.001) or a web viewer (OR 2.3, 95% CI 1.64-3.31; P<.001) was considered the most important for an mHealth solution by surgeons, followed by the inclusion of periodic self-measurements (OR 2, 95% CI 1.64-2.46; P<.001), the local adjustment of patient information (OR 1.8, 95% CI 1.42-2.33; P<.001), local hospital identification (OR 1.7, 95% CI 1.31-2.10; P<.001), complication detection (OR 1.5, 95% CI 1.21-1.84; P<.001), and the personalization of rehabilitation through artificial intelligence (OR 1.4, 95% CI 1.13-1.62; P=.001). CONCLUSIONS: In the context of trauma care, end users have many requirements for an mHealth solution that addresses psychosocial functioning; dependable information; and, possibly, a prediction of how a patient's recovery trajectory is evolving. A structured development approach provided insights into value drivers and facilitated mHealth prototype enhancement. The findings imply that iterative development should move on from simple and easily implementable mHealth solutions to those that are suitable for broader innovations of care pathways that most-but plausibly not yet all-end users in trauma care will value. This study could inspire the trauma care community.

Experiences of recovery and posthospital care needs of working-age adults after physical trauma: a qualitative focus group study.

OBJECTIVE: To explore experiences of recovery after physical trauma and identify long-term needs for posthospital care. DESIGN, PARTICIPANTS AND SETTING: A qualitative study was conducted consisting of seven online focus groups among working-age adults who sustained their injury between 9 months and 5 years ago. Trauma patients discharged from a level 1 trauma centre in the Netherlands were divided into three groups based on the type of their physical trauma (monotrauma, polytrauma and traumatic brain injury). Group interviews were transcribed verbatim, and thematic analysis was conducted. RESULTS: Despite differences in type and severity of their injuries, participants all struggled with the impact that trauma had on various aspects of their lives. They experienced recovery as an unpredictable and inconstant process aimed at resuming a meaningful life. Work was often perceived as an important part of recovery, though the value attributed to work could change over time. Participants struggled to bring the difficulties they encountered in their daily lives and at work to the attention of healthcare professionals (HCPs). While posthospital care needs varied between and across groups, all people stressed the need for flexible access to person-centred, multidisciplinary care and support after hospital discharge. CONCLUSIONS: This study reveals that people with a broad variety of injury experience recovery as a process towards resuming a meaningful life and report the need to expand trauma care to include comprehensive support to live well long term. Person-centred care might be helpful to enable HCPs to take people's individual long-term needs and life situations into account. Furthermore, providing timely access to coordinated, multidisciplinary care after discharge is advocated. Integrated care models that span a network of multidisciplinary support around the person may help align existing services and may facilitate easy and timely access to the most suitable support for injured people and their loved ones.

Severe isolated injuries have a high impact on resource use and mortality: a Dutch nationwide observational study.

PURPOSE: The Berlin poly-trauma definition (BPD) has proven to be a valuable way of identifying patients with at least a 20% risk of mortality, by combining anatomical injury characteristics with the presence of physiological risk factors (PRFs). Severe isolated injuries (SII) are excluded from the BPD. This study describes the characteristics, resource use and outcomes of patients with SII according to their injured body region, and compares them with those included in the BPD. METHODS: Data were extracted from the Dutch National Trauma Registry between 2015 and 2019. SII patients were defined as those with an injury with an Abbreviated Injury Scale (AIS) score ≥ 4 in one body region, with at most minor additional injuries (AIS ≤ 2). We performed an SII subgroup analysis per AIS region of injury. Multivariable linear and logistic regression models were used to calculate odds ratios (ORs) for SII subgroup patient outcomes, and resource needs. RESULTS: A total of 10.344 SII patients were included; 47.8% were ICU admitted, and the overall mortality was 19.5%. The adjusted risk of death was highest for external (2.5, CI 1.9-3.2) and for head SII (2.0, CI 1.7-2.2). Patients with SII to the abdomen (2.3, CI 1.9-2.8) and thorax (1.8, CI 1.6-2.0) had a significantly higher risk of ICU admission. The highest adjusted risk of disability was recorded for spine injuries (10.3, CI 8.3-12.8). The presence of ≥ 1 PRFs was associated with higher mortality rates compared to their poly-trauma counterparts, displaying rates of at least 15% for thoracic, 17% for spine, 22% for head and 49% for external SII. CONCLUSION: A severe isolated injury is a high-risk entity and should be recognized and treated as such. The addition of PRFs to the isolated anatomical injury criteria contributes to the identification of patients with SII at risk of worse outcomes.

There are more things in physical function and pain: a systematic review on physical, mental and social health within the orthopedic fracture population using PROMIS.

BACKGROUND: The Patient-Reported Outcomes Information System (PROMIS®) is more and more extensively being used in medical literature in patients with an orthopedic fracture. Yet, many articles studied heterogeneous groups with chronic orthopedic disorders in which fracture patients were included as well. At this moment, there is no systematic overview of the exact use of PROMIS measures in the orthopedic fracture population. Therefore this review aimed to provide an overview of the PROMIS health domains physical health, mental health and social health in patients suffering an orthopedic fracture. METHODS: This systematic review was documented according to the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) guidelines. We searched Embase, Medline, Web of Science Core Collection, and Cochrane Central Register of controlled Trials, CINAHL and Google Scholar in December 2020 using a combination of MeSH terms and specific index terms related to orthopedic fractures and PROMIS questionnaires. Inclusion criteria were available full text articles that were describing the use of any PROMIS questionnaires in both the adult and pediatric extremity fracture population. RESULTS: We included 51 relevant articles of which most were observational studies (n = 47, 92.2%). A single fracture population was included in 47 studies of which 9 involved ankle fractures (9/51; 17.6%), followed by humeral fractures (8/51; 15.7%), tibia fractures (6/51; 11.8%) and radial -or ulnar fractures (5/51; 9.8%). PROMIS Physical Function (n = 32, 32/51 = 62.7%) and PROMIS Pain Interference (n = 21, 21/51 = 41.2%) were most frequently used questionnaires. PROMIS measures concerning social (n = 5/51 = 9.8%) and mental health (10/51 = 19.6%) were much less often used as outcome measures in the fracture population. A gradually increasing use of PROMIS questionnaires in the orthopedic fracture population was seen since 2017. CONCLUSION: Many different PROMIS measures on multiple domains are available and used in previous articles with orthopedic fracture patients. With physical function and pain interference as most popular PROMIS measures, it is important to emphasize that other health-domains such as mental and social health can also be essential to fracture patients.

Impact of the SARS-CoV-2 pandemic on trauma care: a nationwide observational study.

PURPOSE: The SARS-CoV-2 pandemic severely disrupted society and the health care system. In addition to epidemiological changes, little is known about the pandemic's effects on the trauma care chain. Therefore, in addition to epidemiology and aetiology, this study aims to describe the impact of the SARS-CoV-2 pandemic on prehospital times, resource use and outcome. METHODS: A multicentre observational cohort study based on the Dutch Nationwide Trauma Registry was performed. Characteristics, resource usage, and outcomes of trauma patients treated at all trauma-receiving hospitals during the first (W1, March 12 through May 11) and second waves (W2, May 12 through September 23), as well as the interbellum period in between (INT, September 23 through December 31), were compared with those treated from the same periods in 2018 and 2019. RESULTS: The trauma caseload was reduced by 20% during the W1 period and 11% during the W2 period. The median length of stay was significantly shortened for hip fracture and major trauma patients (ISS ≥ 16). A 33% and 66% increase in the prevalence of minor self-harm-related injuries was recorded during the W1 and W2 periods, respectively, and a 36% increase in violence-related injuries was recorded during the INT. Mortality was significantly higher in the W1 (2.9% vs. 2.2%) and W2 (3.2% vs. 2.7%) periods. CONCLUSION: The imposed restrictions in response to the SARS-CoV-2 pandemic led to diminished numbers of acute trauma admissions in the Netherlands. The long-lasting pressing demand for resources, including ICU services, has negatively affected trauma care. Further caution is warranted regarding the increased incidence of injuries related to violence and self-harm.

Modification of the TRISS: simple and practical mortality prediction after trauma in an all-inclusive registry.

PURPOSE: Numerous studies have modified the Trauma Injury and Severity Score (TRISS) to improve its predictive accuracy for specific trauma populations. The aim of this study was to develop and validate a simple and practical prediction model that accurately predicts mortality for all acute trauma admissions. METHODS: This retrospective study used Dutch National Trauma Registry data recorded between 2015 and 2018. New models were developed based on nonlinear transformations of TRISS variables (age, systolic blood pressure (SBP), Glasgow Coma Score (GCS) and Injury Severity Score (ISS)), the New Injury Severity Score (NISS), the sex-age interaction, the best motor response (BMR) and the American Society of Anesthesiologists (ASA) physical status classification. The models were validated in 2018 data and for specific patient subgroups. The models' performance was assessed based on discrimination (areas under the curve (AUCs)) and by calibration plots. Multiple imputation was applied to account for missing values. RESULTS: The mortality rates in the development and validation datasets were 2.3% (5709/245363) and 2.5% (1959/77343), respectively. A model with sex, ASA class, and nonlinear transformations of age, SBP, the ISS and the BMR showed significantly better discrimination than the TRISS (AUC 0.915 vs. 0.861). This model was well calibrated and demonstrated good discrimination in different subsets of patients, including isolated hip fractures patients (AUC: 0.796), elderly (AUC: 0.835), less severely injured (ISS16) (AUC: 878), severely injured (ISS ≥ 16) (AUC: 0.889), traumatic brain injury (AUC: 0.910). Moreover, discrimination for patients admitted to the intensive care (AUC: s0.846), and for both non-major and major trauma center patients was excellent, with AUCs of 0.940 and 0.895, respectively. CONCLUSION: This study presents a simple and practical mortality prediction model that performed well for important subgroups of patients as well as for the heterogeneous population of all acute trauma admissions in the Netherlands. Because this model includes widely available predictors, it can also be used for international evaluations of trauma care within institutions and trauma systems.

The Detrimental Impact of the COVID-19 Pandemic on Major Trauma Outcomes in the Netherlands: A Comprehensive Nationwide Study.

OBJECTIVE: To evaluate the impact of the COVID-19 pandemic on the outcome of major trauma patients in the Netherlands. SUMMARY BACKGROUND DATA: Major trauma patients highly rely on immediate access to specialized services, including ICUs, shortages caused by the impact of the COVID-19 pandemic may influence their outcome. METHODS: A multi-center observational cohort study, based on the Dutch National Trauma Registry was performed. Characteristics, resource usage, and outcome of major trauma patients (injury severity score ≥16) treated at all trauma-receiving hospitals during the first COVID-19 peak (March 23 through May 10) were compared with those treated from the same period in 2018 and 2019 (reference period). RESULTS: During the peak period, 520 major trauma patients were admitted, versus 570 on average in the pre-COVID-19 years. Significantly fewer patients were admitted to ICU facilities during the peak than during the reference period (49.6% vs 55.8%; P=0.016). Patients with less severe traumatic brain injuries in particular were less often admitted to the ICU during the peak (40.5% vs 52.5%; P=0.005). Moreover, this subgroup showed an increased mortality compared to the reference period (13.5% vs 7.7%; P=0.044). These results were confirmed using multivariable logistic regression analyses. In addition, a significant increase in observed versus predicted mortality was recorded for patients who had a priori predicted mortality of 50% to 75% (P=0.012). CONCLUSIONS: The COVID-19 peak had an adverse effect on trauma care as major trauma patients were less often admitted to ICU and specifically those with minor through moderate brain injury had higher mortality rates.

Long-term medical and productivity costs of severe trauma: Results from a prospective cohort study.

BACKGROUND: Through improvements in trauma care there has been a decline in injury mortality, as more people survive severe trauma. Patients who survive severe trauma are at risk of long-term disabilities which may place a high economic burden on society. The purpose of this study was to estimate the health care and productivity costs of severe trauma patients up to 24 months after sustaining the injury. Furthermore, we investigated the impact of injury severity level on health care utilization and costs and determined predictors for health care and productivity costs. METHODS: This prospective cohort study included adult trauma patients with severe injury (ISS≥16). Data on in-hospital health care use, 24-month post-hospital health care use and productivity loss were obtained from hospital registry data and collected with the iMTA Medical Consumption and Productivity Cost Questionnaire. The questionnaires were completed 1 week and 1, 3, 6, 12 and 24 months after injury. Log-linked gamma generalized linear models were used to investigate the drivers of health care and productivity costs. RESULTS: In total, 174 severe injury patients were included in this study. The median age of participants was 55 years and the majority were male (66.1%). The mean hospital stay was 14.2 (SD = 13.5) days. Patients with paid employment returned to work 21 weeks after injury. In total, the mean costs per patient were €24,760 with in-hospital costs of €11,930, post-hospital costs of €7,770 and productivity costs of €8,800. Having an ISS ≥25 and lower health status were predictors of high health care costs and male sex was associated with higher productivity costs. CONCLUSIONS: Both health care and productivity costs increased with injury severity, although large differences were observed between patients. It is important for decision-makers to consider not only in-hospital health care utilization but also the long-term consequences and associated costs related to rehabilitation and productivity loss.

Evaluation of the Berlin polytrauma definition: A Dutch nationwide observational study.

BACKGROUND: The Berlin polytrauma definition (BPD) was established to identify multiple injury patients with a high risk of mortality. The definition includes injuries with an Abbreviated Injury Scale score of ≥3 in ≥2 body regions (2AIS ≥3) combined with the presence of ≥1 physiological risk factors (PRFs). The PRFs are based on age, Glasgow Coma Scale, hypotension, acidosis, and coagulopathy at specific cutoff values. This study evaluates and compares the BPD with two other multiple injury definitions used to identify patients with high resource utilization and mortality risk, using data from the Dutch National Trauma Register (DNTR). METHODS: The evaluation was performed based on 2015 to 2018 DNTR data. First, patient characteristics for 2AIS ≥3, Injury Severity Score (ISS) of ≥16, and BPD patients were compared. Second, the PRFs prevalence and odds ratios of mortality for 2AIS ≥3 patients were compared with those from the Deutsche Gesellschaft für Unfallchirurgie Trauma Register. Subsequently, the association between PRF and mortality was assessed for 2AIS ≥3-DNTR patients and compared with those with an ISS of ≥16. RESULTS: The DNTR recorded 300,649 acute trauma admissions. A total of 15,711 patients sustained an ISS of ≥16, and 6,263 patients had suffered a 2AIS ≥3 injury. All individual PRFs were associated with a mortality of >30% in 2AIS ≥3-DNTR patients. The increase in PRFs was associated with a significant increase in mortality for both 2AIS ≥3 and ISS ≥16 patients. A total of 4,264 patients met the BPDs criteria. Overall mortality (27.2%), intensive care unit admission (71.2%), and length of stay were the highest for the BPD group. CONCLUSION: This study confirms that the BPD identifies high-risk patients in a population-based registry. The addition of PRFs to the anatomical injury scores improves the identification of severely injured patients with a high risk of mortality. Compared with the ISS ≥16 and 2AIS ≥3 multiple injury definitions, the BPD showed to improve the accuracy of capturing patients with a high medical resource need and mortality rate. LEVEL OF EVIDENCE: Epidemiological study, level III.

Prognostic factors for recovery of health status after injury: a prospective multicentre cohort study.

OBJECTIVES: To determine prognostic factors for health status and recovery patterns during the first 2 years after injury in the clinical trauma population. DESIGN: A prospective longitudinal cohort study. SETTING: Ten participating hospitals in Brabant, the Netherlands. PARTICIPANTS: Injured adult patients admitted to a hospital between August 2015 and November 2016 were followed: 4883 (50%) patients participated. MAIN OUTCOME MEASURES: Primary outcome was health status, measured with the EuroQol-5-dimensions-3-levels (EQ-5D), including a cognition item and the EuroQol Visual Analogue Scale. Health status was collected at 1 week, 1, 3, 6, 12 and 24 months after injury. Potential prognostic factors were based on literature and clinical experience (eg, age, sex, pre-injury frailty (Groningen Frailty Index), pre-injury EQ-5D). RESULTS: Health status increased mainly during the first 6 months after injury with a mean EQ-5D utility score at 1 week of 0.49 and 0.79 at 24 months. The dimensions mobility, pain/discomfort and usual activities improved up to 2 years after injury. Lower pre-injury health status, frailty and longer length of stay at the hospital were important prognostic factors for poor recovery. Spine injury, lower and upper extremity injury showed to be prognostic factors for problems after injury. Traumatic brain injury was a prognostic factor for cognitive problems. CONCLUSION: This study contributes to the increase in knowledge of health recovery after injury. It could be a starting point to develop prediction models for specific injury classifications and implementation of personalised medicine. TRIAL REGISTRATION NUMBER: NCT02508675.

Relationship between health status and functional outcome during two years after a severe trauma.

BACKGROUND: With the improved survival rates after trauma, the population of patients with disabilities increased. The knowledge about functional outcome and the relationship between health status and functional outcome is limited. The aim of the present prospective cohort study was to describe the functional outcome and health status over time, and the relationship between both. METHODS: Adult severely injured patients (ISS≥16) were included if hospitalised in Noord-Brabant within 48 h after injury between August 2015 and December 2016. The functional outcome (Glasgow Outcome Scale Extended - GOSE) and health status (EQ-5D) were measured at 1, 3, 6, 12 and 24 months after injury. Logistic and linear mixed models were used to examine functional outcome and health status over time. Measurements were divided into short- (1-3 months), mid- (6-12 months) and long-term (24 months). RESULTS: In total 239 severely injured patients were included. Functional outcome and health status improved over time. Prognostic factors during two years were a longer hospital length of stay, female gender and Glasgow Coma Scale. Besides age was a prognostic factor for health status and education level for functional outcome. A higher ASA classification was a long-term prognostic factor for a lower functional outcome and a lower health status. The patients with a good functional recovery showed a significant higher EQ-5D utility score and patients with a poor functional recovery reported significant more problems in the EQ-5 domains. CONCLUSION: There is a good relationship between the functional outcome and the health status during two years after a severe injury. It appears reliable to use functional outcome in terms of physical impairments in daily clinic to determine patients at risk for both a lower functional outcome and a lower health status over time.

Health care costs of injury in the older population: a prospective multicentre cohort study in the Netherlands.

BACKGROUND: With the ageing population, the number of older trauma patients has increased. The aim of this study was to assess non-surgical health care costs of older trauma patients and to identify which characteristics of older trauma patients were associated with high health care costs. METHODS: Trauma patients aged ≥65 years who were admitted to a hospital in Noord-Brabant, the Netherlands, were included in the Brabant Injury Outcome Surveillance (BIOS) study. Non-surgical in-hospital and up to 24- months post-hospital health care use were obtained from hospital registration data and collected with the iMTA Medical Consumption Questionnaire which patients completed 1 week and 1, 3, 6, 12 and 24 months after injury. Log-linked gamma generalized linear models were used to identify cost-driving factors. RESULTS: A total of 1910 patients were included in the study. Mean total health care costs per patient were €12,190 ranging from €8390 for 65-69 year-olds to €15,550 for those older than 90 years. Main cost drivers were the post-hospital costs due to home care and stay at an institution. Falls (72%) and traffic injury (15%) contributed most to the total health care costs, although costs of cause of trauma varied with age and sex. In-hospital costs were especially high in patients with high injury severity, frailty and comorbidities. Age, female sex, injury severity, frailty, having comorbidities and having a hip fracture were independently associated with higher post-hospital health care costs. CONCLUSIONS: In-hospital health care costs were chiefly associated with high injury severity. Several patient and injury characteristics including age, high injury severity, frailty and comorbidity were associated with post-hospital health care costs. Both fall-related injuries and traffic-related injuries are important areas for prevention of injury in the older population.

Motivation and Weight Loss Expectations in Bariatric Surgery Candidates: Association with 1- and 2-Year Results After Bariatric Surgery.

PURPOSE: There are discrepancies between patients' expected weight loss and what is considered achievable after bariatric surgery. This study describes the association between patients' expectations and actual weight loss, 1 and 2 years postoperatively. MATERIALS AND METHODS: A prospective observational study was performed. The association between expectations and actual weight loss (% total weight loss) was explored using linear regression analyses, adjusting for baseline demographics, surgery types, and self-esteem (Rosenberg self-esteem scale) and repeated separately per gender. Gender differences in motivations were explored using Chi-square tests. RESULTS: Of 440 patients at baseline, results on 368 (84%) at 1 year and 341 (78%) patients at 2 years were available. Significant and opposite associations were found when analyzing genders separately. There was a significant negative association between expectations and %TWL in men at 1 year (ß - 0.23, p = 0.04) and 2 years postoperatively (ß - 0.26, p = 0.03), indicating smaller weight loss for greater expectations. In women, a significant positive association (ß 0.24, p < 0.01) was found 2 years postoperatively, indicating greater weight loss for greater expectations. Both genders were mainly motivated by health concerns, but women were also motivated by reduced self-confidence to lose weight. CONCLUSIONS: Higher expectations were negatively associated with weight loss in men, but positively in women. This may be due to men being motivated by physical complaints, which improve with lower weight-loss. Women are also driven by reduced self-confidence, which may influence weight loss maintenance behaviors. Higher weight loss goals should not be considered as a contra-indication for surgery, but may be utilized to achieve patients' goals.