20-year depressive symptoms, dementia, and structural neuropathology in older women.

INTRODUCTION: The course of depressive symptoms and dementia risk is unclear, as are potential structural neuropathological common causes. METHODS: Utilizing joint latent class mixture models, we identified longitudinal trajectories of annually assessed depressive symptoms and dementia risk over 21 years in 957 older women (baseline age 72.7 years old) from the Women's Health Initiative Memory Study. In a subsample of 569 women who underwent structural magnetic resonance imaging, we examined whether estimates of cerebrovascular disease and Alzheimer's disease (AD)-related neurodegeneration were associated with identified trajectories. RESULTS: Five trajectories of depressive symptoms and dementia risk were identified. Compared to women with minimal symptoms, women who reported mild and stable and emerging depressive symptoms were at the highest risk of developing dementia and had more cerebrovascular disease and AD-related neurodegeneration. DISCUSSION: There are heterogeneous profiles of depressive symptoms and dementia risk. Common neuropathological factors may contribute to both depression and dementia. Highlights The progression of depressive symptoms and concurrent dementia risk is heterogeneous. Emerging depressive symptoms may be a prodromal symptom of dementia. Cerebrovascular disease and AD are potentially shared neuropathological factors.

Associations of plasma proteomics and age-related outcomes with brain age in a diverse cohort.

Machine learning models are increasingly being used to estimate "brain age" from neuroimaging data. The gap between chronological age and the estimated brain age gap (BAG) is potentially a measure of accelerated and resilient brain aging. Brain age calculated in this fashion has been shown to be associated with mortality, measures of physical function, health, and disease. Here, we estimate the BAG using a voxel-based elastic net regression approach, and then, we investigate its associations with mortality, cognitive status, and measures of health and disease in participants from Atherosclerosis Risk in Communities (ARIC) study who had a brain MRI at visit 5 of the study. Finally, we used the SOMAscan assay containing 4877 proteins to examine the proteomic associations with the MRI-defined BAG. Among N = 1849 participants (age, 76.4 (SD 5.6)), we found that increased values of BAG were strongly associated with increased mortality and increased severity of the cognitive status. Strong associations with mortality persisted when the analyses were performed in cognitively normal participants. In addition, it was strongly associated with BMI, diabetes, measures of physical function, hypertension, prevalent heart disease, and stroke. Finally, we found 33 proteins associated with BAG after a correction for multiple comparisons. The top proteins with positive associations to brain age were growth/differentiation factor 15 (GDF-15), Sushi, von Willebrand factor type A, EGF, and pentraxin domain-containing protein 1 (SEVP 1), matrilysin (MMP7), ADAMTS-like protein 2 (ADAMTS), and heat shock 70 kDa protein 1B (HSPA1B) while EGF-receptor (EGFR), mast/stem-cell-growth-factor-receptor (KIT), coagulation-factor-VII, and cGMP-dependent-protein-kinase-1 (PRKG1) were negatively associated to brain age. Several of these proteins were previously associated with dementia in ARIC. These results suggest that circulating proteins implicated in biological aging, cellular senescence, angiogenesis, and coagulation are associated with a neuroimaging measure of brain aging.

Association of CT-Derived Skeletal Muscle and Adipose Tissue Metrics with Frailty in Older Adults.

RATIONALE AND OBJECTIVES: Tools are needed for frailty screening of older adults. Opportunistic analysis of body composition could play a role. We aim to determine whether computed tomography (CT)-derived measurements of muscle and adipose tissue are associated with frailty. MATERIALS AND METHODS: Outpatients aged ≥ 55 years consecutively imaged with contrast-enhanced abdominopelvic CT over a 3-month interval were included. Frailty was determined from the electronic health record using a previously validated electronic frailty index (eFI). CT images at the level of the L3 vertebra were automatically segmented to derive muscle metrics (skeletal muscle area [SMA], skeletal muscle density [SMD], intermuscular adipose tissue [IMAT]) and adipose tissue metrics (visceral adipose tissue [VAT], subcutaneous adipose tissue [SAT]). Distributions of demographic and CT-derived variables were compared between sexes. Sex-specific associations of muscle and adipose tissue metrics with eFI were characterized by linear regressions adjusted for age, race, ethnicity, duration between imaging and eFI measurements, and imaging parameters. RESULTS: The cohort comprised 886 patients (449 women, 437 men, mean age 67.9 years), of whom 382 (43%) met the criteria for pre-frailty (ie, 0.10 < eFI ≤ 0.21) and 138 (16%) for frailty (eFI > 0.21). In men, 1 standard deviation changes in SMD (ß = -0.01, 95% confidence interval [CI], -0.02 to -0.001, P = .02) and VAT area (ß = 0.008, 95% CI, 0.0005-0.02, P = .04), but not SMA, IMAT, or SAT, were associated with higher frailty. In women, none of the CT-derived muscle or adipose tissue metrics were associated with frailty. CONCLUSION: We observed a positive association between frailty and CT-derived biomarkers of myosteatosis and visceral adiposity in a sex-dependent manner.

Is an MRI-derived anatomical measure of dementia risk also a measure of brain aging?

Machine learning methods have been applied to estimate measures of brain aging from neuroimages. However, only rarely have these measures been examined in the context of biologic age. Here, we investigated associations of an MRI-based measure of dementia risk, the Alzheimer's disease pattern similarity (AD-PS) scores, with measures used to calculate biological age. Participants were those from visit 5 of the Atherosclerosis Risk in Communities Study with cognitive status adjudication, proteomic data, and AD-PS scores available. The AD-PS score estimation is based on previously reported machine learning methods. We evaluated associations of the AD-PS score with all-cause mortality. Sensitivity analyses using only cognitively normal (CN) individuals were performed treating CNS-related causes of death as competing risk. AD-PS score was examined in association with 32 proteins measured, using a Somalogic platform, previously reported to be associated with age. Finally, associations with a deficit accumulation index (DAI) based on a count of 38 health conditions were investigated. All analyses were adjusted for age, race, sex, education, smoking, hypertension, and diabetes. The AD-PS score was significantly associated with all-cause mortality and with levels of 9 of the 32 proteins. Growth/differentiation factor 15 (GDF-15) and pleiotrophin remained significant after accounting for multiple-testing and when restricting the analysis to CN participants. A linear regression model showed a significant association between DAI and AD-PS scores overall. While the AD-PS scores were created as a measure of dementia risk, our analyses suggest that they could also be capturing brain aging.

Age-based differences in the disability of spine injuries in pediatric and adult motor vehicle crash occupants.

OBJECTIVE: The objective was to develop a disability-based metric for quantifying disability rates as a result of motor vehicle crash (MVC) spine injuries and compare functional outcomes between pediatric and adult subgroups. METHODS: Disability rate was quantified using Functional Independence Measure (FIM) scores within the National Trauma Data Bank-Research Data System for the top 95% most frequent Abbreviated Injury Scale (AIS) 3 spine injuries (14 unique injuries). Pediatric (7-18 years), young adult (19-45 years), middle-aged adult (46-65 years), and older adult (66+ years) MVC occupants with FIM scores available and at least one of the 14 spine injuries were included. FIM scores of 1 or 2 at time of discharge were used to define disability and correspond to full functional or modified dependence in self-feeding, locomotion, and/or verbal expression. Disability rate was evaluated on a per injury basis for each AIS 3 spine injury and calculated as the proportion of cases associated with disability (i.e. FIM of 1 or 2) out of the total cases of that particular injury. Disability rates were calculated with and without the exclusion of cases with severe co-injuries (AIS 4+) to minimize bias from additional non-spinal injuries that could have contributed to disability. Associations between adjusted disability rates and existing mortality rates were investigated. RESULTS: Locomotion impairment alone was the most frequent disability type for the top 14 AIS 3 spine injuries (7 cervical, 4 thoracic, and 3 lumbar) across all age groups and spine regions. Adjusted and unadjusted disability rates ranged from 0-69%. Adjusted disability rates increased with age: 14.8 ± 10% (mean ± SD) in pediatrics to 16.2 ± 6.6% (young adults), 29.2 ± 10.9% (middle-aged adults), and 45.0 ± 12.2% (older adults). Among all adult populations, adjusted mortality and disability rates were positively correlated (R2>0.24), with disability rates consistently greater than corresponding mortality rates. CONCLUSIONS: Older adults had significantly greater disability rates associated with MVC spine injuries across all spinal regions. MVC disability rates for pediatrics were considerably lower. Overall, rates of mortality were significantly lower than rates of disability. The adjusted disability rates developed can supplement existing injury metrics by accounting for age- and location-specific functional implications of MVC spine injuries.

Advanced Automatic Crash Notification Algorithm for Children.

BACKGROUND: Advanced automatic crash notification (AACN) can improve triage decision-making by using vehicle telemetry to alert first responders of a motor vehicle crash and estimate an occupant's likelihood of injury. The objective was to develop an AACN algorithm to predict the risk that a pediatric occupant is seriously injured and requires treatment at a Level I or II trauma center. METHODS: Based on 3 injury facets (severity; time sensitivity; predictability), a list of Target Injuries associated with a child's need for Level I/II trauma center treatment was determined. Multivariable logistic regression of motor vehicle crash occupants was performed creating the pediatric-specific AACN algorithm to predict risk of sustaining a Target Injury. Algorithm inputs included: delta-v, rollover quarter-turns, belt status, multiple impacts, airbag deployment, and age. The algorithm was optimized to achieve under-triage ≤5% and over-triage ≤50%. Societal benefits were assessed by comparing correctly triaged motor vehicle crash occupants using the AACN algorithm against real-world decisions. RESULTS: The pediatric AACN algorithm achieved 25% to 49% over-triage across crash modes, and under-triage rates of 2% for far-side, 3% for frontal and near-side, 8% for rear, and 14% for rollover crashes. Applied to real-world motor vehicle crashes, improvements of 59% in under-triage and 45% in over-triage are estimated: more appropriate triage of 32,320 pediatric occupants annually. CONCLUSIONS: This AACN algorithm accounts for pediatric developmental stage and will aid emergency personnel in correctly triaging pediatric occupants after a motor vehicle crash. Once incorporated into the trauma triage network, it will increase triage efficiency and improve patient outcomes.

Comparing data-driven and hypothesis-driven MRI-based predictors of cognitive impairment in individuals from the Atherosclerosis Risk in Communities (ARIC) study.

INTRODUCTION: A data-driven index of dementia risk based on magnetic resonance imaging (MRI), the Alzheimer's Disease Pattern Similarity (AD-PS) score, was estimated for participants in the Atherosclerosis Risk in Communities (ARIC) study. METHODS: AD-PS scores were generated for 839 cognitively non-impaired individuals with a mean follow-up of 4.86 years. The scores and a hypothesis-driven volumetric measure based on several brain regions susceptible to AD were compared as predictors of incident cognitive impairment in different settings. RESULTS: Logistic regression analyses suggest the data-driven AD-PS scores to be more predictive of incident cognitive impairment than its counterpart. Both biomarkers were more predictive of incident cognitive impairment in participants who were White, female, and apolipoprotein E gene (APOE) ε4 carriers. Random forest analyses including predictors from different domains ranked the AD-PS scores as the most relevant MRI predictor of cognitive impairment. CONCLUSIONS: Overall, the AD-PS scores were the stronger MRI-derived predictors of incident cognitive impairment in cognitively non-impaired individuals.

Age-based differences in the disability of extremity injuries in pediatric and adult occupants.

Objective: The objective was to develop a disability-based metric for motor vehicle crash (MVC) upper and lower extremity injuries and compare functional outcomes between children and adults.Methods: Disability risk (DR) was quantified using Functional Independence Measure (FIM) scores within the National Trauma Data Bank-Research Data System for the top 95% most frequently occurring Abbreviated Injury Scale (AIS) 3 extremity injuries (22 unique injuries). Pediatric (7-18 years), young adult (19-45 years), middle-aged (46-65 years), and older adult (66+ years) MVC occupants with an FIM score and at least one of the 22 extremity injuries were included. DR was calculated for each injury as the proportion of occupants who were disabled of those sustaining the injury. A maximum AIS-adjusted disability risk (DRMAIS) was also calculated for each injury, excluding occupants with AIS 4+ co-injuries.Results: Locomotion impairment was the most frequent disability type across all ages. DR and DRMAIS of the extremity injuries ranged from 0.06 to 1.00 (6%-100% disability risk). Disability risk increased with age, with DRMAIS increasing from 25.9% ± 8.6% (mean ± SD) in pediatric subjects to 30.4% ± 6.3% in young adults, 39.5% ± 6.6% in middle-aged adults, and 60.5 ± 13.3% in older adults. DRMAIS for upper extremity fractures differed significantly between age groups, with higher disability in older adults, followed by middle-aged adults. DRMAIS for pelvis, hip, shaft, knee, and other lower extremity fractures differed significantly between age groups, with older adult DRMAIS being significantly higher for each fracture type. DRMAIS for hip and lower extremity shaft fractures was also significantly higher in middle-aged occupants compared to pediatric and young adult occupants. The maximum AIS-adjusted mortality risk (MRMAIS, proportion of fatalities among occupants sustaining an MAIS 3 injury) was not correlated with DRMAIS for extremity injuries in pediatric, young adult, middle-aged, and older adult occupants (all R2 < 0.01). Disability associated with each extremity injury was higher than mortality risk.Conclusions: Older adults had significantly greater disability for MVC extremity injuries. Lower disability rates in children may stem from their increased physiological capacity for bone healing and relative lack of bone disease. The disability metrics developed can supplement AIS and other severity-based metrics by accounting for the age-specific functional implications of MVC extremity injuries.

Development, Validation and Pilot Field Deployment of a Custom Mouthpiece for Head Impact Measurement.

The objective of this study was to develop a mouthpiece sensor with improved head kinematic measurement for use in non-helmeted and helmeted sports through laboratory validation and pilot field deployment in female youth soccer. For laboratory validation, data from the mouthpiece sensor was compared to standard sensors mounted in a headform at the center of gravity as the headform was struck with a swinging pendulum. Linear regression between peak kinematics measured from the mouthpiece and headform showed strong correlation, with r2 values of 0.95 (slope = 1.02) for linear acceleration, 1.00 (slope = 1.00) for angular velocity, and 0.97 (slope = 0.96) for angular acceleration. In field deployment, mouthpiece data were collected from four female youth soccer players and time-synchronized with film. Film-verified events (n = 915) were observed over 9 practices and 5 games, and 632 were matched to a corresponding mouthpiece event. This resulted in an overall sensitivity of 69.2% and a positive predictive value of 80.3%. This validation and pilot field deployment data demonstrates that the mouthpiece provides highly accurate measurement of on-field head impact data that can be used to further study the effects of impact exposure in both helmeted and non-helmeted sports.

General and domain-specific cognitive reserve, mild cognitive impairment, and dementia risk in older women.

INTRODUCTION: In a geographically diverse sample of women, we asked whether cognitive reserve (CR) is best viewed as a general or cognitive domain-specific construct and whether some cognitive reserve domains but not others exert protective effects on risk of developing mild cognitive impairment (MCI) or dementia. METHODS: Estimates of general and domain-specific CR were derived via variance decomposition in 972 cognitively intact women from the Women's Health Initiative Study of Cognitive Aging and Women's Health Memory Study Magnetic Resonance Imaging. Women were then followed up for 13 years. RESULTS: General CR was the strongest predictor of reduced risk for both MCI and dementia, compared to domain-specific CR measures. Verbal memory, figural memory, and spatial CR were independently protective of MCI, but only verbal memory was independently associated with reduced risk for dementia. DISCUSSION: Cognitive reserve is a heterogenous construct with valid quantitative measures identifiable across different neuropsychological processes associated with MCI and dementia.

Using high-dimensional machine learning methods to estimate an anatomical risk factor for Alzheimer's disease across imaging databases.

INTRODUCTION: The main goal of this work is to investigate the feasibility of estimating an anatomical index that can be used as an Alzheimer's disease (AD) risk factor in the Women's Health Initiative Magnetic Resonance Imaging Study (WHIMS-MRI) using MRI data from the Alzheimer's Disease Neuroimaging Initiative (ADNI), a well-characterized imaging database of AD patients and cognitively normal subjects. We called this index AD Pattern Similarity (AD-PS) scores. To demonstrate the construct validity of the scores, we investigated their associations with several AD risk factors. The ADNI and WHIMS imaging databases were collected with different goals, populations and data acquisition protocols: it is important to demonstrate that the approach to estimating AD-PS scores can bridge these differences. METHODS: MRI data from both studies were processed using high-dimensional warping methods. High-dimensional classifiers were then estimated using the ADNI MRI data. Next, the classifiers were applied to baseline and follow-up WHIMS-MRI GM data to generate the GM AD-PS scores. To study the validity of the scores we investigated associations between GM AD-PS scores at baseline (Scan 1) and their longitudinal changes (Scan 2 -Scan 1) with: 1) age, cognitive scores, white matter small vessel ischemic disease (WM SVID) volume at baseline and 2) age, cognitive scores, WM SVID volume longitudinal changes respectively. In addition, we investigated their associations with time until classification of independently adjudicated status in WHIMS-MRI. RESULTS: Higher GM AD-PS scores from WHIMS-MRI baseline data were associated with older age, lower cognitive scores, and higher WM SVID volume. Longitudinal changes in GM AD-PS scores (Scan 2 - Scan 1) were also associated with age and changes in WM SVID volumes and cognitive test scores. Increases in the GM AD-PS scores predicted decreases in cognitive scores and increases in WM SVID volume. GM AD-PS scores and their longitudinal changes also were associated with time until classification of cognitive impairment. Finally, receiver operating characteristic curves showed that baseline GM AD-PS scores of cognitively normal participants carried information about future cognitive status determined during follow-up. DISCUSSION: We applied a high-dimensional machine learning approach to estimate a novel AD risk factor for WHIMS-MRI study participants using ADNI data. The GM AD-PS scores showed strong associations with incident cognitive impairment and cross-sectional and longitudinal associations with age, cognitive function, cognitive status and WM SVID volume lending support to the ongoing validation of the GM AD-PS score.

Computer simulations for assessing cognitively intensive instrumental activities of daily living in older adults.

INTRODUCTION: Aim is to evaluate validity, reliability, diagnostic precision, and user acceptability of computer simulations of cognitively demanding tasks when administered to older adults with and without cognitive impairment. METHODS: Five simulation modules were administered to 161 individuals aged ≥60 years with no cognitive impairment (N = 81), mild cognitive impairment (N = 52), or dementia (N = 28). Groups were compared on total accuracy and time to complete the tasks (seconds). Receiver operating characteristics were evaluated. Reliability was assessed over one month. Participants rated face validity and acceptability. RESULTS: Total accuracy (P < .0001) and time (P = .0015) differed between groups. Test-retest correlations were excellent (0.79 and 0.88, respectively). Area under the curve ranged from good (0.77) to excellent (0.97). User ratings supported their face validity and acceptability. DISCUSSION: Brief computer simulations can be useful in assessing cognitive functional abilities of older adults and distinguishing varying degrees of impairment.

Functional outcomes of thoracic injuries in pediatric and adult occupants.

OBJECTIVE: To develop a disability metric for motor vehicle crash (MVC) thoracic injuries and compare functional outcomes between pediatric and adult populations. METHODS: Disability risk (DR) was quantified using Functional Independence Measure (FIM) scores within the National Trauma Data Bank (NTDB) for the top 95% most frequently occurring AIS 2, 3, 4, and 5 thoracic injuries in NASS-CDS 2000-2011. The NTDB contains a truncated form of the FIM score, including three items (self-feed, locomotion, and verbal expression), each graded from full functional dependence to full functional independence. Pediatric (ages 7-18 years), adult (19-45), middle-aged adult (46-65), and older adult (66+) MVC occupants were classified as disabled or not disabled based on the FIM scale. The DR was calculated for each injury within each age group by dividing the number of patients who were disabled that sustained the specific injury by the number of patients who sustained the specific injury. To account for the impact of more severe co-injuries, a maximum Abbreviated Injury Scale (MAIS) adjusted DR (DRMAIS) was also calculated. DR and DRMAIS could range from 0 (0% disability risk) to 1 (100% disability risk). RESULTS: The mean DRMAIS for MVC thoracic injuries was 20% for pediatric occupants, 22% for adults, 29% for middle-aged adults, and 43% for older adults. Older adults possessed higher DRMAIS values for diaphragm laceration/rupture, heart laceration, hemo/pneumothorax, lung contusion/laceration, rib fracture, and sternum fracture compared to the other age groups. The pediatric population possessed a higher DRMAIS value for flail chest compared to the other age groups. CONCLUSIONS: Older adults had significantly greater overall disability than each of the other age groups for thoracic injuries. The developed disability metrics are important in quantifying the significant burden of injuries and loss of quality life years. Such metrics can be used to better characterize severity of injury and further the understanding of age-related differences in injury outcomes, which can impact future age-specific modifications to AIS.

Characterization of the occult nature of frequently occurring pediatric motor vehicle crash injuries.

BACKGROUND: Occult injuries are those likely to be missed on initial assessment by first responders and, though initially asymptomatic, they may present suddenly and lead to rapid patient decompensation. No scoring systems to quantify the occultness of pediatric injuries have been established. Such a scoring system will be useful in the creation of an Advanced Automotive Crash Notification (AACN) system that assists first responders in making triage decisions following a motor vehicle crash (MVC). STUDY DESIGN: The most frequent MVC injuries were determined for 0-4, 5-9, 10-14 and 15-18 year olds. For each age-specific injury, experts with pediatric trauma expertise were asked to rate the likelihood that the injury may be missed by first responders. An occult score (ranging from 0-1) was calculated by averaging and normalizing the responses of the experts polled. RESULTS: Evaluation of all injuries across all age groups demonstrated greater occult scores for the younger age groups compared to older age groups (mean occult score 0-4yo: 0.61 ±â€¯0.23, 5-9yo: 0.53 ±â€¯0.25, 10-14yo: 0.48 ±â€¯0.23, and 15-18yo: 0.42 ±â€¯0.22, p < 0.01). Body-region specific occult scores revealed that experts judged abdominal, spine and thoracic injuries to be more occult than injuries to other body regions. CONCLUSIONS: The occult scores suggested that injuries are more difficult to detect in younger age groups, likely given their inability to express symptoms. An AACN algorithm that can predict the presence of clinically undetectable injuries at the scene can improve triage of children with these injuries to higher levels of care.

Functional outcomes of motor vehicle crash thoracic injuries in pediatric and adult occupants.

OBJECTIVE: Characterization of the severity of injury should account for both mortality and disability. The objective of this study was to develop a disability metric for thoracic injuries in motor vehicle crashes (MVCs) and compare the functional outcomes between the pediatric and adult populations. METHODS: Disability risk (DR) was quantified using Functional Independence Measure (FIM) scores within the National Trauma Data Bank for the most frequently occurring Abbreviated Injury Scale (AIS) 2-5 thoracic injuries. Occupants with thoracic injury were classified as disabled or not disabled based on the FIM scale, and comparisons were made between the following age groups: pediatric, adult, middle-aged, and older occupants (ages 7-18, 19-45, 46-65, and 66+, respectively). For each age group, DR was calculated by dividing the number of patients who were disabled and sustained a given injury by the number of patients who sustained a given injury. To account for the effect of higher severity co-injuries, a maximum AIS adjusted DR (DRMAIS) was also calculated for each injury. DR and DRMAIS could range from 0 to 100% disability risk. RESULTS: The mean DRMAIS for MVC thoracic injuries was 20% for pediatric occupants, 22% for adults, 29% for middle-aged adults, and 43% for older adults. Older adults possessed higher DRMAIS values for diaphragm laceration/rupture, heart laceration, hemo/pneumothorax, lung contusion/laceration, and rib and sternum fracture compared to the other age groups. The pediatric population possessed a higher DRMAIS value for flail chest compared to the other age groups. CONCLUSION: Older adults had significantly greater overall disability than each of the other age groups for thoracic injuries. The developed disability metrics are important in quantifying the significant burden of injuries and loss of quality life years. Such metrics can be used to better characterize severity of injury and further the understanding of age-related differences in injury outcomes, which can influence future age-specific modifications to AIS.

Predicting Pediatric Patients Who Require Care at a Trauma Center: Analysis of Injuries and Other Factors.

BACKGROUND: Triage decision correctness for children in motor vehicle crashes can be affected by occult injuries. There is a need to develop a transfer score (TS) metric for children that can help quantify the likelihood that an injury is present that would require transfer to a trauma center (TC) from a non-TC, and improve triage decision making. Ultimately, the TS metric might be useful in an advanced automatic crash notification algorithm, which uses vehicle telemetry data to predict the risk of serious injury after a motor vehicle crash using an approach that includes metrics to describe injury severity, time sensitivity, and predictability. STUDY DESIGN: Transfer score metrics were calculated in 4 pediatric age groups (0 to 4, 5 to 9, 10 to 14, 15 to 18 years) for the most frequent motor vehicle crash injuries using the proportions of children transferred to a TC or managed at a non-TC using the National Inpatient Sample years 1998 to 2007. To account for the maximum Abbreviated Injury Scale (MAIS) injury, a co-injury adjusted transfer score (TSMAIS) was calculated. The TS and TSMAIS range from 0 to 1, with 1 indicating highly transferred injuries. RESULTS: Injuries in younger patients were more likely to be transferred (median TS 0.48, 0.35, 0.25, and 0.23 for 0 to 4, 5 to 9, 10 to 14, and 15 to 18 years, respectively). Injuries more likely to be transferred in younger children occurred in the thorax and abdomen. Regardless of age, spine (median TSMAIS 0.59), head (median TSMAIS 0.48), and thorax (median TSMAIS 0.46) injuries had the highest frequency for transfer. CONCLUSIONS: The TS metrics quantitatively describe age-specific transfer practices for children with particular injuries. This information can be useful in advanced automatic crash notification systems to alert first responders to the possibility of occult injuries and reduce undertriage of commonly missed injuries.

Disability risk in pediatric motor vehicle crash occupants.

BACKGROUND: Mortality rates among children in motor vehicle crashes (MVCs) are typically low; however, nonfatal injuries can vary in severity by imposing differing levels of short- and long-term disability. To better discriminate the severity of nonfatal MVC injuries, a pediatric-specific disability risk (DR) metric was created. METHODS: The National Automotive Sampling System 2000 to 2011 was used to define the top 95% most common Abbreviated Injury Scale (AIS) 2+ injuries among pediatric MVC occupants. Functional Independence Measure scores were abstracted from the National Trauma Data Bank 2002 to 2006. Multiple imputation was used to account for missing data. The DR and coinjury-adjusted DR (DRMAIS) of the most common AIS 2+ MVC-induced injuries were calculated for 7-year-old to 18-year-old children by determining the proportion of those disabled after an injury to those sustaining the injury. DR and DRMAIS values ranged from 0 to 1, representing 0% to 100% DR. RESULTS: The mean DR and DRMAIS of all injuries were 0.290 and 0.191, respectively. DR and DRMAIS were greatest for injuries to the head (DR, 0.340; DRMAIS, 0.279), thorax (DR, 0.320; DRMAIS, 0.233), and spine (DR, 0.315; DRMAIS, 0.200). The mean DR and DRMAIS increased with increasing AIS severity but there was significant variation and overlapping values across AIS severity levels. Comparison of DRMAIS to coinjury-adjusted mortality risk (MRMAIS) revealed that among 118 injuries with MRMAIS of 0.000, DRMAIS ranged from 0.000 to 0.429. CONCLUSION: Incorporation of DR metrics into injury severity metrics may improve the ability to distinguish between the severity of different nonfatal injuries. This is especially crucial in the pediatric population where permanent disability can result in a high number of years lost due to disability. The accuracy of such severity metrics is crucial to the success of pediatric triage algorithms such as Advanced Automatic Crash Notification algorithms. LEVEL OF EVIDENCE: Epidemiologic/prognostic study, level III.

Expert Perspectives on Time Sensitivity and a Related Metric for Children Involved in Motor Vehicle Crashes.

OBJECTIVE: Advanced Automatic Crash Notification (AACN) uses vehicle telemetry data to predict risk of serious injury among motor vehicle crash occupants and can thus improve the accuracy with which injured children are triaged by first responders. To better define serious injury for AACN systems (which typically use Abbreviated Injury Scale [AIS] metrics), an age-specific approach evaluating severity, time sensitivity (TS), and predictability of injury has been developed. This study outlines the development of the TS score. METHODS: The 95% most frequent AIS 2+ injuries in a national motor vehicle crash data set spanning 2000 to 2011 were determined for the following age groups: 0 to 4, 5 to 9, 10 to 14, and 15 to 18 years. For each age-specific injury, clinicians with pediatric trauma expertise were asked if treatment at a trauma center was required and were asked about the urgency of treatment. A TS score (range 0-1) was calculated by combining the mean trauma center decision and urgency scores. RESULTS: A total of 30 to 32 responses were obtained for each age-specific injury. The most frequent motor vehicle crash-induced injuries in the younger groups received significantly higher scores than those in the older groups (median TS score 0 to 4 years: 0.89, 5-9 years: 0.87, 10-14 years: 0.82, 15-18 years: 0.72, P < .001). Large variations in TS existed within each AIS severity level; for example, scores among AIS 2 injuries in 0- to 4-year-olds ranged from 0.12 to 0.98. CONCLUSIONS: The TS of common pediatric injuries varies on the basis of age and may not be accurately reflected by AIS metrics. AIS may not capture all aspects of injury that should be considered by AACN systems.

Characterization of the occult nature of injury for frequently occurring motor vehicle crash injuries.

BACKGROUND: Occult injuries are not easily detected and can be potentially life-threatening. The purpose of this study was to quantify the perceived occultness of the most frequent motor vehicle crash injuries according to emergency medical services (EMS) professionals. STUDY DESIGN: An electronic survey was distributed to 1,125 EMS professionals who were asked to quantify the likelihood that first responders would miss symptoms related to a particular injury on a 5-point Likert scale. The Occult Score for each injury was computed from the average of all the survey responses and normalized to be a continuous metric ranging from 0 to 1 where 0 is a non-occult (highly apparent on initial presentation) injury and 1 is an occult (unapparent on initial presentation) injury. RESULTS: Overall, 110,671 survey responses were collected. The Occult Score ranged from 0 to 1 with a mean, median, and standard deviation of 0.443, 0.450, and 0.233, respectively. When comparing the Occult Score of an injury to its corresponding AIS severity, there was no relationship between the metrics. When stratifying by body region, injury type, and AIS severity, it was evident that AIS 2-4 abdominal injuries with lacerations, hemorrhage, or contusions were perceived as the most occult injuries. CONCLUSIONS: Timely triage is key to reduce the morbidity and mortality associated with occult injuries. The Occult Score developed in this study to describe the predictability of an injury in a motor vehicle crash will be used as part of a larger effort, including incorporation into an advanced automatic crash notification (AACN) algorithm to detect crash conditions associated with a patient's need for prompt treatment at a trauma center.

Functional outcomes of motor vehicle crash head injuries in pediatric and adult occupants.

OBJECTIVE: The objective of the study was to develop a disability-based metric for motor vehicle crash (MVC) injuries, with a focus on head injuries, and compare the functional outcomes between the pediatric and adult populations. METHODS: Disability risk (DR) was quantified using Functional Independence Measure (FIM) scores within the National Trauma Data Bank-Research Data System (NTDB-RDS) for the top 95% most frequently occurring Abbreviated Injury Scale (AIS) 3, 4, and 5 head injuries in NASS-CDS 2000-2011. Pediatric (ages 7-18), adult (19-45), middle-aged (46-65), and older adult (66+) patients with an FIM score available who were alive at discharge and had an AIS 3, 4, or 5 injury were included in the study. The NTDB-RDS contains a truncated form of the FIM instrument, including 3 items (self-feed, locomotion, and verbal expression), each graded on a scale of 1 (full functional dependence) to 4 (full functional independence). Patients within each age group were classified as disabled or not disabled based on the FIM scale. The DR was calculated for each age group by dividing the number of patients who sustained a specific injury and were disabled by the number of patients who sustained the specific injury. To account for the impact of more severe associated coinjuries, a maximum AIS (MAIS) adjusted DR (DRMAIS) was also calculated for each injury. DR and DRMAIS ranged from 0 (0% disability risk) to 1 (100% disability risk). RESULTS: An analysis of the most frequent FIM components associated with disabling MVC head injuries revealed that disability across all 3 items (self-feed, locomotion, and expression) was the most frequent for pediatric and adult patients. Only locomotion was the most frequent for middle-aged and older adults. The mean DRMAIS for MVC head injuries was 35% for pediatric patients, 36% for adults, 38% for middle-aged adults, and 44% for older adults. Further analysis was conducted by grouping the head injuries into 8 groups based on the structure of injury and injury type. The pediatric population possessed higher DRMAIS values for brain stem injuries as well as loss of consciousness injuries. Older adults possessed higher DRMAIS values for contusion/hemorrhage injuries, epidural hemorrhage, intracerebral hemorrhage, skull fracture, and subdural/subarachnoid hemorrhage. CONCLUSION: At-risk populations such as pediatric and older adult patients possessed higher DRMAIS values for different head injuries. Disability in pediatric patients is critical due to loss of quality life years. Disability risk can supplement severity metrics to improve the ability of such metrics to discriminate the severity of different injuries that do not lead to death. Understanding of age-related differences in injury outcomes when compared to adults could inform future age-specific modifications to the AIS.