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The Low Fall as a Surrogate Marker of Frailty Predicts Long-Term Mortality in Older Trauma Patients

The Low Fall as a Surrogate Marker of Frailty Predicts Long-Term Mortality in Older Trauma Patients

  • Ting Hway Wong, 
  • Hai V. Nguyen, 
  • Ming Terk Chiu, 
  • Khuan Yew Chow, 
  • Marcus Eng Hock Ong, 
  • Gek Hsiang Lim, 
  • Nivedita Vikas Nadkarni, 
  • Dianne Carrol Tan Bautista, 
  • Jolene Yu Xuan Cheng, 
  • Lynette Mee Ann Loo
PLOS
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Abstract

Background

Frailty is associated with adverse outcomes including disability, mortality and risk of falls. Trauma registries capture a broad range of injuries. However, frail patients who fall comprise a large proportion of the injuries occurring in ageing populations and are likely to have different outcomes compared to non-frail injured patients. The effect of frail fallers on mortality is under-explored but potentially significant. Currently, many trauma registries define low falls as less than three metres, a height that is likely to include non-frailty falls. We hypothesized that the low fall from less than 0.5 metres, including same-level falls, is a surrogate marker of frailty and predicts long-term mortality in older trauma patients.

Methods

Using data from the Singapore National Trauma Registry, 2011–2013, matched till September 2014 to the death registry, we analysed adults aged over 45 admitted via the emergency department in public hospitals sustaining blunt injuries with an injury severity score (ISS) of 9 or more, excluding isolated hip fractures from same-level falls in the over 65. Patients injured by a low fall were compared to patients injured by high fall and other blunt mechanisms. Logistic regression was used to analyze 12-month mortality, controlling for mechanism of injury, ISS, revised trauma score (RTS), co-morbidities, gender, age and age-gender interaction. Different low fall height definitions, adjusting for injury regions, and analyzing the entire adult cohort were used in sensitivity analyses and did not change our findings.

Results

Of the 8111 adults in our cohort, patients who suffered low falls were more likely to die of causes unrelated to their injuries (p<0.001), compared to other blunt trauma and higher fall heights. They were at higher risk of 12-month mortality (OR 1.75, 95% CI 1.18–2.58, p = 0.005), independent of ISS, RTS, age, gender, age-gender interaction and co-morbidities. Falls that were higher than 0.5m did not show this pattern. Males were at higher risk of mortality after low falls. The effect of age on mortality started at age 55 for males, and age 70 for females, and the difference was attributable to the additional mortality in male low-fallers.

Conclusions

The low fall mechanism can optimize prediction of long-term mortality after moderate and severe injury, and may be a surrogate marker of frailty, complementing broader-based studies on aging.

Introduction

Trauma in older patients has emerged as an important multi-disciplinary issue, not just for the surgical disciplines but also for the geriatric, rehabilitation, intensive care, emergency medicine and pre-hospital specialties [15]. Predicting health outcomes in these patients is important for clinical benchmarking as well as formulating health policy. Trauma in older adults differs from young adult trauma in its epidemiology[68], resource utilization[911], risk factors for morbidity and mortality[12, 13], performance on injury outcome predictors[14, 15], and volume-outcome relationships[1618].

Frailty is also a growing public health issue in ageing populations. The incidence of frailty increases with age, from just 3.2% for the age group 65–70 to 25.7% for the age group 85–89[19]. Frail elderly, when compared to the non-frail, have been found to have a higher rate of falls, hospitalization, functional decline and mortality.

Injury severity scores alone are poor predictors of mortality in older trauma patients[20]. Other factors specific to older adults need to be accounted for, such as frailty[21] and comorbidities[14, 15, 2224]. The incorporation of co-morbidities can improve prediction of mortality after injury[14, 15, 22]. Co-morbidities, however, do not represent all that is known about frailty[25, 26]. Frailty has been shown to predict mortality independent of injury severity scores in prospective studies[21]. However, pre-injury frailty data are usually not available in trauma registry data, which are collected at the time of presentation with injury. Post-injury tests of frailty may be affected by injury and subsequent disability. In a study on injured elderly patients in intensive care, radiologically-diagnosed low skeletal muscle mass was significantly more common in falls and low-energy patients[27]. As injuries arising from lower fall heights are more likely to be frailty-related than those from higher fall heights, the low fall is a potential marker of frailty in trauma registry data and is expected to be a predictor of mortality. While the full spectrum of frailty cannot be explored from the information routinely captured in trauma databases, we propose that low falls (including same-level falls) could be a surrogate marker of frailty and explains some of the excess mortality seen in older trauma patients.

Our hypothesis is that the low fall is associated with increased long-term mortality in elderly trauma patients independent of age, gender, co-morbidities and injury severity scores. Data on mechanism of injury is routinely collected in trauma registries and diagnosis codes[28]. Studies have examined the effect of sub-categories of mechanism of injury on outcomes[29], as well as the relative increased mortality from same-level falls compared to higher level falls[30]. We set out to build on these studies by controlling for injury severity and co-morbidities. Exact fall heights are difficult to extrapolate from patient histories, and consensus or expert definitions of “same-level fall” or “low fall”[31] are not easily standardized for data entry teams. In view of these difficulties, many large registries either do not differentiate fall heights, or define low falls as less than three metres [32, 33], a height that is likely to include non-frailty falls, and can be life-threatening for young adults as well. For our registry, we implemented a standardized conversion table (furniture, steps, buildings) for converting patient histories to fall heights (Table 1). Using this data, we set out to define which low fall height optimally predicts mortality, using a standardized conversion methodology for patient histories. Higher energy injury is usually associated with a higher risk of mortality, which is why penetrating injury is treated differently from blunt trauma in injury severity scoring systems[34, 35]. Hence, if our hypothesis holds true that the low-energy mechanism is paradoxically associated with a higher risk of death and complications, then this could be because such patients are more frail than patients with similar injury patterns after high energy trauma.

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Table 1. Guidelines for Conversion of Patient Histories to Heights in Metres.

https://doi.org/10.1371/journal.pone.0137127.t001

Methods

Data Source and Data Collection

Data are from the Singapore National Trauma Registry (NTR), established in 2011[8].

All hospitals that receive Singapore Civil Defence Force (SCDF) ambulances (i.e., all public hospitals) provide data for the NTR42. Data collection for the NTR is performed by teams of trained trauma data coordinators based at each public hospital, with data cleaning, data completeness, data quality and inter-rater audits performed annually. Quarterly reviews of data capture problems are performed by a central pool based at the National Registry of Diseases Office (NRDO). Patients meet inclusion criteria for the NTR if they present to hospitals’ emergency departments with any injury with the diagnostic codes 800–959.9, defined in the International Classification of Diseases, 9th Revision, Clinical Modification, excluding late effects of injury (codes 905–909.9)43. Once a trauma patient is identified by its ICD9 code in the emergency department, data coding personnel will check that the patient meets the inclusion criteria. Some fields are then automatically included in the registry by data capture from electronic medical records and all fields are checked by data coding personnel. Personnel are trained in coding of the Abbreviated Injury Scale (AIS), version 2005 update 200838, capturing the physiological and anatomical variables from medical records for the calculation of the RTS and ISS respectively. Death date and cause of death are captured at quarterly intervals from the registry of births and deaths, provided by the National Registry of Diseases Office.

Study Design

Retrospective data from January 2011 to December 2013 was matched with death registry data up to September 2014. The association between low falls and mortality (12-month and in-hospital) for patients aged over 45 was examined, controlling for injury severity score (ISS)[36], revised trauma score (RTS)[37], co-morbidities prevalent in 5% or more of the study population, Charlson co-morbidity index (CCI) [38], race (as entered by data entry personnel), gender, age and the age by gender interaction.

The effect of low fall on long-term survival and cause of death were explored by age-group and gender. Expanded sets of control variables were used in sensitivity analyses including residency status, pattern of injury (Abbreviated Injury Scale (AIS) score of three or more in each AIS region[39]), polytrauma [40, 41], and co-morbidities prevalent in 1% or more of the study population known to be associated with fall risk, worse outcomes after trauma or frailty (history of previous injury, visual defects, anaemia, dementia, depression and other psychiatric illness)[14, 42].

Study Population

Study population included patients age 45 and over, as the low falls in the age-group 18 to 45 constituted less than one percent of all blunt trauma in this age-group. For patients with ISS less than 9 and patients aged 65 and over with isolated hip fractures (neck of femur or inter-trochanteric) sustained in same-level falls, detailed co-morbidity data, ISS and RTS were not available in the NTR. These patients were excluded from our analysis.

Outcome measures

The primary outcome measure was mortality 12 months post-injury. Secondary outcome measures were long-term survival (death at any point during from the study period up to September 2014) and in-hospital mortality (primary admission for the injury). Cause of death was considered trauma-related if the death certificate showed any trauma-related diagnosis in the primary or secondary causes of death, and as non-trauma-related if there was no mention of trauma.

Covariates

Mechanism of Injury.

In the registry, injury mechanism is coded into the following categories: motor vehicle accident, fall, interpersonal violence, machinery, tools / objects, sports, unknown and others. Additional mechanism of injury details are available for motor vehicle injuries (vehicle, motorcycle, pedestrian, cyclist) and falls (height of fall). Burns and penetrating injuries were excluded from analysis.

Defining Low Falls.

Falls in the registry are sub-divided into same-level falls and falls with height documented. The definition of same-level fall was set as falls from 0.5 m or less, to include falls from sitting or lying positions. Some patients in the category of falls with height documented had fall heights of 0.5 m or less, and were included in this final definition of low fall. Furniture, step and storey heights were defined based on consensus and building guidelines to convert patient histories (Table 1).

We compared low falls as a blunt mechanism subtype to falls from other heights, and to other blunt mechanism sub-types, including motor vehicle injuries. Sensitivity analyses included sub-dividing the motor vehicle injuries into the commonest sub-types (car, motorcycle, pedestrian) and using different cut-offs for low falls (1m, 2m, and 3m)[3234].

Age.

Age was analyzed in ten-year bands from age 45, the highest age band as age 85 and over. The 65–74 year age band was split into 5-year bands, to include many commonly used age cut-offs in the literature[34, 35, 41, 4345]. The referent age band was the 45–54 year band.

Measures of Injury Severity and Comorbidity.

ISS and RTS were the anatomical and physiological measures of injury severity respectively.

Co-morbidity was alternately measured by: 1. CCI; 2. comorbid conditions that contributed more than 5% (by frequency) to co-morbidities found in our study population (diabetes, hypertension, hyperlipidaemia and cancer); 3. as in (2), plus comorbid conditions that contributed 1–5% (by frequency) and known to be associated with fall risks or frailty[42] (sensitivity analysis).

Statistical Analysis.

Patient characteristics at baseline were summarized by mean (standard deviation) or median (inter-quartile range) or frequency (%) as appropriate. Chi-square tests and Fisher’s exact test were performed to evaluate associations between the outcomes of interest and other categorical predictors of interest. Univariate logistic regression was used to analyze mortality (12-month and in-hospital). The predictors which were significant (p<0.05) in the univariate regression were entered into the multivariable regression. Variables which were not statistically significant but were clinically meaningful were retained in the multivariable model. Stata 13.0 was used.

Due to the age-gender interactions, sub-group analyses by gender were performed. Relative performance of prediction models was assessed using the Hosmer-Lemeshow goodness-of-fit test and c-statistic (i.e. area under the receiver operating characteristic curve ROC). The ROC was generated based on the final model to visualize sensitivity and specificity of the chosen model. Likelihood ratio tests were carried out to assess predictor significance by comparison between nested models. Long-term survival generated using Kaplan-Meier compared low fallers and non-low fallers using the log rank test.

Patients with missing data were omitted from the analysis: ISS (<0.5% missing), RTS (<0.5% missing), co-morbidities (missing 1.85%) and fall height (unknown 1.31%).

The first author’s (Singapore General Hospital) Institutional Review Board granted ethical approval for this retrospective study, as required prior to gaining access to the NTR data, which is de-identified prior to release for research, password-protected and access limited to the premises of the National Registry of Diseases Office (NRDO). Consent was not obtained because information was anonymized and de-identified prior to analysis, as per NRDO protocol.

Results

Descriptive analysis

In the three years of data collection 2011 to 2013, there were 8111 cases of blunt trauma patients meeting our study inclusion criteria. Summary statistics are presented in Table 2. Patients with low fall mostly suffered injuries to the head (48.1% AIS scorei3), extremities (37.2%), and torso (8.4% thoracic, 6.4% abdominal), with 2.7% having an AIS score of 3 or more in 2 or more body regions[40, 41]. The ISS ranged from 9 to 75. The AIS scores for all the body regions ranged from 0 (no injury) to 6 (unsurvivable injury), except for the “external” region (0 to 3) as isolated burns patients were excluded from this study.

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Table 2.

Characteristics of National Trauma Registry Patients aged over 45 (n = 8111).

https://doi.org/10.1371/journal.pone.0137127.t002

Multivariate Analysis of Age, Gender, ISS, RTS, Co-morbidities and Low Fall

The low fall was found to be an independent predictor of one-year mortality compared to higher levels of fall and other blunt mechanisms of injury after adjusting for age, gender, age by gender interaction, CCI, ISS and RTS (Table 3). The c-statistic of 0.8279 compared favorably with the model of the same covariates without low falls (0.8173), without age-gender interaction (0.8205), the model with age, gender, ISS, RTS and CCI (0.8169), and the model with only age, gender, ISS and RTS (0.8053).

Subgroup analysis by gender (Table 3) showed that the effect of increasing age on one-year and in-hospital mortality started at age 55 for males and 70 for females. Low falls were predictive of one-year mortality for males but not for females.

For in-hospital mortality, although the effect of low falls were not statistically significant after controlling for age, gender, co-morbidities, ISS and RTS, the odds of death in males were more than 30% higher, compared to other fall heights and other blunt injuries. Females were not at higher risk of mortality.

Some authors have explored the contribution of individual comorbidities to mortality after trauma[14], instead of using the CCI. For example, diabetes has been found to predict mortality in trauma patients independent of injury severity [46]. In our study, when the CCI was replaced by the co-morbidities that were prevalent in 5% or more of the study population, the low fall was still a significant predictor of twelve-month mortality (OR 1.88, 95% CI 1.24–2.86, p = 0.003) and remained significant in the sub-group analysis for males.

Long-term Survival

Long-term survival curves comparing low falls vs higher falls for males, and male vs female patients after low fall are shown in Figs 1 and 2 respectively. These were significantly different based on the log rank test (p<0.001). For higher fall and other blunt trauma patients, there was no gender difference in long-term survival. The effect of low fall on increased mortality went beyond 12 months, the time-frame that most trauma studies use to study the out-of-hospital impact of trauma on mortality. For males, the effect of low fall on increased mortality was significant based on the log rank test for each age-band and hence was not due to the higher age of low fallers alone. The gender differences after low falls peaked in the first half of the study period, and declined towards the end of the study period. We did not consider time to event analysis because of the high number of in-hospital deaths.

Cause of Death

Studies of gender differences for trauma have attributed excess mortality to the increased risk of infection in males after injury[47, 48]. In our population, the certified cause of death for low fall patients was less likely to be trauma-related (defined as any mention of injury in the primary or secondary causes of death) than for other mechanisms of blunt trauma in the same age group, and was the case for both genders and all ages (Table 4).

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Table 4. Cause of Death for Patients with Mortality within 12 Months of Injury, by Age Group and Low Fall, High Fall and Road Injury.

https://doi.org/10.1371/journal.pone.0137127.t004

Sensitivity analyses

The following checks were conducted to test the robustness of our result, with no effect on our findings: (i) Controlling for pattern of injury, adjusting for pattern of injury by Abbreviated Injury Scale (AIS) region with AIS score of 3 or more, and for polytrauma; (ii) Excluding non-residents (death registry captures 100% long-term death for residents); (iii) Different cut-off for defining low- versus high- falls: changing the low fall height definition to one metre, two metres and three metres showed a lower c-statistic than the initial definition of 0.5 m. Using same-level (as entered) versus any higher level showed similar c-statistics to low falls and similar effects; (iv) Addition of sub-categories of road injuries (pedestrian, motor vehicle, motorcycle)[29], the second commonest mechanism of injury after falls; (v) Separate sub-group analysis of moderate (ISS 9–15) and severe injuries (ISS>15); (vi) Regression using the entire adult population (age over 18), as in a recent study[14]; and (vii) Addition of clinically relevant 1–5% co-morbidities (see methods).

Discussion

Our study shows that low fall patients were almost twice as likely to die within a year of injury compared to trauma patients with high fall heights and other blunt injuries, especially males, independent of injury severity. The cause of death in these cases was mostly not trauma-related.

The age-gender interaction after low falls adds an important dimension to modelling outcomes after trauma. Different authors have proposed different cut-offs for the effect of age on mortality after trauma[41, 43, 45]. In our study, there is excess mortality for males compared to females from age 70, and this excess mortality is mostly in patients with the low falls. Sub-group analyses by gender suggest that the effect of age on mortality begins at 55 for men and 70 years for women. Hence, there is no single age cut-off that would capture these interactions.

This may explain some of the conflicting findings in the literature on gender differences when low fall mechanism is not controlled for. In one study using matched-pair analysis, while males had a lower mortality rate, the proportion of falls below 3m for males was only 13% in the study population, versus 27% for females[47]. Both males and females in their study included some older patients, as the mean age was 43.5 and 52.1 years respectively. A study using American National Trauma Data Bank (NTDB) data showed females had fewer complications after injury[48], but while they controlled for mechanism of injury (falls), the height threshold to define high versus low fall in the NTDB is set at three metres.

Our study builds on recent literature showing poor outcomes after low falls[49, 50]. We found an effect in males at a younger age (55) than explored in these recent studies, controlling for region of injury, severity of injury and co-morbidities. Decreased upper and lower extremity strength are part of the clinical indicators of frailty[42, 51] and contribute to the mechanism of a low fall. We postulate that the low fall could be a surrogate marker of frailty and that frailty could explain the increased mortality in studies of fallers, even after controlling for age and injury severity. The increased mortality in males is similar to what has been reported on frailty and gender[52, 53]. The validity of this hypothesis should be further explored through future prospective studies which would examine other markers of frailty in patients after low falls compared to other trauma.

While our study was not designed to explore improvements in clinical outcomes, it is likely that patients who are frail are more likely to benefit from early comprehensive geriatric assessment and collaborative care, compared to non-frail older patients after trauma[54, 55]. Ideally, early comprehensive assessment should be performed for all older patients presenting with a fall, but for a busy geriatric service in a rapidly ageing population, our study suggests that priority be given to patients suffering significant injury after low falls compared to those suffering falls from a greater height, and that some of the conventional age cut-offs (65 or 70 being the commonest in our citations) may miss the younger males whose risk start at age 55. This can result in targeted interventions, better resource prioritization, and could explain the volume-outcome phenomenon specific to older trauma patients [1618]. The low fall mechanism should be considered in the case mix when benchmarking trauma centres handling significant volumes of geriatric trauma[1618].

While this is a national hospital-based cohort from an urban country in Asia, our study population appears fairly similar to other ageing populations. Our population life expectancy is long[56] and the overall fall incidence in our study is similar to that reported in a recent study from a state-wide trauma registry in North America with similar inclusion criteria[18]. All public hospitals have inpatient geriatric and orthogeriatrics services.

Our study has some limitations. First, injuries for which the SCDF ambulance was not called and were admitted to a private hospital would not enter the National Trauma Registry. This would have a minor effect on the capture of moderate injuries as SCDF usage is high[8, 57]. Secondly, injuries with ISS below 9 and isolated hip fractures in the over 65 sustained in same-level falls were excluded from our study as detailed physiological and co-morbidity data were not captured. Our findings are significant despite being an underestimate for the over 65, since the over-65 isolated same-level fall hip fracture patients could not be included in our study due to lack of co-morbidity data. While there are good arguments both for and against the inclusion of isolated hip fractures in trauma registries[5456], outcomes after hip fractures have been well-studied, showing increased mortality for males despite a lower incidence[5862], and high incidence of frailty[63, 64]. These are consistent with the findings in our study, and suggest our findings would be similar if we were to repeat this study in future to include isolated hip fractures sustained in same-level falls in the over 65. Third, functional outcomes were not considered in this study as some were not yet available at the time of analysis. This would require comparison to baseline pre-injury functional information for comparison (only post-injury function is in NTR), especially in the frail patients, which we will include in a future prospective study.

Conclusion

The low fall mechanism of injury was found to predict long-term and non-trauma-related mortality, independent of co-morbidities and injury severity, especially in males, and as such may be a surrogate marker of frailty in trauma registry data. We recommend a low fall definition of 0.5 m or less to optimize interpretation of trauma registry data in older adults sustaining moderate and severe injury. This study provides evidence for a different mechanism for long term mortality after moderate and severe injury for same-level and low falls, and further work should be undertaken to explore how to improve outcomes for these patients.

Acknowledgments

The authors would like to thank Dr Tong G On, the National Trauma Committee, the National Trauma Registry working group, Tan Tock Seng Trauma Unit, the trauma database co-ordinators, colleagues at the National Registry of Diseases Office, and Shweta Mital for help with manuscript preparation.

Author Contributions

Conceived and designed the experiments: THW HVN DCCS. Analyzed the data: THW HVN GHL NVN DCTB JYXC. Contributed reagents/materials/analysis tools: THW HVN GHL NVN DCTB JYXC. Wrote the paper: THW HVN MTC KYC MEHO LMAL DCCS.

References

  1. 1. Lenartowicz M, Parkovnick M, McFarlan A, Haas B, Straus SE, Nathens AB, et al. An evaluation of a proactive geriatric trauma consultation service. Annals of surgery. 2012;256(6):1098–101. pmid:23108129
  2. 2. Abraham CM, Obremskey WT, Song Y, Jackson JC, Ely EW, Archer KR. Hospital Delirium and Psychological Distress at 1 Year and Health-Related Quality of Life After Moderate-to-Severe Traumatic Injury Without Intracranial Hemorrhage. Archives of physical medicine and rehabilitation. 2014;95(12):2382–9. pmid:25175161
  3. 3. Ichwan B, Darbha S, Shah MN, Thompson L, Evans DC, Boulger CT, et al. Geriatric-Specific Triage Criteria Are More Sensitive Than Standard Adult Criteria in Identifying Need for Trauma Center Care in Injured Older Adults. Annals of emergency medicine. 2014:S0196–644.
  4. 4. Wasserman EB, Shah MN, Jones CM, Cushman JT, Caterino JM, Bazarian JJ, et al. Identification of a neurologic scale that optimizes ems detection of older adult traumatic brain injury patients who require transport to a trauma center. Prehospital emergency care. 2014.
  5. 5. Lehmann R, Beekley A, Casey L, Salim A, Martin M. The impact of advanced age on trauma triage decisions and outcomes: a statewide analysis. American journal of surgery. 2009;197(5):571–4. pmid:19393350
  6. 6. Hwabejire JO, Kaafarani HM, Lee J, Yeh DD, Fagenholz P, King DR, et al. Patterns of Injury, Outcomes, and Predictors of In-Hospital and 1-Year Mortality in Nonagenarian and Centenarian Trauma Patients. JAMA surgery. 2014;149(10):1054–9. pmid:25133434
  7. 7. Oyetunji TA, Ong’uti SK, Bolorunduro OB, Gonzalez DO, Cornwell EE, Haider AH. Epidemiologic trend in elderly domestic injury. Journal of surgical research. 2012;173(2):206–11. pmid:21704329
  8. 8. National Registry of Diseases Office S. National Trauma Registry Annual Registry Report 2012–2013. 2014.
  9. 9. McKevitt EC, Calvert E, Ng A, Simons RK, Kirkpatrick AW, Appleton L, et al. Geriatric trauma: resource use and patient outcomes. Canadian journal of surgery. 2003;46(3):211.
  10. 10. Kelley-Quon L, Min L, Morley E, Hiatt JR, Cryer H, Tillou A. Functional status after injury: a longitudinal study of geriatric trauma. The American surgeon. 2010;76(10):1055–8. pmid:21105608
  11. 11. Tillou A, Kelley-Quon L, Burruss S, Morley E, Cryer H, Cohen M, et al. Long-term postinjury functional recovery: outcomes of geriatric consultation. JAMA surgery. 2014;149(1):83–9. pmid:24284836
  12. 12. Labib N, Nouh T, Winocour S, Deckelbaum D, Banici L, Fata P, et al. Severely injured geriatric population: morbidity, mortality, and risk factors. The Journal of trauma. 2011;71(6):1908–14. pmid:21537212
  13. 13. Hranjec T, Sawyer RG, Young JS, Swenson BR, Calland JF. Mortality factors in geriatric blunt trauma patients: creation of a highly predictive statistical model for mortality using 50,765 consecutive elderly trauma admissions from the National Sample Project. The American surgeon. 2012;78(12):1369–75. pmid:23265126
  14. 14. Thompson HJ, Rivara FP, Nathens A, Wang J, Jurkovich GJ, Mackenzie EJ. Development and validation of the mortality risk for trauma comorbidity index. Annals of surgery. 2010;252(2):370–5. pmid:20622665
  15. 15. West TA, Rivara FP, Cummings P, Jurkovich GJ, Maier RV. Harborview assessment for risk of mortality: an improved measure of injury severity on the basis of ICD-9-CM. The Journal of trauma. 2000;49(3):530–40. pmid:11003333
  16. 16. MacKenzie EJ, Rivara FP, Jurkovich GJ, Nathens AB, Frey KP, Egleston BL, et al. A national evaluation of the effect of trauma-center care on mortality. The New England journal of medicine. 2006;354(4):366–78. pmid:16436768
  17. 17. Moore L, Turgeon AF, Sirois MJ, Lavoie A. Trauma centre outcome performance: a comparison of young adults and geriatric patients in an inclusive trauma system. Injury. 2012;43(9):1580–5. pmid:21382620
  18. 18. Matsushima K, Schaefer EW, Won EJ, Armen SB, Indeck MC, Soybel DI. Positive and negative volume-outcome relationships in the geriatric trauma population. JAMA surgery. 2014;149(4):319–26. pmid:24452778
  19. 19. Fried LP, Tangen CM, Walston J, Newman AB, Hirsch C, Gottdiener J, et al. Frailty in older adults evidence for a phenotype. The Journals of Gerontology Series A: Biological Sciences and Medical Sciences. 2001;56(3):M146–M57.
  20. 20. Brooks SE, Mukherjee K, Gunter OL, Guillamondegui OD, Jenkins JM, Miller RS, et al. Do models incorporating comorbidities outperform those incorporating vital signs and injury pattern for predicting mortality in geriatric trauma? Journal of the American College of Surgeons. 2014;219(5):1020–7. pmid:25260686
  21. 21. Joseph B, Pandit V, Zangbar B, Kulvatunyou N, Tang A, O'Keeffe T, et al. Validating trauma-specific frailty index for geriatric trauma patients: a prospective analysis. Journal of the American College of Surgeons. 2014;219(1):10–7. pmid:24952434
  22. 22. Davie G, Cryer C, Langley J. Improving the predictive ability of the ICD-based Injury Severity Score. Injury prevention: journal of the International Society for Child and Adolescent Injury Prevention. 2008;14(4):250–5.
  23. 23. Morris JA, MacKenzie EJ, Edelstein SL. The effect of preexisting conditions on mortality in trauma patients. Jama. 1990;263(14):1942–6. pmid:2313871
  24. 24. MILZMAN DP, BOULANGER BR, RODRIGUEZ A, SODERSTROM CA, MITCHELL KA, MAGNANT CM. Pre-existing disease in trauma patients: a predictor of fate independent of age and injury severity score. Journal of Trauma and Acute Care Surgery. 1992;32(2):236–44.
  25. 25. Romero-Ortuno R, Kenny RA. The frailty index in Europeans: association with age and mortality. Age and ageing. 2012;41(5):684–9. pmid:22522775
  26. 26. Sternberg SA, Wershof S, Karunananthan S, Bergman H, Mark C. The identification of frailty: a systematic literature review. Journal of the American Geriatrics Society. 2011;59(11):2129–38. pmid:22091630
  27. 27. Moisey LL, Mourtzakis M, Cotton BA, Premji T, Heyland DK, Wade CE, et al. Skeletal muscle predicts ventilator-free days, ICU-free days, and mortality in elderly ICU patients. Crit Care. 2013;17(5):R206. pmid:24050662
  28. 28. Centers for Disease C, Prevention. Proposed Matrix of E-code Groupings| WISQARS | Injury Center | CDC. 2011.
  29. 29. Haider AH, Chang DC, Haut ER, Cornwell EE, Efron DT. Mechanism of injury predicts patient mortality and impairment after blunt trauma. The Journal of surgical research. 2009;153(1):138–42. pmid:18805554
  30. 30. Chien WC, Lai CH, Chung CH, Lin CH. A retrospective population-based data analyses of unintentional fall mortality and hospitalisation in Taiwan during 2005–2007. International journal of injury control and safety promotion. 2013;20(1):50–8. pmid:22486220
  31. 31. Glance LG, Osler TM, Mukamel DB, Meredith W, Wagner J, Dick AW. TMPM-ICD9: a trauma mortality prediction model based on ICD-9-CM codes. Annals of surgery. 2009;249(6):1032–9. pmid:19474696
  32. 32. American College of Surgeons Committee on T. National Trauma Data Standard of the National Trauma Data Bank—Data Dictionary. 2014.
  33. 33. Lefering R, Huber-Wagner S, Nienaber U, Maegele M, Bouillon B. Update of the trauma risk adjustment model of the TraumaRegister DGU™: the Revised Injury Severity Classification, version II. Critical care (London, England). 2014;18(5):476.
  34. 34. Champion HR, Copes WS, Sacco WJ, Lawnick MM, Bain LW, Gann DS, et al. A new characterization of injury severity. The Journal of trauma. 1990;30(5):539–45. pmid:2342136
  35. 35. Boyd CR, Tolson MA, Copes WS. Evaluating trauma care: the TRISS method. Trauma Score and the Injury Severity Score. The Journal of trauma. 1987;27(4):370–8. pmid:3106646
  36. 36. Baker SP, o'Neill B, Haddon W Jr, Long WB. The injury severity score: a method for describing patients with multiple injuries and evaluating emergency care. Journal of Trauma and Acute Care Surgery. 1974;14(3):187–96.
  37. 37. Champion HR, Sacco WJ, COPES WS, GANN DS, Gennarelli TA, Flanagan ME. A revision of the Trauma Score. Journal of Trauma and Acute Care Surgery. 1989;29(5):623–9.
  38. 38. Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. Journal of chronic diseases. 1987;40(5):373–83. pmid:3558716
  39. 39. 'Association for the Advancement of Automotive Medicine' 2011 [updated 201118 February 2015]. Available from: http://www.aaam.org/about-ais.html.
  40. 40. Butcher N, Balogh ZJ. The definition of polytrauma: the need for international consensus. Injury. 2009;40:S12–S22.
  41. 41. Pape H-C, Lefering R, Butcher N, Peitzman A, Leenen L, Marzi I, et al. The definition of polytrauma revisited: An international consensus process and proposal of the new ‘Berlin definition’. Journal of trauma and acute care surgery. 2014;77(5):780–6. pmid:25494433
  42. 42. Tinetti ME, Inouye SK, Gill TM, Doucette JT. Shared risk factors for falls, incontinence, and functional dependence: unifying the approach to geriatric syndromes. Jama. 1995;273(17):1348–53. pmid:7715059
  43. 43. Goodmanson NW, Rosengart MR, Barnato AE, Sperry JL, Peitzman AB, Marshall GT. Defining geriatric trauma: when does age make a difference? Surgery. 2012;152(4):668–74. pmid:23021136
  44. 44. Jacobs DG, Plaisier BR, Barie PS, Hammond JS, Holevar MR, Sinclair KE, et al. Practice management guidelines for geriatric trauma: the EAST Practice Management Guidelines Work Group. The Journal of trauma. 2003;54(2):391–416. pmid:12579072
  45. 45. Caterino JM, Valasek T, Werman HA. Identification of an age cutoff for increased mortality in patients with elderly trauma. The American journal of emergency medicine. 2010;28(2):151–8. pmid:20159383
  46. 46. Tebby J, Lecky F, Edwards A, Jenks T, Bouamra O, Dimitriou R, et al. Outcomes of polytrauma patients with diabetes mellitus. BMC medicine. 2014;12(1):111.
  47. 47. Schoeneberg C, Kauther MD, Hussmann B, Keitel J, Schmitz D, Lendemans S. Gender-specific differences in severely injured patients between 2002 and 2011: data analysis with matched-pair analysis. Critical care (London, England). 2013;17(6):10.
  48. 48. Haider AH, Crompton JG, Oyetunji T, Stevens KA, Efron DT, Kieninger AN, et al. Females have fewer complications and lower mortality following trauma than similarly injured males: a risk adjusted analysis of adults in the National Trauma Data Bank. Surgery. 2009;146(2):308–15. pmid:19628090
  49. 49. Gelbard R, Inaba K, Okoye OT, Morrell M, Saadi Z, Lam L, et al. Falls in the elderly: a modern look at an old problem. American journal of surgery. 2014;208(2):249–53. pmid:24814307
  50. 50. Ayoung-Chee P, McIntyre L, Ebel BE, Mack CD, McCormick W, Maier RV. Long-term outcomes of ground-level falls in the elderly. The journal of trauma and acute care surgery. 2014;76(2):498–503. pmid:24458057
  51. 51. Daniels R, van Rossum E, de Witte L, Kempen GI, van den Heuvel W. Interventions to prevent disability in frail community-dwelling elderly: a systematic review. BMC health services research. 2008;8(1):278.
  52. 52. Syddall H, Roberts HC, Evandrou M, Cooper C, Bergman H, Aihie S. Prevalence and correlates of frailty among community-dwelling older men and women: findings from the Hertfordshire Cohort Study. Age and ageing. 2010;39(2):197–203. pmid:20007127
  53. 53. Puts MT, Lips P, Deeg DJ. Sex differences in the risk of frailty for mortality independent of disability and chronic diseases. Journal of the American Geriatrics Society. 2005;53(1):40–7. pmid:15667374
  54. 54. Sletvold O, Helbostad JL, Thingstad P, Taraldsen K, Prestmo A, Lamb SE, et al. Effect of in-hospital comprehensive geriatric assessment (CGA) in older people with hip fracture. The protocol of the Trondheim Hip Fracture trial. BMC geriatrics. 2011;11:18. pmid:21510886
  55. 55. Fallon WF, Rader E, Zyzanski S, Mancuso C, Martin B, Breedlove L, et al. Geriatric outcomes are improved by a geriatric trauma consultation service. The Journal of trauma. 2006;61(5):1040–6. pmid:17099506
  56. 56. Ministry of Health S. Ministry of Health Population Statistics. Available from: https://www.moh.gov.sg/content/moh_web/home/statistics/Health_Facts_Singapore/Population_And_Vital_Statistics.html.
  57. 57. Ho AF, Chew D, Wong TH, Ng YY, Pek PP, Lim SH, et al. Prehospital Trauma Care in Singapore. Prehospital emergency care: official journal of the National Association of EMS Physicians and the National Association of State EMS Directors. 2014.
  58. 58. Wehren LE, Hawkes WG, Orwig DL, Hebel JR, Zimmerman SI, Magaziner J. Gender differences in mortality after hip fracture: the role of infection. Journal of bone and mineral research: the official journal of the American Society for Bone and Mineral Research. 2003;18(12):2231–7.
  59. 59. Holt G, Smith R, Duncan K, Hutchison JD, Gregori A. Gender differences in epidemiology and outcome after hip fracture: evidence from the Scottish Hip Fracture Audit. The Journal of bone and joint surgeryBritish volume. 2008;90(4):480–3.
  60. 60. Koh G-H, Tai B, Ang L-W, Heng D, Yuan J-M, Koh W-P. All-cause and cause-specific mortality after hip fracture among Chinese women and men. Osteoporosis International. 2013;24(7):1981–9. pmid:23224227
  61. 61. Abrahamsen B, Van Staa T, Ariely R, Olson M, Cooper C. Excess mortality following hip fracture: a systematic epidemiological review. Osteoporosis International. 2009;20(10):1633–50. pmid:19421703
  62. 62. Sterling RS. Gender and race/ethnicity differences in hip fracture incidence, morbidity, mortality, and function. Clinical orthopaedics and related research. 2011;469(7):1913–8. pmid:21161737
  63. 63. Krishnan M, Beck S, Havelock W, Eeles E, Hubbard RE, Johansen A. Predicting outcome after hip fracture: using a frailty index to integrate comprehensive geriatric assessment results. Age and ageing. 2014;43(1):122–6. pmid:23832264
  64. 64. Watne LO, Torbergsen AC, Conroy S, Engedal K, Frihagen F, Hjorthaug GA, et al. The effect of a pre-and postoperative orthogeriatric service on cognitive function in patients with hip fracture: randomized controlled trial (Oslo Orthogeriatric Trial). BMC medicine. 2014;12(1):63.