j o u r n a l o f s u r g i c a l r e s e a r c h 1 9 5 ( 2 0 1 5 ) 1 e9
Available online at www.sciencedirect.com
ScienceDirect journal homepage: www.JournalofSurgicalResearch.com
Association for Academic Surgery
Traumatic brain injury in the elderly: morbidity and mortality trends and risk factors R. Sterling Haring, BA,a,b,c,1 Kunal Narang, MPH,c,1 Joseph K. Canner, MHS,c Anthony O. Asemota, MBBS, MPH,c,d Benjamin P. George, MD, MPH,c,e Shalini Selvarajah, MD, MPH,c Adil H. Haider, MD, MPH,a,c and Eric B. Schneider, PhDc,* a
Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland b Department of Osteopathic Medicine, Lake Erie College of Osteopathic Medicine, Bradenton, Florida c Department of Surgery, Center for Surgical Trials and Outcomes Research (CSTOR), Johns Hopkins University, Baltimore, Maryland d Department of Neurology and Neurosurgery, Johns Hopkins University, Baltimore, Maryland e Department of Neurology, School of Medicine and Dentistry, University of Rochester, Rochester, New York
article info
abstract
Article history:
An estimated 1.7 million people sustain a traumatic brain injury (TBI) annually in the
Received 11 November 2014
United States. We sought to examine factors contributing to mortality among TBI patients
Received in revised form
aged 65 y in the United States. TBI data from the Nationwide Inpatient Sample were
2 January 2015
combined from 2000e2010. Patients were stratified by age, sex, mechanism of injury, payer
Accepted 9 January 2015
status, comorbidity, injury severity, and other factors. Odds of death were explored using
Available online 15 January 2015
an adjusted multivariable logistic regression. A total of 950,132 TBI-related hospitalizations
Keywords:
most common mechanism of injury was falling, and falls were more common among the
Older adult
oldest age groups. Logistic regression analysis showed highest odds of death among male
TBI
patients, those whose mechanism of injury was motor vehicle related, patients with three
Mortality
or more comorbidities, and patients who were designated as self-paying.
and 107,666 TBI-related deaths occurred among adults aged 65 y from 2000e2010. The
Morbidity
ª 2015 Elsevier Inc. All rights reserved.
Risk factors
1.
Introduction
Traumatic brain injury (TBI) among adults age 65 y is a major public health problem in the United States [1]. The Centers for Disease Control and Prevention (CDC) estimate that at least
1.7 million people sustain a TBI annually [2]. Of those individuals, 52,000 die and approximately 275,000 are hospitalized, with a significant proportion being older adults. From 2002e2006, the CDC estimated that older adults accounted for over 80,000 of the TBI-related hospitalizations per year. This is
* Corresponding author. Department of Surgery, Center for Surgical Trials and Outcomes Research (CSTOR), Johns Hopkins University, 600 N. Wolfe Street, Blalock 618, Baltimore, MD 21287. Tel.: þ1 410 502 2601; fax: þ1 410 955 8101. E-mail address: [email protected] (E.B. Schneider). 1 Both authors contributed equally to this work. 0022-4804/$ e see front matter ª 2015 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.jss.2015.01.017
2
j o u r n a l o f s u r g i c a l r e s e a r c h 1 9 5 ( 2 0 1 5 ) 1 e9
more than double that of TBI-related hospitalizations for children aged 0e14 y [3]. For many patients, the effects of TBI can be felt long after discharge; one study estimated that up to 43% of hospitalized TBI survivors experience long-term disability [4]. The adverse neuropsychological sequelae of TBI can affect an individual’s function in both social and work environments for 6e12 mo after injury or longer, and up to 20% of survivors do not return to work within the year after an employment-related TBI [5,6]. The economic impact of this loss of productivity is just as notable: in 2000, these losses totaled an estimated $76.5 billion in the United States alone, representing a sizeable increase from the 1995 level of $56.3 billion [7,8]. The proportion of TBI among elderly populations is expected to increase in coming years as the proportion of elderly individuals in the United States grows from 13% of the 2006 population to an estimated 20% by 2030 [9e11]. This growth will be most visible among the oldest Americans, as the number of individuals aged 85 y is expected to double by 2025 [10]. This study sought to identify and characterize the aggregate number of TBI-related hospitalizations among older adults from 2000e2010 using data from over 40 states. We examine the impact of mechanism of external injury, sex, payer status, and other factors on in-hospital mortality.
2.
Methods
A nationwide retrospective observational analysis was completed using hospital discharge data from the Nationwide Inpatient Sample (NIS) of the Healthcare Cost and Utilization Project of the Agency for Healthcare Research and Quality [12]. The NIS is an all-payer inpatient care database containing approximately 8 million annual hospital stays and can be weighted to approximate the entire US population. For the most recent year, 2010, the NIS accounted for 1051 hospitals in 45 states, representing a 20% stratified sample of all community hospitals in the United States. Although the NIS provides a variety of information relating to patient demographics, diagnosis, and hospital course, no protected health information is included. The Johns Hopkins Institutional Review Board approved the study. Over 425 million hospitalizations from 2000e2010 are included in the NIS database [12]. We identified patients aged 65 y who had a primary or secondary diagnosis of TBI (as identified using the International Classification of Diseases, Ninth Edition, Clinical Modification [ICD-9-CM] [800.0e801.9, 803.0e804.9, and 850.0e854.19, as recommended by the CDC]) [2,13]. Within this group, we identified those whose records included data for sex, in-hospital mortality status, external mechanism of injury, severity of head injury, comorbidities, and insurance type, as well as hospital characteristics such as region, location, and teaching status for study inclusion. Because of age-reporting differences between states in the NIS (e.g., some states report age in 5-y increments), we chose to stratify age of patients into five age groups (65e69, 70e74, 75e79, 80e84, and 85) [12]. Mechanisms of external injury classified by E-codes were identified using the CDC recommended framework for External Cause of Injury Categorization for ICD-9-CM codes [14]. In keeping with previous work by
the CDC on TBI-related hospitalization, we used only the first E-code when determining mechanism of external injury. To measure the burden of comorbid disease, we used the reliable and validated Charlson comorbidity index [15]. In keeping with previous TBI-related hospitalization literature, we dichotomized calculated Charlson comorbidity scores as follows: patients with two or fewer comorbid diseases versus those with three or more comorbid diseases [16]. In comparing injuries, we used the Abbreviated Injury Scale (AIS). The AIS is the most widely used anatomic scale for rating severity of injuries [17,18] and has been historically used in conjunction with Injury Severity Scores to identify the effect of multiple injuries for trauma victims [19]. AIS scores are assigned by healthcare providers at the time of a patient’s initial evaluation; data on injury type, location, and severity are documented as a part of the AIS notation [18]. We used the freely available Stata program International Classification of Diseases Programs for Injury Classification to calculate headspecific AIS scores for all patients [20,21]. The program works by translating ICD-9 diagnosis codes into commonly used scoring systems and scales [20]. International Classification of Diseases Programs for Injury Classification is current to both ICD-9-CM and the most recent iteration of the AIS [22]. In our analysis, AIS scores for Injury Severity Score body region 1 (head and/or neck) were categorized on a scale from 1 (“minor”) to 6 (“unsurvivable”). To classify TBI severity, we used the highest head-AIS score for a given patient [23]. Race is not collected and/or reported by certain states in the NIS, and collection patterns varied from year to year [12]. An a priori decision was made to include only those patients whose demographic information included data on race if doing so would reduce the size of the data set by less than 10%; otherwise, race would be considered in a separate subset analysis. Patients whose race was available were grouped into four categories as follows: white, black, Hispanic, and other (where “other” included individuals identified in the data set as being Asian, Native American, or other.) The race variable provided in the NIS includes “Hispanic” as an exclusive category; therefore, it was not possible to examine further subsets of race within the group of individuals identified as being Hispanic [12]. Hospital regions were separated into four categories as follows: northeast, midwest, south, and west. Hospital locations were dichotomized into rural and urban (as defined by the American Hospital Association Annual Survey of Hospitals before 2004 and using updated 2000 census data from 2004 on), and hospital teaching status was dichotomized into nonteaching and teaching. NIS data from 2000e2010 were combined for analysis. Patient age group, sex, in-hospital mortality, mechanism of injury, insurance type, severity of injury, comorbid disease, and hospital characteristics were reported using descriptive statistics. TBI-related hospitalizations within each age group were stratified by mechanism of external injury. Alpha was defined as 0.05, and P values less than this were considered statistically significant. All data analysis was conducted using Stata 12.1 (StataCorp, College Station, TX). Multivariable logistic regression models were used to calculate the odds of death among older adult TBI patients. These were adjusted for sex, age group, external mechanism
j o u r n a l o f s u r g i c a l r e s e a r c h 1 9 5 ( 2 0 1 5 ) 1 e9
of injury, insurance type, comorbid disease, injury severity, hospital region, hospital location, and hospital teaching status [16]. A sensitivity analysis with separate multivariable logistic regression models was used to look at odds of death for TBI patients with all primary analysis factors as well as race. The 209,476 patients with a missing race variable accounted for 22% of our primary analysis sample, which exceeded the 10% a priori threshold and thus a subset analysis was performed for all patients for whom race was known. Population-based incidence rates were calculated using data from the US Census Bureau [24]. As a sensitivity analysis, regression models were repeated accounting for hospital-specific patient clustering using clustered-robust standard error (SE) estimates. The results from these models were then compared with those from the models using standard SE estimates to determine if all significant associations between predictors and outcomes identified in the standard SE models remained significant in models using cluster-robust SE estimates.
3.
Results
There were approximately 424,776,000 hospitalizations in the United States from 2000e2010 (Table 1). Of these, 146,396,357 (34.5%) occurred among individuals aged 65 y. TBI was the primary or secondary diagnosis in 959,743 (0.7%) of this set, and we identified 950,132 (99.0%) whose records included the data points described previously (Table 1). Data on race were missing for 209,476 (22.0%) of the patients, so a subset was created including the 740,656 TBI patients whose records included all primary analysis factors and race.
3.1.
Demographics
Patients aged 65e69 accounted for 123,930 (13.0%) of TBIrelated hospitalizations, where patients 85 accounted for 287,976 (30.3%) over the study period (Table 1). The rate of TBIrelated hospitalizations in the US population also increased by age, from 106.3 per 100,000 for ages 65e69 to 547.4 per 100,000 for ages 85 (Supplemental Table 1). Of TBIs requiring hospitalization among older adults, 21,828 (11.4%) resulted in death. Females accounted for 503,140 (53.0%) of TBI-related hospitalizations among the elderly, and males accounted for 446,992 (47.0%; Table 1). Approximately 82.6% of patients listed Medicare as payer, 13.2% private insurance/health maintenance organization, 1.2% Medicaid, and 1.2% were identified as self-paying (Table 1). As identified using the previously described Charlson comorbidity index, approximately 87.2% of the study group had two or fewer comorbid diseases, whereas 12.8% had three or more (Table 1). Proportional causality by external mechanism of injury for TBI-related hospitalizations among older adults was as follows: 10.0% for motor vehicle-related, 65.3% for falls, 0.8% for struck by and against, 0.7% for assault (including firearms), and 8.7% for other injuries (Table 1). The external mechanism of injury was missing for 13.9% of TBI-related hospitalizations. Causation varied by age stratum (Figure); the percentage of TBI-related hospitalizations attributable to falls increased with age, from 51.3% in the 65e69 age group to 74.0% in the 85 age group, whereas the percentage attributable to motor
3
vehicle-related injuries decreased with age, from 19.3% for 65e69 age group to 4.3% for 85 age group (Table 2). Approximately 16.7% of individuals with TBI had a headAIS score of 2, 30.2% had a score of 3, 47.4% had a score of 4, and 2.3% had an AIS score of 5 (Table 1). The Southern census region accounted for the greatest share of TBI-related hospitalizations with 35.1% (Table 3). Approximately 91.3% of all TBI-related hospitalizations were at urban hospitals, whereas 8.7% were at rural hospitals; 55.9% were designated as teaching hospitals and 44.1% as nonteaching hospitals.
3.2.
Mortality
When compared with the 65e69 age group, the adjusted odds of death increased with age (Supplemental Table 1). Compared with males, females had 33.1% lower odds of death after adjusting for all other covariates (odds ratio [OR] 0.67, 95% confidence interval [CI]: 0.65e0.69, P < 0.001). Significantly lower odds of death were also seen among those whose external mechanisms of injury were listed as falls, struck by and against, and assault as compared with motor vehicle traffic-related accidents. Compared with Medicare patients, those designated as selfpaying for the TBI-related hospitalization had a 91% increase in odds of death after adjusting for all other covariates (OR 1.91, 95% CI: 1.62e2.25, P < 0.001). After adjustment, there was a 30% increase in odds of death at teaching hospitals compared with nonteaching hospitals (OR 1.30, 95% CI: 1.23e1.37, P < 0.001). Patients with three or more comorbid diseases had approximately 48% increase in odds of death compared with patients with two or fewer comorbidities after adjusting for all other covariates (OR 1.48, 95% CI: 1.42e1.55, P < 0.001). After adjustment, patients with a head-AIS score of 3 or 4 were six times more likely to die than those with a score of 1, whereas those with TBI having a head-AIS score of 5 demonstrated 184 times greater odds of mortality compared with those having head-AIS ¼ 1 (OR 183.5, 95% CI: 147.9e227.8, P < 0.001).
3.3.
Subset analysis
There were 740,656 TBI-related hospitalizations among older adults from 2000e2010 in the United States whose race was known (Supplemental Table 2). Whites accounted for the greatest proportion of all TBI-related hospitalizations, making up approximately 83.1% of TBI hospitalizations. Blacks accounted for 5.1%, Hispanics for 6.0%, and all others accounted for 5.6% (Supplemental Table 2). After adjusting for all other covariates, the odds of death were significantly reduced for blacks (OR 0.78, 95% CI: 0.71e0.85, P < 0.001) and Hispanics (OR 0.83, 95% CI: 0.73e0.94, P ¼ 0.004) when compared with whites (Supplemental Table 3). Overall trends for age, sex, mechanism of external injury, payer status, and hospital demographics were similar to those in the primary analysis.
3.4.
Sensitivity analysis
The results from logistic regression models constructed to examine possible effects of patient clustering within specific hospitals were similar to those found in the simple models.
4
Table 1 e Patient-specific characteristics of TBI-related hospitalizations among older adults, aged ‡65 y, in the United States from 2000e2010. Patient characteristics
Year 2000
2001
HMO ¼ health maintenance organization.
2002
2003
2004
2005
2006
2007
2008
2009
2010
64,759
76,039
82,196
80,568
91,802
95,679
107,142
110,521
128,837
14,253 (13.3) 15,068 (14.1) 20,121 (18.8) 23,869 (22.3) 33,831 (31.6)
15,384 (13.9) 15,660 (14.2) 20,448 (18.5) 24,253 (21.9) 34,777 (31.5)
7774 10,124 13,565 14,392 18,905
(12) (15.6) (20.9) (22.2) (29.2)
8494 (13.1)
9153 11,664 15,760 17,409 22,053
(12) (15.3) (20.7) (22.9) (29)
11,048 13,210 16,123 18,690 23,125
(13.4) (16.1) (19.6) (22.7) (28.1)
9790 (12.9) 10,577 (12.9)
30,091 (46.5) 35,365 (46.5) 39,243 (47.7) 34,668 (53.5) 40,674 (53.5) 42,953 (52.3)
10,103 11,796 15,859 18,433 24,377
(12.5) (14.6) (19.7) (22.9) (30.3)
11,852 13,546 18,132 20,886 27,386
(12.9) (14.8) (19.8) (22.8) (29.8)
9275 (11.5) 10,236 (11.2)
12,423 14,239 18,515 21,323 29,178
(13) (14.9) (19.4) (22.3) (30.5)
9992 (10.4) 10,885 (10.2) 10,640 (9.63)
37,120 (46.1) 43,194 (47.1) 45,423 (47.5) 50,319 (47) 43,448 (53.9) 48,608 (52.9) 50,256 (52.5) 56,823 (53)
52,488 (47.5) 58,033 (52.5)
18,324 18,843 23,124 27,542 41,004
(14.2) (14.6) (17.9) (21.4) (31.8)
950,132 123,930 141,288 185.506 211,431 287,976
(13)
Available online at www.sciencedirect.com
ScienceDirect journal homepage: www.JournalofSurgicalResearch.com
Association for Academic Surgery
Traumatic brain injury in the elderly: morbidity and mortality trends and risk factors R. Sterling Haring, BA,a,b,c,1 Kunal Narang, MPH,c,1 Joseph K. Canner, MHS,c Anthony O. Asemota, MBBS, MPH,c,d Benjamin P. George, MD, MPH,c,e Shalini Selvarajah, MD, MPH,c Adil H. Haider, MD, MPH,a,c and Eric B. Schneider, PhDc,* a
Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland b Department of Osteopathic Medicine, Lake Erie College of Osteopathic Medicine, Bradenton, Florida c Department of Surgery, Center for Surgical Trials and Outcomes Research (CSTOR), Johns Hopkins University, Baltimore, Maryland d Department of Neurology and Neurosurgery, Johns Hopkins University, Baltimore, Maryland e Department of Neurology, School of Medicine and Dentistry, University of Rochester, Rochester, New York
article info
abstract
Article history:
An estimated 1.7 million people sustain a traumatic brain injury (TBI) annually in the
Received 11 November 2014
United States. We sought to examine factors contributing to mortality among TBI patients
Received in revised form
aged 65 y in the United States. TBI data from the Nationwide Inpatient Sample were
2 January 2015
combined from 2000e2010. Patients were stratified by age, sex, mechanism of injury, payer
Accepted 9 January 2015
status, comorbidity, injury severity, and other factors. Odds of death were explored using
Available online 15 January 2015
an adjusted multivariable logistic regression. A total of 950,132 TBI-related hospitalizations
Keywords:
most common mechanism of injury was falling, and falls were more common among the
Older adult
oldest age groups. Logistic regression analysis showed highest odds of death among male
TBI
patients, those whose mechanism of injury was motor vehicle related, patients with three
Mortality
or more comorbidities, and patients who were designated as self-paying.
and 107,666 TBI-related deaths occurred among adults aged 65 y from 2000e2010. The
Morbidity
ª 2015 Elsevier Inc. All rights reserved.
Risk factors
1.
Introduction
Traumatic brain injury (TBI) among adults age 65 y is a major public health problem in the United States [1]. The Centers for Disease Control and Prevention (CDC) estimate that at least
1.7 million people sustain a TBI annually [2]. Of those individuals, 52,000 die and approximately 275,000 are hospitalized, with a significant proportion being older adults. From 2002e2006, the CDC estimated that older adults accounted for over 80,000 of the TBI-related hospitalizations per year. This is
* Corresponding author. Department of Surgery, Center for Surgical Trials and Outcomes Research (CSTOR), Johns Hopkins University, 600 N. Wolfe Street, Blalock 618, Baltimore, MD 21287. Tel.: þ1 410 502 2601; fax: þ1 410 955 8101. E-mail address: [email protected] (E.B. Schneider). 1 Both authors contributed equally to this work. 0022-4804/$ e see front matter ª 2015 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.jss.2015.01.017
2
j o u r n a l o f s u r g i c a l r e s e a r c h 1 9 5 ( 2 0 1 5 ) 1 e9
more than double that of TBI-related hospitalizations for children aged 0e14 y [3]. For many patients, the effects of TBI can be felt long after discharge; one study estimated that up to 43% of hospitalized TBI survivors experience long-term disability [4]. The adverse neuropsychological sequelae of TBI can affect an individual’s function in both social and work environments for 6e12 mo after injury or longer, and up to 20% of survivors do not return to work within the year after an employment-related TBI [5,6]. The economic impact of this loss of productivity is just as notable: in 2000, these losses totaled an estimated $76.5 billion in the United States alone, representing a sizeable increase from the 1995 level of $56.3 billion [7,8]. The proportion of TBI among elderly populations is expected to increase in coming years as the proportion of elderly individuals in the United States grows from 13% of the 2006 population to an estimated 20% by 2030 [9e11]. This growth will be most visible among the oldest Americans, as the number of individuals aged 85 y is expected to double by 2025 [10]. This study sought to identify and characterize the aggregate number of TBI-related hospitalizations among older adults from 2000e2010 using data from over 40 states. We examine the impact of mechanism of external injury, sex, payer status, and other factors on in-hospital mortality.
2.
Methods
A nationwide retrospective observational analysis was completed using hospital discharge data from the Nationwide Inpatient Sample (NIS) of the Healthcare Cost and Utilization Project of the Agency for Healthcare Research and Quality [12]. The NIS is an all-payer inpatient care database containing approximately 8 million annual hospital stays and can be weighted to approximate the entire US population. For the most recent year, 2010, the NIS accounted for 1051 hospitals in 45 states, representing a 20% stratified sample of all community hospitals in the United States. Although the NIS provides a variety of information relating to patient demographics, diagnosis, and hospital course, no protected health information is included. The Johns Hopkins Institutional Review Board approved the study. Over 425 million hospitalizations from 2000e2010 are included in the NIS database [12]. We identified patients aged 65 y who had a primary or secondary diagnosis of TBI (as identified using the International Classification of Diseases, Ninth Edition, Clinical Modification [ICD-9-CM] [800.0e801.9, 803.0e804.9, and 850.0e854.19, as recommended by the CDC]) [2,13]. Within this group, we identified those whose records included data for sex, in-hospital mortality status, external mechanism of injury, severity of head injury, comorbidities, and insurance type, as well as hospital characteristics such as region, location, and teaching status for study inclusion. Because of age-reporting differences between states in the NIS (e.g., some states report age in 5-y increments), we chose to stratify age of patients into five age groups (65e69, 70e74, 75e79, 80e84, and 85) [12]. Mechanisms of external injury classified by E-codes were identified using the CDC recommended framework for External Cause of Injury Categorization for ICD-9-CM codes [14]. In keeping with previous work by
the CDC on TBI-related hospitalization, we used only the first E-code when determining mechanism of external injury. To measure the burden of comorbid disease, we used the reliable and validated Charlson comorbidity index [15]. In keeping with previous TBI-related hospitalization literature, we dichotomized calculated Charlson comorbidity scores as follows: patients with two or fewer comorbid diseases versus those with three or more comorbid diseases [16]. In comparing injuries, we used the Abbreviated Injury Scale (AIS). The AIS is the most widely used anatomic scale for rating severity of injuries [17,18] and has been historically used in conjunction with Injury Severity Scores to identify the effect of multiple injuries for trauma victims [19]. AIS scores are assigned by healthcare providers at the time of a patient’s initial evaluation; data on injury type, location, and severity are documented as a part of the AIS notation [18]. We used the freely available Stata program International Classification of Diseases Programs for Injury Classification to calculate headspecific AIS scores for all patients [20,21]. The program works by translating ICD-9 diagnosis codes into commonly used scoring systems and scales [20]. International Classification of Diseases Programs for Injury Classification is current to both ICD-9-CM and the most recent iteration of the AIS [22]. In our analysis, AIS scores for Injury Severity Score body region 1 (head and/or neck) were categorized on a scale from 1 (“minor”) to 6 (“unsurvivable”). To classify TBI severity, we used the highest head-AIS score for a given patient [23]. Race is not collected and/or reported by certain states in the NIS, and collection patterns varied from year to year [12]. An a priori decision was made to include only those patients whose demographic information included data on race if doing so would reduce the size of the data set by less than 10%; otherwise, race would be considered in a separate subset analysis. Patients whose race was available were grouped into four categories as follows: white, black, Hispanic, and other (where “other” included individuals identified in the data set as being Asian, Native American, or other.) The race variable provided in the NIS includes “Hispanic” as an exclusive category; therefore, it was not possible to examine further subsets of race within the group of individuals identified as being Hispanic [12]. Hospital regions were separated into four categories as follows: northeast, midwest, south, and west. Hospital locations were dichotomized into rural and urban (as defined by the American Hospital Association Annual Survey of Hospitals before 2004 and using updated 2000 census data from 2004 on), and hospital teaching status was dichotomized into nonteaching and teaching. NIS data from 2000e2010 were combined for analysis. Patient age group, sex, in-hospital mortality, mechanism of injury, insurance type, severity of injury, comorbid disease, and hospital characteristics were reported using descriptive statistics. TBI-related hospitalizations within each age group were stratified by mechanism of external injury. Alpha was defined as 0.05, and P values less than this were considered statistically significant. All data analysis was conducted using Stata 12.1 (StataCorp, College Station, TX). Multivariable logistic regression models were used to calculate the odds of death among older adult TBI patients. These were adjusted for sex, age group, external mechanism
j o u r n a l o f s u r g i c a l r e s e a r c h 1 9 5 ( 2 0 1 5 ) 1 e9
of injury, insurance type, comorbid disease, injury severity, hospital region, hospital location, and hospital teaching status [16]. A sensitivity analysis with separate multivariable logistic regression models was used to look at odds of death for TBI patients with all primary analysis factors as well as race. The 209,476 patients with a missing race variable accounted for 22% of our primary analysis sample, which exceeded the 10% a priori threshold and thus a subset analysis was performed for all patients for whom race was known. Population-based incidence rates were calculated using data from the US Census Bureau [24]. As a sensitivity analysis, regression models were repeated accounting for hospital-specific patient clustering using clustered-robust standard error (SE) estimates. The results from these models were then compared with those from the models using standard SE estimates to determine if all significant associations between predictors and outcomes identified in the standard SE models remained significant in models using cluster-robust SE estimates.
3.
Results
There were approximately 424,776,000 hospitalizations in the United States from 2000e2010 (Table 1). Of these, 146,396,357 (34.5%) occurred among individuals aged 65 y. TBI was the primary or secondary diagnosis in 959,743 (0.7%) of this set, and we identified 950,132 (99.0%) whose records included the data points described previously (Table 1). Data on race were missing for 209,476 (22.0%) of the patients, so a subset was created including the 740,656 TBI patients whose records included all primary analysis factors and race.
3.1.
Demographics
Patients aged 65e69 accounted for 123,930 (13.0%) of TBIrelated hospitalizations, where patients 85 accounted for 287,976 (30.3%) over the study period (Table 1). The rate of TBIrelated hospitalizations in the US population also increased by age, from 106.3 per 100,000 for ages 65e69 to 547.4 per 100,000 for ages 85 (Supplemental Table 1). Of TBIs requiring hospitalization among older adults, 21,828 (11.4%) resulted in death. Females accounted for 503,140 (53.0%) of TBI-related hospitalizations among the elderly, and males accounted for 446,992 (47.0%; Table 1). Approximately 82.6% of patients listed Medicare as payer, 13.2% private insurance/health maintenance organization, 1.2% Medicaid, and 1.2% were identified as self-paying (Table 1). As identified using the previously described Charlson comorbidity index, approximately 87.2% of the study group had two or fewer comorbid diseases, whereas 12.8% had three or more (Table 1). Proportional causality by external mechanism of injury for TBI-related hospitalizations among older adults was as follows: 10.0% for motor vehicle-related, 65.3% for falls, 0.8% for struck by and against, 0.7% for assault (including firearms), and 8.7% for other injuries (Table 1). The external mechanism of injury was missing for 13.9% of TBI-related hospitalizations. Causation varied by age stratum (Figure); the percentage of TBI-related hospitalizations attributable to falls increased with age, from 51.3% in the 65e69 age group to 74.0% in the 85 age group, whereas the percentage attributable to motor
3
vehicle-related injuries decreased with age, from 19.3% for 65e69 age group to 4.3% for 85 age group (Table 2). Approximately 16.7% of individuals with TBI had a headAIS score of 2, 30.2% had a score of 3, 47.4% had a score of 4, and 2.3% had an AIS score of 5 (Table 1). The Southern census region accounted for the greatest share of TBI-related hospitalizations with 35.1% (Table 3). Approximately 91.3% of all TBI-related hospitalizations were at urban hospitals, whereas 8.7% were at rural hospitals; 55.9% were designated as teaching hospitals and 44.1% as nonteaching hospitals.
3.2.
Mortality
When compared with the 65e69 age group, the adjusted odds of death increased with age (Supplemental Table 1). Compared with males, females had 33.1% lower odds of death after adjusting for all other covariates (odds ratio [OR] 0.67, 95% confidence interval [CI]: 0.65e0.69, P < 0.001). Significantly lower odds of death were also seen among those whose external mechanisms of injury were listed as falls, struck by and against, and assault as compared with motor vehicle traffic-related accidents. Compared with Medicare patients, those designated as selfpaying for the TBI-related hospitalization had a 91% increase in odds of death after adjusting for all other covariates (OR 1.91, 95% CI: 1.62e2.25, P < 0.001). After adjustment, there was a 30% increase in odds of death at teaching hospitals compared with nonteaching hospitals (OR 1.30, 95% CI: 1.23e1.37, P < 0.001). Patients with three or more comorbid diseases had approximately 48% increase in odds of death compared with patients with two or fewer comorbidities after adjusting for all other covariates (OR 1.48, 95% CI: 1.42e1.55, P < 0.001). After adjustment, patients with a head-AIS score of 3 or 4 were six times more likely to die than those with a score of 1, whereas those with TBI having a head-AIS score of 5 demonstrated 184 times greater odds of mortality compared with those having head-AIS ¼ 1 (OR 183.5, 95% CI: 147.9e227.8, P < 0.001).
3.3.
Subset analysis
There were 740,656 TBI-related hospitalizations among older adults from 2000e2010 in the United States whose race was known (Supplemental Table 2). Whites accounted for the greatest proportion of all TBI-related hospitalizations, making up approximately 83.1% of TBI hospitalizations. Blacks accounted for 5.1%, Hispanics for 6.0%, and all others accounted for 5.6% (Supplemental Table 2). After adjusting for all other covariates, the odds of death were significantly reduced for blacks (OR 0.78, 95% CI: 0.71e0.85, P < 0.001) and Hispanics (OR 0.83, 95% CI: 0.73e0.94, P ¼ 0.004) when compared with whites (Supplemental Table 3). Overall trends for age, sex, mechanism of external injury, payer status, and hospital demographics were similar to those in the primary analysis.
3.4.
Sensitivity analysis
The results from logistic regression models constructed to examine possible effects of patient clustering within specific hospitals were similar to those found in the simple models.
4
Table 1 e Patient-specific characteristics of TBI-related hospitalizations among older adults, aged ‡65 y, in the United States from 2000e2010. Patient characteristics
Year 2000
2001
HMO ¼ health maintenance organization.
2002
2003
2004
2005
2006
2007
2008
2009
2010
64,759
76,039
82,196
80,568
91,802
95,679
107,142
110,521
128,837
14,253 (13.3) 15,068 (14.1) 20,121 (18.8) 23,869 (22.3) 33,831 (31.6)
15,384 (13.9) 15,660 (14.2) 20,448 (18.5) 24,253 (21.9) 34,777 (31.5)
7774 10,124 13,565 14,392 18,905
(12) (15.6) (20.9) (22.2) (29.2)
8494 (13.1)
9153 11,664 15,760 17,409 22,053
(12) (15.3) (20.7) (22.9) (29)
11,048 13,210 16,123 18,690 23,125
(13.4) (16.1) (19.6) (22.7) (28.1)
9790 (12.9) 10,577 (12.9)
30,091 (46.5) 35,365 (46.5) 39,243 (47.7) 34,668 (53.5) 40,674 (53.5) 42,953 (52.3)
10,103 11,796 15,859 18,433 24,377
(12.5) (14.6) (19.7) (22.9) (30.3)
11,852 13,546 18,132 20,886 27,386
(12.9) (14.8) (19.8) (22.8) (29.8)
9275 (11.5) 10,236 (11.2)
12,423 14,239 18,515 21,323 29,178
(13) (14.9) (19.4) (22.3) (30.5)
9992 (10.4) 10,885 (10.2) 10,640 (9.63)
37,120 (46.1) 43,194 (47.1) 45,423 (47.5) 50,319 (47) 43,448 (53.9) 48,608 (52.9) 50,256 (52.5) 56,823 (53)
52,488 (47.5) 58,033 (52.5)
18,324 18,843 23,124 27,542 41,004
(14.2) (14.6) (17.9) (21.4) (31.8)
950,132 123,930 141,288 185.506 211,431 287,976
(13)
