Introduction: Traumatic brain injury (TBI) is a leading cause of disability and is associated with decreased survival. Although it is generally accepted that TBI increases risk of death in acute and postacute periods after injury, causes of premature death after TBI in the long term are less clear. Methods: A cohort sample of Olmsted County, Minnesota, residents with confirmed TBI from January 1987 through December 1999 was identified. Each case was assigned an age- and sex-matched non-TBI referent case, called regular referent. Confirmed TBI cases with simultaneous nonhead injuries were identified, labeled special cases. These were assigned 2 age- and sex-matched special referents with nonhead injuries of similar severity. Underlying causes of death in each case were categorized using death certificates, International Classification of Diseases, Ninth Revision, International Statistical Classification of Diseases, Tenth Revision, and manual health record review. Comparisons were made over the study period and among 6-month survivors. Results: Case-regular referent pairs (n = 1,257) were identified over the study period, and 221 were special cases. In total, 237 deaths occurred among these pairs. A statistically significant difference was observed between total number of deaths among all cases (n = 139, 11%) and regular referents (n = 98, 8%) (p = 0.006) over the entire period. This outcome was not true for special cases (32/221, 14%) and special referents (61/441, 14%) (p = 0.81). A greater proportion of deaths by external cause than all other causes was observed in all cases (52/139, 37%) versus regular referents (3/98, 3%) and in special cases (13/32, 41%) versus special referents (5/61, 8%) (p < 0.001 for both). Among all case-referent pairs surviving 6 months, no difference was found between total number of deaths (p = 0.82). The underlying cause of death between these 2 groups was significantly different for external causes only (p < 0.01). For special cases surviving 6 months versus special referents, no difference was observed in total number of deaths (p = 0.24) or underlying causes of death (p = 1.00) between groups. Discussion/Conclusion: This population-based case-matched referent study showed that increased risk of death after TBI existed only during the first 6 months after injury, and the difference was due to external causes.

Traumatic brain injury (TBI) is a leading cause of death and disability [1]. It is accepted that moderate to severe TBI increases risk of death acutely after injury [2-6]. Yet, an association between TBI and premature cause of death in the long term is not well understood. Investigators have reported specific causes of death after TBI in the long term. However, TBI cases were most commonly identified through use of hospital-based International Classification of Diseases (ICD) coding [7-13], and death rates were compared with the general population through use of standardized mortality ratios (SMRs) [9-12, 14-21]. These methods have well-recognized limitations, including underestimating TBI cases and not controlling for other traumatic injuries associated with the event that can affect mortality rate [18-23].

Understanding the relationships between TBI, death, and the underlying cause of death in the acute, postacute, and chronic phases after injury is essential for the development of preventive and clinical surveillance strategies to reduce TBI-associated death. The goals of the present analysis had 3 tiers. The study aimed to identify underlying causes of death in a population-based sample of patients with health-record-confirmed TBI and compare the underlying cause of death in the cases with their corresponding population-based referents. It studied the effect of nonhead trauma on causes of death by matching TBI patients experiencing nonhead trauma with referents experiencing nonhead trauma of the same severity. Further, the study aimed to determine whether cause of death differs between the postacute and chronic phases after injury; these categories were compared between study groups over the entire study period and among 6-month survivors.

This study was approved by the Mayo Clinic and Olmsted Medical Center Institutional Review Boards. Rochester, Minnesota, county seat of Olmsted County (2018 census population: 156,277), is home to Mayo Clinic, a large private medical center. Comprehensive data about each patient at Mayo Clinic have been linked to a unique identification number since 1907. This linkage was developed into the Rochester Epidemiology Project (REP) in 1966 [24]. This health records linkage system is widely recognized as a powerful tool for population-based epidemiologic studies [25, 26], allowing for unique assessment of the natural history of TBI [27-31].

REP has data from >500,000 persons and includes all demographic information, surgical procedure codes, drug prescription, and diagnostic codes assigned at every medical contact for each person in this geographically defined region [32]. These data can be screened electronically with a coding system developed at Mayo Clinic for clinical purposes specifically, using 3 different systems and a modification of ICD, Eighth Revision, and ICD, Ninth Revision (ICD-9) [33], shown to have high sensitivity and specificity [25] (see online suppl. material; for all online suppl. material, see www.karger.com/doi/10.1159/000514807).

TBI was defined as a “traumatically induced injury that contributed to the physiological disruption of brain function” [30, 31, 34, 35]. Each TBI event severity was categorized using the Mayo Classification System (Table 1) [36]. This classification system uses all health record data available, which creates an inclusive classification system superior to single clinical indicators of TBI severity (e.g., loss of consciousness, initial Glasgow Coma Scale [GCS] score, and length of posttraumatic amnesia) when applied to an epidemiologic cohort [35, 36]. TBI severity classification categories included definite (consistent with moderate-severe TBI), probable (consistent with mild TBI), or possible (consistent with concussive TBI) (Table 1).

Table 1.

Mayo Clinic TBI classification system

Mayo Clinic TBI classification system
Mayo Clinic TBI classification system

Case Identification

Methods for sample identification have been described previously [31, 34, 35]. A search of Olmsted County residents in the REP from January 1, 1985, through December 31, 1999, identified 46,114 cases with a TBI-related diagnostic code. Because of the labor-intensive effort involved in manually reviewing each case, a 20% random sample was initially selected. Time and budgetary constraints subsequently limited the cases to a 16% random sample, identifying 7,175 records. Trained nurse abstractors manually reviewed these records under the direction of a board-certified physiatrist (A.W.B.). Confirmed cases were defined as individuals without a documented history of prior TBI who had their first TBI event between January 1, 1985, and December 31, 1999. This abstraction confirmed 1,429 TBI cases. Information required to identify cases and their referents was available from January 1, 1987, limiting the sample to 1,257.

Selection of Referents

As described previously [31, 34, 35], TBI cases were matched to an individual of same sex and birth year (±1 year) seen by a REP clinician while an Olmsted County resident in the year (±1 year) of the case’s TBI. These were referred to as regular referents.

TBI cases associated with additional nonhead injuries were then identified among all cases, and the severity of those nonhead injuries was quantified with a Trauma Mortality Prediction Model [37]. These cases were referred to as special cases. Each of these cases was matched to 2 individuals of the same sex and birth year (±2 years) seen by a REP clinician while an Olmsted County resident in the year (±1 year) of the case’s TBI and had a traumatic injury of the same severity as their case’s, unassociated with head trauma, within a year of their case’s TBI. These referents were referred to as special referents. Of 1,257 TBI cases, 221 cases had TBI with other nonhead injuries and were categorized as special cases.

Underlying Cause of Death

The underlying cause of death was identified and was defined as the diagnosis of longest duration in the sequence of events leading to death. This compares with the immediate cause of death or the final diagnosis that caused death. Underlying causes of death were categorized through extensive chart review using death certificates, ICD-9 and International Statistical Classification of Diseases, Tenth Revision (ICD-10), and manual review of specific factors of external causes of death (D.E. and A.W.B.) [38]. All ICD-9 codes were converted to ICD-10 equivalents under the direction of a board-certified physiatrist (A.W.B.). Similarly, related ICD-10 categories were collapsed (Table 2).

Table 2.

Collapsed ICD-10 categories

Collapsed ICD-10 categories
Collapsed ICD-10 categories

Statistical Analysis

Underlying cause of death categories were compared between 2 case and referent groups: all cases (regular and special) matched with all regular referents (not considering nonhead trauma) and special cases each matched with 2 special referents. This strategy enhanced the analytical power for the smaller special case sample. To determine any difference between cause of death in the postacute and chronic phases after injury, the categories were compared between case and referent groups during the entire study period and among 6-month survivors.

Descriptive summaries were reported as mean (SD) for continuous variables and as frequency (percentage) for categorical variables. Comparisons of proportions between cases and referents were performed with Fisher’s exact test. All tests were 2 sided, and p < 0.05 was considered statistically significant. Analysis was performed with statistical software (SAS version 9.4; SAS Institute Inc.).

Case characteristics and the mechanism of TBI were tabulated for the sample (n = 1,257 cases) and by age group (Table 3). The mean time to follow-up for cases was 10.5 years. In total, 237 deaths occurred over the study period for the 1,257 case-referent pairs when all cases were matched to all regular referents – 139 among cases and 98 among referents (p = 0.006) (Table 4). Death occurred in 48% of cases after definite TBI, 10% after probable TBI, and 6% after possible TBI (Table 4). The underlying cause of death among cases was proportionally largest for external causes (52/139, 37%) compared with 3 among matched referents (3/98, 3%) (p < 0.001) (Table 5). The number of deaths in the other collapsed categories for cases and referents was not significantly different.

Table 3.

All case cohort characteristics

All case cohort characteristics
All case cohort characteristics
Table 4.

Proportion of deaths among cases and their regular referents by injury severity over the entire study period

Proportion of deaths among cases and their regular referents by injury severity over the entire study period
Proportion of deaths among cases and their regular referents by injury severity over the entire study period
Table 5.

Underlying cause of death listed by collapsed ICD-10 categories for the 1,257 all regular case-regular referent pairs over the entire study period

Underlying cause of death listed by collapsed ICD-10 categories for the 1,257 all regular case-regular referent pairs over the entire study period
Underlying cause of death listed by collapsed ICD-10 categories for the 1,257 all regular case-regular referent pairs over the entire study period

Over the entire study period, a total of 93 deaths occurred among the 221 special cases (32/221, 14%) and the 441 matched special referents (61/441, 14%) (Table 6) (for 1 special case, only 1 referent could be identified). No significant difference was observed in the proportion of total deaths in each sample (p = 0.81). However, the proportion of deaths due to external causes in the special cases (13/32, 41%) was significantly greater than for special referents (5/61, 8%) (p < 0.001). No significant difference was observed in the proportion of deaths for other causes.

Table 6.

Underlying cause of death listed by collapsed ICD-10 categories for 221 special cases and 441 matched special referentsa over the study period and among 6-month survivors

Underlying cause of death listed by collapsed ICD-10 categories for 221 special cases and 441 matched special referentsa over the study period and among 6-month survivors
Underlying cause of death listed by collapsed ICD-10 categories for 221 special cases and 441 matched special referentsa over the study period and among 6-month survivors

Within all case-regular referent pairs surviving 6 months, 185 deaths occurred, and no significant difference was observed between the numbers of death among cases and referents (p = 0.82) (Table 5). The proportion of underlying cause of death due to external causes among cases was significantly different than among referents (p < 0.01). Seventy-five deaths of 6-month survivors occurred among the 221 special cases and the 441 matched special referents (Table 6). No difference was detected in total deaths (p = 0.24) or in proportion of deaths due to external causes between special cases and referents (p = 1.00) among 6-month survivors (Table 6).

This population-based case-matched referent analysis of underlying cause of death after TBI showed that death due to external causes accounted for the greatest proportion of case deaths and was significantly greater than for matched referents. Further, when TBI cases whose injury included nonhead trauma were compared with referents having a similar severity of traumatic nonhead injury, the proportion of deaths due to external causes was significantly different from the referents only during the first 6 months after injury. Previous findings in this cohort have shown that the increased risk of death after TBI exists only in the first 6 months after injury [34].

In the context of the present analysis, it is reasonable to conclude that the external causes of death during the first 6 months after injury relate predominantly to the injuries associated with the traumatic event. The term external cause of death refers to the effect that comes from outside the body (e.g., injury, poison, assault, and exposure). Of all deaths from external causes across the case and referent groups, manual record review of death certificates and ICD coding of external cause of death found only 3 of the deaths attributable to factors not related to injury (e.g., poison and overdose).

The population-based results reported herein are consistent with those reported by Selassie et al. [10] that unintentional injury was the leading cause of death during the 15 months following discharge among patients hospitalized for TBI in South Carolina. A large national Swedish study also showed a preponderance of deaths due to external causes among 6-month survivors of TBI, particularly due to suicide, compared with both a population-based sample and sibling referents [8]. In a separate Swedish study of individuals hospitalized with severe TBI (GCS <8), a strong cause of death rate from external causes early after injury was found, but the rate did not differ from the general population after 1 year [39].

Among studies reporting cause of death in subgroups of individuals hospitalized for TBI and monitored over the longer term – with cases identified through hospital-determined ICD codes and deaths reported using SMRs – a large-scale nationally representative sample showed that external causes of death (18%) predominated after natural causes [11]. SMRs for suicide were 2.7–4.0, depending on the diagnosis group, and a suicide SMR for concussive injury was 3.02.

Ventura et al. [12] analyzed a state-based trauma registry sample of patients hospitalized after TBI. Cases were identified with hospital-based ICD codes and death reported using SMR. They found that deaths within the first month after injury were caused by circulatory conditions and unknown causes, with TBI a contributing cause. Death due to mental health or behavioral disorders and nervous system diseases dominated this sample. Deaths due to external causes were the fifth highest SMR overall.

Studies showing statistically significant associations between TBI and cause of death differing from the findings reported herein likely relate to methodologic differences in case identification (manual review and abstraction vs. administrative ICD coding by hospitals) and reference samples (population-based referents vs. the general population). We have shown that only 40% of TBI cases in a population-based cohort confirmed by health record review were identified when only using ICD-9 coding recommended by the Centers for Disease Control and Prevention for identifying TBI [22]. Use of SMRs to compare the number of TBI-related deaths in a given sample may limit the accuracy of attributing deaths to TBI because the comparison group is not controlled for other contributors of death, such as other traumatic injuries associated with the event [23].

The strengths of this study include confirmation of TBI cases in a defined population through manual health record review, stratification of injury severity across its spectrum, comparison of cause of death in cases to population-based referents considering nonhead trauma, and determination of underlying cause of death through detailed manual review of death certificates and diagnostic coding. Consistent with other studies in this population, the incidence of TBI in the present cohort was dominated by probable and possible TBI, with definite injury occurring in 8% (105 cases) of the sample. This population-based cohort also confirmed the association between injury severity and death (Table 4). However, other studies using samples exclusive to moderate-severe TBI cases have found cause of death to be significantly higher not only for external causes but also for respiratory, circulatory, and nervous system disorders [40-43]. These differences in findings may relate to the small proportion of definite cases in our sample.

Limitations

This study has several limitations. The lack of statistical significance in the number of deaths, particularly among 6-month survivors in special cases and special referents, may be due to too few deaths, particularly of persons with definite TBI. Although the present analysis considered simultaneous nonhead injuries using 2 matched referents, other preexisting comorbidities of cases were not considered when selecting referents, potentially affecting results. In addition, the use of 2 regular referents for all cases would have strengthened the power of the study, considering the relatively few definite TBI cases.

The population of Olmsted County is predominantly White, with age and sex distribution similar to that for Minnesota, the Upper Midwest, and the US White population [24]. The applicability of this study’s findings to other community settings is limited because of the underrepresentation of persons of color and the distinctive medical care system of the region (i.e., entire population served by primarily 2 group practices).

Finally, advances in the development of models of trauma care in the period since these data were acquired may potentially limit the relevance of these findings for current practice. However, there has been no consistent indication that mortality rate specifically after TBI has improved in recent decades, supporting the pertinence of these results [17, 44, 45].

Using the REP diagnostic record linkage resource to confirm cases and population-based matched referents, this study provides a distinctive report of the underlying cause of death after TBI over the full spectrum of age and injury severity, considering the influence of nonhead trauma for matched referents. Results show that in a population-based sample, TBI is associated with higher mortality rates during only the first 6 months after injury, and this increased risk of death is due to external causes. This in turn has implications for the long-term medical and rehabilitation treatment of individuals who survive the postacute phase after TBI as their health needs change with recovery and aging.

This study was approved by the Mayo Clinic and Olmsted Medical Center Institutional Review Boards. All study participants provided authorization for their health data to be used for research purposes.

The authors have no conflicts of interest to declare.

This research was supported by Grant No. UL1 TR000135 from the National Center for Advancing Translational Sciences (NCATS) and by the Mayo Clinic Center for Clinical and Translational Science, which is funded by the National Institutes of Health (NIH) Clinical and Translational Science Awards program. This project was made possible with use of the resources of REP, which is supported by the National Institute on Aging of the NIH under Award No. R01AG034676. The contents of this article are solely the responsibility of the authors and do not necessarily represent the official views of the NIH.

Dmitry Esterov, Erica Bellamkonda, Jay Mandrekar, Jeanine E. Ransom, and Allen W. Brown provided substantial contributions to the conception and design, acquisition of data, or analysis and interpretation of data. Dmitry Esterov, Erica Bellamkonda, Jay Mandrekar, Jeanine E. Ransom, and Allen W. Brown drafted the article or revised it critically for important intellectual content and gave final approval of the version to be published. Dmitry Esterov, Erica Bellamkonda, Jay Mandrekar, Jeanine E. Ransom, and Allen W. Brown agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy and integrity of any part of the work are appropriately investigated and resolved.

1.
Taylor
CA
,
Bell
JM
,
Breiding
MJ
,
Xu
L
.
Traumatic brain injury-related emergency department visits, hospitalizations, and deaths: United States, 2007 and 2013
.
MMWR Surveill Summ
.
2017 Mar 17
;
66
(
9
):
1
16
. .
2.
Gerber
LM
,
Chiu
YL
,
Carney
N
,
Härtl
R
,
Ghajar
J
.
Marked reduction in mortality in patients with severe traumatic brain injury
.
J Neurosurg
.
2013 Dec
;
119
(
6
):
1583
90
. .
3.
Kraus
JF
,
Black
MA
,
Hessol
N
,
Ley
P
,
Rokaw
W
,
Sullivan
C
, et al
The incidence of acute brain injury and serious impairment in a defined population
.
Am J Epidemiol
.
1984 Feb
;
119
(
2
):
186
201
. .
4.
Stocchetti
N
,
Carbonara
M
,
Citerio
G
,
Ercole
A
,
Skrifvars
MB
,
Smielewski
P
, et al
Severe traumatic brain injury: targeted management in the intensive care unit
.
Lancet Neurol
.
2017 Jun
;
16
(
6
):
452
64
. .
5.
Watanitanon
A
,
Lyons
VH
,
Lele
AV
,
Krishnamoorthy
V
,
Chaikittisilpa
N
,
Chandee
T
, et al
Clinical epidemiology of adults with moderate traumatic brain injury
.
Crit Care Med
.
2018 May
;
46
(
5
):
781
7
. .
6.
McGarry
LJ
,
Thompson
D
,
Millham
FH
,
Cowell
L
,
Snyder
PJ
,
Lenderking
WR
, et al
Outcomes and costs of acute treatment of traumatic brain injury
.
J Trauma
.
2002 Dec
;
53
(
6
):
1152
9
. .
7.
McMillan
TM
,
Teasdale
GM
,
Weir
CJ
,
Stewart
E
.
Death after head injury: the 13 year outcome of a case control study
.
J Neurol Neurosurg Psychiatry
.
2011 Aug
;
82
(
8
):
931
5
. .
8.
Fazel
S
,
Wolf
A
,
Pillas
D
,
Lichtenstein
P
,
Långström
N
.
Suicide, fatal injuries, and other causes of premature mortality in patients with traumatic brain injury: a 41-year Swedish population study
.
JAMA Psychiatry
.
2014 Mar
;
71
(
3
):
326
33
. .
9.
Shavelle
RM
,
Strauss
D
,
Whyte
J
,
Day
SM
,
Yu
YL
.
Long-term causes of death after traumatic brain injury
.
Am J Phys Med Rehabil
.
2001 Jul
;
80
(
7
):
510
9
. quiz 17-9. .
10.
Selassie
AW
,
Cao
Y
,
Church
EC
,
Saunders
LL
,
Krause
J
.
Accelerated death rate in population-based cohort of persons with traumatic brain injury
.
J Head Trauma Rehabil
.
2014 May–Jun
;
29
(
3
):
E8
E19
. .
11.
Teasdale
TW
,
Engberg
AW
.
Suicide after traumatic brain injury: a population study
.
J Neurol Neurosurg Psychiatry
.
2001 Oct
;
71
(
4
):
436
40
. .
12.
Ventura
T
,
Harrison-Felix
C
,
Carlson
N
,
Diguiseppi
C
,
Gabella
B
,
Brown
A
, et al
Mortality after discharge from acute care hospitalization with traumatic brain injury: a population-based study
.
Arch Phys Med Rehabil
.
2010 Jan
;
91
(
1
):
20
9
. .
13.
Eric Nyam
TT
,
Ho
CH
,
Chio
CC
,
Lim
SW
,
Wang
JJ
,
Chang
CH
, et al
Traumatic brain injury increases the risk of major adverse cardiovascular and cerebrovascular events: a 13-year, population-based study
.
World Neurosurg
.
2019 Feb
;
122
:
e740
e53
. .
14.
Harrison-Felix
C
,
Whiteneck
G
,
Devivo
MJ
,
Hammond
FM
,
Jha
A
.
Causes of death following 1 year postinjury among individuals with traumatic brain injury
.
J Head Trauma Rehabil
.
2006 Jan–Feb
;
21
(
1
):
22
33
. .
15.
Harrison-Felix
C
,
Kolakowsky-Hayner
SA
,
Hammond
FM
,
Wang
R
,
Englander
J
,
Dams-OʼConnor
K
, et al
Mortality after surviving traumatic brain injury: risks based on age groups
.
J Head Trauma Rehabil
.
2012 Nov–Dec
;
27
(
6
):
E45
56
. .
16.
Lystad
RP
,
Cameron
CM
,
Mitchell
RJ
.
Excess mortality among adults hospitalized with traumatic brain injury in Australia: a population-based matched cohort study
.
J Head Trauma Rehabil
.
2019 May/Jun
;
34
(
3
):
E1
E9
.
17.
Cheng
P
,
Yin
P
,
Ning
P
,
Wang
L
,
Cheng
X
,
Liu
Y
, et al
Trends in traumatic brain injury mortality in China, 2006–2013: a population-based longitudinal study
.
PLoS Med
.
2017 Jul
;
14
(
7
):
e1002332
. .
18.
Bazarian
JJ
,
Veazie
P
,
Mookerjee
S
,
Lerner
EB
.
Accuracy of mild traumatic brain injury case ascertainment using ICD-9 codes
.
Acad Emerg Med
.
2006 Jan
;
13
(
1
):
31
8
. .
19.
Powell
JM
,
Ferraro
JV
,
Dikmen
SS
,
Temkin
NR
,
Bell
KR
.
Accuracy of mild traumatic brain injury diagnosis
.
Arch Phys Med Rehabil
.
2008 Aug
;
89
(
8
):
1550
5
. .
20.
Rodriguez
SR
,
Mallonee
S
,
Archer
P
,
Gofton
J
.
Evaluation of death certificate-based surveillance for traumatic brain injury: Oklahoma 2002
.
Public Health Rep
.
2006 May–Jun
;
121
(
3
):
282
9
. .
21.
Barker-Collo
S
,
Theadom
A
,
Jones
K
,
Feigin
VL
,
Kahan
M
.
Accuracy of an international classification of diseases code surveillance system in the identification of traumatic brain injury
.
Neuroepidemiology
.
2016
;
47
(
1
):
46
52
. .
22.
Leibson
CL
,
Brown
AW
,
Ransom
JE
,
Diehl
NN
,
Perkins
PK
,
Mandrekar
J
, et al
Incidence of traumatic brain injury across the full disease spectrum: a population-based medical record review study
.
Epidemiology
.
2011 Nov
;
22
(
6
):
836
44
. .
23.
Jones
ME
,
Swerdlow
AJ
.
Bias in the standardized mortality ratio when using general population rates to estimate expected number of deaths
.
Am J Epidemiol
.
1998 Nov 15
;
148
(
10
):
1012
7
. .
24.
Melton
LJ
 3rd
.
History of the Rochester epidemiology project
.
Mayo Clin Proc
.
1996 Mar
;
71
(
3
):
266
74
.
25.
St Sauver
JL
,
Grossardt
BR
,
Yawn
BP
,
Melton
LJ
 3rd
,
Pankratz
JJ
,
Brue
SM
, et al
Data resource profile: the Rochester Epidemiology Project (REP) medical records-linkage system
.
Int J Epidemiol
.
2012 Dec
;
41
(
6
):
1614
24
. .
26.
St Sauver
JL
,
Grossardt
BR
,
Yawn
BP
,
Melton
LJ
 3rd
,
Rocca
WA
.
Use of a medical records linkage system to enumerate a dynamic population over time: the Rochester epidemiology project
.
Am J Epidemiol
.
2011 May 1
;
173
(
9
):
1059
68
.
27.
Annegers
JF
,
Grabow
JD
,
Groover
RV
,
Laws
ER
 Jr
,
Elveback
LR
,
Kurland
LT
.
Seizures after head trauma: a population study
.
Neurology
.
1980 Jul
;
30
(
7 Pt 1
):
683
9
. .
28.
Annegers
JF
,
Hauser
WA
,
Coan
SP
,
Rocca
WA
.
A population-based study of seizures after traumatic brain injuries
.
N Engl J Med
.
1998 Jan 1
;
338
(
1
):
20
4
. .
29.
Annegers
JF
,
Grabow
JD
,
Kurland
LT
,
Laws
ER
 Jr
.
The incidence, causes, and secular trends of head trauma in Olmsted County, Minnesota, 1935–1974
.
Neurology
.
1980 Sept
;
30
(
9
):
912
9
. .
30.
Brown
AW
,
Leibson
CL
,
Malec
JF
,
Perkins
PK
,
Diehl
NN
,
Larson
DR
.
Long-term survival after traumatic brain injury: a population-based analysis
.
NeuroRehabilitation
.
2004
;
19
(
1
):
37
43
. .
31.
Flaada
JT
,
Leibson
CL
,
Mandrekar
JN
,
Diehl
N
,
Perkins
PK
,
Brown
AW
, et al
Relative risk of mortality after traumatic brain injury: a population-based study of the role of age and injury severity
.
J Neurotrauma
.
2007 Mar
;
24
(
3
):
435
45
. .
32.
Rocca
WA
,
Yawn
BP
,
St Sauver
JL
,
Grossardt
BR
,
Melton
LJ
 3rd
.
History of the Rochester Epidemiology Project: half a century of medical records linkage in a US population
.
Mayo Clin Proc
.
2012 Dec
;
87
(
12
):
1202
13
. .
33.
Commission on Professional and Hospital Activities, National Center for Health Statistics (U.S.)
.
H-ICDA; hospital adaptation of ICDA
. 2d ed.
Northumberland
:
Ann Arbor
;
1973
.
34.
Brown
AW
,
Leibson
CL
,
Mandrekar
J
,
Ransom
JE
,
Malec
JF
.
Long-term survival after traumatic brain injury: a population-based analysis controlled for nonhead trauma
.
J Head Trauma Rehabil
.
2014 Jan-Feb
;
29
(
1
):
E1
8
. .
35.
Leibson
CL
,
Brown
AW
,
Hall Long
K
,
Ransom
JE
,
Mandrekar
J
,
Osler
TM
, et al
Medical care costs associated with traumatic brain injury over the full spectrum of disease: a controlled population-based study
.
J Neurotrauma
.
2012 Jul 20
;
29
(
11
):
2038
49
. .
36.
Malec
JF
,
Brown
AW
,
Leibson
CL
,
Flaada
JT
,
Mandrekar
JN
,
Diehl
NN
, et al
The Mayo classification system for traumatic brain injury severity
.
J Neurotrauma
.
2007 Sept
;
24
(
9
):
1417
24
. .
37.
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
.
Ann Surg
.
2009 Jun
;
249
(
6
):
1032
9
. .
38.
Swain
GR
,
Ward
GK
,
Hartlaub
PP
.
Death certificates: let’s get it right
.
Am Fam Physician
.
2005 Feb 15
;
71
(
4
):
652
6.652
39.
Ulfarsson
T
,
Lundgren-Nilsson
A
,
Blomstrand
C
,
Jakobsson
KE
,
Oden
A
,
Nilsson
M
, et al
Ten-year mortality after severe traumatic brain injury in western Sweden: a case control study
.
Brain Inj
.
2014
;
28
(
13–14
):
1675
81
.
40.
Harrison-Felix
C
,
Kreider
SE
,
Arango-Lasprilla
JC
,
Brown
AW
,
Dijkers
MP
,
Hammond
FM
, et al
Life expectancy following rehabilitation: a NIDRR traumatic brain injury model systems study
.
J Head Trauma Rehabil
.
2012 Nov–Dec
;
27
(
6
):
E69
80
. .
41.
Greenwald
BD
,
Hammond
FM
,
Harrison-Felix
C
,
Nakase-Richardson
R
,
Howe
LL
,
Kreider
S
.
Mortality following traumatic brain injury among individuals unable to follow commands at the time of rehabilitation admission: a national institute on disability and rehabilitation research traumatic brain injury model systems study
.
J Neurotrauma
.
2015 Dec 1
;
32
(
23
):
1883
92
. .
42.
Baguley
IJ
,
Nott
MT
,
Howle
AA
,
Simpson
GK
,
Browne
S
,
King
AC
, et al
Late mortality after severe traumatic brain injury in New South Wales: a multicentre study
.
Med J Aust
.
2012 Jan 16
;
196
(
1
):
40
5
.
43.
Baguley
IJ
,
Nott
MT
,
Slewa-Younan
S
.
Long-term mortality trends in functionally-dependent adults following severe traumatic-brain injury
.
Brain Inj
.
2008 Nov
;
22
(
12
):
919
25
. .
44.
Brooks
JC
,
Shavelle
RM
,
Strauss
DJ
,
Hammond
FM
,
Harrison-Felix
CL
.
Long-term survival after traumatic brain injury part II: life expectancy
.
Arch Phys Med Rehabil
.
2015 Jun
;
96
(
6
):
1000
5
. .
45.
Stein
SC
,
Georgoff
P
,
Meghan
S
,
Mizra
K
,
Sonnad
SS
.
150 years of treating severe traumatic brain injury: a systematic review of progress in mortality
.
J Neurotrauma
.
2010 Jul
;
27
(
7
):
1343
53
. .

Additional information: portions of this manuscript have been published in an abstract form: Brain Inj. 2014 May;28(5–6):833.Publisher: to expedite proof approval, send proof via email to scipubs@mayo.edu.©2020 Mayo Foundation for Medical Education and Research.

Copyright / Drug Dosage / Disclaimer
Copyright: All rights reserved. No part of this publication may be translated into other languages, reproduced or utilized in any form or by any means, electronic or mechanical, including photocopying, recording, microcopying, or by any information storage and retrieval system, without permission in writing from the publisher.
Drug Dosage: The authors and the publisher have exerted every effort to ensure that drug selection and dosage set forth in this text are in accord with current recommendations and practice at the time of publication. However, in view of ongoing research, changes in government regulations, and the constant flow of information relating to drug therapy and drug reactions, the reader is urged to check the package insert for each drug for any changes in indications and dosage and for added warnings and precautions. This is particularly important when the recommended agent is a new and/or infrequently employed drug.
Disclaimer: The statements, opinions and data contained in this publication are solely those of the individual authors and contributors and not of the publishers and the editor(s). The appearance of advertisements or/and product references in the publication is not a warranty, endorsement, or approval of the products or services advertised or of their effectiveness, quality or safety. The publisher and the editor(s) disclaim responsibility for any injury to persons or property resulting from any ideas, methods, instructions or products referred to in the content or advertisements.