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Gulf War and Health, Volume 7: Long-Term Consequences of Traumatic Brain Injury 3 EPIDEMIOLOGY OF ADULT TRAUMATIC BRAIN INJURY This chapter reviews the scientific literature on the epidemiology of traumatic brain injury (TBI) and on incidence, prevalence, severity, external causes, risk factors, mortality, case-fatality rates, and disability estimates among others. For purposes of this chapter, the papers reviewed were published in 1980 or later, focus on adults only, include incidence reports, and use established methods that resulted in a minimum of sources of bias and misclassification similar to criteria established by the committee for review of studies of long-term health outcomes. Review articles are included only as a source of reference. Scales and Scoring Systems Used to Describe Traumatic Brain Injury There are many classifications of TBI; for example, Knightly and Pulliam (1996) address the various components of TBI incurred in the military. As noted in Chapter 1, there are two basic types of head injury: closed and open. Closed head injuries result from the concussive effects of such exposures as munitions explosions, falls, and deceleration injuries from vehicular crashes; the latter two have also been termed blunt-force injuries. Open head injuries include those caused by penetrating forces, for example, from gunshots or shrapnel, or by impaling forces, such as from knives (see also Chapter 2). Gross Severity of Traumatic Brain Injury Different methods have been used in the last three decades to measure the magnitude of brain damage and to predict the outcome of injuries (see Chapter 2). The mostly widely used tool for measuring severity is the Glasgow Coma Scale (GCS), which was developed in 1974 by Teasdale and Jennett (1974) as a measure of neurologic deficits after TBI and was an important contribution to the standardization of early assessment of TBI. It uses a simple method of scoring three domains: eye opening, verbal response, and motor function (Table 3.1) and yields a total score of from 3 (comatose or nonresponsive) to 15 (no deficits in any of the three domains). The interpretation of scores at the ends of the scale is relatively straightforward, but scores like 8 or 9 or 11 or 12 may be subject to judgment error. Although the GCS is relatively straightforward in its numeric results, the classification of severity has been inconsistent. Many incidence studies have classified severity according to GCS scores of 3–8, severe; 9–12, moderate; and 13–15, mild or minor (e.g., Kraus et al., 1984; Thurman et al., 1996; Langlois et al., 2003). Permutations of that approach are summarized in Table 3.2 (US studies) and Table 3.3 (non-US studies).
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Gulf War and Health, Volume 7: Long-Term Consequences of Traumatic Brain Injury It was originally intended that the GCS would be applied repeatedly during a patient’s hospital course to monitor improvement or deterioration—during emergency transport, in the emergency department (ED), during intensive care, and throughout primary care. Because GCS scores have been reported in almost all recent studies of TBI severity, it is important to compare only readings taken at similar times after injury among studies. The most common time for determining the GCS score is 6 hours after injury, which is generally when the patient is in the ED. The GCS is subject to limitations when used on some patients, such as young children, people with extensive facial injuries that would preclude eye assessment, people subject to cross-language misunderstandings, and people who have been intubated or sedated on arrival at the ED. A major limitation of the GCS is the effect of intoxication. As many as 35–50% of adult civilian patients transported to the ED may be under the influence of alcohol (Jagger et al., 1984a), so its effect on the GCS score and its interpretation cannot be ignored. A study by Sperry et al. (2006), however, suggests that alcohol intoxication had little effect on the GCS. Nell and associates (2000) introduced an extended version of the GCS (GCS-E) to address difficulties of its application to the mild forms of TBI (Table 3.1). A study by Drake and colleagues (2006) showed that the extended GCS is a useful tool for the prediction of symptoms connected with mild TBI. The GCS should not be confused with the Glasgow Outcome Scale (GOS) (Table 3.1). The GCS is a physiologic measure of consciousness and the GOS is a gross measure of complications or residual effects following severe brain injury (Jennett and Bond, 1975). Other methods and instruments have been used as alternatives to the GCS, such as the Abbreviated Injury Scale (AIS) (see Chapter 2) and the International Classification of Diseases (ICD). Clinical measures—such as loss of consciousness (LOC) and duration of posttraumatic amnesia (PTA)—and computed tomography of brain lesions have also been used to assess TBI severity. Table 3.2 shows examples of TBI incidence studies conducted in the United States that used those measures. As can be seen there is no consistency in severity classification systems reflecting available clinical symptoms or evidence from neuroimaging. A review of popular injury scales can be found in the review by MacKenzie (1984). Outcome Scores and Predictors The literature is replete with attempts to predict TBI outcomes on the basis of measurements in the ED or soon after intensive care. One of the most commonly used measures is the GOS (Table 3.1) developed by Jennett and Bond (1975). Although the intent of the GOS was to address severe TBI, it has been applied over the years to less severe TBI. It is acknowledged as a crude measure of medical (neurologic) complications and sequelae but has found favor as a quick and reliable indicator of outcome especially of severe TBI (Teasdale et al., 1998). The GOS is most commonly applied at 3, 6, or 12 months postinjury but can be used at any time after intensive care. Pettigrew and associates (2003) recently showed that the GOS can be successfully applied over the telephone. There are many other measures, but only the GOS is covered in this chapter to assess patient disposition at hospital discharge. Because the gross categories of the GOS have some limitations, an extended version (the GOS-E) was developed (Jennett et al., 1981); the GOS-E adds three categories to the GOS and has good inter-rater agreement.
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Gulf War and Health, Volume 7: Long-Term Consequences of Traumatic Brain Injury INCIDENCE OF TRAUMATIC BRAIN INJURY Incidence is the number of newly diagnosed cases occurring in a defined period, usually expressed with reference to a base of 100,000 persons. An incidence study is one in which only newly diagnosed TBI cases in a specified period of time in a population of known size have been enumerated and are included in the study group. Some 30 population-based TBI incidence studies conducted in the United States have been published since 1980 (Table 3.4). Early studies were limited to counties (Kraus et al., 1984), cities (Cooper et al., 1983; Whitman et al., 1984), and states, such as Oklahoma, Massachusetts, Louisiana, and Alaska. National or subnational estimates of the incidence of TBI have recently been published from the Centers for Disease Control and Prevention (CDC) TBI surveillance system (Langlois et al., 2003) or from existing national administrative datasets (Langlois et al., 2006). Methods used for incidence studies have varied. For example, some earlier studies (e.g., Rimel, 1981; Kraus et al., 1984) relied on hospital or coroner records for case findings based on discharge codes, reviewed original institutional records, and abstracted pertinent data. Later studies used hospital discharge records and electronic files; in a few instances, a trauma registry was the source of data on TBI (Warren et al., 1995). On the basis of the data available from those studies, the incidence of hospitalizations for TBI in the United States is about 140/100,000 persons per year. If the highest reported rate (367/100,000) and the lowest reported rate (69/100,000) are excluded, the average rate of hospitalization for TBI (plus cases of immediately fatal TBI) in the United States is about 130/100,000 persons per year. Those estimates do not include ED-based studies, with rates of 444/100,000 (Jager et al., 2000) or 392/100,000 (Guerrero et al., 2000). The rates given in Table 3.4 represent three case-finding methods: hospitalized cases and those identified from medical-examiner records, hospital discharge records only, and trauma-registry files. The differences in case-finding approaches and other methodologic differences result in different rates. Some 36 TBI incidence studies conducted outside the United States have been published since the middle 1970s, most coming from Europe and Australia (Table 3.5). As in the US studies, a wide variety of methods were used in TBI case definition and ascertainment methods. Even when ICD TBI codes were used in existing hospital electronic discharge files, the codes selected were not uniform. About half the incidence studies did not evaluate TBI severity. Therefore, it is difficult to synthesize findings from the non-US studies. Time Trends in Incidence Few incidence studies have collected data beyond a single year or two. MacKenzie and associates (1990) reported an increase in TBI incidence in Maryland from 1979 to 1986. There did not appear to be any remarkable changes in TBI identification procedures in the state’s database, and only patients admitted to the state’s 56 acute-care nonfederal hospitals were counted. Using the US National Hospital Discharge Survey, a yearly survey sampled in such a way as to be representative of the US general population, Thurman and Guerrero (1999) reported a 51% decline in incidence from 1980 through 1995. The change over that period was from 199/100,000 to 98/100,000. They noted that the TBI-associated death rate also declined, possibly because of the preventive measures associated with motor-vehicle crash outcomes. The authors noted also that the greatest change in hospitalization rates was in those with mild TBI; that suggested a change in hospital admission practices.
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Gulf War and Health, Volume 7: Long-Term Consequences of Traumatic Brain Injury Time-trend studies of incidence are rare in Europe and nonexistent in Asia. Engberg and Teasdale (2001), in an analysis of 1979–1996 data from Denmark, reported an overall decline of 41% in the rate of hospitalization for TBI. The percentage decline varied with ICD code. The authors speculate that the decreases may be explained by changes in hospital admission practices and the possible effect of national prevention programs. Kleiven and associates (2003) observed a varied change in incidence in Sweden from 1987 to 2000: persons over 85 years old appear to have experienced an increase in TBI rates and younger persons a decrease. Mortality The most recent estimates in four US reports indicate an average of about 50,000 deaths each year with TBI-related causes (Table 3.6). The most recent reported TBI mortality in the United States is 17.5/100,000 persons per year (Rutland-Brown et al., 2006). Sixteen incidence reports provide mortality data on subsets of the US population. The years in question are from 1974 through 2003, and the rates vary from 17/100,000 per year to 30/100,000 per year. The large US studies are based on data from the National Center for Health Statistics, and the rates for the latest years are tightly clustered from 17/100,000 per year to 21/100,000 per year. It should be kept in mind that methods of collecting mortality data vary somewhat, but the rates in most studies are based on death-certificate review. TBI mortality in non-US countries varies much more widely than that in the United States (Table 3.7). The lowest rate reported—5.2/100,000 of populations in Aquitaine, France—reflects only inpatient deaths (Masson et al., 2001). Low rates have also been reported in northeast Italy, South Australia, and Norway. The highest TBI-death rates on record are in Johannesburg, South Africa (81/100,000), and Hualien County, Taiwan (82/100,000) (Nell and Brown, 1991; Chiu et al., 1997). Prevalence of Traumatic Brain Injury (Disability) Prevalence reflects the total number of cases of TBI at a specified point in time and includes all newly diagnosed patients plus those persons with residual physical and neuropsychologic problems. It should not be confused with incidence. Prevalence is a measure of the cumulative occurrence of TBI in the population at the point or period when measured. It is difficult to determine the exact prevalence of TBI in the United States, but there are estimates of disability—physical, mental, or social impairment—as a result of TBI. The literature on TBI disability is large and is based on occurrence of disability in a group of persons who have survived and might not be representative of the entire population. For purpose of this chapter, two recent US studies are highlighted because their findings were based on original incidence cohorts with excellent followup methods to ascertain outcomes. From 1996 to 1999, 2,771 Colorado residents 16 years old or older were discharged alive from an acute-care hospital after a diagnosis of moderate or severe TBI (Whiteneck et al., 2004). After multiple attempts at contact, 1,591 were located and responded to structured interviews on a variety of outcomes. Information was sought 1 year after injury on health-service use, the Functional Independence Measure, the Craig Handicap Assessment and Reporting Technique (CHART), and a single question on quality of life. The study authors noted that 65% had problems in cognition (any symptom); 71% used at least one service after injury; 15–37% had activity limitations, depending on the type of activity; and 24% failed to return to work. With
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Gulf War and Health, Volume 7: Long-Term Consequences of Traumatic Brain Injury regard to CHART components, 16% were impaired or disabled; and 29% reported less than good quality of life. The authors concluded that “substantial percentages of people hospitalized with TBI in a population-based sample reported a variety of problematic outcomes at 1 year postinjury.” It is noteworthy that the problems experienced by members of that injury cohort were in many cases similar in all levels of initial TBI severity. The second study of the incidence of disability was a South Carolina population-based prospective cohort study reported by Pickelsimer et al. (2006). Followup was completed at 1 year after injury with such outcome measures as service needs, psychosocial health, health-related quality of life, functional status, TBI-related symptoms, employment, and life satisfaction. Outcome findings included one or more functional limitations in about 47% of the subjects, unmet service needs in about one-third (35%), and dissatisfaction in quality of life in about one-third (35%). In a second report of that study, Selassie et al. (2008) used the same population sample and outcome measures to estimate the incidence of long-term disability in the United States. The researchers concluded that among the 288,009 survivors hospitalized for TBI in 2003, almost 125,000 (over 43%) had long-term disability. The disability rate varied by age and sex; it was higher in females than in males and was highest in people who fell and in those with self-inflicted injuries. Information on annual disability does not quantify the cumulative prevalence of TBI disability or impairment in the population. If 43% of a hospital-discharged TBI population sustains some form of disability or impairment in 1 year, the question remains, how much of the total population is disabled or impaired from TBI sustained in earlier years? Thurman and colleagues (1999) attempted to estimate that number by using the US National Hospital Discharge Survey data to approximate incidence and then classified the data by TBI severity by applying the computer algorithm known as ICDMAP-90 developed by MacKenzie et al. (1989b). The probability of disability was estimated for each level of severity by using outcome findings on disability from the Colorado state TBI registry and estimation parameters developed by Kraus and McArthur (1996). On the basis of that model, CDC estimated that 5.3 million US citizens (2%) were living with TBI-related disability in 1996. If that proportion is applied to the 2007 US population of over 301 million people, then just over 6 million people are living with the effects of TBI, and 2 million people have unmet health-service needs. BRAIN INJURY SEVERITY As discussed above, LOC is the most common measure used for evaluating brain injury severity and the most widely used tool for LOC is the GCS. Problems that arise in comparing the GCS measured in different places come from differences in timing. For example, intubation and sedation of the brain-injured patient during transport to the ED will obviously affect the person's verbal and motor abilities and eye responses. Differences in timing in the administration of any measurement tool can be critical so Teasdale and Jennett suggested that the GCS be applied at 6 hours post-injury. However, because a patient's injury may require ED procedures like intubation and sedation or acute surgical intervention, repeat measures may be necessary, often minutes or hours apart. Hence there does not appear to be an ideal window that is the best for the GCS, but, if it is to have any predictive quality, it should be applied early in the clinical management of TBI.
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Gulf War and Health, Volume 7: Long-Term Consequences of Traumatic Brain Injury Severity Distributions The distribution of severity of brain injury as assessed by the GCS (or other parameters) is shown in Table 3.8. Of the more than 60 population-based incidence studies published worldwide since 1980 only 22 address the degree of TBI severity in the study populations; 10 are from US and 12 from non-US countries. Most studies used the GCS to evaluate brain injury severity but some also used the AIS. The majority of hospital-admitted brain injuries are classified as "mild" (generally, a GCS score of 13 to15 or AIS of 1 or 2). However, the mild category is viewed differently by different researchers some of whom use mild to describe any GCS score above 7 while others refer to GCS scores above 8, above 10, above 13, or 15 only (Kraus and Chu, 2004). Studies published in the 1980s, with the exception of the report from Oklahoma, showed a ratio of mild to moderate to severe of about 8:1:1. With one or two exceptions almost all studies in the United States show less than 20% of patients admitted to a hospital are in the severe TBI range, and mild TBI is diagnosed 60% or more of the time. However, researchers outside the US report severity distribution proportions at even more consistent levels. A study by Hillier et al. (1997) evaluated TBI severity using three different measures: the GCS, LOC, and PTA; results were very similar, which provides support to the acceptance of severity classification when each of those measures is used. Severity distribution findings from non-US studies (Table 3.8) are similar to those from the United States with a ratio of mild to moderate to severe of 7:1:1. The high percentage of severe TBI admissions for Northeast Italy (Baldo et al., 2003) and the Romagna region of Italy (Servadei et al., 2002a) may reflect the referral practice of the acute medical care treatment institutions involved. RISK FACTORS FOR TRAUMATIC BRAIN INJURY Several risk factors have been examined in connection with the incidence of TBI: age, sex, ethnicity, and socioeconomic status. Data on age and sex in TBI can be found in 60 of the 66 papers reviewed (Tables 3.9 and 3.10). Although the papers do not necessarily group ages similarly, findings are remarkably consistent; the age group with the highest incidence of TBI is 15–24 years. In some reports, age groups at highest risk depend on TBI severity. For example, the very young (0–4 years old) and the very old (at least 85 years old) present to an ED with a brain injury most frequently, whereas those 15–24 years old and over the age of 65 years are hospitalized with TBI most frequently. The age-specific rates tend to reflect differences in exposure, particularly to motor-vehicle crashes and falls. Males are at greater risk for TBI than females at all ages in all incidence studies. Every report that gives data on sex-specific incidence shows that males have much higher TBI rates than females, and the ratio of male incidence to female incidence often exceeds 2. In one report (Nell and Brown, 1991), the incidence ratio of males to females exceeded 4 in both blacks and whites in Johannesburg, South Africa. The researchers posit that men in Johannesburg are involved in much higher levels of aggressive activities than women in the same city. The sex-specific mortality ratio is about 3.5:1, strongly indicative of more severe injuries among males (Adekoya et al., 2002). The US TBI death rate in 1989–1998 averaged 27/100,000 in American Indians and Alaskan Natives, 25/100,000 in blacks, and 20/100,000 in whites (Adekoya et al., 2002). The nonfatal-TBI hospitalization rate in 1997 (based on a 14-state surveillance system) was
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Gulf War and Health, Volume 7: Long-Term Consequences of Traumatic Brain Injury 74/100,000 in blacks, 75/100,000 in American Indians and Alaskan Natives, and 63/100,000 in whites (Langlois et al., 2003). ED incidence studies of TBI show similar results, albeit often lacking complete racial and ethnic categories. For example, the report by Jager and associates (2000) shows the rate of ED-treated TBI in blacks as 582/100,000 and the rates in whites and all others as 429/100,000 and 333/100,000, respectively. Data from the US National Health Interview Survey for 1991 (Sosin et al., 1996) show that whereas ED TBI rates were higher in whites than in blacks or Hispanics, the TBI hospital-admission rates were the opposite, that is, lower in whites than in other race and ethnic groups. Similarly, Nell and Brown (1991), in a 1986 TBI study in Johannesburg, South Africa, reported an incidence 3.3 times higher in blacks, 1.9 times higher in Asians, and 2.7 times higher in coloureds (mixed race) than in whites. Higher risk of TBI is often associated with lower socioeconomic status (SES) because there might be increased exposure to physically demanding or unsafe employment settings, increased exposure to violence, or increased exposure to less well-maintained residences or older vehicles without newer safety features (Hoofien et al., 2003). In the United States, families at the lowest income levels have been shown to incur the highest numbers of injuries of all types on a per capita basis (Collins, 1990). That was found to be true for TBI in a study of San Diego County residents (Kraus et al., 1986), in two Chicago communities (Whitman et al., 1984) and in Rhode Island (Fife et al., 1986). The San Diego County study demonstrated that the link between injury and low SES was not modified when the analysis controlled for race or ethnicity. Two more recent studies have demonstrated the link between the incidence of TBI and race or SES. Selassie et al. (2003, 2004) in a large cohort study of TBI in South Carolina showed that the disposition of TBI patients from the ED might be influenced by insurance status and other factors. Furthermore, black females and the uninsured were less likely to be hospitalized for TBI after adjustment for important confounders. However, Yates et al. (2006) determined hospital TBI “attendance” rates in an ED in a large UK population from 1997 to early 2003 by using the Index of Multiple Deprivation and noted that the highest TBI attendance rates were in groups with the lowest SES. Alcohol consumption can disrupt brain activity. Intoxication greatly increases various risks, including risks posed by motor-vehicle operation and the risk of self-inflicted injury and assault (e.g., Waller et al., 1986; Modell and Mountz, 1990). Also, intoxication can complicate diagnosis in the ED by increasing LOC independently of brain-injury severity (e.g., Jagger et al., 1984a). The association between blood alcohol concentration (BAC) and risk of TBI is well established for all external causes, such as motor-vehicle crashes, violence, and even falls. One of the earliest incidence reports on TBI and alcohol involvement was by Rimel (1981), who showed that 72% of patients identified in a central Virginia TBI databank had positive BAC rates on admission and 55% were legally drunk (BAC, 0.10% or higher). Kraus et al. (1989) reported in a TBI incidence study of San Diego County residents in 1981 that 49% of those who were tested for BAC had a BAC of 0.10% or higher (which is either an offense itself or presumptive evidence of driving under the influence). Langlois et al. (2003), reporting on a 14-state TBI surveillance system in 1997, found that 43% of those (including pedestrians) who sustained TBI in motor-vehicle crashes had a BAC of 0.10% or higher; the percentages of those who sustained TBI in falls and assaults were 7% and 28%, respectively. Warren et al. (1995), in a study of TBI in Alaskan residents, reported that almost 67% of those tested had a BAC of 0.10% or higher. Findings like those are not peculiar to the United States. A few non-US TBI incidence studies show evidence of alcohol use. Chiu and colleagues (2007) found that 15% of adults who
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Gulf War and Health, Volume 7: Long-Term Consequences of Traumatic Brain Injury sustained TBI in 2001 in Taipei City, Taiwan, used alcohol before the injury incident compared with 42% in Hualein County in the southern part of Taiwan. Researchers in Spain (Vazquez-Barquero et al., 1992) reported that 55% of males and 40% of females with TBI who presented for admission were intoxicated. Similarly, positive BAC rates were reported by Nestvold et al. (1988) and Ingebrigtsen et al. (1998). Simpson and co-workers (1981) reported that among those who died of TBI in New South Wales and were tested, 44% of motor-vehicle drivers, 39% of suicides, and 27% of people who sustained TBI in falls had BAC of 80 mg% or higher. The percentages of people who were tested for BAC in the last four reports were not reported. External Causes of Traumatic Brain Injury Only about half the 66 US and non-US studies reporting the incidence of TBI give details on the exposures that led to it. Data from those studies (Tables 3.11 and 3.12) suggest that the most frequent exposure associated with brain injury is transportation. That category includes automobile and truck occupants, bicycles and motorcycle riders, and pedestrians hit by vehicles and, less frequently, aircraft, watercraft, and road farm equipment. One precaution in discussing reported external causes is that the specific components of each of the general categories are not always uniform. For example, TBI stemming from bicycle–motor-vehicle collisions may be classified as “motor vehicle” or “sports or recreation,” depending on the inclination of the researcher. As can be seen from Tables 3.11 and 3.12, the distributions of those gross external causes can vary widely among studies, but they do illustrate vast differences within a general cause. For example, in the two US ED-based studies (Guerrero et al., 2000; Jager et al., 2000), the most important exposure reported is falls, compared with hospital-based studies, in which transportation is the most frequent cause of brain injury. But in two US studies and the study in South Africa, the most frequently reported external cause is violence (which includes the use of firearms and self-inflicted injury); in these studies, incidence was determined on the basis of inner-city populations. An analysis by Adekoya et al. (2002) in the United States reported that the leading cause of TBI deaths was violence, especially related to firearms. Falls are also an important cause of TBI in the United States. Recent studies reported by Rutland-Brown et al. (2006) in the United States and Ingebrigtsen et al. (1998) in Norway show falls as the leading cause of TBI. Additional important exposures involve sports and recreational activities. Misclassifications are likely, however; for example, sports-related events may account for up to 10% of TBI deaths but might be reported as falls or as being struck by an object (Whitman et al., 1984). Reports from Alaska (Warren et al., 1995) and Australia (Tate et al., 1998) show sports and recreation activities account for one-fifth to one-fourth of TBI hospital admissions. Military Exposures Although there is ample literature on injury in military populations (e.g., Smith et al., 2000), only three population-based TBI incidence studies could be located. McCarroll and Gunderson (1990) published a report on TBI hospitalization rates in the US Army. The database used was the US Army Patient Administration Systems and Biostatistics Activity for fiscal years 1983–1987. The number of active-duty personnel was obtained from the Defense Manpower Data Center. ICD-9 codes 800, 801, 850, 851, 852, 853, and 854 were used to identify hospital-admitted TBI patients. Incidences per 100,000 persons were derived by age group, sex, and race. About 2,500 patients were admitted each year over the 5-year study period. Rates of concussion and intracranial injury were somewhat higher in males than in females, but the reverse was
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Gulf War and Health, Volume 7: Long-Term Consequences of Traumatic Brain Injury observed in some years. The investigators found that 10% of the TBI patients had alcohol or drug involvement, and 97% of the alcohol related-TBIs were in males. Ommaya and associates (1996) evaluated TBI incidence in the US military medical system. Records of discharges from military facilities and private facilities reimbursed by the military for fiscal year 1992 were reviewed for TBI admissions. Medical records of persons with a head-injury diagnosis—ICD-9-CM codes 800–801, 803–804, and 850–854—were identified. ICDMAP (MacKenzie et al., 1989b) was used to convert ICD codes to AIS values. The investigators reported an incidence of 21 (female beneficiaries) to 231 (male active-duty) per 100,000 of population by age group. TBI admission rates were higher in active-duty males 15–17 years old and 18–24 years old. The most common diagnosis was intracranial injury in military hospital admissions and frequently involved firearms. Falls and motor-vehicle crashes accounted for over 62% of the admissions, and fighting 10%. Case-fatality rates (CFRs) ranged from 0% for parachuting to 41% for firearms-related injury. Details on injury severity were not highlighted. Ivins and associates (2006) studied rates of TBI hospitalization of active-duty US Army personnel in 1990–1999. The data source was the Standard Inpatient Data Record database. TBI was identified on the basis of at least one IDC-9-CM code of 800–801, 803–804, and 850–854 in the medical record. ICDMAP-90 was used to assign AIS severity scores for each diagnosis. When there was a lack of information, such as LOC, severity of the TBI was assigned by using criteria developed by the American Congress of Rehabilitation Medicine. Rate ratios were used to compare the incidence of TBI hospitalizations in the Army with the incidence in US civilians 17–49 years old. The overall TBI hospital admission rate in fiscal year 1990 was 248/100,000 active-duty personnel. The rate in 1999 was 62/100,000, 75% lower. TBI incidence declined in each of the three severity classes, but the largest decline in admission rates was in those who had a diagnosis of mild TBI. Overall admission rates declined equally in males and females and in all age groups. There was little change in rates of TBI hospitalization of military active-duty personnel treated in civilian hospitals during the same period. The researchers concluded that the basis of the dramatic decline in rates was effective injury-prevention measures, such as stricter drug- and alcohol-abuse policies, and changes in the Army population; and that changes in hospital admission policies most likely contributed to the decrease in rates of hospitalization for mild TBI. RECURRENT TRAUMATIC BRAIN INJURY Researchers at the Mayo Clinic (Annegers et al., 1980) were among the first to measure the relative risk (RR) of TBI in those with a previous brain injury. They estimated that the risk of a second TBI in those with an earlier TBI was about 3 times the risk of TBI in the general population without such a history. The RR of recurrent TBI given any initial head injury increased with age, and the RR of a third TBI given a second head injury was 8–9 times that of an initial head injury. Jagger et al. (1984b) observed that 31% of their TBI patients reported a previous hospitalization for a head injury. Nestvold and associates (1988) reported that 17% of 465 patients admitted to three hospitals in Akershus County, Norway, had reported an earlier head injury, and about one-fourth of those reported more than one previous TBI. Salcido and Costich (1992) called attention to some possible effects of repeat TBI, including psychosocial aspects and the course of a second rehabilitation. Ruff and co-workers (1990), Kreutzer and co-
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Gulf War and Health, Volume 7: Long-Term Consequences of Traumatic Brain Injury workers (1990), and Corrigan et al. (1995) reviewed the literature on TBI and recurrent injury and showed a strong association with alcohol abuse. Closely related to repeat TBI is what has been called the “second-impact syndrome,” in which a repeat mild TBI was catastrophic or even fatal (Kelly et al., 1991). Gronwall and Wrightson (1975) concluded that the effects of concussion might be cumulative especially in sports, in which populations may be easily monitored. Recurrent head injury in sports has been the subject of several case reports and case-series studies (e.g., Kelly et al., 1991; Cantu and Voy, 1995). Their findings of risks posed by recurrent TBI have prompted recommendations on when players can return to games in the event of even a minor concussion (CDC, 1997). TRAUMATIC BRAIN INJURY AND SHORT-TERM OUTCOMES One outcome of TBI is death. Whereas mortality is an ideal measure of the magnitude of severity of TBI in the general population, the CFR after hospital admission is a measure of the immediate gross consequences of brain injury. The CFR has been used for decades as an indicator of hospital quality of care, but its use is subject to biases as described below. Case-Fatality Rates CFR data are available from 15 US population-based incidence studies (Table 3.13). They range from 4.4/100 hospitalized patients in Maryland (MacKenzie et al., 1989a) to about 25/100 in the Bronx, New York (Cooper et al., 1983), and 23/100 in Oklahoma (Oklahoma State Department of Health, 1991). The range in rates may reflect gross differences in hospital patient-admission practices. That is, hospitals that admit a high proportion of patients with severe brain injury would be expected to have higher CFRs than hospitals that admit a large proportion of patients with mild brain injury, who are less likely to die. CFRs in the most recent reports in the United States show the effect of changes in hospital admission practices of the last decade: fewer of the mildly head-injured persons were admitted. Table 3.14 summarizes CFR data from outside the United States. The rates in the 15 studies range from 0.8/100 hospitalized patients in a report from South Australia (Badcock, 1988) to 30/100 in a county in Denmark (Engberg and Teasdale, 2001); the latter CFR represented only hospital-admitted patients with ICD-9-CM codes 850–854. The very low rate in South Australia may reflect the fact that over 90% of the patient cohort admitted to the hospitals in the study region had mild TBI. The CFR in severe-TBI patients in the study was 55%, which is comparable with rates in other studies that focused on severe-TBI patients. Discounting the single high CFR from Denmark, all remaining rates are less than 10/100 admitted patients. Occasionally, a total or general CFR appears in the literature (e.g., Servadei et al., 2002a). Such a rate would reflect both in-hospital and prehospital deaths and express the risk of death from the moment of injury to hospital discharge. It is often 2 or 3 times the in-hospital CFR. Examples are found in Kraus et al. (1984), Vazquez-Barquero et al. (1992), and Tiret et al. (1990).
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Gulf War and Health, Volume 7: Long-Term Consequences of Traumatic Brain Injury Disposition at the End of Acute Care As previously noted, one of the scales used to assess early outcome after hospitalization for TBI is the GOS. The GOS is a crude indicator of medical (neurologic) complications or of residual effects at the time of discharge from a primary treatment center. The major difficulty with the GOS is its inability to classify patients properly because of the lack of specific criteria that separate severe from moderate and moderate from the good-recovery categories. Good recovery does not mean, nor was it ever intended to mean, complete recovery, and, as noted above, Jennett and Teasdale (1981) devised an extended version of the GOS (GOS-E) to account for the insensitivity of the scale to some changes in functional ability, especially in the moderate and severe categories. The large number of population-based TBI incidence studies might suggest the availability of much more information on the GOS as an early hospital-discharge tool, but only seven of the 66 studies (US and non-US) reported on the scale. Rimel (1981) observed that 69% of TBI patients had a “good recovery” at the time of discharge. The highest percentage of persistent vegetative state was also reported in that study. Almost all other studies in Table 3.15 had a rate of good recovery of 75% or higher. The one exception is the study by Masson et al. (2003), in which only 18% of patients were discharged with a good recovery; their study population, however, consisted of only patients admitted to the hospital with severe TBI. SUMMARY Almost all the incidence studies had shortcomings, and that should be considered in drawing conclusions. No two published studies are identical in methods. However, many studies have used reasonable methods to identify patient cases, defined and measured the populations that gave rise to the patients, used acceptable methods in identifying patients in treatment facilities or in administrative datasets, defined TBI (and severity levels) in reasonable ways, classified exposures that gave rise to the injuries in ways that make sense, recorded basic descriptive information about patients in uniform formats, and, in longitudinal studies, followed patients for outcomes by using acceptable methods to reduce losses and used accepted outcome instruments. Thus, we can learn a great deal about the epidemiology of TBI and use that knowledge to help in designing prevention strategies.
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Gulf War and Health, Volume 7: Long-Term Consequences of Traumatic Brain Injury TABLE 3.12 Percent Distributions of TBI Incidence Cases by External Cause: Non-US Studies Reference Transport Falls Firearms / Violencea Sport / Recreation Otherb Tiret et al., 1990 60 33 <1 NS 7 Nell and Brown, 1991c Females: 40 3 39 NS 16 Males: 36 4 46 15 Vazquez-Barquero et al., 1992 60 24 NS NS 16 Chiu et al., 1997 69 20 7 1 3 Hillier et al., 1997 57 29 10 NS 4 Servadei et al., 1988 69 26 1 NS 5 Ingebrigtsen et al., 1998 21 62 7 NS 10 Tate et al., 1998 40 20 8 25 6 Alaranta et al., 2000 26 61 5 NS 8 Firsching and Woischneck, 2001 56 31 12 NS NS Masson et al., 2001 48 42 3 NS 7 Servadei et al., 2002a 48 33 1 1 17 Andersson et al., 2003 16 58 NS NS 26 Kleiven et al., 2003 26 54 15 NS 7 Masson et al., 2003 59 16 10 NS 14 Chiu et al., 2007 Taipei: 45 34 11 NS 10 Hualien Co:55 28 13 NS 4 aIncludes self-inflicted injury. bIncludes work and all other causes. cBoth races, nonfatal TBI. NOTE: Co = county, NS = not stated.
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Gulf War and Health, Volume 7: Long-Term Consequences of Traumatic Brain Injury TABLE 3.13 TBI In-Hospital Case Fatality Rates (CFR) from US Population-Based Studies Reference Location Source of Data and Study Population N = Sample Size CFR % Rimel, 1981 Central Virginia Hospital medical records N = 1330 7.0 Cooper et al., 1983 Bronx, New York Hospital medical and medical exam records N = 1209 24.9 Kraus et al., 1984 San Diego County, California Hospital medical records and medical exam records N = 3358 5.2 Whitman et al., 1984 Chicago area Hospital medical records and medical exam records N = 782 6.9 Jagger, 1984b North Central Virginia Hospital records N = 735 6.5 Fife et al., 1986 Rhode Island Hospital records N = 2870 4.9 MacKenzie et al., 1989a Maryland Hospital records N = 5838 4.4 Oklahoma State Department of Health, 1991 Oklahoma Hospital/medical examiner records N = 3672 23 Schuster, 1994 Massachusetts Hospital/medical examiner records N = 5778 10.1 Warren et al., 1995 Alaska Trauma registry N = 2178 5.6 Gabella et al., 1997b Colorado TBI surveillance N = 6863 7.6 Gabella et al., 1997a Colorado, Missouri, Oklahoma, Utah Hospital discharge data N = 11,611 6.9 Langlois et al., 2003 US 14 state TBI surveillance system N = 67,309 6.9 Rutland-Brown et al., 2006 US National Hospital Discharge Survey and Multiple Cause of Death tape N = 340,757 14.9 Langlois et al., 2006 US Same as Rutland-Brown, 2003 N = 284,900 17.5 NOTE: CFR = case fatality rate, TBI = traumatic brain injury.
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Gulf War and Health, Volume 7: Long-Term Consequences of Traumatic Brain Injury TABLE 3.14 TBI In-Hospital Case Fatality Rates (CFR) from Non-US Population-Based Studies Reference Location Source of Data and Study Population Group Size CFR % Badcock, 1988 South Australia Medical record 1698 0.8 Nestvold et al., 1988 Norway Medical record 488 3.3a Servadei et al., 1988 Ravenna, Italy Hospital record 578 1.9a Tiret et al., 1990 Aquitaine, France Medical record review 281 4.4 Vazquez-Barquero et al., 1992 Cantabria, Spain Hospital record review 477 1.7 Engberg, 1995 Frederisksborg County, Denmark National hospital discharge registry 95 16a Tate et al., 1998 New South Wales Hospital record review 1259 3.9 Engberg and Teasdale, 2001 Denmark National hospital discharge registry NS 30b Gururaj, 2002 Bangalore, India Neurotrauma registry 2814 9 Servadei et al., 2002b Romagna and Trentino, Italy Hospital discharge records 4442 1.0a Servadei et al., 2002a Romagna, Italy Hospital discharge records 2430 2.8c Baldo et al., 2003 Northeast Italy Hospital discharge records 11,074 3.2d Santos et al., 2003 Portugal National Institute of Statistics 39,042 9.8a Steudel et al., 2005 Germany Federal Bureau of Statistics 276,758 1 Chiu et al., 2007 Taipei and Hualien County, Taiwan TBI registry Taipei: 5754 Taipei: 5.4 Hualein County: 1474 Hualein County: 6.7 aCFR derived from text. bCFR for ICD 851 –854. cFor residents and nonresidents. dFrom severity rates reported. NOTE: CFR = case fatality rates, TBI = traumatic brain injury.
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Gulf War and Health, Volume 7: Long-Term Consequences of Traumatic Brain Injury TABLE 3.15 Percent Distribution of GOS Outcome Categories at Hospital Discharge Rate for US and Non-US Studies Reference Good Recovery Moderate Disability Severe Disability Persistent Vegetative State Death Rimel, 1981 69 12 8 4 7 Kraus et al., 1984 90 3 1 0.5 6 Chiu et al., 1997 87 4 3 1 5 Masson et al., 2003 18 9 16 3 52 Langlois et al., 2003 74 10 6 0.6 NS Chiu et al., 1997 (Taipei City only) 87 6 4 0.3 3 Wu et al., 2008 77 7 2 3 11 NOTE: GOS = Glasgow Outcome Score, NS = not stated.
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Gulf War and Health, Volume 7: Long-Term Consequences of Traumatic Brain Injury Drake, A. I., E. C. McDonald, N. E. Magnus, N. Gray, and K. Gottshall. 2006. Utility of Glasgow Coma Scale-Extended in symptom prediction following mild traumatic brain injury. Brain Injury 20(5):469–475. Engberg, A. 1995. Severe traumatic brain injury—epidemiology, external causes, prevention, and rehabilitation of mental and physical sequelae. Acta Neurologica Scandinavica. Supplementum 164:1–151. Engberg, A., and T. Teasdale. 2001. Traumatic brain injury in Denmark 1979–1996. European Journal of Epidemiology 17:437–442. Fife, D. 1987. Head injury with and without hospital admission: Comparisons of incidence and short-term disability. American Journal of Public Health 77(7):810–812. Fife, D., G. Faich, W. Hollinshead, and W. Boynton. 1986. Incidence and outcome of hospital-treated head injury in Rhode Island. American Journal of Public Health 76(7):773–778. Firsching, R., and D. Woischneck. 2001. Present status of neurosurgical trauma in Germany. World Journal of Surgery 25(9):1221–1223. Fuortes, L., K. Phillips, and J. Muldoon. 1990. Traumatic head and spinal cord injury in Iowa. Iowa Medicine 80(12):560–562. Gabella, B., R. Hoffman, and G. Land. 1997a. Traumatic brain injury—Colorado, Missouri, Oklahoma, and Utah 1990–1993. Morbidity and Mortality Weekly Report 46:8–11. Gabella, B., R. E. Hoffman, W. W. Marine, and L. Stallones. 1997b. Urban and rural traumatic brain injuries in Colorado. Annals of Epidemiology 7(3):207–212. Gronwall, D., and P. Wrightson. 1975. Cumulative effect of concussion. Lancet 2(7943):995–997. Guerrero, J. L., D. J. Thurman, and J. E. Sniezek. 2000. Emergency department visits associated with traumatic brain injury: United States, 1995–1996. Brain Injury 14(2):181–186. Gururaj, G. 2002. Epidemiology of traumatic brain injuries: Indian scenario. Neurological Research 24(1):24–28. Hillier, S. L., J. E. Hiller, and J. Metzer. 1997. Epidemiology of traumatic brain injury in South Australia. Brain Injury 11(9):649–659. Hoofien, D., E. Vakil, A. Gilboa, and P. Donovick. 2003. Comparison of the predictive power of socioeconomic variables, severity of injury and age on long-term outcome of traumatic brain injury: Sample specific variables versus factors as predictors. Brain Injury 16:9–27. Ingebrigtsen, T., K. Mortensen, and B. Romner. 1998. The epidemiology of hospital-referred head injury in northern Norway. Neuroepidemiology 17(3):139–146. Ivins, B. J., K. A. Schwab, G. Baker, and D. L. Warden. 2006. Hospital admissions associated with traumatic brain injury in the US Army during peacetime: 1990s trends. Neuroepidemiology 27(3):154–163. Jager, T. E., H. B. Weiss, J. H. Coben, and P. E. Pepe. 2000. Traumatic brain injuries evaluated in US emergency departments, 1992–1994. Academic Emergency Medicine 7(2):134–140. Jagger, J., D. Fife, K. Vernberg, and J. A. Jane. 1984a. Effect of alcohol intoxication on the diagnosis and apparent severity of brain injury. Neurosurgery 15(3):303–306. Jagger, J., J. I. Levine, J. A. Jane, and R. W. Rimel. 1984b. Epidemiologic features of head injury in a predominantly rural population. Journal of Trauma-Injury Infection and Critical Care 24(1):40–44.
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Gulf War and Health, Volume 7: Long-Term Consequences of Traumatic Brain Injury Langlois, J. A., W. Rutland-Brown, and K. E. Thomas. 2006. Traumatic Brain Injury in the United States: Emergency Department Visits, Hospitalizations, and Deaths. Atlanta, GA: Centers for Disease Control and Prevention, National Center for Injury Prevention and Control. Levi, L., S. Linn, M. Revach, and M. Feinsod. 1990. Head trauma in northern Israel: Incidence and types. Neuroepidemiology 9(5):278–284. Louisiana Office of Public Health Injury and Research Prevention Section. 2004. Traumatic Brain and Spinal Cord Injury in Louisiana: 1996–1999. Baton Rouge, LA: Department of Health and Hospitals, Office of Public Health. MacKenzie, E. J. 1984. Injury severity scales: Overview and directions for future research. American Journal of Emergency Medicine 2(6):537–549. MacKenzie, E. J., S. L. Edelstein, and J. P. Flynn. 1989a. Hospitalized head-injured patients in Maryland: Incidence and severity of injuries. Maryland Medical Journal 38(9):725–732. ———. 1990. Trends in hospitalized discharge rates for head injury in Maryland, 1979–86. American Journal of Public Health 80(2):217–219. MacKenzie, E. J., D. M. Steinwachs, and B. Shankar. 1989b. Classifying trauma severity based on hospital discharge diagnoses. Validation of an ICD-9-CM to AIS-85 conversion table. Medical Care 27(4):412–422. Masson, F., M. Thicoipe, P. Aye, T. Mokni, P. Senjean, V. Schmitt, P. H. Dessalles, M. Cazaugade, and P. Labadens. 2001. Epidemiology of severe brain injuries: A prospective population-based study. Journal of Trauma-Injury Infection and Critical Care 51(3):481–489. Masson, F., M. Thicoipe, T. Mokni, P. Aye, P. Erny, and P. Dabadie. 2003. Epidemiology of traumatic comas: A prospective population-based study. Brain Injury 17(4):279–293. McCarroll, J. E., and C. Gunderson. 1990. 5-year study of incidence rates of hospitalized cases of head injuries in the US Army. Neuroepidemiology 9(6):296–305. Modell, J. G., and J. M. Mountz. 1990. Drinking and flying—the problem of alcohol use by pilots. New England Journal of Medicine 323(7):455–461. Nell, V., and D. S. Brown. 1991. Epidemiology of traumatic brain injury in Johannesburg—II. Morbidity, mortality and etiology. Social Science and Medicine 33(3):289–296. Nell, V., D. W. Yates, and J. Kruger. 2000. An extended Glasgow Coma Scale (GCS-E) with enhanced sensitivity to mild brain injury. Archives of Physical Medicine and Rehabilitation 81(5):614–617. Nestvold, K., T. Lundar, G. Blikra, and A. Lonnum. 1988. Head injuries during one year in a central hospital in Norway: A prospective study. Epidemiologic features. Neuroepidemiology 7(3):134–144. Oklahoma State Department of Health. 1991. Traumatic Brain Injuries Oklahoma, 1989. Oklahoma City, OK. Ommaya, A. K., A. K. Ommaya, A. L. Dannenberg, and A. M. Salazar. 1996. Causation, incidence, and costs of traumatic brain injury in the US military medical system. Journal of Trauma-Injury Infection and Critical Care 40(2):211–217.
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Gulf War and Health, Volume 7: Long-Term Consequences of Traumatic Brain Injury Pettigrew, L. E., J. T. Wilson, and G. M. Teasdale. 2003. Reliability of ratings on the Glasgow Outcome Scales from in-person and telephone structured interviews. Journal of Head Trauma Rehabilitation 18(3):252–258. Pickelsimer, E. E., A. W. Selassie, J. K. Gu, and J. A. Langlois. 2006. A population-based outcomes study of persons hospitalized with traumatic brain injury: Operations of the South Carolina traumatic brain injury follow-up registry. Journal of Head Trauma Rehabilitation 21(6):491–504. Pickett, W., C. Ardern, and R. J. Brison. 2001. A population-based study of potential brain injuries requiring emergency care. Canadian Medical Association Journal 165(3):288–292. Rimel, R. W. 1981. A prospective study of patients with central nervous system trauma. Journal of Neurosurgical Nursing 13(3):132–141. Ruff, R., F. Marshall, and M. R. Klauber. 1990. Alcohol abuse and neurologic outcomes of the severely head injured. Journal of Head Trauma Rehabilitation 5:21–31. Rutland-Brown, W., J. A. Langlois, K. E. Thomas, and Y. L. Xi. 2006. Incidence of traumatic brain injury in the United States, 2003. Journal of Head Trauma Rehabilitation 21(6):544–548. Salcido, R., and J. F. Costich. 1992. Recurrent traumatic brain injury. Brain Injury 6(3):293–298. Santos, M. E., L. De Sousa, and A. Castro-Caldas. 2003. [Epidemiology of craniocerebral trauma in Portugal]. Acta Médica Portuguesa 16(2):71–76. Schootman, M., M. Harlan, and L. Fuortes. 2000. Use of the capture-recapture method to estimate severe traumatic brain injury rates. Journal of Trauma-Injury Infection and Critical Care 48(1):70–75. Schuster, M. 1994. Traumatic Brain Injury in Massachusetts. Massachusetts Department of Public Health, Bureau of Family and Community Health, Injury and Prevention Control Program. Selassie, A. W., M. L. McCarthy, and E. E. Pickelsimer. 2003. The influence of insurance, race, and gender on emergency department disposition. Academic Emergency Medicine 10(11):1260–1270. Selassie, A. W., E. E. Pickelsimer, L. Frazier, Jr., and P. L. Ferguson. 2004. The effect of insurance status, race, and gender on ED disposition of persons with traumatic brain injury. American Journal of Emergency Medicine 22(6):465–473. Selassie, A. W., E. Zaloshnja, J. A. Langlois, T. Miller, P. Jones, and C. Steiner. 2008. Incidence of long-term disability following traumatic brain injury hospitalization, United States, 2003. Journal of Head Trauma Rehabilitation 23(2):123–131. Selecki, B. R., I. T. Ring, and D. Simpson. 1981. Injuries to the Head, Spine, and Peripheral Nerves. Neurological Society of Australia, Truama Subcommittee and Division of Health Services Research, Health Commission of New South Wales. Servadei, F., V. Antonelli, L. Betti, A. Chieregato, E. Fainardi, E. Gardini, G. Giuliani, L. Salizzato, and J. F. Kraus. 2002a. Regional brain injury epidemiology as the basis for planning brain injury treatment. The Romagna (Italy) experience. Journal of Neurosurgical Sciences 46(3–4):111–119.
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