Sex and age-related implications for preventive measures of intensive care admitted traumatic brain injury patients in Switzerland: an observational study

TL;DR

This study explores how sex and age influence traumatic brain injury causes in Swiss ICU patients, suggesting tailored prevention strategies.

Contribution

The study identifies sex- and age-specific patterns in TBI causes and risk behaviors in Switzerland.

Findings

Men were more likely to suffer road traffic accidents, while women were more likely to suffer low energy falls.

Young patients were more likely to be involved in road traffic accidents, while older patients in low energy falls.

Males showed higher rates of alcohol intoxication, while females were less likely to wear helmets in two-wheeled accidents.

Abstract

Epidemiological studies of traumatic brain injury (TBI) in Switzerland have, to date, poorly investigated sex-related differences in causality and predisposing factors. This study examines differences in sex and age related TBI epidemiology in a high-volume trauma centre intensive care unit (ICU) cohort, aiming to identify potential targets for prevention.

This retrospective, single centre study includes all consecutive TBI patients admitted to the ICU in a 4-year study period. Patient demographics, comorbidities, co-medication, trauma setting and associated risk behaviour were compared between sexes and age groups (over/under 65 years).

592 patients (73.3% male, 26.7% female) were included. The leading cause of TBI was falls (52.4%), followed by road traffic accidents (RTA) (35.8%). Overall, men were more likely to suffer from a road traffic accident, while women were more likely to suffer a low energy fall. No differences in injury severity and comorbidities between sexes were observed. Young patients most likely suffered from a RTA while older patients from a low energy fall irrespective of sex. Both sexes portrayed risk associated behaviors with higher rates of alcohol intoxication in males, while females were less likely to wear a helmet in two-wheeled RTAs.

We conclude that sex- and age-related epidemiologic differences in TBI exist. Our results suggest that sex and age-specific prevention measures might be advisable for optimal mitigation of TBI and its sequelae.

Full text

Background

Traumatic brain injury (TBI) continues to be a significant cause of morbidity and mortality worldwide, with relevant public health and social impact contributing to societal disease burden and loss of productive years [1–3]. The epidemiology of TBI is well described in the developed world [2, 4–6], with socio-economic, cultural, and geopolitical factors impacting differences in local incidence, trauma mechanisms, and long-term outcomes. Sex, age, and gender-specific factors play a role in the epidemiology of TBI [7]. For example, men are more prone to suffer a work related TBI or a road traffic accident (RTA), while women are at a higher risk of TBI due to violence in interpersonal relationships [8–10]. Furthermore, falls are the most predominant cause of TBI in older patients [11].

Switzerland is a well-developed central European country ranked highest in the global Human development index (HDI) [12] and 13 th in the global gender gap index in 2022 [13]. Few studies describing the epidemiology of TBI in Switzerland exist [14–17]. Sex-related differences in causality have not been investigated in-depth. To date, only one study has described sex-related differences in a Swiss TBI cohort [18]. As growing evidence supports improved outcomes with personalized care[19], we aimed to identify specific potential prevention targets in different patient populations, focusing on epidemiologic causality differences between the sexes.

Materials and methods

This is a single-center, retrospectively analyzed registry-based observational study conducted at the Institute for Intensive Care, University Hospital of Zurich in Switzerland. All consecutive TBI patients [20] admitted to the ICU between January 2018 and August 2021 were screened for eligibility.

Inclusion and exclusion criteria

All adult patients (≥ 18 years of age) with TBI admitted to the ICU of the University Hospital Zurich were included. Patients were excluded if the time interval between trauma and hospital admission was greater than 24 h, or if they refused analysis of their data (documented written or oral refusal).

Clinical management

All patients were treated according to current best practice and an institutional clinical protocol based on the Brain trauma foundation guidelines [21], focusing on the prevention of secondary brain injury. An interdisciplinary team of ICU consultants, neurosurgeons and trauma surgeons were responsible for clinical decision-making.

Data collection

The registry (built within the Research electronic data capture (REDcap; Vanderbilt University, Nashville, USA)[22, 23]) was established retrospectively and data were collected from the electronic medical record (KISIM-TM; Cistec® Zurich, Switzerland) and the electronic patient data management system (MetaVision Suite; iMDsoft®, Tel Aviv, Israel). Demographic data collected includes age, sex, comorbidities based on the Charlson Comorbidity Index (CCI)[24], prior chronic medication, clinical frailty index [25], living situation (alone, with other persons at home, retirement home, nursing home) and level of social or physical dependence (independent vs. dependency on ambulatory social or medical services).

The injury event was characterized by location and setting (rural, urban, indoor, outdoor, home environment, workplace, school, at sports or leisure activities, military setting) and cause (RTA, fall, criminal activity, and others). In the case of RTAs, a distinction of the involved transport mode was recorded (car, motorcycle, e-scooter, bicycle, e-bicycle or pedestrian) as well as the usage of safety equipment (cars: usage of seatbelts; other modes of transport: usage of helmets). The incidence of concomitant drug use (alcohol and illicit substances), self-inflicted injuries, and attempted suicide was also recorded.

Injury Severity Score (ISS) [26] and Abbreviated Injury Scale (AIS) [27], as well as initial Glasgow Coma Scales score (GCS) [28, 29] were used to assess injury severity. Lastly, in-hospital mortality rate was noted.

Methods

Statistical analysis was performed using R version 3.3.1. Data was dichotomized by sex (male vs. female). A subgroup analysis was performed describing different age groups (over/under 65 years). Consequently, analysis between sex and between sex and age was carried out. Data are reported as counts/percentages, or as median including the interquartile range (IQR) as appropriate [30]. All continuous data were tested for normality using Shapiro–Wilk's test. Categorical or ordinal variables were compared using Pearson's χ2 or Fisher's exact test, while continuous variables were compared using Student's t-tests or Mann–Whitney U tests for parametric and non-parametric data, respectively, where appropriate [31, 32]. The significance level was set at p < 0.05. Our primary aim was to describe sex related differences relevant for prevention rather than the effect of these differences on outcome. Consequently, we abstained from performing a multivariable analysis.

Results

592 consecutive patients (73.3% male) with a median age of 56 (IQR 35–74) years were included in this study (Tables 1 and 2). Men were significantly younger, with a median age of 53 vs. 65 years (p = 0.001). Women were less likely to be independent (82.3 vs. 91.4%, p = 0.01). Furthermore, women had a significantly higher incidence of psychiatric comorbidities (21.5% vs 12.1%, p = 0.014) and were taking psychotropic co-medication more frequently than men (26.8% vs 17.1%, p = 0.012). Regarding trauma setting, women were more frequently injured indoors (37.3% vs 22.1%, p < 0.001) and within the home environment (44.9% vs 22.6%, p < 0.001), while men were more frequently injured in a rural setting (26% vs 16.5%, p = 0.02). The most frequent trauma mechanism in men was RTAs (37.9%). Low energy falls were the most common trauma mechanism in women and were significantly more common versus men (44.9 vs. 28.8%, p < 0.001). Men were more frequently under the influence of alcohol at the time of trauma than women (23.3% vs 12%, p = 0.004). Women suffered two-wheeled RTAs while not wearing a helmet significantly more frequently than men (57.1 vs. 22.8%, p = 0.045).Table 1. Whole population: demographics, injury severity and outcomeWhole population (N = 592)Male (73.3%)Female (26.7%)p-valueAge53 (33—71)65 (49–79)** < 0.001Living situationalone at home109 (25.1%)52 (32.9%)0.712with other persons at home263 (60.6%)77 (48.7%)0.118Support in everyday lifeindependent395 (91.4%)130 (82.3%)0.01Comorbiditiespsychiatric diagnosis56 (12.1%)34 (21.5%)0.014alcoholism86 (19.8%)29 (18.4%)0.779smoking74 (17.1%)29 (18.4%)0.804Charlson Comorbidity Indextotal0 (0—1)0 (0—1)0.58Injury Severity Score22 (14—29)24.5 (16—30)0.864Abbreviated Injury ScoreHead and Neck3 (2—4)3(3—5)0.166Facial0 (0—2)0 (0—1)0.448Chest0 (0—3)0 (0—3)0.523Abdomen0 (0—0)0 (0—2)0.679Extremity, pelvis0 (0—2)0 (0—2)0.185Other1 (0—1)1 (0—1)0.058First preclinical GCS13 (7—15)13 (6—14)0.171OutcomeAlive at discharge370 (85.3%)115 (72.8%) < 0.001**^^Data shown as number (%) or as median (IQR)Table 2. Whole population: Trauma setting, mechanism, risk behaviour and co-medicationTrauma settingMale (73.3%)Female (26.7%)p-valueRural113 (26.0%)26 (16.5%)0.02Urban103 (23.7%)34 (21.5%)0.649Home environment98 (22.6%)71 (44.9%)** < 0.001Workplace/school29 (6.7%)2 (1.3%)0.006Indoor95 (22.1%)59 (37.3%) < 0.001**Trauma mechanismRoad traffic accidenttotal164 (37.9%)47 (29.9%)0.754car33 (7.6%)10 (6.3%)motorcyclist52 (12.0%)8 (5.1%)e-scooter6 (1.4%)0 (0.0%)bicycle50 (11.5%)10 (6.3%)e-bike10 (2.3%)3 (1.9%)pedestrian12 (2.8%)16 (10.1%)Railway accident17 (3.9%)0 (0.0%)Falllow energy fall < 2 m125 (28.8%)71 (44.9%) < 0.001**high energy fall > 2 m90 (20.7%)31 (19.6%)0.855Criminal activity22 (5.1%)1 (0.6%)0.137Gunshot7 (1.6%)1 (0.6%)0.688Burial/Avalanche4 (0.9%)2 (1.3%)0.66Risk behavior and co-medicationUnder influence of alcohol101 (23.3%)19 (12.0%)0.004Under influence of other substances25 (5.8%)4 (2.5%)0.133Self-inflicted injury30 (6.9%)16 (10.1%)0.263Not belted8 (24.2%)1 (10.0%)0.623Not helmetedtotal39 (22.8%)9 (57.1%)0.045motorcyclist4 (7.7%)0 (0.0%)e-scooter6 (100.0%)0 (0.0%)cyclist24 (48.0%)8 (80.0%)e-bike cyclist5 (55.6%)1 (33.3%)Prior medicationpsychotropics74 (17.1%)42 (26.8%)0.012anticoagulation35 (8.1%)21 (13.4%)0.074antiaggregation76 (17.5%)23 (14.7%)0.485^^Data shown as number (%); significant results in the subgroup analysis are with an asterix ()

Younger population (age < 65 years)

In the younger population (Tables 3 and 4), epidemiologic and trauma-associated factors were similar compared to the whole patient population. Specifically, median age, incidence of psychiatric diagnoses, and rate of psychotropic co-medication was higher in women versus men (49 years vs. 38 years, p = 0.035; 32% vs 14%, p < 0.001; 26.3% vs 13.3%, p = 0.01, respectively). Younger women were also more frequently injured at home (32.2% vs 14.7%, p = 0.001). Relative to the whole population, trauma mechanisms were comparable between sexes with the primary cause of TBI being RTAs in both sexes.Table 3. Younger Population: Demographics, injury severity and outcome < 65 years (N = 370)Male (79.9%)Female (20.1%)p-valueAge38 (29—54)49 (33–55)0.035Living situationalone at home83 (28.3%)22 (28.6%)1.00with other persons at home161 (54.9%)41 (53.2%)1.00Support in everyday lifeindependent279 (95.9%)72 (93.5%)0.43Comorbiditiespyschiatric diagnosis42 (14%)25 (32%)** < 0.001**alcoholism64 (21.8%)19 (24.7%)0.706smoking55 (18.8%)20 (26.0%)0.215ilicit drug use38 (13.0%)8 (10.4%)0.677Charlson Comorbidity Index0 (0—0)0 (0—0)0.428Injury Severity Score ISStotal22 (16—29)24 (14—29)0.93Abbreviated Injury ScoreHead and Neck3 (2—4)3 (2—4)0.633Facial0 (0—2)0 (0—1)0.64Chest1 (0—3)(0—3)0.603Abdomen0 (0—2)0 (0—2)0.517Extremity, pelvis1 (0—2)2 (0—2)0.07Other1 (0—1)1 (0—1)0.113First preclinical GCS13 (8—15)12 (5—14)0.461OutcomeAlive at discharge268 (91.5%)63 (81.8%)0.025^^Data shown as number (%) or as median (IQR)Table 4. Younger population: Trauma setting, mechanism, risk behaviour, and co-medicationTrauma settingMale (79.9%)Female (20.1%)p-valueRural88 (30.0%)17 (22.1%)0.216Urban73 (24.9%)19 (24.7%)1Home environment43 (14.7%)24 (31.2%)0.001Workplace/school28 (9.6%)2 (2.6%)0.058Indoor42 (14.5%)15 (19.5%)0.368Trauma mechanismRoad traffic accidenttotal122 (41.8%)31 (40.8%)0.28car25 (8.5%)5 (6.5%)motorcycle42 (14.3%)8 (10.4%)e-scooter5 (1.7%)0 (0.0%)bicycle33 (11.3%)9 (11.7%)e-bike7 (2.4%)2 (2.6%)pedestrian9 (3.1%)7 (9.1%)Railway accident14 (4.8%)0 (0.0%)Falllow energy fall < 2 m55 (18.8%)19 (24.7%)0.321high energy fall > 2 m67 (22.9%)23 (29.9%)0.26Delict21 (7.2%)1 (1.3%)0.543Gunshot5 (1.7%)1 (1.3%)1Burial/Avalanche4 (1.4%)1 (1.3%)1Risk behavior and co-medicationUnder influence of alcohol81 (27.6%)14 (18.2%)0.122Under influence of other substances23 (7.9%)4 (5.2%)0.622Self-inflicted injury26 (8.9%)13 (16.9%)0.068Not belted7 (28.0%)0 (0.0%)Not helmetedTotal31 (35.6%)8 (42.1%)0.281motorcyclist4 (9.5%)0 (0.0%)e-scooter5 (100.0%)0 (0.0%)cyclist17 (51.5%)8 (88.9%)e-bike cyclist5 (71.4%)0 (0.0%)Prior medicationpsychotropics39 (13.3%)20 (26.3%)0.01anticoagulation9 (3.1%)2 (2.6%)1antiaggregation15 (5.1%)3 (3.9%)1^^Data shown as number (%)

Older population (age ≥ 65 years)

When looking at the older population cohort (Tables 5 and 6), there were considerable differences in living situation. Older women were living more commonly alone than men (37% vs 18.4%, p = 0.026). They were more frequently injured indoors (54.3% vs 37.9%, p = 0.025) and within the home environment (58% vs 39%, p = 0.009). Compared to the younger population, there was a considerable shift in cause of trauma with low energy falls being the primary cause of TBI in both sexes.Table 5. Older population: Demographics, injury severity and outcome > 65 years (N = 222)Male (63.5%)Female (36.5%)p-valueAge78 (72—84)79 (72—85)0.082Living situationalone at home26 (18.4%)30 (37.0%)0.026with other persons at home102 (72.3%)36 (44.4%)** < 0.001**retirement home8 (5.7%)7 (8.6%)1.00nursing home2 (1.4%)2 (2.5%)1.00Support in everyday lifeindependent116 (82.3%)58 (71.6%)0.379Estimated Clinical Frailty Index3 (2—4)3 (2—4)0.593Comorbiditiespsychiatric diagnosis14 (9.9%)9 (11.1%)0.961alcoholism22 (15.6%)10 (12.3%)0.641smoking19 (13.5%)9 (11.1%)0.764Charlson Comorbidity Index1 (0—3)1 (0—2)0.15Injury Severity Score ISStotal22 (14—29)25 (16—30)0.289Abbreviated Injury ScoreHead and Neck3 (3—4)4 (3—5)0.072Facial0 (0—2)0 (0—1)0.783Chest0 (0—3)0 (0—2)0.564Abdomen0 (0—0)0 (0—0)0.801Extremity, pelvis0 (0—2)0 (0—2)0.299Other1 (0—1)1 (0—1)0.313First preclinical GCS13 (7—15)13 (6—15)0.257OutcomeAlive at discharge102 (72.3%)52 (64.2%)0.264^^Data shown as number (%) or as median (IQR)Table 6. Older population: Trauma setting, mechanism, risk behaviour and co-medicationTrauma settingMale (63.5%)Female (36.5%)p-valueRural25 (17.7%)9 (11.1%)0.261Urban30 (21.3%)15 (18.5%)0.75Home environment55 (39.0%)47 (58.0%)0.009Indoor53 (37.9%)44 (54.3%)0.025Trauma mechanismRoad traffic accidenttotal42 (29.8%)16 (19.8%)0.216car8 (5.7%)5 (6.2%)motorcycle10 (7.1%)0 (0.0%)e-scooter1 (0.7%)0 (0.0%)bicycle17 (12.1%)1 (1.2%)e-bike3 (2.1%)1 (1.2%)pedestrian3 (2.1%)9 (11.1%)Railway accident3 (2.1%)0 (0.0%)Falllow energy fall < 2 m70 (49.6%)52 (64.2%)0.051high energy fall > 2 m23 (16.3%)8 (9.9%)0.258Delict1 (0.7%)0 (0.0%)Gunshot2 (1.4%)0 (0.0%)Burial/Avalanche0 (0.0%)1 (1.2%)Risk behavior and co-medicationUnder influence of alcohol20 (14.2%)5 (6.2%)0.11Under influence of other substances2 (1.4%)0 (0.0%)Self-inflicted injury4 (2.8%)3 (3.7%)0.708Not belted1 (12.5%)1 (20.0%)0.928Not helmetedtotal7 (23.3%)1 (50.0%)0.711motorcyclist0 (0.0%)0 (0.0%)e-scooter0 (0.0%)0 (0.0%)cyclist7 (41.2%)0 (0.0%)e-bike cyclist0 (0.0%)1 (100.0%)Prior medicationpsychotropics35 (24.8%)22 (27.2%)0.823anticoagulation26 (18.4%)19 (23.5%)0.47antiaggregation61 (43.3%)20 (24.7%)0.009^^Data shown as number (%)

Discussion

Sex-related differences

Our results confirm that sex and age-related differences exist and are in line with previous studies referring to patients with severe TBI in other high income countries (HIC) [2, 4, 33–37]. TBI remains a male predominant patient population across all age groups [2]. With respect to trauma mechanism, we observed distinct sex and age-related differences. Overall, the most common cause of TBI was RTAs in men and low energy falls in women. However, this difference was only observed in the patient population as a whole. Younger patients primarily suffered RTAs and older patients primarily suffered from low energy falls irrespective of sex. The incidence of being under the influence of alcohol when the TBI occurred was higher in men suggesting an increased affinity for risk-taking behaviour. Both alcohol-consumption and stress are associated with higher cortisol levels which in turn has been linked to enhanced risk taking in men but not in women [38–40]. Interestingly, over half of the women compared to less than 25% of men were not helmeted in two-wheeled RTAs.

Women of all ages were more likely to suffer a TBI in the home environment compared to men. The women in this study population were older and more commonly lived independently at home, which could explain this observation. Fall-rate increases with age and remains higher in women with the majority resulting from low energy falls. Furthermore, younger women had a significantly higher rate of previous psychiatric diagnoses and psychiatric co-medication. This may affect trauma incidence, as psychotropic medications are known for increasing the rate of falls [41].

Changing demographics of TBI in Switzerland

There is a shift in global causality of TBI from RTAs to falls, with a continued male predominance and an increasing sex-heterogeneity with age [10, 35]. Previous epidemiologic studies in Switzerland [15, 16] have mirrored these changes and our data further supports this trend. When comparing our study cohort with the most recent Swiss population-based study by Walder et. al. [15], notable parallels are apparent in terms of median age, sex, and age distribution, as well as the distribution of causative factors, with falls being the most common causator of TBI in our cohort, followed by RTAs.

Implications for preventive measures

Based on the presented results, sex specific prevention strategies should be developed and their effects studied. Prevention in men will be most effective if risky behaviour, particularly in younger male road users, is targeted. With the increasing use of two-wheeled e-mobility, especially e-bikes and e-scooters, and their typical injury patterns with even higher rates of TBI [42–44], the importance of wearing a helmet cannot be understated [45]. For example, in this study, none of the patients (all were younger males, n = 6) who suffered an e-scooter accident wore a helmet. This mirrors the data seen in other HIC patient populations [46–49]. Without stricter traffic regulations and mandatory helmet laws, TBI incidence in this group is likely to rise [45, 49]. It is of particular note that overall helmet use was particularly low in women in this patient population, with almost 60% of women not having worn a helmet, underscoring the need for targeted road traffic surveillance in this group also.

Women are most likely to suffer from falls within the home environment irrespective of age, while, in males, this mechanism of injury only becomes the most common cause of TBI in older patients. Focus should continue to be placed on fall prevention in the home environment (removal of tripping hazards, use of handrails, housing on one level etc.). Frailty reduction through exercise intervention [50] might prove beneficial. Rigorous reviews and reduction of co-medications which increase fall rate should be considered[41, 51]. Finally, especially in the very old population, the use of antiaggregation or anticoagulation should be critically assessed as they present an ever-increasing risk factor in severe TBI [52].

Strength and limitations of the study

The patient population was collected using a database of consecutive TBI patients over a 4-year period treated in the trauma ICU of a high-volume trauma centre with standard treatment guidelines of clinical care for TBI through which internal treatment bias was reduced. Extensive data collection and few missing data enabled a high patient inclusion rate. A few study characteristics limit the generalizability of the study, namely the retrospective nature, single centre data collection and the study population originating from a highly developed country with high safety standards. Because our inclusion criteria were limited to patients admitted to the ICU within the first 24 h of hospital admission, cases of secondary or delayed-onset TBI, as well as mild TBI not requiring ICU care, were not captured. Lastly, we abstained from performing a multivariable analysis since our interest was the description of the cohort rather than evaluating whether the differences are relevant for outcome.

Conclusion

Similar to previously reported HIC patient populations, TBI in Switzerland is male predominant. Sex-related epidemiologic differences in TBI were observed. Men most commonly suffered from a RTA trauma mechanism, while women most commonly suffered from low energy falls. Both sexes exhibit risk-associated behaviour. Men demonstrated a higher incidence of being under alcohol while women were frequently not helmeted. Our results suggest that sex and age-specific prevention have great potential impact to mitigate TBI outcomes.