In elite rugby union, suspected concussions lead to immediate removal from play for either permanent exclusion or a temporary 12-min assessment as part of the Head Injury Assessment 1 (HIA1) protocol. The study aims to retrospectively identify a head acceleration event (HAE) severity measure associated with HIA1 removals in elite rugby union using instrumented mouthguards (iMGs).
Methods
HAEs were recorded from 215 men and 325 women, with 30 and 28 HIA1 removals from men and women, respectively. Logistical regression was calculated to identify whether peak power, maximum principal strain (MPS) and/or the Head Acceleration Response Metric (HARM) were associated with HIA1 events compared to non-cases. Optimal threshold values were determined using the Youden Index. Area under the curve (AUC) was compared using a paired-sample approach. Significant differences were set at p < 0.05.
Results
All three severity measures (peak power, HARM, MPS) were associated with HIA1 removals in both the men’s and women’s game. Peak power performed most consistent of the three severity measures for HIA1 removals based on paired-sample AUC comparisons in the men’s and women’s games. The HARM and MPS were found to perform lower than peak linear acceleration in the women’s game based on AUC comparisons (p = 0.006 and 0.001, respectively), with MPS performing lower than peak angular acceleration (p = 0.001).
Conclusion
Peak power, a measure based on fundamental mechanics and commonly communicated in sports performance, was the most effective metric associated with HIA1 removals in elite rugby. The study bridges the gap by identifying a consistent HAE severity measure applicable across sexes.
In most sports, current suspected concussion detection methods rely on visual identification. Peak head kinematic values are often used as a proxy for head acceleration event (HAE) severity, though this has led to inconsistencies in the literature.
Peak power may be a suitable HAE severity measure in sport. Peak power had the most consistent association with Head Injury Assessment 1 (HIA1) removals in men’s and women’s professional rugby union when compared to other severity measures.
Peak power has the potential to be utilised as a severity measure for HAE mitigation strategies and suspected concussion detection tools in sport. Peak power may be easier to adopt as a severity measure by players, coaches and other stakeholders owing to its common use in sports performance.
1 Introduction
Identifying suspected concussions on the field remains challenging in sport [1, 2]. In most sports, current detection methods primarily rely on visual identification and video review by sideline medical practitioners, who look for signs such as cognitive and balance abnormalities [3]. If no observable signs of concussion are present, detection depends on player-reported symptoms. In elite rugby union, suspected concussions lead to immediate removal from play for either permanent exclusion or a temporary 12-min assessment as part of the Head Injury Assessment 1 (HIA1) protocol [4]. The HIA process continues with two post-match evaluations within 2 h (HIA2) and 36–48 h (HIA3) using the Sport Concussion Assessment Tool 6 (SCAT6) protocol [4]. Studies indicate that approximately 20% of concussions in elite men’s rugby union are not identified on-field, despite video evidence showing signs of concussion at the time [4].
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Head acceleration events (HAEs) occur in sport through direct or indirect head loading with more severe events associated with concussion risk [5]. However, it is still unclear what linear and/or rotational head kinematic measures constitute a more severe HAE, with peak kinematic values (e.g. peak linear acceleration [PLA], peak angular acceleration [PAA] and peak change in angular velocity [dPAV]) often used as a proxy [1].
Instrumented mouthguards (iMGs) have proven effective for measuring head kinematics and are superior to other wearable head sensors (e.g. skin patches) due to a more rigid coupling to the skull [6]. World Rugby has introduced iMGs at the elite level to aid current HIA detection procedures, particularly where players may lack visible signs [7]. PLA and PAA thresholds (75 g and 4.5 krad/s2 for men and 65 g and 4.5 krad/s2 for women) are utilised, though these are based on HAE match incidence rather than a direct link to suspected/confirmed concussions [7]. Field-based iMG studies in sport have historically been male focused and lack suspected/confirmed concussion cases [1]. A recent study found that PLA and dPAV were associated with male HIAs but that PAA was associated with female HIAs [7]. The inconsistency in peak head kinematic measures associated with men’s and women’s HIA events undermines their potential as an HAE severity measure. The omission of a clear iMG-based severity measure for HAE can lead to ineffectiveness in practice and confusion amongst practitioners/stakeholders, ultimately acting as a barrier to iMG adoption in sport [8]. The aim of this study was to identify an HAE severity measure associated with HIA1 removals in elite-level rugby union. This study has the potential to identify an HAE metric associated with suspected concussions in elite rugby and bridge the gap by identifying a consistent severity measure applicable across sexes.
2 Methods
2.1 Study Design
A retrospective analysis was conducted using data from previously published studies from elite-level Premiership (men), Premier 15s (women) and Farah Palmer Cup (women) competitions utilising the Prevent Biometrics (Edina, US) iMG system [9‐11]. The iMGs incorporate an accelerometer and gyroscope sampling at 3200 Hz, with measurement ranges of ± 200 g and ± 35 rad/s, respectively. An embedded infrared proximity sensor assesses the iMG’s coupling to the upper dentition during HAEs. Previous studies have validated the Prevent Biometrics iMG in both field and laboratory environments [12‐15]. The concordance correlation coefficient for PLA and PAA measurements ranged between 0.97 and 0.98 and 0.91 and 0.98, respectively, when compared to reference head form measurements [13, 14].
An HAE was identified when linear acceleration at the mouthguard exceeded 8 g on a single accelerometer axis [16]. HAE kinematics were recorded 10 ms pre-trigger and 40 ms post-trigger. For reporting, kinematic signals were transformed to the head’s centre of gravity (CG) following Society of Automotive Engineers (SAE) J211 standards [17]. A recording threshold of 400 rad/s2 and 5 g at the head CG were set and exhibited a positive predictive value of 0.99 (95% confidence interval [CI] 0.97–1.00) for identifying contact-related HAEs [9]. For each HAE utilised in the current study, three severity measures were calculated: the Head Acceleration Response Metric (HARM), maximum principal strain (MPS) and peak power.
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2.1.1 Head Acceleration Response Metric (HARM)
The HARM is currently used as a severity measure to assess American Football helmet performance for the National Football League (NFL) [18]. In brief, the HARM is a combination of the rotational-based Diffuse Axonal Multi-Axis General Evaluation (DAMAGE) and linear-based Head Injury Criterion (HIC) metrics; see Eq. 1 [19, 20]. The combination of a linear and rotational metric was shown to better distinguish between concussion and non-injurious events than HIC or DAMAGE separately [18].
where C1 = 0.0148 and C2 = 15.6, constants determined from fits to head kinematics measured in test dummy reconstructions.
2.1.2 Maximum Principal Strain (MPS)
Finite element (FE) brain models are computational tools that examine the mechanical response of the brain at a tissue level to head loading [21]. Previous FE brain model studies have shown that MPS is the key mechanical metric that predicts concussion and traumatic brain injury [22‐24]. An instantaneous brain strain model was utilised to calculate the 95th percentile MPS in the current study [25].
2.1.3 Peak Power
It has been postulated that injury is dependent on the rate at which energy is transferred to the body [26, 27] Accordingly, HAE severity may relate to the maximum value associated with the rate of change of kinetic energy that the head undergoes during an HAE (i.e. peak power); see Eq. 2.
where \({I}_{xx}\), \({I}_{yy}\) and \({I}_{zz}\) are the componential moments of inertia of the head (kg m2), \(m\) is the head mass (kg), \(\partial t\) is the infinitesimal change in time (s), \({\propto }_{x}\), \({\propto }_{y}\) and \({\propto }_{z}\) are the componential angular accelerations of the head (rad/s2) and \({a}_{x}\), \({a}_{y}\), \({a}_{z}\) are the componential linear accelerations of the head (m/s2). All head components are in the SAE J211 coordinate system. Since power must be calculated relative to the head reference frame, at time equal zero, the velocity associated with power must also equal zero [26, 27]. Peak power can be considered synonymous with the measure ‘head impact power’ [27]. For this study, head mass was approximated based on average male and female cadaveric data (4.1 kg and 3.2 kg, respectively) [28], and moments of inertia were based on Eqs. 3, 4 and 5 [28]. The MATLAB code for the calculation of peak power utilised in this study is openly available on GitHub [29].
$${I}_{xx}(\text{kg cm}^{2})=74.8m-125.5$$
(3)
$${I}_{yy}(\text{kg cm}^{2})=71.4m-90.2$$
(4)
$${I}_{zz}(\text{kg cm}^{2})=45.6m-26.5$$
(5)
2.2 Instrumented Mouthguards and Head Injury Assessment Event Identification
Removals from play for HIA1 assessments were obtained from the World Rugby Specialised Concussion Rugby Management (SCRM) database [7]. The SCRM app securely records all clinical assessments and HIA protocol data globally, incorporating in-built validation checks to enhance data accuracy. An independent researcher undertakes weekly quality control to ensure data accuracy for research purposes.
To identify the HAE event inciting an HIA1 removal, match footage and event data were sourced from StatsPerform (Chicago, Illinois, USA). The match data included details on player contact events (e.g. tackles, carries, rucks) and removal timings. For players removed for HIA1 assessments, the time of removal was used to synchronise iMG HAE timestamps with the contact events [7]. The contact events preceding the player’s removal were reviewed to identify the HAE responsible for the HIA1, similar to Allan et al. [7]. If the HAE was not clearly identifiable from the video footage, the HIA1 case was excluded from the analysis, and potential HAEs leading to the player’s removal were removed [7]. Over the included competitions, match HAEs were recorded from 215 individual men and 325 individual women. A total of 30 and 28 HIA1 removals from 27 and 27 individual players wearing an iMG were identified in the men’s and women’s cohorts, respectively.
2.3 Statistical Analysis
All statistical analyses were conducted using commercially available software (IBM® SPSS®v.29). Ten random non-case impacts (i.e. HAEs that did not lead to an HIA1 removal) were taken per unique player with ten or more impacts (2150 for men and 3250 for women) to limit oversampling of the non-case events in relation to the HIA1 events [7]. No non-case event was included more than once across the ten random impacts. Simple binary logistical regression and odd ratios (ORs) with 95% CIs were calculated to identify if peak power, MPS and/or the HARM were associated with HIA1 events compared to non-cases [7]. Allan et al. [7] previously conducted the same analysis for PLA, PAA and dPAV.
Receiver operator characteristic (ROC) curves were calculated for the independent variables (peak power, MPS, HARM, PLA, PAA and dPAV) for men and women separately, and optimal thresholds for HIA1 player removal were calculated [7]. ROC curves show the trade-off between a test’s sensitivity (true positive rate) and specificity (false positive rate) at various threshold levels [7]. Optimal threshold values were determined using the Youden Index, which maximises the independent variables’ sensitivity and specificity and is critical for on-field applications [7]. Area under the curve (AUC) measures the overall performance of a classifier, with higher values indicating better discrimination between classes and were compared using the paired-sample approach built into the statistical software. Significant differences were set at p < 0.05.
3 Results
Peak power, HARM and MPS were associated with HIA1 removals in both the men’s and women’s game (Tables 1, 2 and 3). Figure 1 shows the breakdown of the kinematic variables for the HIA1 and non-cases for both men and women. Peak power performed most consistent of the three severity measures for HIA1 removals based on paired-sample AUC comparisons from the ROC analysis in the men’s and women’s games (Table 4; Fig. 2). Power and HARM performed greater than dPAV in the men’s and women’s games based on AUC comparisons (Table 4). The HARM and MPS were found to perform lower than PLA in the women’s game, with MPS also performing lower than PAA (Table 4).
Table 1
Logistic regression coefficients, area under the curve (AUC) and p values for the three severity measures in the men’s and women’s game
Coefficients (95% CI)
Wald
P value
AUC (95% CI)
Sensitivity (%)
Specificity y (%)
Men
Power
1.001 (1.001–1.001)
99.7
< 0.001
0.961 (0.924–0.998)
90.00
91.30
MPS
3.03e16 (1.61e13–5.72e19)
97.2
< 0.001
0.948 (0.906–0.990)
86.70
94.50
HARM
4.206 (3.191–5.543)
104.0
< 0.001
0.954 (0.914–0.994)
86.70
95.00
Women
Power
1.001 (1.001–1.001)
88.1
< 0.001
0.923 (0.862–0.983)
82.10
93.70
MPS
1.47e10 (5.24e7–4.11e12)
66.3
< 0.001
0.849 (0.774–0.924)
82.10
76.20
HARM
3.138 (2.488–3.959)
93.1
< 0.001
0.883 (0.808–0.958)
71.40
94.30
HARM Head Acceleration Response Metric, MPS maximum principal strain
Table 2
Median and quartile (Q) values for the three severity and kinematic measures with area under the curve (AUC) and cut-off value for sensitivity and specificity in the men’s game
Median
Q1–Q3
AUC (95% CI)
Cut-off
Sensitivity (%)
Specificity (%)
Power (W)
Non-case
427.43
(230.92–769.67)
0.961 (0.923–0.998)
1508.25
90.00
91.30
HIA1
6002.07
(3709.22–8478.88)
MPS
Non-case
0.09
(0.08–0.12)
0.948 (0.906–0.991)
0.17
86.70
94.50
HIA1
0.23
(0.20–0.27)
HARM
Non-case
1.23
(0.88–1.68)
0.954 (0.914–0.995)
2.87
86.70
95.00
HIA1
5.41
(3.85–6.33)
PAA (krad/s2)
Non-case
0.91
(0.66–1.35)
0.937 (0.886–0.987)
1.96
86.70
89.20
HIA1
4.07
(2.60–6.22)
PLA (g)
Non-case
11.42
(8.37–17.13)
0.947 (0.906–0.989)
30.64
86.70
93.90
HIA1
56.47
(34.48–70.59)
dPAV (rad/s)
Non-case
7.99
(5.53–11.37)
0.927 (0.875–0.980)
14.75
86.70
88.60
HIA1
23.09
(18.43–32.26)
dPAV peak change in angular velocity, HARM Head Acceleration Response Metric, HIA1 Head Injury Assessment 1, MPS maximum principal strain, PAA peak angular acceleration, PLA peak linear acceleration
Table 3
Median and quartile (Q) values for the three severity and kinematic measures with area under the curve (AUC) and cut-off value for sensitivity and specificity in the women’s game
Median
Q1–Q3
AUC (95% CI)
Cut-off
Sensitivity (%)
Specificity (%)
Power (W)
Non-case
335.21
(190.12–583.52)
0.923 (0.861–0.984)
1193.78
82.10
93.70
HIA1
2184.62
(1397.23–4668.55)
MPS
Non-case
0.09
(0.08–0.12)
0.849 (0.773–0.926)
0.12
82.10
76.70
HIA1
0.15
(0.12–0.22)
HARM
Non-case
1.22
(0.88–1.69)
0.883 (0.807–0.959)
2.67
71.40
94.30
HIA1
2.91
(1.90–4.96)
PAA (krad/s2)
Non-case
0.90
(0.65–1.33)
0.917 (0.844–0.990)
1.68
92.90
86.50
HIA1
3.17
(2.07–4.95)
PLA (g)
Non-case
10.91
(8.13–15.51)
0.947 (0.911–0.983)
25.05
85.70
92.80
HIA1
43.13
(27.62–60.49)
dPAV (rad/s)
Non-case
8.14
(5.61–11.68)
0.821 (0.738–0.903)
11.16
82.10
72.50
HIA1
16.92
(11.42–20.79)
dPAV peak change in angular velocity, HARM Head Acceleration Response Metric, HIA1 Head Injury Assessment 1, MPS maximum principal strain, PAA peak angular acceleration, PLA peak linear acceleration
Fig. 1
Breakdown of the three severity (a–c) and kinematic measures (d–f) in the men’s and women’s game, illustrating median (box centre line), interquartile range (IQR) (box), outliers greater than 1.5 × IQR (crosses) and nonoutlier maximum/minimum (whiskers). dPAV peak change in angular velocity, HARM Head Acceleration Response Metric, HIA1 Head Injury Assessment 1, MPS maximum principal strain, PAA peak angular acceleration, PLA peak linear acceleration
Significant paired-sample area under the curve (AUC) comparisons based on the receiver operating characteristic analysis in the men’s and women’s games
Test pairs
AUC difference
95% CI
Lower bound
95% CI
Upper bound
P value
Men
Power—dPAV
0.034
0.006
0.061
0.016
MPS—dPAV
0.021
0.007
0.035
0.003
HARM—dPAV
0.027
0.013
0.041
0.001
Women
Power—dPAV
0.102
0.038
0.165
0.002
MPS—PAA
− 0.068
− 0.108
− 0.028
0.001
MPS—PLA
− 0.098
− 0.154
− 0.041
0.001
HARM—PLA
− 0.064
− 0.110
− 0.018
0.006
HARM—dPAV
0.062
0.026
0.098
0.001
The full comparative analysis is available in Supplementary Material 1 (see the electronic supplementary material)
CI confidence interval, dPAV peak change in angular velocity, HARM Head Acceleration Response Metric, MPS maximum principal strain, PAA peak angular acceleration, PLA peak linear acceleration
Fig. 2
Receiver operating characteristic analysis of HIA1 and non-cases for the men’s (a) and women’s game (b). Precision-recall curves are available in Supplementary Material 2 (see the electronic supplementary material). dPAV peak change in angular velocity, HARM Head Acceleration Response Metric, HIA1 Head Injury Assessment 1, MPS maximum principal strain, PAA peak angular acceleration, PLA peak linear acceleration
Of the three severity measures examined within this study, peak power appears to be the most consistent severity measure associated with HIA1 removals during match play in men’s and women’s professional rugby union. Peak power has the potential to be utilised as a severity measure for research focused on HAE incidence and mechanisms, mitigation strategies and suspected concussion detection tools. The peak power equation is based on fundamental mechanics rather than empirical evidence and includes six degree-of-freedom head acceleration and velocity measures (the latter are represented by the integral terms in Eq. 2). Peak power is a common metric already used in sports performance (e.g. strength and conditioning testing) [30] and, therefore, may be easier to adopt as a severity measure by players, coaches and other stakeholders rather than multiple peak kinematic values, which have previously led to confusion.
Peak power, with a six degree-of-freedom head acceleration and velocity measure, performing best in the current study may shed light on conflicting research in the literature that has found different peak kinematic values associated with concussion/suspected concussion. Data from helmet sensor field-based studies have illustrated that linear or rotational acceleration, or both, may be associated with concussion [31]. The purpose of the statistical analysis in the current study is not to derive any form of diagnostic tests, nor to propose HIA1 removal thresholds. Instead, these findings provide a step forward towards understanding HAE severity and what measures may be associated with HIA1 removal. iMGs are not currently a replacement for the HIA process in rugby union but an additional tool to aid clinical decision making for HIA removals. Removals based on peak power threshold values should be assessed formally to ensure high performance in terms of sensitivity, specificity and other accuracy measures. For example, a high rate of false-positive cases could overwhelm medical support staff and disrupt matches to an extent that iMG use is rejected by coaches and players [7]. In the women’s game, the HARM and MPS underperformed relative to certain peak head kinematics, potentially highlighting the need for HAE severity measures to be sex specific/adaptable [1].
Previous research noted significant variability in the relationship between head impact power and MPS across different head impact types [32]. The discrepancy may arise from differences in methodologies and datasets. Zhan et al. [32] utilised a combination of Hybrid III laboratory reconstructions, numerical simulations and a limited dataset from the Stanford iMG system. Each of these approaches, while valuable, has its own inherent limitations, including the use of surrogate models and reconstructed impacts that may not fully capture on-field HAE. Additionally, their analyses focused on correlating various brain injury criteria (e.g. head impact power) to MPS metrics derived from FE brain models, rather than directly linking these criteria to suspected concussions. In contrast, the current study may have benefited from the use of on-field HAE data from professional rugby players wearing validated iMGs. This direct, real-world dataset enables HIA1 event to non-case comparisons.
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4.2 Limitations
High severity measures were identified in non-clinical cases (Fig. 1), although no real-time observations of clinical signs, symptoms or behavioural changes were made. These signs may have been absent or the player may have continued to play without disclosing or displaying any effects of the HAE [4]. It remains unclear whether these HAEs resulted in the clinical presentation of signs and symptoms post-match. Analysis of these cases should be a focus of future work.
The current study may not comprehensively capture the range of playing styles and conditions across all levels of rugby globally. HAE severity measures could vary in different sports and cohorts, especially in youth, as well as amateur-level games.
Kinematic signal processing was performed using the Prevent Biometrics system, similar to other commercially available iMG systems [13]. The kinematic signal processing used in this study has been included in validation studies for the Prevent Biometrics iMG system [13], and is currently utilised in professional rugby [7]. However, a standardised and openly available signal-processing method for iMG systems, such as the HEADSport filter, may be necessary [33]. A consensus-agreed and consistent signal-processing approach is crucial for enabling inter-study comparisons within and between different sports, particularly when multiple iMG systems are utilised [17].
The MPS measures in the current study were based on a validated instantaneous brain strain estimation model trained on a large number of FE brain model predictions [25]. The rationale for the selection was that an instantaneous brain strain measure would be practically required pitch-side for HIA detection. FE, multibody and other biomechanical modelling can complement iMG data in uncovering injury mechanisms [1, 34]. The head mass and, thus, moment of inertia were approximated for the peak power calculation. However, a more subject-specific approach could be beneficial by measuring head circumference (C) and utilising Eq. 6 [28]. Differences in head mass and neck strength may explain the variation in metrics between men and women [1]. Further studies should explore sex-specific calibration of severity measures.
In future research, the incorporation of clinical outcomes from the entire HIA process will allow for an evaluation of the diagnostic accuracy of iMGs in concussion detection. However, the current mandate by World Rugby is to use iMGs as part of the criteria for identifying players who require the HIA1 screen, rather than for direct concussion diagnosis. This approach facilitates a larger sample size for evaluation, and in the future, a combined approach could investigate the associations between HAE severity, HIA1 indicators and concussion outcomes.
5 Conclusion
Peak power, a measure based on fundamental mechanics, may be a suitable HAE severity measure in sport. Peak power was most consistently associated with HIA1 removals during match play in men’s and women’s professional rugby union. All three severity measures were associated with HIA1 removals in both the men’s and women’s game. However, peak power performed greatest for HIA1 removals in men’s and women’s professional rugby union, based on overall AUC, and sensitivity values. Peak power and the HARM performed greater than dPAV in the men’s and women’s game based on AUC comparisons. The HARM and MPS were found to perform lower than PLA in the women’s game, based on AUC comparisons, with MPS also performing lower than PAA. The findings progress our understanding of HAE severity and measures associated with HIA1 removals. Peak power may be easier to adopt as a severity measure by players, coaches and other stakeholders owing to its common use in sports performance.
6 Policy Implications
Peak power has the potential to be utilised as a severity measure for HAE mitigation strategies and suspected concussion detection tools in sport.
Acknowledgements
The authors would like to thank all staff and players at the participating clubs for their time and involvement in this study. The authors would also like to thank StatsPerform for providing the authors access to their platform. The Rugby Players Association were supportive and endorsed and helped promote the study.
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Declarations
Competing Interests
GT and BJ have received research funding from Prevent Biometrics and World Rugby. KS and MB have received research funding from World Rugby. LS, RT, EF, DS and JB are employed by or contracted as consultants to World Rugby. GT previously conducted consultancy work for World Rugby. KS and SK are employed by the Rugby Football Union. SH receives funding for his PhD studies from the Rugby Football Union and Premiership Rugby. BJ is a consultant with Premiership Rugby and the Rugby Football League. MC is employed by Premiership Rugby and was previously employed by the Rugby Football Union. POH has previously been contracted by the Rugby Football Union and is employed by Marker Diagnostics UK Ltd, a company developing salivary biomarker testing for sport related concussion. DA and JT declare they have no conflicts of interest.
Availability of Data and Material
Anonymised data are available upon reasonable request by contacting Lindsay Starling (lindsay.starling@worldrugby.org).
Ethical Approval
This project was approved by the University’s Research Ethics Committee, University of Ulster (#REC-21–0061) and University of Otago Human Ethics Committee (#H21-056). The study was performed in accordance with the standards of ethics outlined in the Declaration of Helsinki.
Consent to Participate
All participants provided written consent.
Consent for Publication
Not applicable.
Authors’ Contributions
GT conceptualised the research project. All authors were involved in the design and data collection for the study. GT and DA were responsible for the analysis and interpretation of the results. GT and DA drafted the manuscript. All authors critically reviewed and edited the manuscript prior to submission. All authors have read and approved the final version of the paper and agree to be accountable for the work.
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
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Peak Power: A Severity Measure for Head Acceleration Events Associated with Suspected Concussions
Verfasst von
Gregory Tierney
Ross Tucker
James Tooby
Lindsay Starling
Éanna Falvey
Danielle Salmon
James Brown
Sam Hudson
Keith Stokes
Ben Jones
Simon Kemp
Patrick O’Halloran
Matt Cross
Melanie Bussey
David Allan
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Grundlagenwissen der Arthroskopie und Gelenkchirurgie erweitert durch Fallbeispiele, Videos und Abbildungen. Zur Fortbildung und Wissenserweiterung, verfasst und geprüft von Expertinnen und Experten der Gesellschaft für Arthroskopie und Gelenkchirurgie (AGA).
Mit dem STAR-Approach, einem modifizierten posterioren Zugang zum Hüftgelenk, erreicht man nicht nur optimalen Überblick, sondern auch die vollständige Schonung des M. piriformis und wichtiger Nerven.
Ob bei Sprunggelenksfrakturen operiert wird, hängt meist von der Stabilität ab. Entscheidend ist die präzise Messung des medialen Gelenkspalts im Belastungsröntgen. Warum die Fünf-Millimeter-Regel hilft, unnötige Operationen zu vermeiden, stellte die Orthopädin Dr. Helen Anwander auf dem diesjährigen Orthopädie und Unfallchirurgie Kongress vor.
Eine periprothetische Gelenkinfektion stellt ein erhebliches Mortalitätsrisiko in der Endoprothetik dar. Der Prothesenwechsel kann in einem einzeitigen oder zweizeitigen Verfahren erfolgen. Die Wahl des Verfahrens beeinflusst die Prognose maßgeblich, weshalb der Trend klar in eine Richtung geht.
Die Tragweite von Muskelverletzungen im Sport wird oftmals verkannt. Sie sind eine wesentliche Ursache für Ausfälle, nicht selten sogar für das Ende der Karriere. Wie sieht die optimale Versorgung aus?
