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Has the athlete trained enough to return to play safely? The acute:chronic workload ratio permits clinicians to quantify a player's risk of subsequent injury

Authors:
  • Gabbett Performance Solutions

Abstract

The return to sport from injury is a difficult multifactorial decision, and risk of reinjury is an important component. Most protocols for ascertaining the return to play status involve assessment of the healing status of the original injury and functional tests which have little proven predictive ability. Little attention has been paid to ascertaining whether an athlete has completed sufficient training to be prepared for competition. Recently, we have completed a series of studies in cricket, rugby league and Australian rules football that have shown that when an athlete's training and playing load for a given week (acute load) spikes above what they have been doing on average over the past 4 weeks (chronic load), they are more likely to be injured. This spike in the acute:chronic workload ratio may be from an unusual week or an ebbing of the athlete's training load over a period of time as in recuperation from injury. Our findings demonstrate a strong predictive (R(2)=0.53) polynomial relationship between acute:chronic workload ratio and injury likelihood. In the elite team setting, it is possible to quantify the loads we are expecting athletes to endure when returning to sport, so assessment of the acute:chronic workload ratio should be included in the return to play decision-making process.
Has the athlete trained enough to return to play
safely? The acute:chronic workload ratio permits
clinicians to quantify a players risk of subsequent
injury
Peter Blanch,
1,2
Tim J Gabbett
3,4
1
Essendon Football Club,
Melbourne, Australia
2
School of Allied Health
Sciences, Grifth University,
Gold Coast, Australia
3
School of Exercise Science,
Australian Catholic University,
Brisbane, Australia
4
School of Human Movement
Studies, University of
Queensland, Brisbane,
Australia
Correspondence to
Peter Blanch, Essendon
Football Club, 275 Melrose Dr,
Melbourne Airport, Vic, 3045;
peterblanch@gmail.com
Accepted 14 November 2015
Published Online First
23 December 2015
To cite: Blanch P,
Gabbett TJ. Br J Sports Med
2016;50:471475.
ABSTRACT
The return to sport from injury is a difcult multifactorial
decision, and risk of reinjury is an important component.
Most protocols for ascertaining the return to play status
involve assessment of the healing status of the original
injury and functional tests which have little proven
predictive ability. Little attention has been paid to
ascertaining whether an athlete has completed sufcient
training to be prepared for competition. Recently, we
have completed a series of studies in cricket, rugby
league and Australian rules football that have shown
that when an athletes training and playing load for a
given week (acute load) spikes above what they have
been doing on average over the past 4 weeks (chronic
load), they are more likely to be injured. This spike in the
acute:chronic workload ratio may be from an unusual
week or an ebbing of the athletes training load over a
period of time as in recuperation from injury. Our
ndings demonstrate a strong predictive (R
2
=0.53)
polynomial relationship between acute:chronic workload
ratio and injury likelihood. In the elite team setting, it is
possible to quantify the loads we are expecting athletes
to endure when returning to sport, so assessment of the
acute:chronic workload ratio should be included in the
return to play decision-making process.
HAS THE ATHLETE TRAINED ENOUGH? A
MISSINGPARTINTHERETURNTOPLAY
DECISION
Current state of play
Since history of past injury is a predictor of subse-
quent injury, the decisions around when a player
should return to play are difcult.
13
It is difcult
for a clinician to nd the right balance between
returning a player too early and the player suffering
a recurrence, or delaying return to play so the team
has few available players.
Much has been written on the politics of who
should make the decision
4
and within those argu-
ments, a comprehensive checklist of considerations
has been developed.
56
In their review of 148
papers on the subject of return to play, Matheson
et al
7
developed a three-tiered decision-making
process which has been recently claried in the
Strategic Assessment of Risk and Risk Tolerance
(StARRT) framework
8
(see table 1). The rst step
outlines the medical factors associated with the
injury to ascertain the level of injury risk with
returning to play. Step 2 predominantly focuses on
the player or sport factors that may mitigate or
augment the risk of reinjury (eg, an American
Football quarterback may be at greater risk of
exacerbating a shoulder injury than a place kicker).
The third step focuses on the factors associated
with whether the nal ascertained risk is worth
taking within the connes of the needs of the
coach, team, athlete and medical service provider.
While steps 2 and 3 are extremely important in the
nal decision, we conne our discussion to step 1
in the initial evaluation of the risk of reinjury.
Several well-credentialed sports medicine govern-
ing bodies have developed a consensus statement
that clearly discusses the political and medicolegal
aspects of return to play.
6
The decision-making
process around the evaluation of the risk of reinjury
within that document appears to be based on the
decision trees described by previous authors.
457
Their nal checklist before return to sport is:
Restoration of sports-specic function;
Restoration of musculoskeletal, cardiopulmon-
ary and psychological functions as well as
overall health of the injured or ill athlete;
Restoration of sport-specic skills;
Ability to perform safely with equipment modi-
cation, bracing and orthoses;
The status of recovery from acute or chronic
illness and associated sequelae;
Psychosocial readiness;
The athlete poses no undue risk to themselves
or the safety of other participants;
Compliance with federal, state, local and gov-
erning body regulations and legislations.
These points are assessed through:
A condition-specic medical history;
A condition-specic physical examination and
functional testing;
Medical and radiological tests and consultations
as indicated;
Psychosocial assessment;
Documentation;
Communication with family, trainers, coaches,
etc.
We conne our discussion to the rst three
points of the nal checklist: the restoration of
sports-specic skills and function and the restor-
ation of the musculoskeletal, cardiopulmonary and
psychological systems of the athlete and, in particu-
lar, how they are assessed.
We believe a critical aspect that has been
excluded from the return to play decision relates to
the amount of training the athlete has completed
over the time of the recuperation in order to be
adequately prepared for the demands of the game.
Blanch P, Gabbett TJ. Br J Sports Med 2016;50:471475. doi:10.1136/bjsports-2015-095445 1of5
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Both of the previously mentioned protocols (the three-step deci-
sion model and the return to sport checklist)
67
refer to medical
history and functional tests but do not specify the training
history compared with the demands of full training and
competition.
EXAMPLES OF THE MYRIAD OF FUNCTIONAL TESTS THAT
CONFRONT THE CLINICIAN MAKING THE RETURN TO PLAY
DECISION
Functional tests come in a myriad of forms. If we specically
examine tests for lower limb injuries, they could include timed
runs, vertical jumps, hop tests and the star excursion balance
test (to name a few). This form of testing may provide an indi-
cation of the athletes ability to perform a single task (eg, run
40 m in a given time). Although the functional test has some
clinical utility in evaluating the rehabilitation progress of an
athlete, these tests do not predict injury.
910
Among 23 physical
performance measures, only the star excursion balance test had
any injury predictive ability.
910
These tests can rule a player out
of competition (ie, if the athlete cannot hop, they probably
cannot play basketball), but they are only a milestone on the
return to play path (ie, athlete can hop, but it is still unclear
whether they are prepared for full training and competition).
Functional tests provide little insight as to how the athlete will
withstand the rigours of full training and competition.
A KEY PIECE OF INFORMATION THAT SHOU LD NOT BE
HIDDEN FROM CLIN ICIANS AND PLAYERS
Recently, we have quantied cricket fast bowlers workload using
both external load (ie, balls bowled) and internal load (time
(mins) X rating of perceived exertion, RPE). We also quantied
external load (ie, distance run) in rugby league and Australian
football players. These data were then modelled comparing the
acute load (ie, the training that had been performed in the
current week) with the chronic load (ie, the training that had
been performed as a rolling average over the previous 4 weeks).
This model, initially proposed by Banister and colleagues
11 12
and more often using the terminology of fatigue (acute load)
and tness (chronic load) has been used previously in perform-
ance studies
13
but not in studies of the relationship between
workloads and injury. The size of the acute load in relation to the
chronic load provides a ratio score referred to as the acute-
chronic workload ratio (also commonly referred to as the
training-stress balance).
An acute:chronic workload ratio of 0.5 would suggest that an
athlete trained or completed only half as much of the workload
in the most recent week as what he/she had prepared for over
the past 4 weeks. An acute:chronic workload ratio of 2.0 sug-
gests that the athlete performed twice as much of the workload
in the current week as what he/she had prepared for over the
previous 4 weeks. We dene spikes in training and playing load
as periods where a player has an acute:chronic workload ratio
of >1.5. While this appears to be the point at which injury risk
starts to rise, the balance between performance enhancement
and injury risk must also be considered. Spikes predict subse-
quent injury in cricket fast bowlers,
14
professional rugby league
players
15
and professional Australian Football players.
COMBINING CLINICAL AND PERFORMANCE PERSPECTIVES
EXPERIENCE FROM ELITE SPORT
When considering the acute:chronic workload ratio, clinicians
should realise that normal training should include ratios above
1.0 when the athlete is increasing his/her training load; how far
above 1.0 and for how long will inuence injury risk.
As with any ratio, a large number can be driven by a large
numerator or a small denominator. In this case, that would
reect a (relatively) large acute workload or a (relatively) small
chronic workload. We have seen injury follow scenarios where
an athlete has undergone signicant loading in a single week
(large numerator). We have also noted circumstance where the
training load has decreased over the past 4 weeks (small denom-
inator) and a player has suffered injury with what seemed like a
normal acute workload. Causes of lower chronic workload can
include injury or illness, signicant sponsor commitments or
suspension from playing with inadequate make up workload.
Table 1 The three-step decision-based model for return to play
presented by Matheson et al
7
1. Evaluation of health
status
2. Evaluation of
participation risk
3. Decision
modification
Patient demographics Type of sport (ie, collision) Timing and season
Symptoms Position played Pressure from athlete
Personal medical history Limb dominance External pressure
(coach, etc)
Physical examination Competitive level Masking the injury
Laboratory tests Ability to protect Conflict of interest
Functional tests Fear of litigation
Psychological state
Potential seriousness
Figure 1 A graphical representation
of the high-speed running loads of a
rugby league player who after a week
of acute:chronic workload ratio of 1.6
suffered a hamstring injury and then
subsequently in the rehabilitation
phase experienced an acute:chronic
workload ratio of 1.9 which led to
reinjury.
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The example of balls bowled in cricket fast bowlers is perhaps
the most easily understood, particularly given that when playing
long form cricket, a large component of a players load occurs
during match play.
16
We can assume that if a fast bowler enters
a long form (45 day) cricket match, they will (on average) be
required to bowl approximately 240 balls during the match.
17
On the basis of these requirements and using data we have pre-
sented previously,
13
if a bowler returning from injury has a
chronic bowling load of 120 balls per week, they will incur an
acute:chronic workload ratio of 2.0 with their likelihood of
injury in the following week at 12%. When considering that
the baseline injury likelihood is approximately 4%, this constitu-
tes a relative risk that represents a 3.0 times greater prospect of
injury. However, if their chronic load was 180 balls per week,
their likelihood of injury is reduced to approximately 5% (a
relative risk of 1.25).
A further real-world example is provided from the training
load history of an elite rugby league player who had sustained a
recurrence/exacerbation of a grade 2 hamstring strain. During
early stage rehabilitation (2 weeks), the intensity of high-speed
running performed was <1.0 m/min (ie, 30 m of high-speed
running in a 30 min session). From the second to third week of
rehabilitation, the players high-speed running load was
increased to 25.0 m/min (ie, 750 m in a 30 min session).
Subsequently, the player suffered a recurrence of the hamstring
strain (a graphical representation can be seen in gure 1). In this
example, several training load factors most likely contributed to
the injury recurrence. First, it was highly likely that the spike
in training loads from week to week considerably increased the
risk of injury. Second, although the applied training load
was specic to the most extreme demands of competition (see
table 2), they also grossly exceeded the load for which the
player was prepared.
We appreciate that the acute:chronic workload ratio can be
applied to a wide range of training variables (eg, total distance,
collisions, accelerations and decelerations, etc). However, this
does not mean that the multitude of increasingly sophisticated
variables should be modelled in this fashion but rather variables
that are specic to the athlete, sport and injury mechanism (ie,
balls bowled by a fast bowler, high-speed running distance
experienced by a footballer). We believe that simple and valid
metrics should be examined before complicating the analysis.
18
UNDERSTANDING RELATIVE WORKLOADS CAN PROVIDE
CLINICIANS AND COACHES WITH AN ABSOLUTE INJURY
RISK AND IT CHANGES WEEK TO WEEK
To further illustrate the value of modelling acute and chronic
loads in the return to play process, we would like to present a
collapsed version of our research in this area. This representa-
tion is illustrative only, and should only be considered a guide to
how the acute and chronic loads of athletes can be manipulated
to minimise the risk of injury.
Figure 2 depicts training load data from studies of three dif-
ferent sports (cricket, rugby league and Australian football). In
the original papers, the acute:chronic workload ratio was pre-
sented as a range and the likelihood of injury as an absolute
gure. For our purposes, we have taken either: (1) The mid-
point of the acute:chronic workload ratio range (ie, 0.5 1.0
becomes 0.75, as our acute:chronic workload ratio score). Or
(2) In the case of the end-point ranges, that is, 0.0 0.5 or
>2.0, the acute:chronic workload ratio has been entered as 0.5
or 2.0. We have included the internal (balls bowled) and external
(session RPE=minutes×self-reported exertion) load measures
from the cricket paper,
14
the total running load data from the
rugby league paper
15
(but have excluded the data taken on very
high training loads as an athlete who has been injured is unlikely
to have a high training load) and the total running load and high-
speed running load from the Australian football paper.
Table 2 High-speed running demands of early stage
rehabilitation, skills training, matches, along with the most extreme
demands of competition for an elite rugby league player with a
grade 2 hamstring strain
Physical
demands
Early stage
rehabilitation
Return
to train
Return to
play
Return to peak
performance
Basic running
drills
Skills
training
Average
match
demands
Peak 5 min
period
Total distance
(m/min)
70 87 95 122
High-speed
running (m/min)
0.6 4.5 6.7 22.7
Collisions
(number/min)
0.4 1.0 3.8
Figure 2 The acute:chronic workload
ratio and subsequent injury likelihood
from studies of three different sports.
The tted polynomial line (±95% CIs)
has an R
2
=0.53 and the equation:
likelihood of subsequent injury=9.98
acute:chronic workload ratio
2
18.42
acute:chronic workload ratio+11.73.
This equation can allow us to
approximate the injury likelihood for
any given acute:chronic workload ratio.
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A second-order polynomial curve was t to the data. This
regression equation demonstrates that 53% of the variance in
the likelihood of injury in the following week can be explained
by the acute:chronic workload ratio (a linear model only
explains 34%). If we then apply the equation for the line to a
number of different combinations of acute and chronic loads,
we can estimate the risk of injury on return to sport associated
with a given acute:chronic workload ratio (see table 3).
We present a range of chronic workloads to represent longer
times of inactivity or rehabilitation. The range of acute work-
loads is provided to demonstrate a range of scenarios (eg, an
athlete on restricted training and only playing as a substitute in
the return to play match (60%) through to the most demanding
match (120%)). Below is an example of a football player who
suffered a grade 2 hamstring injury and missed three matches
(see gure 3).
If the decision to return to play is made during week 8, with
possible variations in the training and play that week (90120%
of a normal week), the player will return with a risk of injury
of between 11% and 15% (which may be entirely acceptable).
However, if left another week with an estimated training load
of 80% in week 8 and return to play in week 9 (with 90120%
load of a normal week), the injury risk decreases to 58%.
DISCUSSION
There are a number of points of debate within this discussion.
As previously mentioned, the collapse of our load and injury
risk data is for illustrative purposes, and each type of loading
for different sports will most likely require its own specic
model. However, this modelling clearly demonstrates that if ath-
letes perform greater workloads than they are prepared for, they
are more likely to sustain an injury. Also, our studies
1415
cap-
tured all injuries and do not specify risk of particular injuries,
that is, bone, soft tissue. In cricket fast bowlers, different acute
and chronic loading histories have either protective or causal
relationships with different types of injuries.
16
Studies with
larger sample sizes and specic injury types will further our
understanding.
What is the better measure of workload? In our fast bowling
study,
14
the internal load (session minutes×self-reported RPE)
data were more sensitive to subsequent injury than the external
load (balls bowled). However, at no stage would we recommend
that fast bowlers should measure their workload exclusively
using internal load measures. While 120 min of elding training
at an RPE of 6 (120×6=720 exertional minutes) is the same
internal load as 90 min of bowling training at an RPE of 8
(90×8=720), the bowling training better prepares the player
for bowling than does the elding training. We believe that the
increased sensitivity of the internal load data came partly from
having a more complete picture of the total training load, and
also the added value of how the athlete is responding to the
load.
Next, let us consider running load data. Hamstring injuries
are associated with high-speed running.
18
If, in the return to
play phase, only total running volume is monitored, the player
could return to 100% of total running volume but have 0% of
required high-speed running volume. We suggest that the
Table 3 The injury likelihood using the equation derived from
studies on three different sports (figure 2) comparing different
scenarios of acute and chronic workload
Chronic workload
(% of normal
average)
110 4.7 4.1 3.6 3.4 3.2 3.3 3.5
100 4.3 3.7 3.4 3.3 3.3 3.6 4.0
90 3.9 3.5 3.3 3.3 3.6 4.2 4.9
80 3.5 3.3 3.3 3.7 4.3 5.3 6.6
70 3.3 3.3 3.7 4.6 5.8 7.5 9.5
60 3.3 3.8 4.9 6.6 8.8 11.6 14.9
50 4.0 5.5 7.9 11.0 14.9 19.6 25.1
40 6.6 10.1 14.9 20.9 28.2 36.7 46.5
30 14.9 23.2 33.7 46.5 61.4 78.6 98.0
60 70 80 90 100 110 120
Acute workload (% of normal average)
For example, if an athlete returned to sport and had a normal 100% loading week
(acute workload) but if over the past 4 weeks due to the rehabilitation of their injury
had only averaged 40% of their normal load (chronic workload), we could expect the
likelihood of suffering an injury in the following week to be 28%.
Figure 3 A representation of an
injured players return to play with
possible injury likelihoods given the
different scenarios of the demands on
return. It shows that as the athlete
progresses through their rehabilitation
phase (weeks 47), their chronic load
starts to ebb away to be around 57%
of a normal week by the end of week
7. Once the decision of return to play
is made at this time with the
possibility of 90120% of average load
in week 8, the acute:chronic workload
ratio will be between 1.7 and 2.0 with
injury likelihoods of 1115%.
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volume of high-speed running plus total running load expected
in a normal week should be the major measures of the workload
in this example. However, as previously noted, the acute:
chronic workload ratio can be calculated for any variable
deemed relevant to the practitioner (eg, collisions, accelerations,
decelerations) as it is the comparison of what is done with what
is prepared for that is critical.
We acknowledge the strong probability that other factors such
as age, training history and injury history will shift the relation-
ship between the acute:chronic workload ratio and injury risk
curve up or down.
16
As with any modelling, the model will
become more accurate with more data over time and may be
specic to the players who provided the data. This will beneta
team that retains a core of players and tness coaches over a
number of years (as many successful teams do) as they should
have a rather precise estimate of risk relative to training loads
While this model may be rened in future studies, the founda-
tion of the modelthat athletes need to be prepared for what
they are asked to dois very solid.
CONCLUSION
In conclusion, we are under no illusions that the return to play
decision is simple. Any athlete competing is at a risk of injury
and that risk is multifactorial. We believe that trying to quantify
that risk will allow for more informed decisions and lower rein-
jury rates. In previous literature, the measurement of the train-
ing load of an athlete relative to the demands of competition
has not been clearly articulated as a consideration in the return
to play decision. The acute:chronic workload ratio should be
included in the return to play decision-making process.
Correction notice This paper has been amended since it was published Online
First. In the gure 2 legend there was an error. The number 9.78 has been
corrected to 9.98.
Competing interests PB used to be employed by Cricket Australia and is now
currently employed by Essendon Football Club.
Provenance and peer review Not commissioned; externally peer reviewed.
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Blanch P, Gabbett TJ. Br J Sports Med 2016;50:471475. doi:10.1136/bjsports-2015-095445 5 of 5
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of subsequent injury
permits clinicians to quantify a player's risk
ratioplay safely? The acute:chronic workload
Has the athlete trained enough to return to
Peter Blanch and Tim J Gabbett
doi: 10.1136/bjsports-2015-095445
23, 2015
2016 50: 471-475 originally published online DecemberBr J Sports Med
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... 'Where is the load?' Revisiting the Strategic Assessment of Risk and Risk Tolerance (StARRT) framework for return to sport by including an athlete's sport-specific training capacity? Matt Taberner ,1,2 Daniel Dylan Cohen , 3,4 Anthony Carter, 5,6 Johann Windt 7,8 ...
... It is perhaps the most ecologically important consideration since it encapsulates the 'actual' demands and requirements of the athlete's sport and their level of participation. [3][4][5] While the importance of monitoring training load in rehabilitation has been established, 6 7 we emphasise that sufficient consideration has not been given to the role of the athlete's sports-specific training capacity in decision-making throughout the RTS continuum. 5 8 ...
... Workload in sport can influence performance and injury risk in individual athletes (Colby et al., 2014). Workload is defined as the ratio between an athlete's short-term training load and the mean of their long-term training load (Blanch & Gabbett, 2016). The workload ratio has been previously quantified using various internal and external workload variables (Hulin et al., 2016). ...
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In recent years, the use of advanced wearable technologies in tennis has improved the ability to monitor workload and performance indicators. Using the device Armbeep Tennis, attached to the wrist of an entry level female tennis player, we recorded 97% of the tennis training and all official matches over two annual competitive seasons. The aim of the study was to determine the variation of different workload indicators during the preparation and competition phases in one annual season and to compare the workload indicators between the two seasons. We found no significant differences in the results of the training, tournament, and performance indicators between the two seasons. Our tennis player trained more on average in the second year (Y1 = 90.9 min, Y2 = 97.5 min) and the percentage of active time was also higher (Y1 = 30.6%, Y2 = 32.4%). A higher number of shots per week (Y1 = 3109.1, Y2 = 2869.4) was observed in the first year, while the number of shots per hour was higher in the second year (Y1 =420.6, Y2 = 430.1). The pace of the rally was higher in the first year (Y1 = 24.6, Y2 = 23.4). The differences between the other workload indicators were not significant in the two years. This single case study provides good insight into the overall progression of training and competition over two annual seasons and can serve as a basis for determining workload indicators for novice tennis players or those just embarking on this path. IZVLEČEK V zadnjih letih napredna tehnološka oprema omogoča spremljanje obremenitve in uspešnost igranja v tenisu. Z uporabo Armbeep Tennis naprave, ki je bila pripeta na igralno roko teniške igralke smo spremljali 97 % vseh njenih treningov in uradnih teniških tekem v dveh teniških sezonah. Cilj raziskave je bilo ugotoviti razlike v obremenitvi v trenažnem in tekmovalnem obdobju ter primerjati obremenitev v prvi in drugi teniški sezoni. Analiza ni pokazala značilnih razlik obremenitev na treningih, tekmah in teniških kazalcihv dveh teniških sezonah. Teniška igralka je trenirala časovno več v drugem letu (Y1 = 90.9 min, Y2 = 97.5 min), prav tako je bil odstotek aktivnega igranja v drugem letu višji (Y1 = 30.6%, Y2 = 32.4%). Večje število udarcev na teden je bilo ugotovljeno v prvem letu (Y1 = 3109.1, Y2 = 2869.4), medtem ko je bilo število udarcev na uro višje v drugem letu (Y1 =420.6, Y2 = 430.1). Tempo udarcev v izmenjavi je bil višji v prvem letu (Y1 = 24.6, Y2 = 23.4). Ostali indikatorji obremenitve se niso značilno različni. Študija primera ponuja vpogled v splošno raven obremenitve na treningih in tekmovanjih v dveh zaporednih teniških sezonah. Podatki lahko služijo kot izhodišče za določanje obremenitve v tenisu za teniške igralke, ki vstopajo na profesionalno teniško pot. Ključne besede: prenosne naprave, profesionalna tekmovanja, načrtovanje, trening, obremenitev med tekmo
... In elite sport, load monitoring has become standard practice, as evidence has demonstrated the risks of high acute and/or chronic workloads on the musculoskeletal system 10 and benefits achieved by tracking and adjusting workloads for individuals as they approach known thresholds. 11 FJA routinely log flight hours, however time of flight has been shown to be unrelated to neck pain complaints. 12 It is likely that better understanding of the intensity, frequency, type and duration of head motion over the duration of flight will be more enlightening. ...
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Objectives Gravitational Force (Gz), head motion and helmet mass are associated with neck pain in high performance aircraft pilots. Few studies have quantified neck kinetics (intersegmental neck moments) during aerial combat manoeuvres. Methods We quantified net joint moments between the skull and C1, and C6–7 during typical flight related headchecks using the Musculoskeletal Model for the Analysis of Spinal Injuries (MASI). We measured the influence of pilot-specific helmets and Gz on joint moments. Nineteen fighter pilots performed four head checks (check6 left, check6 right, extension hold and extension scan) under two helmet conditions. Motion data were transferred to OpenSim where joint moments were calculated at 1G to 9G. Net joint moments were compared across helmet conditions, Gz and headchecks. Results The Joint Helmet Mounted Cueing System (JHMCS) resulted in higher moments at each segment- by a factor of 1.25 per unit of Gz, at C1, and by a factor of 1.08 per unit of Gz for C7. ExtensionScan and Check6Left were associated with the highest peak (96.13 Nm and 92.56 Nm). ExtensionScan and ExtensionHold accrued the highest mean cumulative loads at C7 at 9Gz (607.35 Nm.sec/motion, 362.99 Nm.sec/motion respectively). Asymmetries were observed between the Left and Right Check6 motions. High variability was evident between and within pilots. Conclusions The MASI model has been successfully applied to quantify intersegmental neck joint moments for typical headchecks that are performed during combat flight manoeuvres. In future, data derived from this model may inform conditioning, rehabilitative and preventative interventions to reduce neck pain in fast jet pilots.
... In elite sports, return-to-play (RTP) decisions often involve a multi-disciplinary team that may include coaches, sports scientists, physicians, physiotherapists, and athletic therapists, alongside the athlete (Shrier et al., 2014). Early return to play increases the risk of injury (Tabener et al., 2019), therefore it is important that injured athletes have completed enough training to ensure they are ready to RTP (Blanch & Gabbett, 2016). Whilst it is not feasible for schools to employ a multi-disciplinary medical team, it is important that schools' Rugby coaches understand their role in the RTP of an injured athlete (Dijkstra et al., 2017). ...
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Objectives To examine the decision-making processes employed by schools' Rugby coaches in the management of injured players and to explore the factors that influenced those decisions. A secondary objective was to gauge interest in an education focused toolkit for schools' Rugby coaches. Design A qualitative study using one-to-one online interviews. Setting Schools who compete in the Ulster Schools' Cup Rugby competition. Participants Eleven Rugby union coaches from four post primary schools. Outcome measures A thematic analysis approach was used to examine the factors that influence schools' Rugby coaches' decision-making processes in the management of injured players. Results Findings suggest coaches are influenced in their decision making by four primary factors: their experience and learning, their relationships with other stakeholders, their knowledge and understanding of the roles and responsibilities of medical staff, healthcare and health fitness professionals, and resources available to them. Conclusions Schools' Rugby coaches play a significant role in the supervision of injured adolescent Rugby players, often drawing from their playing and coaching experiences. Schools retain, or recommend the services, of healthcare professionals (HCPs) and health and fitness professionals (HFPs). The role of these healthcare and health and fitness professionals, along with their qualifications and experience is not fully understood by coaches. Coaches acknowledge that there is a need for further training and would welcome education initiatives aimed at increasing awareness of musculoskeletal injury in schoolboy Rugby players.
... Returning to train after a long period of sport-specific load reduction without gradual reconditioning may increase the risk of sustaining an injury. 3,37,41,48 This progressive load planning, in which sport physiotherapists take part, is not limited to lockdown conditions but is applicable to musculoskeletal rehabilitations where the remaining or reduced load periods have been extensive, as in the case of severe tendinopathies or anterior cruciate ligament reconstruction rehabilitation. ...
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Background: During the COVID-19 pandemic, training routines of most athletes around the world were abruptly interrupted, potentially increasing the risk of injury. The purpose of this study was to compare three measures of training load (TL): tennis-specific TL, physical TL, and total TL management before, during and after lockdown in three professional male tennis players. Case Presentation: Three professional male tennis players were monitored throughout the 2020 season. Outcome and Follow-up: The median total weekly TL (CR 10 Borg RPE • session length in minutes) was 5783 AU. Before, during and after lockdown total weekly TL were 7195, 3753 and 5950, respectively. During lockdown tennis TL was reduced to 0 while physical TL (including preventive loads) increased by 73%. All players suffered an injury/illness during tennis training resumption following lockdown, two of them musculoskeletal related and the other due to COVID-19. There was no association between total ACWR and injury. However, one case had a spike (>1.5) in tennis-specific ACWR two weeks before injury, despite maintaining total ACWR between 0.8-1.5. Discussion: Tennis and physical differential TL monitoring should be carried out separately in order to ensure tennis-specific player readiness. If only total load is monitored during lockdown or rehabilitation from injury, subsequent increases in tennis load upon return to play could potentially increase the risk of injury. The three participants showed a similar pattern of total TL throughout the season with pre-lockdown loads being the highest.
... En el presente estudio, se encontró una alta variabilidad en el perfil de carga de trabajo externo en múltiples ubicaciones de las jugadoras de baloncesto, especialmente en las extremidades inferiores (rodilla y tobillo), donde se obtuvieron las desviaciones estándar más altas. En este sentido, la identificación de perfiles individuales puede ser fundamental para identificar el perfil de referencia tras una lesión así como para analizar la evolución de la forma física a lo largo de una temporada (Blanch & Gabbett, 2016;Shrier et al., 2014). ...
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La acelerometría es un método de cuantificación de la carga externa que está teniendo una aplicación exponencial gracias a su integración en dispositivos electrónicos para el análisis del rendimiento en deportes colectivos. La carga externa ha sido comúnmente cuantificada a través del desplazamiento (distancia y velocidad), no teniendo en cuenta su efecto a nivel neuromuscular. Por ello, el objetivo principal de la presente Tesis Doctoral es el análisis de la carga externa que soportan múltiples ubicaciones anatómicas de forma simultánea en los desplazamientos deportivos, específicamente en baloncesto. Para ello, se realiza una revisión sistemática detectando que diferentes aspectos técnicos requieren una evaluación previa al registro así como que los acelerómetros miden la aceleración del segmento al que están unidos. Para subsanar ambos aspectos, se realiza un análisis de la precisión y fiabilidad del sensor, se identifican los índices de carga y frecuencia de muestreo adecuados, así como se diseña y valida un protocolo de registro multi-ubicación y una batería de evaluaciones que representa los desplazamientos más comunes en los deportes de invasión. Finalmente, se realiza la evaluación multi-ubicación de la carga externa en test de laboratorio y test de campo para evaluar el efecto de la velocidad, sexo y tipo de desplazamiento, así como establecer perfiles de rendimiento individual. A partir de estos resultados, los entrenadores podrán identificar la carga externa específica de cada estructura musculoesquelética para diseñar programas individualizados de acondicionamiento físico, prevención de lesiones y recuperación adaptados a los grupos musculares con mayor carga externa. Accelerometry is a method for quantifying external load that is having an exponential application thanks to its integration in electronic performance and tracking systems in team sports. External load has been commonly quantified through displacement (distance and speed), not considering its effect at the neuromuscular level. Therefore, the main objective of this Doctoral Thesis is the analysis of the external load supported by multiple anatomical locations simultaneously in sports movements, specifically in basketball. To do this, a systematic review is carried out, detecting those different technical aspects that require an evaluation prior to registration, as well as that the accelerometers measure the acceleration of the segment to which they are attached. To correct both aspects, an analysis of the precision and reliability of the sensor was performed, the appropriate load index and sampling frequency were identified, as well as a multi-location registration protocol and a battery of evaluations that represent the most common displacements in invasion sports were designed and validated. Finally, the multi-location evaluation of the external load was performed in laboratory and field tests to evaluate the effect of speed, sex and type of movement, as well as to establish individual performance profiles. From these results, trainers will be able to identify the specific external load of each musculoskeletal structure to design individualized programs for physical conditioning, injury prevention and recovery adapted to the muscle groups with the highest external load.
... Des états de surmenage ou de sous entrainement (Gabbett, 2016) ne sont pas propices à la performance. Les joueurs blessés devraient pouvoir réintégrer l'effectif progressivement afin de favoriser un retour à la compétition sans risque potentiel de récidive (Blanch et Gabbett, 2015). Cette phase, souvent tronquée par les entraineurs, servirait au développement de certaines qualités physiques. ...
Thesis
Ce travail de thèse avait pour objectif d'analyser l'influence d'une saison sportive sur les caractéristiques physiques, physiologiques et psychologiques des joueurs de handball du club de Montpellier Agglomération Handball, un des meilleurs clubs européens. Dans un premier temps (Etude 1), nous nous sommes intéressés à l'évolution du profil musculaire isocinétique des membres inférieurs pendant la phase de préparation pré-compétitive (Pc2P). Bien que cette période soit courte (8 semaines), nos résultats montrent que la plupart des valeurs de force, de puissance (à 30±.s¡1, 60±.s¡1 et 240±.s¡1, en concentrique et en excentrique), et des différents ratios (agoniste vs antagoniste, dominant vs non dominant ainsi que le ratio mixte) augmentent significativement pendant Pc2P. Dans un deuxième temps (Etude 2), nous nous sommes intéressés à l'évolution du profil musculaire isocinétique des membres inférieurs pendant la période de compétition. Nos résultats montrent qu'une saison de compétition n'impacte pas significativement l'évolutionde la plupart des paramètres isocinétiques suscités. Enfin, au cours de notre 3e travail, nous avons étudié l'évolution de certains marqueurs (biologiques, physiologiques et psychologiques) au cours d'une saison sportive. Les principaux résultats de nos travaux montrent (i) une baisse des valeurs moyennes de VFC concernant les valeurs de HF et de RMSSD, couplée à une légère augmentation de FC en T4, laissant supposer une baisse de l'activité parasympathique en position couchée, (ii) une augmentation des valeurs au questionnaire d'état de forme en T4 et (iii) une diminution des valeurs de [C]sg , [F]sg , IGF-1 et Hématocrite,respectivement en T5 et T4. Les résultats des valeurs de Testostérone montrent une augmentation significative en T5. Ils ne montrent aucune modification significative des valeurs de CPK et d'IGFBP-3. Ces travaux soulignent la nécessité de développer les qualités de force et de puissance le plus efficacement possible pendant Pc2P et de cibler les marqueurs les plus pertinents pour le suivi longitudinal des joueurs de handball
... Open access chronic load is a measure of fitness and absolute acute load is a measure of fatigue. 17 High loads relative to the previous time period are thought to increase risk, while low loads relative to the previous time period decrease risk: a linear relationship. Therefore, for this time-lag scenario, we simulated a linear relationship with the absolute training load, and the relative training load was not considered (online supplemental figure S2B). ...
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Objectives Determine how to assess the cumulative effect of training load on the risk of injury or health problems in team sports. Methods First, we performed a simulation based on a Norwegian Premier League male football dataset (n players=36). Training load was sampled from daily session rating of perceived exertion (sRPE). Different scenarios of the effect of sRPE on injury risk and the effect of relative sRPE on injury risk were simulated. These scenarios assumed that the probability of injury was the result of training load exposures over the previous 4 weeks. We compared seven different methods of modelling training load in their ability to model the simulated relationship. We then used the most accurate method, the distributed lag non-linear model (DLNM), to analyse data from Norwegian youth elite handball players (no. of players=205, no. of health problems=471) to illustrate how assessing the cumulative effect of training load can be done in practice. Results DLNM was the only method that accurately modelled the simulated relationships between training load and injury risk. In the handball example, DLNM could show the cumulative effect of training load and how much training load affected health problem risk depending on the distance in time since the training load exposure. Conclusion DLNM can be used to assess the cumulative effect of training load on injury risk.
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Zusammenfassung Einleitung Verletzungen im Sport sind in jeder Altersklasse unvermeidbar. Häufig unterscheiden sich durchgeführte Rehabilitationsmethoden weitreichend und der Zeitpunkt der Bereitschaft für eine Rückkehr in den Sport kann nicht eindeutig bestimmt werden. Ein funktionsbasiertes Rehabilitationsmodell in Form des Return-to-Prozesses könnte den Wiedereinstieg in den Sport, anhand von Testbatterien, strukturierter gestalten und Aussagen über die Funktionsfähigkeit der betroffenen Struktur ermöglichen. Bisher erfolgten in diesem Themenbereich vorwiegend Untersuchungen der unteren Extremität. Ziel dieser Studie ist es Erweiterungsmerkmale für den Return-to-Prozess der oberen Extremität darzustellen. Methode Die Erstellung der systematischen Übersichtsarbeit orientierte sich an den PRISMA-Guidelines. Für die Literaturrecherche wurden die Datenbanken Pubmed, Cochrane Library und Web of Science nach relevanten Studien durchsucht. Anhand der Studienergebnisse wurden die angewandten Testverfahren zusammengetragen und miteinander verglichen. Ergebnisse Den Einschlusskriterien entsprachen eine Kohortenstudie, 6 Fallstudien und 7 Expertenmeinungen. Zum aktuellen Zeitpunkt gibt es keine einheitliche Definition für die Anwendung des Return-to-Prozesses. Der Begriff Return-to wird häufig auch unabhängig von Rehabilitationsmaßnahmen verwendet, um den Wiedereinstieg in den Sport zu beschreiben. Die Organisation innerhalb des Return-to-Prozesses unterscheiden sich zwischen den Autoren deutlich. Auch die angewandten Testverfahren wiesen kaum Überschneidungen auf. Die Bereitschaft für die Rückkehr in den Sport ist nicht einheitlich definiert und wird sowohl mit Hilfe von Funktionstests als auch Krafttests dargestellt. Für einen erfolgreichen Return-to-Prozess werden transparente und athletenzentrierte Entscheidungen im interdisziplinären Team, die Integration des biopsychosozialen Ansatzes und eine nachhaltige Steuerung der Belastung empfohlen. Schlussfolgerung Der funktionsbasierte Rehabilitationsansatz des Return-to-Prozesses für die obere Extremität benötigt einer einheitlichen Begriffsdefinition, sowie einer festgelegten Testbatterie, deren Gütekriterien wissenschaftlich nachgewiesen wurden. Der Return-to-Prozess muss funktions- und kraftbasierten Testverfahren beinhalten und ergänzende Komponenten, wie akute und chronische Belastungsverhältnisse einschließen.
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RESUMEN Introducción El concepto de monitorización y periodización es un visión que se ha desarrollado en la última década, donde se busca que se pueda tener un control de la carga interna y externa en los deportistas de distintas disciplinas deportivas producidas por el proceso de interacción con variables de prescripción de ejercicio que causan modificaciones a nivel fisiológico, bioquímico, biomecanico, muscular, neuromuscular ocasionando la tensión en los subsistemas del movimiento corporal humano generando adaptaciones especificas ante una carga determinada la cual puede ser medida mediante el uso de tecnología especifica o test indirectos Metodología Revisión de la literatura con la combinación de palabras clave como Monitoring, Performance, sports training load, Periodization en bases de datos como Pubmed, Ebsco, Medline, Scopus, Science Direct Resultados se pudo identificar 65 artículos que referencian la existencia de herramientas tecnológicas para realizar un proceso de monitorización y periodización desde la rehabilitación , prevención, control de carga, recuperación y readaptación deportiva que permiten la generación de datos estadísticos y crear perfiles desde cada área de actuación del fisioterapeuta deportivo. Conclusión la fisioterapia es una profesión encargada de muchos procesos deportivos que deben ser monitorizados y generen datos que permitan estandarizar procesos, crear perfiles de seguimiento específicos para facilitar la toma de decisiones desde el equipo biomédico e investigaciones en el deporte de alto rendimiento fusionando la practica con la evidencia científica.
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Aim: Investigate whether acute workload (1 week total distance) and chronic workload (4-week average acute workload) predict injury in elite rugby league players. Methods: Data were collected from 53 elite players over two rugby league seasons. The ‘acute:chronic workload ratio’ was calculated by dividing acute workload by chronic workload. A value of greater than 1 represented an acute workload greater than chronicworkload. All workload data were classified into discrete ranges by z-scores. Results Compared with all other ratios, a very-high acute:chronic workload ratio (≥2.11) demonstrated the greatest risk of injury in the current week (16.7% injury risk) and subsequent week (11.8% injury risk). High chronic workload (>16 095 m) combined with a very high 2-week average acute:chronic workload ratio (≥1.54) was associated with the greatest risk of injury (28.6% injury risk). High chronic workload combined with a moderate workload ratio (1.02–1.18) had a smaller risk of injury than low chronic workload combined with several workload ratios (relative risk range from 0.3 to 0.7×/÷1.4 to 4.4; likelihood range=88–94%, likely). Considering acute and chronic workloads in isolation (ie, not as ratios) did not consistently predict injury risk. Conclusions: Higher workloads can have either positive or negative influences on injury risk in elite rugby league players. Specifically, compared with players who have a low chronic workload, players with a high chronic workload are more resistant to injury with moderate-low through moderate-high (0.85–1.35)acute:chronic workload ratios and less resistant to injury when subjected to ‘spikes’ in acute workload, that is, very-high acute:chronic workload ratios ∼1.5.
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Objective To review the measurement properties of physical performance tests (PPTs) of the knee as each pertain to athletes, and to determine the relationship between PPTs and injury in athletes age 12 years to adult. Methods A search strategy was constructed by combining the terms ‘lower extremity’ and synonyms for ‘performance test’, and names of performance tests with variants of the term ‘athlete’. In this, part 1, we report on findings in the knee. The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines were followed and the Consensus-based Standards for the selection of health Measurement Instruments (COSMIN) checklist was used to critique the methodological quality of each paper. A second measure was used to analyse the quality of the measurement properties of each test. Results In the final analysis, we found 29 articles pertinent to the knee detailing 19 PPTs, of which six were compiled in a best evidence synthesis. The six tests were: one leg hop for distance (single and triple hop), 6 m timed hop, crossover hop for distance, triple jump and single leg vertical jump. The one leg hop for distance is the most often studied PPT. There is conflicting evidence regarding the validity of the hop and moderate evidence that the hop test is responsive to changes during rehabilitation. No test has established reliability or measurement error as assessed by the minimal important change or smallest detectable change. No test predicts knee injury in athletes. Conclusions Despite numerous published articles addressing PPTs at the knee, there is predominantly limited and conflicting evidence regarding the reliability, agreement, construct validity, criterion validity and responsiveness of commonly used PPTs. There is a great opportunity for further study of these tests and the measurement properties of each in athletes.
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To determine if the comparison of acute and chronic workload is associated with increased injury risk in elite cricket fast bowlers. Data were collected from 28 fast bowlers who completed a total of 43 individual seasons over a 6-year period. Workloads were estimated by summarising the total number of balls bowled per week (external workload), and by multiplying the session rating of perceived exertion by the session duration (internal workload). One-week data (acute workload), together with 4-week rolling average data (chronic workload), were calculated for external and internal workloads. The size of the acute workload in relation to the chronic workload provided either a negative or positive training-stress balance. A negative training-stress balance was associated with an increased risk of injury in the week after exposure, for internal workload (relative risk (RR)=2.2 (CI 1.91 to 2.53), p=0.009), and external workload (RR=2.1 (CI 1.81 to 2.44), p=0.01). Fast bowlers with an internal workload training-stress balance of greater than 200% had a RR of injury of 4.5 (CI 3.43 to 5.90, p=0.009) compared with those with a training-stress balance between 50% and 99%. Fast bowlers with an external workload training-stress balance of more than 200% had a RR of injury of 3.3 (CI 1.50 to 7.25, p=0.033) in comparison to fast bowlers with an external workload training-stress balance between 50% and 99%. These findings demonstrate that large increases in acute workload are associated with increased injury risk in elite cricket fast bowlers.
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The sport medicine clinician is faced with return-to-play (RTP) decisions for every patient who wants to return to activity. The complex interaction of factors related to history, physical examination, testing, activity and baseline characteristics can make RTP decision-making challenging. Further, when reasoning is not explicit, unnecessary conflict can arise among clinicians themselves, or among clinicians and patients. This conflict can have negative health consequences for the patient. In 2010, a transparent framework for RTP decisions was proposed. However, some have identified limitations to the framework and found difficulties in its implementation. This paper presents a revised framework that addresses the limitations, and provides concrete examples of how to apply it in simple and complex cases. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
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To assess workload-related risk factors for injuries to particular tissue types in cricket fast bowlers. 235 fast bowlers who bowled in 14600 player innings over a period of 15 years were followed in a prospective cohort risk factor study to compare overs bowled in each match (including preceding workload patterns) and injury risk in the 3-4 weeks subsequent to the match. Injuries were categorised according to the affected tissue type as either: bone stress, tendon injuries, muscle strain or joint injuries. Workload risk factors were examined using binomial logistic regression multivariate analysis, with a forward stepwise procedure requiring a significance of <0.05. High acute match workload and high previous season workload were risk factors for tendon injuries, but high medium term (3-month workload) was protective. For bone stress injuries, high medium term workload and low career workload were risk factors. For joint injuries, high previous season and career workload were risk factors. There was little relationship between muscle injury and workload although high previous season workload was slightly protective. The level of injury risk for some tissue types varies in response to preceding fast bowling workload, with tendon injuries most affected by workload patterns. Workload planning may need to be individualised, depending on individual susceptibility to various injury types. This study supports the theory that tendons are at lowest risk with consistent workloads and susceptible to injury with sudden upgrades in workload. Gradual upgrades are recommended, particularly at the start of a bowler's career to reduce the risk of bone stress injury. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
Article
To review the quality of literature and measurement properties of physical performance tests (PPTs) of the lower extremity in athletes. Using the PICOS method we established our research question as to whether individual PPTs of the lower extremity have any relationship to injury in competitive athletes ages 12 years to adult (no limit). A search strategy was constructed by combining the terms 'lower extremity' and synonyms for 'performance test' and names of performance tests with variants of the term 'athlete'. After examining the knee in part 1 of this 2 part series, the current report focuses on findings in the rest of the lower extremity. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed and the Consensus-based Standards for the selection of health Measurement Instruments (COSMIN) checklist was used to critique the methodological quality of each paper. A second measure was used to analyse the quality of the measurement properties of each test. Thirty-one articles examined the measurement properties of 14 PPTs pertaining to the lower extremity. The terminology used to name and describe the tests and methodology by which the tests were conducted was inconsistent. The star excursion balance test performed in three directions (anterior, posteromedial, and posterolateral) appears to be the only test to be associated with increased injury risk. There is moderate evidence that the one leg hop for distance and the hexagon hop can distinguish between normal and unstable ankles. There is also moderate evidence that the medial hop can distinguish between painful and normal hips in dancers. Currently, there is relatively limited research-backed information on PPTs of the lower extremity in athletes. We would suggest convening an international consortium comprised of experts in sports to standardise the descriptions and methodologies, and to set forth a research agenda to establish definitively the measurement properties of the most common PPTs. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
Article
Objectives: This study examined whether high match fast bowling workloads in the short to medium term were associated with increased bowling injury rates. Design: Prospective cohort study. Methods: Over a 15 year period, workload patterns for 235 individual fast bowlers during time periods from 5 to 26 days were examined to consider whether there was an increased injury rate during the month (28 days) subsequent to the workload. Results: Fast bowlers who bowled more than 50 match overs in a 5 day period had a significant increase in injury over the next month compared to bowlers who bowled 50 overs or less RR 1.54 (95% CI 1.04-2.29). For periods ranging from 12 to 26 days, there was no statistically-significant increase in injury over the next month from exceeding thresholds of certain amounts of overs, although bowlers who bowled more than 100 overs in 17 days had a non-significant increase in injury over the next month RR 1.78 (95% CI 0.90-3.50). Conclusion: There were no statistically-significant increases in subsequent injury risk for high workloads for periods of 12-26 days, although exceeding 100 overs in 17 days (or less) was associated with higher injury rates. Compression of cricket fixtures is likely to have only a minimal contribution to increased fast bowling injury rates being seen in the T20 era (along with sudden workload increases due to transferring between forms of the game, which has been previously established as a major contributor).
Article
Objective To estimate the incidence, type and severity of musculoskeletal injuries in youth and adult elite athletics athletes and to explore risk factors for sustaining injuries. Design Prospective cohort study conducted during a 52-week period. Setting Male and female youth and adult athletics athletes ranked in the top 10 in Sweden (n=292). Results 199 (68%) athletes reported an injury during the study season. Ninety-six per cent of the reported injuries were non-traumatic (associated with overuse). Most injuries (51%) were severe, causing a period of absence from normal training exceeding 3 weeks. Log-rank tests revealed risk differences with regard to athlete category (p=0.046), recent previous injury (>3 weeks time-loss; p=0.039) and training load rank index (TLRI; p=0.019). Cox proportional hazards regression analyses showed that athletes in the third (HR 1.79; 95% CI 1.54 to 2.78) and fourth TLRI quartiles (HR 1.79; 95% CI 1.16 to 2.74) had almost a twofold increased risk of injury compared with their peers in the first quartile and interaction effects between athlete category and previous injury; youth male athletes with a previous serious injury had more than a fourfold increased risk of injury (HR=4.39; 95% CI 2.20 to 8.77) compared with youth females with no previous injury. Conclusions The injury incidence among both youth and adult elite athletics athletes is high. A training load index combing hours and intensity and a history of severe injury the previous year were predictors for injury. Further studies on measures to quantify training content and protocols for safe return to athletics are warranted.
Article
Along with the enjoyment and the other positive benefits of sport participation, there is also the risk of injury that is elevated in contact sport. This review provides a summary of injury incidence in Australian Rules Football (ARF), identifies injury risk factors, assesses the efficacy of interventions to reduce injury risk and makes recommendations for future research. The most common injuries were found to be muscle strains, particularly hamstrings; joint ligament sprains, especially ankle; haematomas and concussion. The most severe joint injury was anterior cruciate ligament rupture. Mouthguards are commonly worn and have been shown to reduce orofacial injury. There is evidence that thigh pads can reduce the incidence of thigh haematomas. There is a reluctance to wear padded headgear and an attempt to assess its effectiveness was unsuccessful due to low compliance. The most readily identified risk factor was a history of that injury. There were conflicting findings as to the influence strength imbalances or deficit has on hamstring injury risk in ARF. Static hamstring flexibility was not related to risk but low hip flexor/quadriceps flexibility increased hamstring injury risk. High lower-limb and high hamstring stiffness were associated with an elevated risk of hamstring injury. Since stiffness can be modulated through strength or flexibility training, this provides an area for future intervention studies. Low postural balance ability was related to a greater risk of ankle injury in ARF, players with poor balance should be targeted for balance training. There are preliminary data signifying a link between deficiencies in hip range of motion and hip adductor strength with groin pain or injury. This provides support for future investigation into the effectiveness of an intervention for high-risk players on groin injury rate. Low cross-sectional area of core-region muscle has been associated with more severe injuries and a motor control exercise intervention that increased core muscle size and function resulted in fewer games missed due to injury. A randomized controlled trial of the effectiveness of eccentric hamstring exercise in decreasing hamstring injury rate in ARF players was unsuccessful due to poor compliance from muscle soreness; a progressive eccentric training intervention for ARF should be given future consideration. Jump and landing training reduced injury risk in junior ARF players and it would be advisable to include this component as part of a neuromuscular training intervention. A multifaceted programme of sport-specific drills for hamstring flexibility while fatigued, sport skills that load the hamstrings and high-intensity interval training to mimic match playing conditions showed some success in reducing the incidence of hamstring injuries in ARF. A countermeasure designed to reduce injury risk is more likely to be adopted by coaches and players if it also has the scope to enhance performance.
Article
Hamstring muscle strain-type injuries are common in sports that involve sprinting,1 acceleration, deceleration, rapid change in direction and jumping.2 ,3 Occurring in both recreational and professional sports, these injuries can result in substantial time lost from sport and commonly recur.4 ,5 In the Australian Football League (AFL), hamstring muscle strain-type injuries have displayed a high incidence rate, with a 10 year mean of 6.1 new injuries per club each year and a 23% average recurrence rate.6 A recurrence rate of 17% has been reported in elite soccer players7 with hamstring injuries also recorded as the most common injury accounting for 12% of all injuries and resulting in an average of four missed games per injury.8 The high incidence of hamstring muscle strain-type injuries and potential associated costs has resulted in a substantial amount of research into the factors related to such injuries. Two recent systematic reviews have been completed in an attempt to collate the evidence around risk factors for hamstring injuries.9 ,10 Both reviews identified hamstring muscle weakness and thigh muscle imbalance, muscle flexibility, previous hamstring injury, other previous injury and age as potential risk factors; however, these reviews concluded that single variables were inconsistently identified as associated factors. Both reviews provided a qualitative synthesis of the literature and included risk factor studies as well as intervention studies, where a potential risk factor was modified with a training programme. The inclusion of intervention studies may potentially complicate risk factor analyses, as such studies assume that the factor being modified is associated with the injury and that the factor can be modified by the treatment programme. The aim of the current review was to assemble all available knowledge and data to identify the intrinsic and extrinsic risk factors associated with …