© 2014 John Wiley & Sons A/S.
Scand J Med Sci Sports 2015: 25: e327–e330 doi: 10.1111/sms.12307
Published by John Wiley & Sons Ltd
King–Devick test normative reference values for professional male ice hockey players M. V. Vartiainen1, A. Holm2, K. Peltonen1, T. M. Luoto3, G. L. Iverson4,5,6,7, L. Hokkanen1 1
Institute of Behavioural Sciences, Division of Cognitive Psychology and Neuropsychology, University of Helsinki, Helsinki, Finland, Department of Clinical Neurophysiology, Satakunta Central Hospital, Pori, Finland, 3Department of Neurosciences and Rehabilitation, Tampere University Hospital, Tampere, Finland, 4Department of Physical Medicine and Rehabilitation, Harvard Medical School, Boston, Massachusetts, USA, 5Spaulding Rehabilitation Hospital, Boston, Massachusetts, USA, 6Red Sox Foundation and Massachusetts General Hospital Home Base Program, Boston, Massachusetts, USA, 7Massachusetts General Hospital Sport Concussion Clinic, Boston, Massachusetts, USA Corresponding author: Matti V. Vartiainen, MSc, Institute of Behavioural Sciences, Division of Cognitive Psychology and Neuropsychology, University of Helsinki, Räisäläntie 24, 00100 Helsinki, Finland. Tel: +35850 585 3884, Fax: +3589 510 2906, E-mail: [email protected] 2
Accepted for publication 15 July 2014
The King–Devick (K-D) test, a measure of processing speed, visual tracking, and saccadic eye movements, has shown promise as a supplemental screening test following concussion. However, limited normative data for this test have been published.The K-D test was administered to 185 professional ice hockey players as a preseason baseline test in seasons 2012–2013 and 2013–2014. Their average age was 23.8 years (median = 22.0 years, range = 16–40 years). The average K-D score was 40.0 s
(SD = 6.1 s, range = 24.0–65.7 s). K-D test performance showed no association with age, education, or the number of self-reported previous concussions in this sample. The association between trials 1 and 2 of the K-D test was good (ICC = 0.92, Pearson = 0.93). Normative values of the K-D test for professional male ice hockey players are reported. K-D test performance did not vary by age, education, or concussion history in this study.
Concussion is a common injury in high-velocity sports. Although sideline tests such as the Sport Concussion Assessment Tool – 3rd Edition (McCrory et al., 2013) are widely used, there is a continuing need for tests that can accurately detect the effects of a concussion immediately following injury. The King–Devick Test® (K-D) was recently highlighted as a promising assessment instrument for concussion (Putukian et al., 2013). For the K-D test, the athlete reads aloud single-digit numbers displayed on three cards. The time to complete these three test cards and the number of errors are recorded. According the test publisher’s recommendation, the test should always be administered at least twice, consecutively. The K-D test measures processing speed, visual tracking, and saccadic eye movements. To date, seven K-D studies that focus on athletes have been published (Galetta et al., 2011a b, 2013; King et al., 2012, 2013; Tjarks et al., 2013; Leong et al., 2014). These studies have reported findings from male athletes between the ages of 12 and 53 years (sports included: rugby, ice hockey, boxing, mixed martial arts, soccer, football, and basketball). Five of these publications report reference baseline K-D test values, but only one study has a sample greater than 50 (Galetta et al.,
2011b). A significant increase in post-concussion K-D test times (means: 3.1–11.1 s) have been observed compared with pre-injury performance. High test–retest and inter-rater reliability have been reported (Galetta et al., 2011b). Subtle learning effects have been associated with repeated K-D performance (Galetta et al., 2011a,b; King et al., 2012, 2013). Post-injury concussion assessments must be interpreted by comparing the post-injury result either with an individual baseline performance or with normative data. In professional contact sports (e.g., the U.S. National Hockey League and National Football League), baseline testing is routinely conducted. In the absence of baseline data, normative values can be used to interpret postinjury performance. Normative data is also helpful when used in combination with an individual’s baseline score, especially when baseline performance is not accurate (e.g., underestimates a person’s true ability; Echemendia et al., 2012; Schmidt et al., 2012). The main purpose of this study was to establish normative values for the K-D test using a large sample of professional male ice hockey players. We also studied the effects of age, education, and prior self-reported concussions on K-D performance.
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Vartiainen et al. Methods Study framework and ethics The K-D test was administered as a preseason [seasons: 2012–13 (n = 118) and 2013–14 (n = 67)] baseline test to 185 professional male ice hockey players from five teams in the Finnish national league. Years of education and the number of prior self-reported concussions were obtained by interview at the time of testing. A concussion 1 month prior to testing, as well as a neurological or other illnesses possibly affecting the test were considered as exclusion criteria. The test was conducted in a quiet environment, at least 15 min after exercise (8:00 to 16:00 h) by a single experienced health care professional (M. V. V.). As per the publisher’s recommendations, the test was administered twice (trial 1 and trial 2) to each player in a single session. The study was approved by the Ethical Committee of the Helsinki Uusimaa Hospital District, and each participating subject signed written informed consent according to the Declaration of Helsinki.
Statistical analyses The better trial (faster time) was recorded for all the subjects. Data for both trials was available for 124 subjects. The normality of distributions was tested with the Shapiro–Wilk test. The effect of age was studied using bivariate correlations and by dividing the subjects into three groups: (a) 16–19 years; (b) 20–26 years; and (c) 27–40 years. The effect of education was studied using bivariate correlations and by forming two groups: (a) 12 years or more; and (b) less than 12 years of education. To study the effect of previous concussions, three groups were used: (a) no concussions; (b) one or two concussions; and (c) three or more concussions. The K-D performance was compared between these groups with the Kruskal–Wallis test. Only time was used as an indicator of performance because no errors were made by the subjects. Additionally, a repeated measures general linear model (GLM) was used to measure the associations between the K-D test and the three grouping variables (age, education, and concussion). The association between the first and second measurement was examined by the intraclass correlation coefficient (ICC) and the Pearson corre-
lation. The level of statistical significance was set at 0.05. IBM SPSS Statistics 21.0 (IBM Corp. Armonk, New York, USA) was used to perform the analyses.
Results The mean age of the subjects was 23.8 years [standard deviation (SD) = 5.6 years, range = 16–40 years]. All of the players were Finnish. Their mean education was 11.6 (SD = 1.4) years. Of the players, 46.5% (n = 86) reported one or more prior concussions. The average number of concussions sustained prior to testing was 0.9 (median = 0, SD = 1.2, range = 0–7). The Pearson correlations between age and K-D scores were as follows: trial 1 = −0.051, trial 2 = −0.040, best = −0.064 (all nonsignificant). The Pearson correlations between education and K-D scores were as follows: trial 1 = −0.082, trial 2 = −0.139, best = −0.146 (all nonsignificant). There were no statistically significant differences in the K-D scores between the age groups [H(2) = 0.270, P = 0.874], the education groups [H(1) = 0.709, P = 0.400], or the concussion groups [H(2) = 0.249, P = 0.883]. In the three repeated measures GLMs, a significant main effect for the trial (P < 0.001) was found. There were no interactions between trial and age, education, or history of concussion (P > 0.1 in each). The K-D test results are presented in Table 1. There was a strong association between the first and second trial (Table 2). The second trial was performed faster in 163 of 185 subjects (88%). Discussion This study presents K-D test normative values for Finnish professional ice hockey players. None of the
Table 1. Normative reference values for the K-D test (time, s) in a sample of Finnish professional ice hockey players
Trial 1 Test card 1 Test card 2 Test card 3 Total score Trial 2 Test card 1 Test card 2 Test card 3 Total score Best score Test card 1 Test card 2 Test card 3 Total score
n
Mean
Median
SD
Superior
Above average
Average
Below average
Unusually low
Extremely low
137 137 137 137
14.0 14.0 14.6 42.5
13.5 13.7 14.3 41.2
2.4 2.5 2.7 7.2
< 11.6 < 11.4 < 11.6 < 34.5
11.6–12.5 11.4–12.2 11.6–12.8 34.5–37.6
12.6–15.1 12.3–15.1 12.9–15.8 37.7–46.2
15.2–16.8 15.2–16.9 15.9–18.4 46.3–51.2
16.9–22.8 17.0–21.2 18.5–22.5 51.3–64.5
> 22.8 > 21.2 > 22.5 > 64.5
172 172 172 172
13.3 13.3 13.9 40.4
13.2 13.0 13.7 40.0
2.2 2.2 2.2 6.3
< 10.9 < 11.0 < 11.5 < 33.8
10.9–11.9 11.0–11.8 11.5–12.3 33.8–36.3
12.0–14.3 11.9–14.4 12.4–15.0 36.4–43.9
14.4–16.0 14.5–15.7 15.1–16.7 44.0–47.7
16.1–19.5 15.8–20.0 16.8–19.9 47.8–59.9
> 19.5 > 20.0 > 19.9 > 59.9
185 185 185 185
13.3 13.3 13.8 40.4
13.2 13.0 13.6 40.0
2.1 2.2 2.2 6.1
< 11.0 < 11.0 < 11.5 < 33.8
11.0–11.9 11.0–11.8 11.5–12.2 33.8–36.3
12.0–14.5 11.9–14.4 12.3–15.0 36.4–44.0
14.6–16.0 14.5–15.8 15.1–16.7 44.1–47.8
16.1–18.1 15.9–19.3 16.8–19.7 47.9–56.7
> 18.1 > 19.3 > 19.7 > 56.7
n = 185, mean age = 23.8 ± 5.6 years, and mean education = 11.6 ± 1.4 years. Total score refers to the time to complete all three cards. There are slight variations in total scores due to rounding. Superior scores occur in fewer than 10% of the sample. Above average scores occur in approximately 15%, average scores in approximately 50%, below average scores in approximately 15%, unusually low in approximately 8%, and extremely low scores in fewer than 2% of the sample. These classification ranges correspond to the following percentile ranks: extremely low = < 2nd percentile; unusually low = 2nd– 9th percentile; below average = 10th–24th percentile; average = 25th–75th percentile; above average = 76th–90th percentile; and superior = > 90th percentile.
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King–Devick test normative values Table 2. Association between first and second test trials in the players who completed two trials (n = 124)
Total score Test card 1 Test card 2 Test card 3
Trial 1–2 difference scores (s)
ICC
Pearson
2.1 (18.0) 0.9 (8.8) 0.6 (8.5) 0.7 (10.4)
0.92 0.88 0.88 0.83
0.93 0.88 0.88 0.88
Total score is the individual combined time to complete all three cards. Difference scores were calculated by subtracting the second from the first test result. ICC, intraclass correlation coefficient; Pearson, Pearson correlation.
players included in the sample were tested with the K-D test prior to this study. There were no statistically significant differences on the K-D test in relation to age, education, or the number of past concussions in the current sample. The test showed good test-retest reliability between the two trials. The second trial was performed faster in 88% of the athletes (i.e., on average 2.1 s faster). In the present study, the median best K-D score was 40.0 s (interquartile range = 36.5–43.9 s; range 24.0– 65.7 s). The current findings are similar to results reported by Galetta and colleagues with professional ice hockey players (n = 27, mean = 40.3 s, SD = +/−6.4 s, range = 29.4–58.3 s) and for football, soccer, and basketball players (n = 219, median = 37.9 s, SD = not reported, range = 23.4–58.0 s; Galetta et al., 2011b, 2013). Those samples had average scores that were in the average classification range in Table 1. The average scores for boxers and MMA fighters (n = 39, median = 44.6 s, SD = not reported, range = 32.0–58.2 s) were slower than the present sample, falling in the below average range (Galetta et al., 2011a). The lowest baseline scores were reported by King and colleagues for amateur rugby league players (n = 37, median 47.3 s, SD = not reported, range = 28.0–80.3 s and n = 50, median 48.2 s, SD = not reported, range = 34.6–62.0 s; King et al., 2012, 2013). The average score for the rugby players was on the border between the below average range and poor compared with the present sample of hockey players (see Table 1). The range of scores on the K-D test in this sample was broad (e.g., 24–65 s for the K-D best score). The normative classification ranges in Table 1 are helpful for interpreting post-concussion test scores. However, the accurate identification of a substantial decline following injury is difficult in athletes who normally have unusually fast or slow performance (e.g., their normal performance is unusually low or superior). For instance, an
athlete achieving a total score of 43 s post-injury will fall into the “average” classification range and is therefore performing at a level where 50% of the athletes normally perform. Without a reliable baseline measurement, it is not possible to know if that score indicates a decline for that particular individual or not. For an athlete with a pre-injury performance time of 33 s (the “superior” classification range), the slowing would indicate a significant decrement. A worsening of an average of 5 s following concussion compared with baseline K-D performance has been reported (King et al., 2012; Galetta et al., 2013). At the other end of the continuum, an athlete performing at 48 s, 24 h after a concussion would have a score in the unusually low classification range – but whether this represents a small or large decline in functioning is unknowable without a reliable baseline. In the absence of baseline scores, a K-D score of over 60 s following a concussion can be considered universally abnormal according to prior studies on athletes (Tjarks et al., 2013). Our results confirm this; only 1.6% (n = 3) of our subjects scored over 60 s on the preseason baseline testing. In general, scores in the unusually low range should be considered potentially problematic because approximately 90% of athletes score above this range. Perspectives The K-D test has recently been highlighted as a promising new sideline test in the field of concussion management (Putukian et al., 2013) and it is reported to have good reliability (Galetta et al., 2011b). We reported normative values for professional male ice hockey players. The preseason K-D performance in our sample was unrelated to age, education, or the number of selfreported prior concussions. The association between the two trials was high, although we found that 88% of the athletes performed the second trial better (e.g., on average 2.1 s faster). Research is needed on the intrarater reliability, test-retest reliability over clinically relevant intervals (e.g., 1 day, 1 week, 1 month, and 3 months), validity, and clinical usefulness of the test in athletes with concussions before health care professionals can have more confidence in using it. In our sample, each athlete performed the test without errors. Compared with the SCAT3, the test measures different aspects of functioning, so it may prove to have value as an additional method for assessing the acute effects of concussion. Key words: sport, concussion, head injury, measurement, neurology.
References Echemendia RJ, Bruce JM, Bailey CM, Sanders JF, Arnett P, Vargas G. The utility of post-concussion neuropsychological data in identifying
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Scand J Med Sci Sports 2015: 25: e327–e330 doi: 10.1111/sms.12307
Published by John Wiley & Sons Ltd
King–Devick test normative reference values for professional male ice hockey players M. V. Vartiainen1, A. Holm2, K. Peltonen1, T. M. Luoto3, G. L. Iverson4,5,6,7, L. Hokkanen1 1
Institute of Behavioural Sciences, Division of Cognitive Psychology and Neuropsychology, University of Helsinki, Helsinki, Finland, Department of Clinical Neurophysiology, Satakunta Central Hospital, Pori, Finland, 3Department of Neurosciences and Rehabilitation, Tampere University Hospital, Tampere, Finland, 4Department of Physical Medicine and Rehabilitation, Harvard Medical School, Boston, Massachusetts, USA, 5Spaulding Rehabilitation Hospital, Boston, Massachusetts, USA, 6Red Sox Foundation and Massachusetts General Hospital Home Base Program, Boston, Massachusetts, USA, 7Massachusetts General Hospital Sport Concussion Clinic, Boston, Massachusetts, USA Corresponding author: Matti V. Vartiainen, MSc, Institute of Behavioural Sciences, Division of Cognitive Psychology and Neuropsychology, University of Helsinki, Räisäläntie 24, 00100 Helsinki, Finland. Tel: +35850 585 3884, Fax: +3589 510 2906, E-mail: [email protected] 2
Accepted for publication 15 July 2014
The King–Devick (K-D) test, a measure of processing speed, visual tracking, and saccadic eye movements, has shown promise as a supplemental screening test following concussion. However, limited normative data for this test have been published.The K-D test was administered to 185 professional ice hockey players as a preseason baseline test in seasons 2012–2013 and 2013–2014. Their average age was 23.8 years (median = 22.0 years, range = 16–40 years). The average K-D score was 40.0 s
(SD = 6.1 s, range = 24.0–65.7 s). K-D test performance showed no association with age, education, or the number of self-reported previous concussions in this sample. The association between trials 1 and 2 of the K-D test was good (ICC = 0.92, Pearson = 0.93). Normative values of the K-D test for professional male ice hockey players are reported. K-D test performance did not vary by age, education, or concussion history in this study.
Concussion is a common injury in high-velocity sports. Although sideline tests such as the Sport Concussion Assessment Tool – 3rd Edition (McCrory et al., 2013) are widely used, there is a continuing need for tests that can accurately detect the effects of a concussion immediately following injury. The King–Devick Test® (K-D) was recently highlighted as a promising assessment instrument for concussion (Putukian et al., 2013). For the K-D test, the athlete reads aloud single-digit numbers displayed on three cards. The time to complete these three test cards and the number of errors are recorded. According the test publisher’s recommendation, the test should always be administered at least twice, consecutively. The K-D test measures processing speed, visual tracking, and saccadic eye movements. To date, seven K-D studies that focus on athletes have been published (Galetta et al., 2011a b, 2013; King et al., 2012, 2013; Tjarks et al., 2013; Leong et al., 2014). These studies have reported findings from male athletes between the ages of 12 and 53 years (sports included: rugby, ice hockey, boxing, mixed martial arts, soccer, football, and basketball). Five of these publications report reference baseline K-D test values, but only one study has a sample greater than 50 (Galetta et al.,
2011b). A significant increase in post-concussion K-D test times (means: 3.1–11.1 s) have been observed compared with pre-injury performance. High test–retest and inter-rater reliability have been reported (Galetta et al., 2011b). Subtle learning effects have been associated with repeated K-D performance (Galetta et al., 2011a,b; King et al., 2012, 2013). Post-injury concussion assessments must be interpreted by comparing the post-injury result either with an individual baseline performance or with normative data. In professional contact sports (e.g., the U.S. National Hockey League and National Football League), baseline testing is routinely conducted. In the absence of baseline data, normative values can be used to interpret postinjury performance. Normative data is also helpful when used in combination with an individual’s baseline score, especially when baseline performance is not accurate (e.g., underestimates a person’s true ability; Echemendia et al., 2012; Schmidt et al., 2012). The main purpose of this study was to establish normative values for the K-D test using a large sample of professional male ice hockey players. We also studied the effects of age, education, and prior self-reported concussions on K-D performance.
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Vartiainen et al. Methods Study framework and ethics The K-D test was administered as a preseason [seasons: 2012–13 (n = 118) and 2013–14 (n = 67)] baseline test to 185 professional male ice hockey players from five teams in the Finnish national league. Years of education and the number of prior self-reported concussions were obtained by interview at the time of testing. A concussion 1 month prior to testing, as well as a neurological or other illnesses possibly affecting the test were considered as exclusion criteria. The test was conducted in a quiet environment, at least 15 min after exercise (8:00 to 16:00 h) by a single experienced health care professional (M. V. V.). As per the publisher’s recommendations, the test was administered twice (trial 1 and trial 2) to each player in a single session. The study was approved by the Ethical Committee of the Helsinki Uusimaa Hospital District, and each participating subject signed written informed consent according to the Declaration of Helsinki.
Statistical analyses The better trial (faster time) was recorded for all the subjects. Data for both trials was available for 124 subjects. The normality of distributions was tested with the Shapiro–Wilk test. The effect of age was studied using bivariate correlations and by dividing the subjects into three groups: (a) 16–19 years; (b) 20–26 years; and (c) 27–40 years. The effect of education was studied using bivariate correlations and by forming two groups: (a) 12 years or more; and (b) less than 12 years of education. To study the effect of previous concussions, three groups were used: (a) no concussions; (b) one or two concussions; and (c) three or more concussions. The K-D performance was compared between these groups with the Kruskal–Wallis test. Only time was used as an indicator of performance because no errors were made by the subjects. Additionally, a repeated measures general linear model (GLM) was used to measure the associations between the K-D test and the three grouping variables (age, education, and concussion). The association between the first and second measurement was examined by the intraclass correlation coefficient (ICC) and the Pearson corre-
lation. The level of statistical significance was set at 0.05. IBM SPSS Statistics 21.0 (IBM Corp. Armonk, New York, USA) was used to perform the analyses.
Results The mean age of the subjects was 23.8 years [standard deviation (SD) = 5.6 years, range = 16–40 years]. All of the players were Finnish. Their mean education was 11.6 (SD = 1.4) years. Of the players, 46.5% (n = 86) reported one or more prior concussions. The average number of concussions sustained prior to testing was 0.9 (median = 0, SD = 1.2, range = 0–7). The Pearson correlations between age and K-D scores were as follows: trial 1 = −0.051, trial 2 = −0.040, best = −0.064 (all nonsignificant). The Pearson correlations between education and K-D scores were as follows: trial 1 = −0.082, trial 2 = −0.139, best = −0.146 (all nonsignificant). There were no statistically significant differences in the K-D scores between the age groups [H(2) = 0.270, P = 0.874], the education groups [H(1) = 0.709, P = 0.400], or the concussion groups [H(2) = 0.249, P = 0.883]. In the three repeated measures GLMs, a significant main effect for the trial (P < 0.001) was found. There were no interactions between trial and age, education, or history of concussion (P > 0.1 in each). The K-D test results are presented in Table 1. There was a strong association between the first and second trial (Table 2). The second trial was performed faster in 163 of 185 subjects (88%). Discussion This study presents K-D test normative values for Finnish professional ice hockey players. None of the
Table 1. Normative reference values for the K-D test (time, s) in a sample of Finnish professional ice hockey players
Trial 1 Test card 1 Test card 2 Test card 3 Total score Trial 2 Test card 1 Test card 2 Test card 3 Total score Best score Test card 1 Test card 2 Test card 3 Total score
n
Mean
Median
SD
Superior
Above average
Average
Below average
Unusually low
Extremely low
137 137 137 137
14.0 14.0 14.6 42.5
13.5 13.7 14.3 41.2
2.4 2.5 2.7 7.2
< 11.6 < 11.4 < 11.6 < 34.5
11.6–12.5 11.4–12.2 11.6–12.8 34.5–37.6
12.6–15.1 12.3–15.1 12.9–15.8 37.7–46.2
15.2–16.8 15.2–16.9 15.9–18.4 46.3–51.2
16.9–22.8 17.0–21.2 18.5–22.5 51.3–64.5
> 22.8 > 21.2 > 22.5 > 64.5
172 172 172 172
13.3 13.3 13.9 40.4
13.2 13.0 13.7 40.0
2.2 2.2 2.2 6.3
< 10.9 < 11.0 < 11.5 < 33.8
10.9–11.9 11.0–11.8 11.5–12.3 33.8–36.3
12.0–14.3 11.9–14.4 12.4–15.0 36.4–43.9
14.4–16.0 14.5–15.7 15.1–16.7 44.0–47.7
16.1–19.5 15.8–20.0 16.8–19.9 47.8–59.9
> 19.5 > 20.0 > 19.9 > 59.9
185 185 185 185
13.3 13.3 13.8 40.4
13.2 13.0 13.6 40.0
2.1 2.2 2.2 6.1
< 11.0 < 11.0 < 11.5 < 33.8
11.0–11.9 11.0–11.8 11.5–12.2 33.8–36.3
12.0–14.5 11.9–14.4 12.3–15.0 36.4–44.0
14.6–16.0 14.5–15.8 15.1–16.7 44.1–47.8
16.1–18.1 15.9–19.3 16.8–19.7 47.9–56.7
> 18.1 > 19.3 > 19.7 > 56.7
n = 185, mean age = 23.8 ± 5.6 years, and mean education = 11.6 ± 1.4 years. Total score refers to the time to complete all three cards. There are slight variations in total scores due to rounding. Superior scores occur in fewer than 10% of the sample. Above average scores occur in approximately 15%, average scores in approximately 50%, below average scores in approximately 15%, unusually low in approximately 8%, and extremely low scores in fewer than 2% of the sample. These classification ranges correspond to the following percentile ranks: extremely low = < 2nd percentile; unusually low = 2nd– 9th percentile; below average = 10th–24th percentile; average = 25th–75th percentile; above average = 76th–90th percentile; and superior = > 90th percentile.
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King–Devick test normative values Table 2. Association between first and second test trials in the players who completed two trials (n = 124)
Total score Test card 1 Test card 2 Test card 3
Trial 1–2 difference scores (s)
ICC
Pearson
2.1 (18.0) 0.9 (8.8) 0.6 (8.5) 0.7 (10.4)
0.92 0.88 0.88 0.83
0.93 0.88 0.88 0.88
Total score is the individual combined time to complete all three cards. Difference scores were calculated by subtracting the second from the first test result. ICC, intraclass correlation coefficient; Pearson, Pearson correlation.
players included in the sample were tested with the K-D test prior to this study. There were no statistically significant differences on the K-D test in relation to age, education, or the number of past concussions in the current sample. The test showed good test-retest reliability between the two trials. The second trial was performed faster in 88% of the athletes (i.e., on average 2.1 s faster). In the present study, the median best K-D score was 40.0 s (interquartile range = 36.5–43.9 s; range 24.0– 65.7 s). The current findings are similar to results reported by Galetta and colleagues with professional ice hockey players (n = 27, mean = 40.3 s, SD = +/−6.4 s, range = 29.4–58.3 s) and for football, soccer, and basketball players (n = 219, median = 37.9 s, SD = not reported, range = 23.4–58.0 s; Galetta et al., 2011b, 2013). Those samples had average scores that were in the average classification range in Table 1. The average scores for boxers and MMA fighters (n = 39, median = 44.6 s, SD = not reported, range = 32.0–58.2 s) were slower than the present sample, falling in the below average range (Galetta et al., 2011a). The lowest baseline scores were reported by King and colleagues for amateur rugby league players (n = 37, median 47.3 s, SD = not reported, range = 28.0–80.3 s and n = 50, median 48.2 s, SD = not reported, range = 34.6–62.0 s; King et al., 2012, 2013). The average score for the rugby players was on the border between the below average range and poor compared with the present sample of hockey players (see Table 1). The range of scores on the K-D test in this sample was broad (e.g., 24–65 s for the K-D best score). The normative classification ranges in Table 1 are helpful for interpreting post-concussion test scores. However, the accurate identification of a substantial decline following injury is difficult in athletes who normally have unusually fast or slow performance (e.g., their normal performance is unusually low or superior). For instance, an
athlete achieving a total score of 43 s post-injury will fall into the “average” classification range and is therefore performing at a level where 50% of the athletes normally perform. Without a reliable baseline measurement, it is not possible to know if that score indicates a decline for that particular individual or not. For an athlete with a pre-injury performance time of 33 s (the “superior” classification range), the slowing would indicate a significant decrement. A worsening of an average of 5 s following concussion compared with baseline K-D performance has been reported (King et al., 2012; Galetta et al., 2013). At the other end of the continuum, an athlete performing at 48 s, 24 h after a concussion would have a score in the unusually low classification range – but whether this represents a small or large decline in functioning is unknowable without a reliable baseline. In the absence of baseline scores, a K-D score of over 60 s following a concussion can be considered universally abnormal according to prior studies on athletes (Tjarks et al., 2013). Our results confirm this; only 1.6% (n = 3) of our subjects scored over 60 s on the preseason baseline testing. In general, scores in the unusually low range should be considered potentially problematic because approximately 90% of athletes score above this range. Perspectives The K-D test has recently been highlighted as a promising new sideline test in the field of concussion management (Putukian et al., 2013) and it is reported to have good reliability (Galetta et al., 2011b). We reported normative values for professional male ice hockey players. The preseason K-D performance in our sample was unrelated to age, education, or the number of selfreported prior concussions. The association between the two trials was high, although we found that 88% of the athletes performed the second trial better (e.g., on average 2.1 s faster). Research is needed on the intrarater reliability, test-retest reliability over clinically relevant intervals (e.g., 1 day, 1 week, 1 month, and 3 months), validity, and clinical usefulness of the test in athletes with concussions before health care professionals can have more confidence in using it. In our sample, each athlete performed the test without errors. Compared with the SCAT3, the test measures different aspects of functioning, so it may prove to have value as an additional method for assessing the acute effects of concussion. Key words: sport, concussion, head injury, measurement, neurology.
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