Concussion is classified as a mild form of traumatic brain injury, but changes in neural function following concussions are far from benign. In pursuit of identifying quick, reliable, and objective metrics to diagnose a concussion, various resources have indicated that as many as 69% of patients with a concussion exhibit some form of visual dysfunction, including accommodative disorders, convergence insufficiency, or saccadic dysfunction.1,2 Receded binocular convergence has been proposed as a chief indicator of neuro-ophthalmologic perturbation.3–5 Binocular convergence, often referred to as near point of convergence (NPC), measures the closest point to which one can focus on an object before diplopia occurs. NPC measurement is an emerging clinical tool with which clinicians can objectively identify abnormal behavioral traits in patients with potential concussion.5 In addition, NPC measurements are advantageous because they require no baseline data, have relatively well-established normative cut-off values, and can be easily administered with the use of an accommodation ruler.6
Athletes with concussions have exhibited threefold worsening in NPC as compared to control individuals, with this single clinical metric yielding 73% of diagnostic accuracy for concussion.5,7,8 In previous clinical studies, we have demonstrated that NPC assessment is also sensitive enough to detect a transient neuronal dysfunction from subconcussive head impacts (eg, soccer heading and football tackle), where NPC worsened by approximately 29% to 38% relative to baseline values.9–11 Not only do mechanical forces to the brain impair NPC, but studies have also shown that neural fatigue from sleep deprivation significantly attenuates ocular-motor function.12,13 However, there is a substantial knowledge gap in the time-of-day influence on NPC. Therefore, this study aimed to answer whether the NPC is stable between morning and night despite potential neural fatigue from daily conscious activity. We hypothesized that there would be a significant worsening (increase) in NPC at night (7 PM) compared to morning (7 AM).
Thirty healthy college-aged adults volunteered to participate in this study. Our sample size was determined by a power analysis using data from previous sleep deprivation literature, and 30 participants was estimated to yield at least 90% statistical power for this study. The study consisted of 16 men and 14 women with an average age of 20.4 ± 1.0 years and body mass index of 24.79 ± 3.0 k/m2, 11 of 30 participants wore contact lenses, and 10 of 30 participants had a history of one concussion. Inclusion criteria were age 18 to 26 years and average sleep duration of 7 hours or more at night, as well as a minimum of 7 hours of sleep a night before the testing, validated by a wrist-worn ActiGraph device (ActiGraph, Pensacola, FL). Exclusion criteria were any history of head injury in the 1 year prior to the study and any neurological, ocular, or sleep disorders. Two days prior to the study and during the study, participants were instructed to refrain from substances that could affect their nervous systems (eg, caffeine, alcohol, or depressants). To control participants' baseline neural fatigue, for 1 week prior to the study, potential participants were instructed to record their sleep cycle on a sleep log and were fitted with an ActiGraph wGT3X-BT to monitor their sleeping duration. Prior to test 1 (7 AM), participants' sleep duration was screened via the data from ActiGraph, and then participants who slept less than an average of 7 hours per night were excluded from the study. All participants gave written informed consent, and Indiana University's Institutional Review Board approved the study.
Sleep and Activity Monitor
The ActiGraph measures human motion and step counts using a tri-axial accelerometer while eliminating non-human motion by suppressing high acceleration data.14 ActiLife (version 6.5.3; ActiGraph) software was used for the sleep analysis, and we employed the Sadeh algorithm to score sleep duration, which has been validated with 91.4% to 96.5% minute-by-minute agreement rates in adults compared with traditional polysomnography.14 A subjective sleep log was used to visually inspect the ActiGraph data.
NPC was assessed at 7 AM and 7 PM based on our established protocol.9,10 Briefly, using the accommodative ruler (Gulden Ophthalmics, Elkins Park, PA), a target was moved toward the eyes at a rate of approximately 1 to 2 cm/s. NPC, the distance between the participant and object, was recorded when the tester observed eye malalignment or when participants verbally signaled experiencing diplopia. The assessment was repeated twice, and mean NPC was used for analyses. One trained tester (SC) assessed all participants at all time points, and an intraclass correlation coefficient (ICC) between trials 1 and 2 indicated that there was a significant agreement between trials (ICC = 0.974, 95% confidence interval [CI] = 0.948 to 0.987, P < .001).
We first used a two-tailed paired t test to compare the means of NPC between 7 AM and 7 PM. In a linear regression model, we evaluated potential covariates that may significantly modulate NPC changes (age, sex, body mass index, contact lens use, average sleep duration from 7 days prior to the study, the time that the participant awoke during the test day, concussion history, and step counts between 7 AM and 7 PM). If significant, these factors were treated as covariates, and we estimated the changes in NPC between 7 AM and 7 PM in the regression model. Statistical analysis was conducted with SAS software (version 9.4 for Windows; SAS Institute, Inc., Cary, NC) and significance was set at a P value of less than .05.
Average sleep duration for a week prior to the study was 7.49 ± 0.70 hours. Average step counts between 7 AM and 7 PM were 9,037.3 ± 2,577.1 steps. There was a significant time-of-day effect on the ocular-motor function, where NPC at 7 PM (6.35 ± 2.37 cm) significantly worsened compared to 7 AM (5.27 ± 2.00 cm, t(32) = 4.95, P < .001), with a mean difference of 1.08 cm, 95% CI (1.49, 0.68). In a linear regression model, after adjusting for a significant covariate (contact lens use), an estimated difference between 7 PM and 7 AM was 0.70 ± 0.98 cm, t(29) = 3.15, P = .0039 (Figure 1).
Near point of convergence (NPC) at 7 AM and 7 PM. (A) Average NPC with standard deviation. (B) Relative change in NPC at 7 PM compared to the baseline (7 AM).
The current brief report demonstrates that NPC values significantly worsened following a 12-hour period of routine daily neural fatigue. This finding remains consistent with previous sleep science literature in that neural fatigue induced by prolonged periods of wakefulness results in the impairment of ocular-motor functions including saccades and smooth pursuit.13 Our data indicate that NPC was able to detect a subtle but significant neural fatigue after a 12-hour wakeful period. Because patients with a concussion experience a 300% increase in NPC (Table A, available in the online version of this article),5,7,15,16 the subtle NPC difference between morning and night (13% change) would not influence an accurate concussion diagnosis. Therefore, it is important to emphasize that, although the increase in NPC scores at 7 PM was statistically significant, a 0.7 cm change is not clinically meaningful, especially in the context of acute concussion diagnosis. Instead, our data are highly relevant to the return-to-play decision-making process. As NPC distance trends to baseline over time, clinicians should consider the temporal variability of NPC and exercise a careful interpretation of whether a subtle NPC increase during a patient's recovery course is due to neurotrauma or time-of-day variability. Our data suggest that magnitude of NPC worsening depends on individuals, but participants uniformly increased their NPC distances at nighttime.
Previous Reports on the Utility of Near Point of Convergence on Mild Traumatic Brain Injury
Two underlying mechanisms may explain our observation. First, as one's wakeful period prolongs, extraocular muscles experience fatigue and then become less sensitive to motor signals from ocular-motor nuclei pertaining to three cranial nerves: oculomotor (III), trochlear (IV), and abducens (VI).17 Various sleep-deprivation studies report that prolonged wakeful periods significantly reduce saccadic amplitude and velocity.18 Second, to focus one's gaze on a predictable moving target (ie, smooth pursuit, NPC), one must facilitate spatial and temporal prediction coupled with attention and anticipation. This connection between peripheral ocular-motor signaling and central neural processing in the brain, referred as a neuro-ophthalmologic circuitry, can be attenuated due to fatigue from sleep deprivation.19,20 These underlying mechanisms may not translate into our study design with the short wakeful period. On the other hand, our data suggest that NPC is able to detect the subtle ocular-motor perturbation even from mild neural fatigue, which has an immense scientific contribution to sports medicine clinical practice, especially to the return-to-play decision-making process as mentioned.
Several key limitations should be noted. The current study did not restrict cognitive activity between 7 AM and 7 PM, and thus it is plausible that cognitive fatigue might have influenced the observed NPC results at 7 PM. However, Cazzoli et al.21 suggested that an individual's visual fixation ability was unaffected by cognitive fatigue; therefore, we anticipate the effect of cognitive load on NPC to be minimal. In addition, a cross-sectional study from Yorke et al.22 indicated that although NPC assessments yielded a strong agreement between trials (ICC = 0.95, P < .001), a minimum detectable change with 95% confidence (MDC95) was 4 cm.22 This relatively large MDC95 value is partly due to NPC's large between-subject variability.23 Our study employed a pretest/posttest design coupled with various covariates, which enabled us to compare the nighttime NPC levels to an individual's baseline. Therefore, the MDC95 derived from a cross-sectional analysis may not be directly applicable to our findings, and thus caution is needed to contrast with normative studies if researchers employ a repeated measures study design, such as ours.
Implications for Clinical Practice
The data from this study underpin the sensitivity of NPC to neural fatigue from daily conscious activity. Our findings have an important implication, particularly for the return-to-play decision-making process, calling for a careful interpretation as to whether subtle NPC increases in the later phase of the recovery course are reflective of neural damage from a concussion or neural fatigue from daily conscious activity. Therefore, the data contribute to clinical practice by factoring the time-of-day variation, promoting accurate management and diagnosis of concussion.
- Master CL, Scheiman M, Gallaway M, et al. Vision diagnoses are common after concussion in adolescents. Clin Pediatr (Phila). 2016;55:260–267. doi:10.1177/0009922815594367 [CrossRef]
- Kontos AP, Elbin RJ, Schatz P, et al. A revised factor structure for the post-concussion symptom scale: baseline and postconcussion factors. Am J Sports Med. 2012;40:2375–2384. doi:10.1177/0363546512455400 [CrossRef]22904209
- Ellis MJ, Cordingley D, Vis S, Reimer K, Leiter J, Russell K. Vestibulo-ocular dysfunction in pediatric sports-related concussion. J Neurosurg Pediatr. 2015;16:248–255. doi:10.3171/2015.1.PEDS14524 [CrossRef]26031619
- Capó-Aponte JE, Beltran TA, Walsh DV, Cole WR, Dumayas JY. Validation of visual objective biomarkers for acute concussion. Mil Med. 2018;183(suppl 1):9–17. doi:10.1093/milmed/usx166 [CrossRef]29635572
- Mucha A, Collins MW, Elbin RJ, et al. A brief Vestibular/Ocular Motor Screening (VOMS) assessment to evaluate concussions: preliminary findings. Am J Sports Med. 2014;42:2479–2486. doi:10.1177/0363546514543775 [CrossRef]25106780
- Pearce KL, Sufrinko A, Lau BC, Henry L, Collins MW, Kontos AP. Near point of convergence after a sport-related concussion: measurement reliability and relationship to neurocognitive impairment and symptoms. Am J Sports Med. 2015;43:3055–3061. doi:10.1177/0363546515606430 [CrossRef]26453625
- Cheever KM, McDevitt J, Tierney R, Wright WG. Concussion recovery phase affects vestibular and oculomotor symptom provocation. Int J Sports Med. 2018;39:141–147. doi:10.1055/s-0043-118339 [CrossRef]
- Howell DR, O'Brien MJ, Raghuram A, Shah AS, Meehan WP 3rd, . Near point of convergence and gait deficits in adolescents after sport-related concussion. Clin J Sport Med. 2018;28:262–267. doi:10.1097/JSM.0000000000000439 [CrossRef]
- Kawata K, Rubin LH, Lee JH, et al. Association of football subconcussive head impacts with ocular near point of convergence. JAMA Ophthalmol. 2016;134:763–769. doi:10.1001/jamaophthalmol.2016.1085 [CrossRef]27257799
- Kawata K, Tierney R, Phillips J, Jeka JJ. Effect of repetitive subconcussive head impacts on ocular near point of convergence. Int J Sports Med. 2016;37:405–410. doi:10.1055/s-0035-1569290 [CrossRef]26859643
- Zonner S, Ejima K, Fulgar CC, et al. Oculomotor response to cumulative subconcussive head impacts in high school football players: a pilot longitudinal study [published online ahead of print December 20, 2018]. JAMA Ophthalmol. doi:10.1001/jamaophthalmol.2018.6193 [CrossRef]
- Fimm B, Blankenheim A. Effect of sleep deprivation and low arousal on eye movements and spatial attention. Neuropsychologia. 2016;92:115–128. doi:10.1016/j.neuropsychologia.2016.03.021 [CrossRef]27018452
- Maruta J, Heaton KJ, Maule AL, Ghajar J. Predictive visual tracking: specificity in mild traumatic brain injury and sleep deprivation. Mil Med. 2014;179:619–625. doi:10.7205/MILMED-D-13-00420 [CrossRef]24902128
- Sadeh A, Sharkey KM, Carskadon MA. Activity-based sleep-wake identification: an empirical test of methodological issues. Sleep. 1994;17:201–207. doi:10.1093/sleep/17.3.201 [CrossRef]7939118
- Matuseviciene G, Johansson J, Moller M, Godbolt AK, Pansell T, Deboussard CN. Longitudinal changes in oculomotor function in young adults with mild traumatic brain injury in Sweden: an exploratory prospective observational study. BMJ Open. 2018;8:e018734. doi:10.1136/bmjopen-2017-018734 [CrossRef]29431132
- Capo-Aponte JE, Beltran TA, Walsh DV, Cole WR, Dumayas JY. Validation of visual objective biomarkers for acute concussion. Mil Med. 2018;183(suppl 1):9–17. doi:10.1093/milmed/usx166 [CrossRef]29635572
- Connell CJ, Thompson B, Kuhn G, Claffey MP, Duncan S, Gant N. Fatigue related impairments in oculomotor control are prevented by caffeine. Sci Rep. 2016;6:26614. doi:10.1038/srep26614 [CrossRef]27222342
- Zils E, Sprenger A, Heide W, Born J, Gais S. Differential effects of sleep deprivation on saccadic eye movements. Sleep. 2005;28:1109–1115. doi:10.1093/sleep/28.9.1109 [CrossRef]16268380
- Kettner RE, Leung HC, Peterson BW. Predictive smooth pursuit of complex two-dimensional trajectories in monkey: component interactions. Exp Brain Res. 1996;108:221–235. doi:10.1007/BF00228096 [CrossRef]8815031
- Lisberger SG, Morris EJ, Tychsen L. Visual motion processing and sensory-motor integration for smooth pursuit eye movements. Annu Rev Neurosci. 1987;10:97–129. doi:10.1146/annurev.ne.10.030187.000525 [CrossRef]3551767
- Cazzoli D, Antoniades CA, Kennard C, Nyffeler T, Bassetti CL, Muri RM. Eye movements discriminate fatigue due to chronotypical factors and time spent on task: a double dissociation. PloS One. 2014;9:e87146. doi:10.1371/journal.pone.0087146 [CrossRef]
- Yorke AM, Smith L, Babcock M, Alsalaheen B. Validity and reliability of the vestibular/ocular motor screening and associations with common concussion screening tools. Sports Health. 2017;9:174–180. doi:10.1177/1941738116678411 [CrossRef]
- Abraham NG, Srinivasan K, Thomas J. Normative data for near point of convergence, accommodation, and phoria. Oman J Ophthalmol. 2015;8:14–18. doi:10.4103/0974-620X.149856 [CrossRef]25709268
Previous Reports on the Utility of Near Point of Convergence on Mild Traumatic Brain Injury
|Author||Subjects||Study Design||Key Findings|
|Mucha et al., 2014||64 athletes, age 13.9 ± 2.5 years||Cross-sectional||NPC distance was significantly greater in the concussed group compared with the control group (P < .001). Mean difference between groups was 4.0 cm (95% CI, 1.9 to 6.1 cm)|
|Anzalone et al., 2016||167 subjects, age 11 to 19 years||Retrospective chart review||CI failed to predict delayed concussion recovery (P = 1.07)|
|Capo-Aponte et al., 2017||500 U.S. military personnel||Retrospective chart review||NPC receded in blast-induced mTBI patients relative to normative values|
|Capo-Aponte et al., 2012||40 U.S. military personnel (20 with mTBI)||Cross-sectional||Blast-induced mTBI significantly receded NPC compared to military control subjects (P = .0003)|
|Cheever et al., 2017||89 athletes (31 with mTBI), age 17.8 to 25.2 years||Prospective repeated measures||NPC was significantly receded during initial visit in acute (DOI ≤ 10 days prior) and post-acute (DOI ≥ 16 days prior) mTBI athletes, and remained receded in the post-acute group during a 2-week follow-up|
|Ellis et al., 2017||399 athletes, age males 13.9 years, females 15.4 years||Retrospective review||Vestibulo-ocular dysfunction (including NPC) was significantly related to development of post-concussion syndrome|
|Ellis et al., 2015||101 athletes, age 14.2 ± 2.3 years||Retrospective review||Vestibulo-ocular dysfunction was prevalent in 28.6% and 62.5% of adolescents following sport-related concussion and post-concussion syndrome, respectively|
|Gallaway et al., 2017||218 mTBI patients, age 6 to 72 years||Retrospective chart review||CI was the most prevalent (47%) oculomotor deficit|
|Howell et al., 2017||64 adolescent athletes (33 with mTBI)||Cross-sectional||Patients with receded NPC (55%) had significantly slower gait speed and shorter stride length|
|Master et al., 2017||432 mTBI patients, age 5 to 18 years||Retrospective cohort||NPC was receded in 35% of patients|
|Pearce et al., 2015||78 athletes, age 14.31 ± 2.77 years||Cross-sectional||Patients with receded NPC (42%) exhibited significantly worse neurocognitive impairment and reported higher symptom scores versus those with normal NPC|
|Storey et al., 2017||275 patients, age 5 to 18 years||Retrospective cohort||Abnormal NPC at initial visit was not correlated to the duration (P = .69, Spearman rho) or use of intervention (P = 1.00, Wilcoxon rank sum) leading to recovery|
|Yorke et al., 2016||105 adolescents, age 15.4 years||Cross-sectional descriptive||NPC demonstrated an intraclass correlation of .95 (95% CI, 0.89 to 0.98, P < .001)|
|Kawata et al., 2016||29 NCAA D1 healthy football athletes||Prospective observational||Subconcussive head impacts resulted in a significant difference in NPC values between high impact vs low impact players across multiple time points|
|Kawata et al., 2016||20 healthy young adults, age controls = 18.9 years, heading = 20.7 years||Repeated measures||10 consecutive soccer headings significantly receded NPC values from baseline (P < .01) and was significantly different from kicking/control subjects (range: P < .01 to P < .001) at both time points post-intervention|
|McDevitt et al., 2016||72 active college student athletes (12 with mTBI), age 21.5 ± 3.4 years||Cross-sectional||NPC values were significantly correlated to participant health status (concussed vs non-concussed) (r = 0.337, P - .004)|
|Adler et al., 2007||51 healthy patients, age 6 to 30 years||Cross-sectional||Use of an accommodative ruler was more effective at detecting receded NPC values versus other methods (eg, pencil tip, fingertip) (P < .001)|
|Zonner et al., 2018||12 high school football players, age 16.4 ± 0.5 years||Prospective observational||Subconcussive head impacts impaired NPC by 33% up to midseason relative to head impact frequency and magnitudes|
|DuPrey et al., 2017||270 athletes, age 14.7 ± 2.0 years (range: 10 to 21 years)||Retrospective cohort study||Increased NPC at initial diagnosis was related to increased risk of prolonged concussion recovery|