CJSM Blog Journal Club — Preinjury & Postinjury Factors Predicting Recovery in Sports-related Concussions

The new year is upon us, and the first issue of the 2021 Clinical Journal of Sports Medicine has published.

There is much to commend in the issue.  It is always difficult to pick one manuscript among many to highlight in the CJSM Blog Journal club (that’s a good ‘problem’ to have).  

This month, our Jr. Associate Editor Jason L Zaremski, MD has decided to evaluate an original research article looking at pre- and post-injury risk factors that affect clinical recovery time in sport-related concussions.

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Jason L Zaremski, MD

Introduction:  As we finish up a fall sport season that has been like no other and begin 2021 with renewed spirit, the editors of CJSM and the CJSM blog journal club would like to take a moment to thank all of the health care professionals working tirelessly to keep all of our athletes, patients, support staff, and family members safe. We are proud of how the sports medicine community has conducted itself during this pandemic, and we are hopeful that vaccination will allow us to put this pandemic in the rear view mirror in the not-too-distant future.

To kick off 2021 we would like to review a wonderful manuscript from a team headed by Margot Putukian, M.D., past-president of the AMSSM, which analyzes preinjury and post-injury factors that predict sports-related concussion and clinical recovery time.

Purpose/Specific Aims:

1) The authors evaluated a possible relationship between preinjury risk factors (RFs) and resultant occurrence of concussion.

2) They also sought to examine whether preinjury RFs or post-injury assessments predicted clinical recovery in collegiate athletes

• defined as days until symptom-free (DUSF) and days until full return to play (DUFRTP)

Setting: Division 1University Student-Athletes (Ivy League)

Methods/Design: The study was approved by the Institutional Review Panel for Human Subjects Research at Princeton University. All participants provided written consent to participate. This is a prospective study with data collected before and after a sustained concussion.

Participants:  Male and female collegiate athletes participating in varsity sports and club rugby. Number of participants are different based on aim 1 versus 2 and are listed in the data section.

Initial baseline assessments included the following:

• 3^rd version of the Sports Concussion Assessment Tool (SCAT3)
  • Administered by a certified athletic trainer (ATC) or team physician
• Generalized Anxiety Disorder 7-item (GAD-7)
• Patient Health Questionnaire (PHQ-9)
• ImPACT (Neuropsychological computer assessment)
  • Also administered within 24-48 hours of injury by the ATC or research staff
• Self-reported history of concussion
• History of:
  • ADHD
  • Learning Disability (LD)
  • Headaches/migraines
  • Depression and anxiety

Baseline Data: Self-reported concussion history was available for 1147 athletes.

• (71.8%) reported no history of concussion
• 208 athletes (18.1%) reported 1 previous concussion
• 74 (6.4%) reported 2 previous concussions
• 38 (3.2%) reported a history of 3 or more concussions (range 3-5)
• Common self-reported health conditions included headache (6.9%),
• LD (2.8%)
• Depression or anxiety (3.0%)

After any sustained concussion, data collected also included:

• Occurrence of SRC
• Length of clinical recovery after SRC
• Post-Injury SCAT
• Neuropsychological computer assessment (ImPACT) within 24-48 hours of injury

Concussion Management:

• An initial period of brief relative rest (24-48 hours)
• Then, cognitive and physical activity were gradually introduced on a symptom-limited basis until full academic and sport participation was achieved.

Statistical Measures/Analysis:  As the authors described (and summarized from their manuscript), all analyses were conducted using IBM SPSS 24.  χ² analyses were calculated for the association between categorical variables and concussion diagnosis. Logistic regression was used to examine the variance associated with previously identified significant predictors of concussion diagnosis. t-tests or Mann–Whitney tests were used to examine group differences in continuous variables. Spearman correlations were used to examine the association between variables of interest and DUSF and DUFRTP. Partial Spearman correlations were used to assess the independent influence of behavioral measures. Significance was set at P < 0.01.

Results:

Aim 1: Predicting Prospective Concussion

152 athletes (69% male) at baseline and 145 (75% male) with baseline data were subsequently diagnosed with concussion. Average age is 19.42 ± 1.35 years. Mean time between baseline evaluation and injury varied widely [410.45 ± 332.43 days].  

Sports represented are listed in table 1 of the manuscript. Football, men’s rugby, women’s rugby, and men’s lacrosse accounted for nearly 43% of all participants.

• Concussion was not associated with sex, χ² = 2.71, P = 0.10] or age (P = 0.62) at baseline evaluation.
• Type of sport played was significantly associated with subsequent diagnosis of concussion.
• There was a main effect of sport type on concussion status (Wald = 44.79, P = 0.002).
• Men’s ice hockey players were significantly more likely to experience a concussion when compared with the rest of the sample, χ² = 22.16, P < 0.001.
• Non-significant trends indicated that athletes playing sprint (lightweight) football, χ² = 4.73, P = 0.03 and men’s rugby, χ² = 4.97, P = 0.03, were also more likely to subsequently receive a diagnosis of concussion.
• Self-reported concussion history was associated with subsequent occurrence of concussion (see table 2 of the manuscript for more detail) (χ² = 14.74, P = 0.001).
• Sport type (Wald = 40.29, P = 0.007) and concussion history (Wald = 9.91, P = 0.007) indicated that concussion history predicted a subsequent diagnosis of concussion even after considering concussion risk by sport type.
• No significance was found between acute concussion and baseline report of headache (χ² = 0.61, P = 0.44), depression or anxiety (χ² = 0.48, P = 0.49), or LD (χ² = 0.26, P = 0.61).

Aim 2: Predicting Recovery Time

All athletes evaluated for their first study-related concussion within 2 weeks of injury.  163 athletes were diagnosed with concussion with 25 of athletes lost to follow-up.  138 (34 female, 24.6%) athletes remained in the study until symptom resolution.  Athletes were 20.41 ± 1.41 years old.  Sports represented are listed in table 4 of the manuscript. Football, men’s ice hockey, and men’s rugby accounted for approximately 40% of all patients.

Previous Concussion History

• 41/138 (29.7%) history of 1 concussion
• 23/138  (16.7%) history of 2 or more previous concussions
• Mean time from concussion to post-injury SCAT3 testing was 0.83 ± 1.79 days (n = 138, range = 0-13 days) and to post-injury ImPACT testing was 2.48 ± 1.58 days (n = 123, range = 0-13 days)
• Mean time to symptom-free was 9.84 ± 11.11 days (n = 138, median = 5 days, range = 1-86)
• Mean time to DUFRTP was 20.21 ± 19.17 days (n = 98, median = 20.21, range = 4-150)

Baseline Predictors

• Days until symptom-free was correlated with DUFRTP (r_s = 0.75, P < 0.001).
• Neither DUSF or DUFRTP was associated with baseline age, sex, self-reported concussion history, headache history, screens for depression (PHQ-9) and anxiety (GAD-7), ImPACT performance indices, SCAT3 performance indices, or baseline symptom report (all P values > 0.05).

Post-injury Predictors (See Table 6 of the manuscript for further detail)

• ImPACT total symptom score (TSS) accounted for variance in DUSF symptom duration associated with reaction time (RT) and visual motor composites (r_s = 0.51, P < 0.001).
• Worse performance on the RT composite was associated with longer symptom duration (r_s = 0.20, P = 0.03).
• The relationship between ImPACT visual motor composite performance and symptom duration was no longer significant after accounting for ImPACT TSS (r_s = −0.15, P = 0.10).
• Post-injury DUSF was not significantly associated with other measures listed in Table 6 (all P values > 0.05).
• ImPACT TSS accounted for unique variance in DUFRTP after accounting for variance associated with RT and visual motor composites (r_s = 0.31, P = 0.004).
• Performance on the RR (r_s = 0.27, P = 0.01) and visual motor (r_s = −0.30, P = 0.006) composites were associated with length of DUFRTP after accounting for variance associated with ImPACT TSS.
• Days until full RTP was not significantly associated with other measures
• Post-injury ImPACT reports of headache (r_s = 0.35, P = 0.001), balance problems (r_s = 0.30, P = 0.004), dizziness (r_s = 0.28, P = 0.008), and difficulty concentrating (r_s = 0.29, P = 0.005) were associated with more DUFRTP.

Strengths:

• Well designed, large prospective study
• Well represented variety of sports (not just contact and collision sports) and both sexes
• Injury risk factor were assessed prospectively (as the authors wrote)

Weaknesses:

• The mean time between baseline evaluation and injury was 410.45 ± 332.43 days.  Consideration should be made to have an annual baseline evaluation to minimize time between baseline evaluation and injury to less than one year
• Small percentage of athletes that sustained concussion are females (34/138, 24.6%), though this is understandable given football is typically male only and accounted for a large number of the concussions.  
• AIM 2 had significantly less study size than AIM 1
• This data applies only to collegiate athletes. Would be interesting to see if this data is reproducible at the adolescent/HS level.
• As the authors wrote, there were a small number of participants that reported a history of headaches/migraines, LD, ADD/ADHD, depression, and anxiety. Further, there is no mention if these symptoms were treated (and could have affected the data/results).
• RFs were based on self-reporting instead of via confirmation by a health care professional
• This study analyzed Ivy league collegiate athletes (NCAA Division 1) and it is not known if the results would be reproducible for all collegiate athletes in other divisions and conferences.
• As the authors do disclose, with respect to football, the Ivy league rules limit the number of contact practice sessions during the competitive season. This practice is not consistent throughout the NCAA as the NCAA does not prescribe limits to the number of contact practices. This special characteristic of Ivy League football may explain why participation in the sport was not found to be a risk factor for subsequent diagnosis of concussion when compared to other contact or collision sports. Conversely, there are not restrictions in the Ivy league for contact practices for men’s icy hockey. Thus, repeating this study at other institutions outside the Ivy League comparing football and men’s ice hockey would be very interesting.

Conclusions:  This study indicates that certain sports as well as concussion history predicted subsequent occurrence of concussion. Additionally, no RFs or baseline measures predicted clinical recovery. However, symptom number and severity predicted longer clinical recovery.

Clinical Relevance:  The data indicate that in collegiate athletes, the average time until symptoms free is about 10 days and return to play is about 3 weeks. Further, playing men’s ice hockey as well as spring football and rugby was associated with concussion diagnosis as well as self-reported history of concussion. Further, RT and visual motor composites on ImPACT provide significant indicators to sports medicine team members for DUSF/DUFRTP. Finally, symptoms of headache, balance problems, dizziness, and difficulty concentrating are associated with DUFRTP. This information will provide guidance to sports medicine team members in patients that either participate in the above sports and/or have symptoms mentioned above that will provide guidance on duration of return to play.