Identifying and Minimizing Incentives for Competing Interests in Sports Medicine Publications

Academics in sports medicine as well as other medical fields are generally expected to publish research and opinions in peer-reviewed journals. The peer-review process is intended to protect against the publication of flawed research and unsubstantiated claims. However, both financial and non-financial competing interests may result in sub-optimal results by affecting investigators, editors, peer reviewers, academic institutions, and publishers. In this article, we focus on the non-financial competing interests created in our current academic system. Because these competing interests are embedded in our current scholastic framework, the potential biases are difficult to quantify. To minimize the effect of these competing interests, we review and highlight some underlying incentives for each stakeholder and some potential solutions to mitigate their effects.

Identifiability of causal effects in test-negative design studies

Causal directed acyclic graphs (DAGs) are often used to select variables in a regression model to identify causal effects. Outcome-based sampling studies, such as the 'test-negative design' used to assess vaccine effectiveness, present unique challenges that are not addressed by the common back-door criterion. Here we discuss intuitive, graphical approaches to explain why the common back-door criterion cannot be used for identification of population average causal effects with outcome-based sampling studies. We also describe graphical rules that can be used instead in outcome-based sampling studies when the objective is limited to determining if the causal odds ratio is identifiable, and illustrate recent changes to the free online software Dagitty which incorporate these principles.

SARS-CoV-2 seroprevalence among healthcare workers

Background

Monitoring COVID-19 infection risk among health care workers (HCWs) is a public health priority. We examined the seroprevalence of SARS-CoV-2 among HCWs following the fall infection surge in Minnesota, and before and after COVID-19 vaccination. Additionally, we assessed demographic and occupational risk factors for SARS-CoV-2 infection.

Methods

We conducted two rounds of seroprevalence testing among a cohort of HCWs: samples in round 1 were collected from 11/22/20–02/21/21 and in round 2 from 12/18/20–02/15/21. Demographic and occupational exposures assessed with logistic regression were age, sex, healthcare role and setting, and number of children in the household. The primary outcome was SARS-CoV-2 IgG seropositivity. A secondary outcome, SARS-CoV-2 infection, included both seropositivity and self-reported SARS-CoV-2 test positivity.

Results

In total, 459 HCWs were tested. 43/454 (9.47%) had a seropositive sample 1 and 75/423 (17.7%) had a seropositive sample 2. By time of sample 2 collection, 54% of participants had received at least one vaccine dose and seroprevalence was 13% among unvaccinated individuals. Relative to physicians, the odds of SARS-CoV-2 infection in other roles were increased (Nurse Practitioner: OR[95%CI] 1.93[0.57,6.53], Physician’s Assistant: 1.69[0.38,7.52], Nurse: 2.33[0.94,5.78], Paramedic/EMTs: 3.86[0.78,19.0], other: 1.68[0.58,4.85]). The workplace setting was associated with SARS-CoV-2 infection (p = 0.04). SARS-CoV-2 seroprevalence among HCWs reporting duties in the ICU vs. those working in an ambulatory clinic was elevated: OR[95%CI] 2.17[1.01,4.68].

Conclusions

SARS-CoV-2 seroprevalence in HCW increased during our study period which was consistent with community infection rates. HCW role and setting—particularly working in the ICU—is associated with higher risk for SARS-CoV-2 infection.

In suspected SARS-CoV-2, rapid antigen detection tests had 67% to 73% sensitivity and 98% to 100% specificity

Favresse J, Gillot C, Oliveira M, et al. Head-to-head comparison of rapid and automated antigen detection tests for the diagnosis of SARS-CoV-2 infection. J Clin Med. 2021;10:265. 33450853.

SARS-CoV-2 Screening Among Symptom-Free Healthcare Workers

Background

Transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is possible among symptom-free individuals and some patients are avoiding medically necessary healthcare visits for fear of becoming infected in the healthcare setting. Limited data are available on the point prevalence of SARS-CoV-2 infection in symptom-free U.S. healthcare workers (HCW).

Methods

A cross-sectional convenience sample of symptom-free HCWs from the metropolitan area surrounding Minneapolis and St. Paul, Minnesota was enrolled between April 20 ^th and June 24 ^th , 2020. A participant self-collected nasopharyngeal swab (NPS) was obtained. SARS-CoV-2 infection was assessed via polymerase chain reaction. Participants were queried about their willingness to repeat a self-collection NPS for diagnostic purposes. We had >95% power to detect at least one positive test if the true underlying prevalence of SARS-CoV2 was ≥1%.

Results

Among n=489 participants 80% were female and mean age±SD was 41±11. Participants reported being physicians (14%), nurse practitioners (8%), physician's assistants (4%), nurses (51%), medics (3%), or other which predominantly included laboratory technicians and administrative roles (22%). Exposure to a known/suspected COVID-19 case in the 14 days prior to enrollment was reported in 40% of participants. SARS-CoV-2 was not detected in any participant. Over 95% of participants reported a willingness to repeat a self-collected NP swab in the future.

Conclusions

The point prevalence of SARS-CoV-2 infection was likely <1% in a convenience sample of symptom-free Minnesota healthcare workers from April 20 ^th and June 24 ^th , 2020. Self-collected NP swabs are well-tolerated and a viable alternative to provider-collected swabs to preserve PPE.

The Inability to Calculate Predictive Values: an Old Problem that Has Not Gone Away

BACKGROUND

Previous studies suggest that many physicians and medical trainees have trouble calculating the probability that a patient has a condition, also known as the predictive value.

ACTIVITY

Two questions from the medical literature were administered to medical students, residents (post-medical school), fellows (post-residency), and faculty physicians.

RESULTS

Only 6% answered both questions correctly. Most commonly, the participants grossly overestimated the probability of disease.

DISCUSSION

Physicians still struggle with the ability to calculate predictive values, a skill that affects all branches of medicine and will become more consequential as new tests are administered to patients at low risk for disease.

Risk Factor Reversal in Studies of Infectious Disease: Making Counterintuitive Results Intuitive Again

A previously published study reported the seemingly paradoxical finding that men who have sex with men status was strongly protective and recent sexual abstinence strongly deleterious in relation to mortality prognosis. We explain why these results are entirely logical and that the counterintuitive direction of the effects derives from the comparison group implied by the study design.

Bone geometry and lower extremity bone stress injuries in male runners

Bone stress injuries (BSI) are common among distance runners and research investigations examining risk factors for BSI among men are limited. Therefore, investigations are needed to determine if men with a history of BSI have skeletal properties that may heighten BSI incidence.

OBJECTIVES

To analyze differences in bone density, bone geometry, and estimates of bone strength in male runners with and without a BSI history.

DESIGN

Cross-sectional.

METHODS

We recruited 36 male distance runners ages 18-41 for this study. We used peripheral quantitative computed tomography (pQCT) to assess volumetric bone mineral density (vBMD, mg/mm³), bone geometry (total and cortical bone area, mm²), tibia robustness (total area/tibia length, mm) and estimates of bone strength (section modulus and polar strength-strain index, mm³) at 5 tibial sites.

RESULTS

After adjusting for age, the BSI group had more slender tibias (9%), lower stress strain indices (-16%), lower section moduli (-17%) and smaller total cross-sectional (-11%) and cortical areas (-12%) at the 66% site of the tibia compared with controls (P < 0.05 for all). Similar differences were found at all other measurement sites. After adjusting for body size, differences in bone outcomes remained significant at the 66% site.

CONCLUSIONS

These results indicate that men with a history of BSI have lower estimated bending strength compared to controls because of narrower tibias. However, differences are largely attenuated in the distal ½ of the tibia after adjusting for body size. Thus, smaller tibia size, particularly at the mid-diaphysis, may be an important indicator for BSI incidence.

Investigating and Remediating Selection Bias in Geriatrics Research: The Selection Bias Toolkit

OBJECTIVES

Selection bias is a well-known concern in research on older adults. We discuss two common forms of selection bias in aging research: (1) survivor bias and (2) bias due to loss to follow-up. Our objective was to review these two forms of selection bias in geriatrics research. In clinical aging research, selection bias is a particular concern because all participants must have survived to old age, and be healthy enough, to take part in a research study in geriatrics.

DESIGN

We demonstrate the key issues related to selection bias using three case studies focused on obesity, a common clinical risk factor in older adults. We also created a Selection Bias Toolkit that includes strategies to prevent selection bias when designing a research study in older adults and analytic techniques that can be used to examine, and correct for, the influence of selection bias in geriatrics research.

RESULTS

Survivor bias and bias due to loss to follow-up can distort study results in geriatric populations. Key steps to avoid selection bias at the study design stage include creating causal diagrams, minimizing barriers to participation, and measuring variables that predict loss to follow-up. The Selection Bias Toolkit details several analytic strategies available to geriatrics researchers to examine and correct for selection bias (eg, regression modeling and sensitivity analysis).

CONCLUSION

The toolkit is designed to provide a broad overview of methods available to examine and correct for selection bias. It is specifically intended for use in the context of aging research. J Am Geriatr Soc 67:1970-1976, 2019.

Causal inference for clinicians

Evidence-based medicine (EBM) calls on clinicians to incorporate the 'best available evidence' into clinical decision-making. For decisions regarding treatment, the best evidence is that which determines the causal effect of treatments on the clinical outcomes of interest. Unfortunately, research often provides evidence where associations are not due to cause-and-effect, but rather due to non-causal reasons. These non-causal associations may provide valid evidence for diagnosis or prognosis, but biased evidence for treatment effects. Causal inference aims to determine when we can infer that associations are or are not due to causal effects. Since recommending treatments that do not have beneficial causal effects will not improve health, causal inference can advance the practice of EBM. The purpose of this article is to familiarise clinicians with some of the concepts and terminology that are being used in the field of causal inference, including graphical diagrams known as 'causal directed acyclic graphs'. In order to demonstrate some of the links between causal inference methods and clinical treatment decision-making, we use a clinical vignette of assessing treatments to lower cardiovascular risk. As the field of causal inference advances, clinicians familiar with the methods and terminology will be able to improve their adherence to the principles of EBM by distinguishing causal effects of treatment from results due to non-causal associations that may be a source of bias.

Paediatric obesity appears to lower the risk of diabetes if selection bias is ignored

BACKGROUND

Frustrated with the onslaught of articles reporting fascination with results that appear paradoxical but are merely due to selection bias, we studied the apparent effect of obesity on diabetes risk in youth who had a test for diabetes. We hypothesised that obese subjects would have lower rates of diabetes than non-obese subjects due to selection bias, and consequently, obesity would appear to lower the risk of diabetes.

METHODS

Retrospective cohort study of children (4-9 years), pre-teens (10-12 years) and teenagers (13-19 years). Participation was restricted to those who had a test of haemoglobin A1C along with measured height and weight. Body mass index percentile via the Centers for Disease Control and Prevention age and sex standards was calculated and categorised. The main outcome was A1C%, subsequently categorised at the level for diagnosis of diabetes mellitus (≥6.5%).

RESULTS

The sample consisted of 134 (2%) underweight, 1718 (30%) healthy weight, 660 (12%) overweight and 3190 (56%) obese individuals. 16% (n=936) had an A1C≥6.5%. Overall, healthy weight children had 8.2 times the risk of A1C≥6.5% (95% CI 5.3 to 12.7) compared with those in the obese category. The relative risk was 13 in pre-teens (95% CI 8.5 to 20.0) and 3.9 in teenagers (95% CI 3.3 to 4.7).

CONCLUSIONS

Healthy weight was associated with a 4-13 times higher relative risk of diabetes mellitus compared with being obese. While apparently shocking, the study's fatal flaw (selection bias) explains the 'paradoxical' finding. Ignoring selection bias can delay advances in medical science.

Effectively engaging patients in everyday health-care decisions

You can improve health outcomes and patient satisfaction--without increasing the length of the patient visit--by employing the tenets of shared decision-making.

Healthy Eating and Activity Across the Lifespan (HEAL): A call to action to integrate research, clinical practice, policy, and community resources to address weight-related health disparities

Despite intense nationwide efforts to improve healthy eating and physical activity across the lifespan, progress has plateaued. Moreover, health inequities remain. Frameworks that integrate research, clinical practice, policy, and community resources to address weight-related behaviors are needed. Implementation and evaluation of integration efforts also remain a challenge. The purpose of this paper is to: (1) Describe the planning and development process of an integrator entity, HEAL (Healthy Eating and Activity across the Lifespan); (2) present outcomes of the HEAL development process including the HEAL vision, mission, and values statements; (3) define the planned integrator functions of HEAL; and (4) describe the ongoing evaluation of the integration process. HEAL team members used a theoretically-driven, evidence-based, systemic, twelve-month planning process to guide the development of HEAL and to lay the foundation for short- and long-term integration initiatives. Key development activities included a review of the literature and case studies, identifying guiding principles and infrastructure needs, conducting stakeholder/key informant interviews, and continuous capacity building among team members. Outcomes/deliverables of the first year of HEAL included a mission, vision, and values statements; definitions of integration and integrator functions and roles; a set of long-range plans; and an integration evaluation plan. Application of the HEAL integration model is currently underway through community solicited initiatives. Overall, HEAL aims to lead real world integrative work that coalesce across research, clinical practice, and policy with community resources to inspire a culture of health equity aimed at improving healthy eating and physical activity across the lifespan.

Statistical testing of baseline differences in sports medicine RCTs: a systematic evaluation

Background/Aim

The CONSORT (Consolidated Standards of Reporting Trials) statement discourages reporting statistical tests of baseline differences between groups in randomised controlled trials (RCTs). However, this practice is still common in many medical fields. Our aim was to determine the prevalence of this practice in leading sports medicine journals.

Methods

We conducted a comprehensive search in Medline through PubMed to identify RCTs published in the years 2005 and 2015 from 10 high-impact sports medicine journals. Two reviewers independently confirmed the trial design and reached consensus on which articles contained statistical tests of baseline differences.

Results

Our search strategy identified a total of 324 RCTs, with 85 from the year 2005 and 239 from the year 2015. Overall, 64.8% of studies (95% CI (59.6, 70.0)) reported statistical tests of baseline differences; broken down by year, this percentage was 67.1% in 2005 (95% CI (57.1, 77.1)) and 64.0% in 2015 (95% CI (57.9, 70.1)).

Conclusions

Although discouraged by the CONSORT statement, statistical testing of baseline differences remains highly prevalent in sports medicine RCTs. Statistical testing of baseline differences can mislead authors; for example, by failing to identify meaningful baseline differences in small studies. Journals that ask authors to follow the CONSORT statement guidelines should recognise that many manuscripts are ignoring the recommendation against statistical testing of baseline differences.

What Definition Is Used to Describe Second Impact Syndrome in Sports? A Systematic and Critical Review

Concern about what has been termed, "second impact syndrome" (SIS) is a major factor determining return-to-play decisions after concussion. However, definitions of SIS vary. We used Scopus to conduct a systematic review and categorize the definitions used to describe SIS. Of the 91 sources identified, 79 (87%) clearly specified that SIS involved either cerebral edema or death after a concussion when a prior concussion had not resolved. Twelve articles (13%) could be interpreted as merely the events of two consecutive concussions. Among the articles that listed mortality rates, nearly all (33/35, 94%) said the rate of death was "high" (e.g., 50% to 100%). Our review found that most articles define SIS as a syndrome requiring catastrophic brain injury after consecutive concussive episodes. Given that it is unclear how common it is to have a second concussion while not fully recovered from a first concussion, the actual mortality rate of SIS is unknown.

Bone strength estimates relative to vertical ground reaction force discriminates women runners with stress fracture history

PURPOSE

To determine differences in bone geometry, estimates of bone strength, muscle size and bone strength relative to load, in women runners with and without a history of stress fracture.

METHODS

We recruited 32 competitive distance runners aged 18-35, with (SFX, n=16) or without (NSFX, n=16) a history of stress fracture for this case-control study. Peripheral quantitative computed tomography (pQCT) was used to assess volumetric bone mineral density (vBMD, mg/mm³), total (ToA) and cortical (CtA) bone areas (mm²), and estimated compressive bone strength (bone strength index; BSI, mg/mm⁴) at the distal tibia. ToA, CtA, cortical vBMD, and estimated strength (section modulus; Zp, mm³ and strength strain index; SSIp, mm³) were measured at six cortical sites along the tibia. Mean active peak vertical (pkZ) ground reaction forces (GRFs), assessed from a fatigue run on an instrumented treadmill, were used in conjunction with pQCT measurements to estimate bone strength relative to load (mm²/N∗kg^-1) at all cortical sites.

RESULTS

SSIp and Zp were 9-11% lower in the SFX group at mid-shaft of the tibia, while ToA and vBMD did not differ between groups at any measurement site. The SFX group had 11-17% lower bone strength relative to mean pkZ GRFs (p<0.05).

CONCLUSION

These findings indicate that estimated bone strength at the mid-tibia and mean pkZ GRFs are lower in runners with a history of stress fracture. Bone strength relative to load is also lower in this same region suggesting that strength deficits in the middle 1/3 of the tibia and altered gait biomechanics may predispose an individual to stress fracture.

SCAT3 assessment of non-head injured and head injured athletes competing in a large international youth soccer tournament

To our knowledge, no study has evaluated Sideline Concussion Assessment Tool -3rd Edition (SCAT3) scores during competition in athletes who have not had a head injury. The purpose of our pilot study was to compare SCAT3 scores in non-injured (NI), injured (but not head injured) (I), and head injured (HI) youth soccer players during competition and to establish preliminary baseline data for non-head injured athletes in a competitive setting. The HI group demonstrated significantly more symptoms (M = 9.7, SE = 0.8) than the I and NI (3.3, SE = 1.2, and 3.2, SE = 0.7, respectively) groups. The HI group also demonstrated a significantly higher symptom severity score (25.3, SE = 2.8) than the I and NI groups (7.7, SE = 4.1, and 5.9, SE = 2.5, respectively). There were no statistically significant differences in mean total Standardized Assessment of Concussion (SAC) scores and mean subsection SAC scores between the groups. Clinicians should also be aware that non-injured in-competition athletes may report more symptoms on the SCAT3 than those evaluated in a non-competition setting.

A multistate framework for the analysis of subsequent injury in sport (M-FASIS)

Physical activity is beneficial for many aspects of health but is associated with a risk of injury. Studies that assess causal risk factors of injury and reinjury provide valuable information to help develop and improve injury prevention programs. However, the underlying assumptions of analytical approaches often used to estimate causal factors in injury and subsequent injury research are often violated. This means that ineffective or even harmful interventions could be proposed because the underlying analyses produced unreliable or invalid causal effect estimates. We describe an adapted version of the multistate framework [multistate framework for the analysis of subsequent injury in sport (M-FASIS)] that makes investigator choices more transparent with respect to outcome and healing time. In addition, M-FASIS incorporates all previous sport injury analytical frameworks and accounts for injuries or conditions that heal or do not heal to 100%, acute and overuse injuries, illnesses, and competing event outcomes.