Reference/Citation: Hamstra-Wright KL, Bliven KC, Bay C. Risk factors for medial tibial stress syndrome in physically active individuals such as runners and military personnel: a systematic review and meta-analysis. Br J Sports Med. 2015;49(6):362-369.Clinical Question: What factors put physically active individuals at risk to develop medial tibial stress syndrome (MTSS)?Data Sources: The authors performed a literature search of CINAHL, the Cochrane Central Register of Controlled Trials, EMBASE, and MEDLINE from each database's inception to July 2013. The following key words were used together or in combination: armed forces, athlete, conditioning, disorder predictor, exercise, medial tibial stress syndrome, militaries, MTSS, military, military personnel, physically active, predictor, recruit, risk, risk characteristic, risk factor, run, shin pain, shin splints, and vulnerability factor.Study Selection: Studies were included in this systematic review based on the following criteria: original research that (1) investigated risk factors associated with MTSS, (2) compared physically active individuals with and without MTSS, (3) was printed in English, and (4) was accessible in full text in peerreviewed journals.Data Extraction: Two authors independently screened titles or abstracts (or both) of studies to identify inclusion criteria and quality. If the article met the inclusion criteria, the authors extracted demographic information, study design and duration, participant selection, MTSS diagnosis, investigated risk factors, mean difference, clinical importance, effect size, odds ratio, and any other data deemed relevant. After the data extraction was complete, the authors compared findings for accuracy and completeness. When the mean and standard deviation of a particular risk factor were reported 3 or more times, that risk factor was included in the meta-analysis. In addition, the methodologic quality was assessed with an adapted checklist developed by previous researchers. The checklist contained 5 categories: study objective, study population, outcome measurements, assessment of the outcome, and analysis and data presentation. Any disagreement between the authors was discussed and resolved by consensus.Main Results: A total of 165 papers were initially identified, and 21 original research studies were included in this systematic review. More than 100 risk factors were identified in the 21 studies. Continuous data were reported 3 or more times for risk factors of body mass index (BMI), navicular drop, ankle plantarflexion range of motion (ROM), ankle-dorsiflexion ROM, ankleeversion ROM, ankle-inversion ROM, quadriceps angle, hip internal-rotation ROM, and hip external-rotation ROM. As compared with the control group, significant risk factors for developing MTSS identified in the literature were (1) Conclusions: The primary factors that appeared to put a physically active individual at risk for MTSS were increased BMI, increased navicular drop, greater ankle plantar-flexion ROM, and greater hip external-rotation...
Artificial intelligence methods are being applied broadly in society and increasingly in health care and research. Machine learning, a subset of artificial intelligence, represents the study of algorithms that improve automatically with experience. This article provides a basic overview of artificial intelligence, machine learning categories, common applications in the business sphere, advantages and disadvantages of using this technology, and example applications in rehabilitation and other fields for contextual purposes. The study and implementation of machine learning and artificial intelligence can function to improve patient care and represents a burgeoning area of research.
Introduction We provide an updated analysis of data about U.S. Physical Medicine and Rehabilitation (PM&R) residency program applicants collected by the National Resident Matching Program (NRMP). Objective Analyze trends within NRMP data for PM&R residency match rates, compare matched to unmatched applicants, and compare PM&R applicants to other medical specialties. Design Secondary analysis of NRMP data. Setting NRMP data set. Participants Residency program applicants who participated in the NRMP Match, 2007 to 2018. Interventions Not applicable. Main Outcome Measures Number of applicants, match rates, difference in characteristics including rank order list (ROL), U.S. Medical Licensing Examination (USMLE) Step 1 and Step 2 Clinical Knowledge (CK) scores, publications, Alpha Omega Alpha (AOA) status, PhD degree, and experiences in research, volunteer, and work. Results Number of applicants and residency positions increased from 2007 to 2018. Length of ROL increased and was longer for matched compared to unmatched applicants, with maximum mean difference of 7.4 in 2016 (95% confidence interval [CI] 5.6‐9.2). Matched U.S. Allopathic Seniors had higher USMLE scores compared to unmatched, with a mean difference of 12.7 for Step 1 (95% CI 8.3‐17.0) and 12.6 (95% CI 8.6‐16.6) for Step 2 CK (P < .001). Number of publications and volunteer experiences were higher for matched U.S. Allopathic Seniors (0.64, 95% CI 0.09‐1.2 and 1.5, 95% CI 0.65‐2.3, respectively). PM&R USMLE Step 1 and 2 CK scores increased at a significantly faster rate than for all other specialties, with estimated rate differences of 0.46 (95% CI 0.21‐0.71) and 0.69 (95% CI 0.45‐0.93) points per year, respectively. Conclusions PM&R residency has become more competitive. USMLE Step 1 and 2 CK scores have outpaced the inflation of scores in other specialties. ROL length has increased, suggesting more ranked programs to successfully match. These analyses update our knowledge about PM&R residency applicants and suggest surrogate markers for a successful match.
In persons with spinal cord injury (SCI), osteoporosis and associated fragility fractures are a prevalent phenomenon with clinically meaningful morbidity and mortality. Prevention of osteoporosis utilizing both physical modalities and pharmacological therapies is an area of high-clinical importance. In our perspective, the current body of research cannot provide clear guidance on prophylactic interventions to prevent osteoporosis specifically to stratify SCI subjects to their risk for fragility fractures. Without this critical research, clinicians cannot weigh the risk versus benefits of interventions, such as bisphosphonates, which is not a benign treatment. Other treatments such as physical modalities provide little risk and have other therapeutic benefit. This perspective is an argument that the current research does not indicate prophylactic pharmacological intervention to prevent osteoporosis in the SCI population.
Chronic pain is pain that lasts for more than 3-6 months. It is a complex health condition that is difficult to treat. Chronic pain is stressful, and can lead to serious and costly physical and mental health problems. Many people affected by chronic pain can become addicted to pain medications, like opioids. It can also lead to depression and loss of income from days out of work. The most common causes are low back pain, arthritis, and headaches. About 40% of the United States population has chronic pain. Of these, 38% of people use complementary and integrative medicine (CIM) approaches to cope with their pain. 1 People use CIM for pain relief and to reduce the side effects of pain medications. CIM is not a typical medical treatment, so it is not regulated by medical or health care institutes. Common CIM approaches are available in our communities though drugstores, supermarkets, health spas, gyms, and private clinics.The goals of CIM therapies are to reduce pain and control the body's response to pain. It also decreases how much pain interferes with everyday life. People use CIM approaches along with usual medical treatments. Hence, these approaches are integrative. CIM is not recommended as a replacement for usual medical care.This guide provides a brief outline of the most common CIM approaches to manage chronic pain that are not nutritional supplements. This guide does not evaluate the usefulness of these CIM approaches. You should talk to your doctor to find out if any CIM approaches may help you. Be aware that your insurance may not pay for these CIM approaches. Contact your health care provider to learn more about the options of including CIM into your treatment plan. Some common CIM approaches that are used for chronic pain are listed below. Many of these approaches are used in combination with other rehabilitation therapies.
Aim: Evidence of factors explaining sports-related concussion (SRC) risk and recovery among high school athletes remains inconclusive. Materials & methods: Prospective study of a real-world sample of high school athletes (n = 77) who sustained ≤1 SRC. Among those with multiple SRCs, recovery time between events was investigated. To investigate concussion risk, baseline characteristics of athletes with a single versus multiple SRC(s) were compared. Results: Recovery time did not differ across events. There were no differences between those with a single versus multiple SRCs. Conclusion: Recovery time between initial and subsequent concussive events did not differ, suggesting that prior concussion may not prolong recovery. Baseline characteristics did not explain heightened concussion risk. Investigation of these relationships using more representative samples is needed.
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