| Literature DB >> 23486209 |
David W Keeley1, Gretchen D Oliver, Christopher P Dougherty.
Abstract
Previous work has postulated that shoulder pain may be associated with increases in both peak shoulder anterior force and peak shoulder proximal force. Unfortunately these relationships have yet to be quantified. Thus, the purpose of this study was to associate these kinetic values with reported shoulder pain in youth baseball pitchers. Nineteen healthy baseball pitchers participated in this study. Segment based reference systems and established calculations were utilized to identify peak shoulder anterior force and peak shoulder proximal force. A medical history questionnaire was utilized to identify shoulder pain. Following collection of these data, the strength of the relationships between both peak shoulder anterior force and peak shoulder proximal force and shoulder pain were analyzed. Although peak anterior force was not significantly correlated to shoulder pain, peak proximal force was. These results lead to the development of a single variable logistic regression model able to accurately predict 84.2% of all cases and 71.4% of shoulder pain cases. This model indicated that for every 1 N increase in peak proximal force, there was a corresponding 4.6% increase in the likelihood of shoulder pain. The magnitude of peak proximal force is both correlated to reported shoulder pain and capable of being used to accurately predict the likelihood of experiencing shoulder pain. It appears that those pitchers exhibiting high magnitudes of peak proximal force are significantly more likely to report experiencing shoulder pain than those who generate lower magnitudes of peak proximal force.Entities:
Keywords: baseball; injury; kinetics; youth
Year: 2012 PMID: 23486209 PMCID: PMC3590837 DOI: 10.2478/v10078-012-0059-8
Source DB: PubMed Journal: J Hum Kinet ISSN: 1640-5544 Impact factor: 2.193
Description of bony landmarks palpated and digitized in the current study
| Bony Landmarks | Bony Process Palpated and Digitized |
|---|---|
| Seventh Cervical Vertebra (C7) | Most dorsal aspect of the spinous process |
| Eighth Thoracic Vertebra (T8) | Most dorsal aspect of the spinous process |
| Suprasternal Notch | Most cranial aspect of the sternum |
| Medial Epicondyle | Most distal/medial aspect of the condyle |
| Lateral Epicondyle | Most distal/lateral aspect of the condyle |
| Center of Glenohumeral Rotation | Estimated* |
| Radial Styloid Process | Most distal/lateral aspect of the radial styloid |
| Ulnar Styloid Process | Most distal/medial aspect of the ulnar styloid |
The center of glenohumeral rotation (and subsequently the joint itself) was not digitized. It was estimated using a least squares algorithm for the point moving least during series of short rotational movements
Descriptive statistics for peak shoulder kinetic parameters
| Parameter | Min | Max | Mean | SD | SE | Skewness | Kurtosis |
|---|---|---|---|---|---|---|---|
| Anterior Force | −9.44 | 53.22 | 28.50 | 17.08 | 3.92 | −0.16 | −0.31 |
| Proximal Force | 130.59 | 296.14 | 201.59 | 48.68 | 11.17 | 0.48 | −0.79 |
Results of logistic regression analysis outlining the predictive relationship between PPFand shoulder pain
| B | S.E | Wald | df | p | EXP(B) | 95% C.I for EXP(B) | ||
|---|---|---|---|---|---|---|---|---|
|
| ||||||||
| Lower | Upper | |||||||
|
| ||||||||
| PPF | 0.046 | 0.019 | 5.762 | 1 | 0.016 | 1.047 | 1.009 | 1.088 |
| Constant | −10.126 | 4.059 | 6.223 | 1 | 0.013 | 0.000 | ||
Final logistic regression model equates to ŷ = 0.046*PPF– 10.126