A case report of a patient with upper extremity symptoms: differentiating radicular and referred pain

<p>Abstract</p> <p>Background</p> <p>Similar upper extremity symptoms can present with varied physiologic etiologies. However, due to the multifaceted nature of musculoskeletal conditions, a definitive diagnosis using physical examination and advanced testing is not always possible. This report discusses the diagnosis and case management of a patient with two episodes of similar upper extremity symptoms of different etiologies.</p> <p>Case Presentation</p> <p>On two separate occasions a forty-four year old female patient presented to a chiropractic office with a chief complaint of insidious right-sided upper extremity symptoms. During each episode she reported similar pain and parasthesias from her neck and shoulder to her lateral forearm and hand.</p> <p>During the first episode the patient was diagnosed with a cervical radiculopathy. Conservative treatment, including manual cervical traction, spinal manipulation and neuromobilization, was initiated and resolved the symptoms.</p> <p>Approximately eighteen months later the patient again experienced a severe acute flare-up of the upper extremity symptoms. Although the subjective complaint was similar, it was determined that the pain generator of this episode was an active trigger point of the infraspinatus muscle. A diagnosis of myofascial referred pain was made and a protocol of manual trigger point therapy and functional postural rehabilitative exercises improved the condition.</p> <p>Conclusion</p> <p>In this case a thorough physical evaluation was able to differentiate between radicular and referred pain. By accurately identifying the pain generating structures, the appropriate rehabilitative protocol was prescribed and led to a successful outcome for each condition. Conservative manual therapy and rehabilitative exercises may be an effective treatment for certain cases of cervical radiculopathy and myofascial referred pain.</p

Reliability of Quantitative Real-Time PCR for Bacterial Detection in Cystic Fibrosis Airway Specimens

The cystic fibrosis (CF) airway microbiome is complex; polymicrobial infections are common, and the presence of fastidious bacteria including anaerobes make culture-based diagnosis challenging. Quantitative real-time PCR (qPCR) offers a culture-independent method for bacterial quantification that may improve diagnosis of CF airway infections; however, the reliability of qPCR applied to CF airway specimens is unknown. We sought to determine the reliability of nine specific bacterial qPCR assays (total bacteria, three typical CF pathogens, and five anaerobes) applied to CF airway specimens. Airway and salivary specimens from clinically stable pediatric CF subjects were collected. Quantitative PCR assay repeatability was determined using triplicate reactions. Split-sample measurements were performed to measure variability introduced by DNA extraction. Results from qPCR were compared to standard microbial culture for Pseudomonas aeruginosa, Staphylococcus aureus, and Haemophilus influenzae, common pathogens in CF. We obtained 84 sputa, 47 oropharyngeal and 27 salivary specimens from 16 pediatric subjects with CF. Quantitative PCR detected bacterial DNA in over 97% of specimens. All qPCR assays were highly reproducible at quantities ≥102 rRNA gene copies/reaction with coefficient of variation less than 20% for over 99% of samples. There was also excellent agreement between samples processed in duplicate. Anaerobic bacteria were highly prevalent and were detected in mean quantities similar to that of typical CF pathogens. Compared to a composite gold standard, qPCR and culture had variable sensitivities for detection of P. aeruginosa, S. aureus and H. influenzae from CF airway samples. By reliably quantifying fastidious airway bacteria, qPCR may improve our understanding of polymicrobial CF lung infections, progression of lung disease and ultimately improve antimicrobial treatments

Plasma biomarkers of depressive symptoms in older adults

The pathophysiology of negative affect states in older adults is complex, and a host of central nervous system and peripheral systemic mechanisms may play primary or contributing roles. We conducted an unbiased analysis of 146 plasma analytes in a multiplex biochemical biomarker study in relation to number of depressive symptoms endorsed by 566 participants in the Alzheimer's Disease Neuroimaging Initiative (ADNI) at their baseline and 1-year assessments. Analytes that were most highly associated with depressive symptoms included hepatocyte growth factor, insulin polypeptides, pregnancy-associated plasma protein-A and vascular endothelial growth factor. Separate regression models assessed contributions of past history of psychiatric illness, antidepressant or other psychotropic medicine, apolipoprotein E genotype, body mass index, serum glucose and cerebrospinal fluid (CSF) τ and amyloid levels, and none of these values significantly attenuated the main effects of the candidate analyte levels for depressive symptoms score. Ensemble machine learning with Random Forests found good accuracy (∼80%) in classifying groups with and without depressive symptoms. These data begin to identify biochemical biomarkers of depressive symptoms in older adults that may be useful in investigations of pathophysiological mechanisms of depression in aging and neurodegenerative dementias and as targets of novel treatment approaches