Search

BACKGROUND: Ischemic compression is widely used to clinically treat neck pain. However, no meta-analysis has been conducted to evaluate the effects of this process on neck pain. OBJECTIVE: This study aimed to evaluate the effects of ischemic compression on the myofascial trigger points for improving neck pain-related symptoms (mainly pain, joint mobility limitation and function limitation) and to compare ischemic compression with other therapies. METHODS: Electronic searches were conducted in PubMed, OVID, Web of Science, EBSCO, SCOUPS, Cochrane Library, PEDro, Wanfang, CNKI and Chinese VIP Database in June 2021. Only randomised controlled trials on the effects of ischemic compression on neck pain were included. The major outcomes were pain intensity, pressure pain threshold, pain-related disability and range of motion. RESULTS: Fifteen studies involving 725 participants were included. Significant differences were observed between ischemic compression and sham/no treatment group in pain intensity, pressure pain threshold and range of motion immediately and in the short term. Significant effect sizes of dry needling were observed over ischemic compression in terms of improving pain intensity (SMD = 0.62; 95% CI: 0.08 to 1.16; P = 0.02), pain-related disability (SMD = 0.68; 95% CI: 0.19 to 1.17; P = 0.007) and range of motion (MD = - 2.12; 95% CI: - 2.59 to - 1.65; P < 0.001) immediately after treatment. Dry needling also showed a significant small effect size for the short-term reduction of pain (SMD = 0.44; 95% CI: 0.04 to 0.85; P = 0.03). CONCLUSION: Ischemic compression can be recommended in the immediate and short-term pain relief and increase in the pressure pain threshold and range of motion. Dry needling is superior to ischemic compression in relieving pain and improving pain-related disability and range of motion immediately after treatment. [ABSTRACT FROM AUTHOR]

The analytical validation is reported for a targeted methylation-based cell-free DNA multi-cancer early detection test designed to detect cancer and predict the cancer signal origin (tissue of origin). A machine-learning classifier was used to analyze the methylation patterns of >105 genomic targets covering >1 million methylation sites. Analytical sensitivity (limit of detection [95% probability]) was characterized with respect to tumor content by expected variant allele frequency and was determined to be 0.07%-0.17% across five tumor cases and 0.51% for the lymphoid neoplasm case. Test specificity was 99.3% (95% confidence interval, 98.6–99.7%). In the reproducibility and repeatability study, results were consistent in 31/34 (91.2%) pairs with cancer and 17/17 (100%) pairs without cancer; between runs, results were concordant for 129/133 (97.0%) cancer and 37/37 (100%) non-cancer sample pairs. Across 3- to 100-ng input levels of cell-free DNA, cancer was detected in 157/182 (86.3%) cancer samples but not in any of the 62 non-cancer samples. In input titration tests, cancer signal origin was correctly predicted in all tumor samples detected as cancer. No cross-contamination events were observed. No potential interferent (hemoglobin, bilirubin, triglycerides, genomic DNA) affected performance. The results of this analytical validation study support continued clinical development of a targeted methylation cell-free DNA multi-cancer early detection test. [ABSTRACT FROM AUTHOR]