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Objective To determine whether anterior knee pain (AKP), during running, acutely affects lower-extremity electromyography (EMG) and articular cartilage metabolism. Methods A within-subjects design was used. Each of 12 able-bodied subjects ran on a treadmill for 30 min for three different sessions: control (no infusion), sham (0.9% NaCl infusion into the involved-leg infrapatellar fat pad), and pain (5.0% NaCl infusion into the involved-leg infrapatellar fat pad). Bilateral surface EMG was monitored for the vastus medialis (VM), vastus lateralis (VL), and gastrocnemius (GA). Serum cartilage oligomeric matrix protein (COMP) concentration was determined before, after, and 60 min after the run. A functional analysis approach was used to compare EMG amplitude, across the entire stance phase, between sessions and legs. Mixed-model analysis of covariance was used to compare serum COMP concentration between sessions, across time. Results Relative to the uninvolved leg, greater involved-leg VL and GA EMG amplitude existed during midstance for the sham and control sessions (P < 0.01). During the painful session, however, involved-leg VM, VL, and GA EMG amplitude was 5-10% less than for the uninvolved leg. COMP concentration immediately post-run was 14% and 21% greater than pre-run (P = 0.01) and 60 min post-run concentrations (P < 0.01), respectively. Session, however, did not significantly influence COMP. Conclusion During a 30-min run, AKP acutely alters midstance VM, VL, and GA EMG amplitude. AKP during a 30-min run does not, however, acutely influence articular cartilage metabolism. [ABSTRACT FROM AUTHOR]

Abstract: Background: Improved automated methods for electrocardiographic (ECG) analysis are needed, particularly for drug development purposes. Objectives: This study compared a novel fully automated method for ECG analysis (QTinno; NewCardio, Santa Clara, CA) to 2 semiautomated digital methods: global measurement from the earliest QRS onset to the latest T-wave offset on representative superimposed beats (global) and tangent measurement on 3 consecutive beats in one lead (tangent). Methods: All 3 methods were used to determine uncorrected and rate-corrected QT interval duration (QT and QTcF) and related metrics in 1422 digital 12-lead ECGs from a phase 1 drug study. Global and tangent annotations were manually adjusted by the same 3 cardiologists wherever necessary. No adjustments were made in QTinno determinations. Results: QTinno returned QTcF change from time-matched baseline (ΔQTcF) that differed minimally from both global and tangent methods (mean pairwise difference: 0.1 millisecond between QTinno and global, 1.1 milliseconds between QTinno and tangent). The average absolute QT and QTcF intervals by QTinno were approximately 5 milliseconds longer than global and 25 milliseconds longer than by tangent. QTinno had lower intrinsic variability for ΔQTcF than either global or tangent (between-subject SD: QTinno 4.0 milliseconds, global 5.6 milliseconds, tangent 6.4 milliseconds; within-subject SD: QTinno 4.8 milliseconds, global 7.4 milliseconds, tangent 10.6 milliseconds). All methods were robust in detecting the largest placebo-adjusted mean time-matched ΔQTcF (15-25 milliseconds) induced by study drug. Conclusions: The methods show good agreement for drug-induced QTc prolongation. Lower intrinsic variability of ΔQTcF by QTinno could facilitate smaller sample sizes or increase study power in thorough QTc studies. [Copyright &y& Elsevier]