PubMed · 10643114
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N Haapanen, S Miilunpalo, I Vuori. 1997. [Regular exercise prevents overweight].. https://pubmed.ncbi.nlm.nih.gov/10643114/
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BACKGROUND: The mechanism by which biphasic waveforms improve defibrillation efficacy is unclear. In addition, the optimal shape of the biphasic waveforms remains controversial. Animal experiments suggest that prolonging the duration of the second phase longer than the first worsens defibrillation thresholds (DFT). The purpose of this study was to determine the strength-duration relation for the second phase of a biphasic defibrillation waveform in humans. METHODS AND RESULTS: This was a prospective, randomized study of biphasic DFT in 36 patients; a uniform dual-coil transvenous lead system was used. In each patient, 3 DFTs were determined with the pulse duration for the second phase of the defibrillation waveform varying between 1 and 18 ms. The duration of the first phase was fixed at 6 ms and the capacitance was 150 microF. There was a significant increase in the leading edge voltage at DFT only when the second-phase pulse duration was decreased to 1 ms. There was no increase in DFT voltage even when the second-phase pulse duration was increased from 2 to 18 ms. Similar relations were observed for stored energy, leading edge current, or phase 2 energy. The normalized average current delivered during phase 2 decreased monotonically with increasing phase 2 duration. CONCLUSIONS: In humans, the biphasic DFT voltage or energy is increased only when the second phase of the waveform is <2 ms. The DFT voltage is insensitive to increasing the second phase of the defibrillator waveform to as long as 18 ms, or 3 times the duration of the first phase of the waveform.
In randomized clinical trials, non-compliance will lead to the loss of power in the standard intention-to-treat analysis and one should account for this in sample size calculations. In this paper a new sample size formula for a binary outcome is proposed in which compliance information is considered. The proposed method is based purely on the treatment randomization. We compare it to the conventional sample size calculation method based on the two independent binomial distributions assumption. We examine 3100 combinations of risks of control group (baseline risks), treatment effects (risk differences), compliances in the test treatment group and the control treatment group, test sizes and powers. We found that, compared to the conventional method, the proposed method gives similar sample sizes for baseline risks 0.4-0.6, larger sample sizes for baseline risks less than 0.4, and smaller sample sizes for baseline risks greater than 0.6 when the true risk difference is negative.
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