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Evidence for non-random sampling in randomised, controlled trials by Yuhji Saitoh
J B Carlisle1, J A Loadsman2,3
1Department of Anaesthesia, Peri-operative Medicine and Intensive Care, Torbay Hospital, Torquay, UK.
Anaesthesia
|December 19, 2016
Summary
Statistical analysis of 32 randomized trials co-authored by Dr. Yuhji Saitoh revealed a very low probability of random sampling. Findings suggest potential data manipulation, warranting further investigation into Saitoh's research integrity.
Area of Science:
- Medical research integrity
- Statistical analysis in clinical trials
Background:
- Numerous randomized trials by Yoshitaka Fujii were retracted due to improbable random sampling.
- Dr. Yuhji Saitoh co-authored 34 of these trials, serving as corresponding author for eight.
- This study examines additional randomized trials where Saitoh was the corresponding author, but Fujii was not involved.
Purpose of the Study:
- To statistically analyze baseline data and outcomes from randomized controlled trials associated with Dr. Yuhji Saitoh.
- To investigate potential non-random sampling and data irregularities in Saitoh's publications.
- To assess the reproducibility and reliability of findings in selected trials.
Main Methods:
- Monte Carlo simulations were employed to analyze baseline data from 32 randomized controlled trials.
- Statistical analysis of muscle twitch recovery ratios and graphical data from Saitoh's publications.
- Comparison of baseline data p-values and homogeneity of outcome ratios across trials.
Main Results:
- 14 out of 32 trials showed baseline data with p < 0.01, seven with p < 0.001.
- Homogeneous distributions of muscle twitch recovery ratios yielded p values below 0.05 for observed Q statistics.
- Graphical analysis revealed coincident curves across multiple publications, inconsistent with random sampling.
- Combined probability of random sampling across 32 trials was extremely low (p = 1.27 × 10⁻⁸).
Conclusions:
- The analysis indicates a high probability of non-random sampling in the examined trials.
- Repetitive graphical patterns suggest potential data fabrication or manipulation.
- Further scrutiny of Dr. Saitoh's research is strongly warranted due to these statistical anomalies.
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