Given strong uniqueness for an It^os stochastic equation, we prove that its solution can beconstructed on any probability space by using, for example, Eulers polygonal approximations. Stochastic equations in $mathbb{R}^{d}$ and in domains in $mathbb{R}^{d}$ are considered. This is almost a copy of an old article in which we correct errors in the original proof of Lemma 4.1 found by Martin Dieckmann in 2013. We present also a new result on the convergence of tamed Euler approximations for SDEs with locally unbounded drifts, which we achieve by proving an estimate for appropriate exponential moments.
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