Recently, communication systems that are both spectrum and energy efficient have attracted significant attention. Different from the existing research, we investigate the throughput and energy efficiency of a general class of multiple-input and multiple-output systems with arbitrary inputs when they are subject to statistical quality-of-service (QoS) constraints, which are imposed as limits on the delay violation and buffer overflow probabilities. We employ the effective capacity as the performance metric. We obtain the optimal input covariance matrix that maximizes the effective capacity under a short-term average power constraint. Following that, we perform an asymptotic analysis of the effective capacity in the low signal-to-noise ratio and large-scale antenna regimes. In the low signal-to-noise ratio regime analysis, we utilize the first and second derivatives of the effective capacity when the signal-to-noise ratio approaches zero in order to determine the minimum energy-per-bit and also the slope of the effective capacity versus energy-per-bit curve at the minimum energy-per-bit. We observe that the minimum energy-per-bit is independent of the input distribution, whereas the slope depends on the input distribution. In the large-scale antenna analysis, we show that the effective capacity approaches the average transmission rate in the channel with the increasing number of transmit and/or receive antennas. Particularly, the gap between the effective capacity and the average transmission rate in the channel, which is caused by the QoS constraints, is minimized with the number of antennas. In addition, we put forward the non-asymptotic backlog and delay violation bounds by utilizing the effective capacity. Finally, we substantiate our analytical results through numerical illustrations.