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A continual increase in the prevalence of osteoarthritis drives growing demand for total joint arthroplasty. So far, a decrease in length of stay has been the target for health professionals globally. However, a consensus pathway of achieving this has not yet been reached. This article reviews recent advances in pre-operative and perioperative factors impacting length of stay.

ImportanceDiscontinuation and nonpublication are established sources of avoidable waste among surgical trials, but rates of delayed completion and recruiting shortfalls remain unclear.ObjectivesTo examine the rate of delayed completion, incomplete enrollment, and discontinuation among randomized clinical trials in surgical populations and the duration of delays and extent of recruiting shortfalls among these trials.Design, Setting, and ParticipantsThis cross-sectional study examined randomized clinical trials in surgical populations registered on ClinicalTrials.gov between January 1, 2010, and December 31, 2014. Analysis was conducted between October 27, 2021, and June 30, 2022.Main Outcomes and MeasuresThe main outcomes were the percentages of trials completed on time or with full enrollment. Delays and recruiting shortfalls were identified by comparing projected enrollment and study timeframes prespecified at the time of registration with the actual study duration and enrollment reported on completion or discontinuation. Absolute and relative differences between planned and actual trial conduct were presented for discontinued trials and those completed with delays or recruiting shortfalls.ResultsIn total, 2542 randomized clinical trials in surgical populations were included in the study sample, of which 370 (14.6%; 95% CI, 13.2%-15.9%) were completed both on time and with full enrollment. Approximately 1 in 5 trials (20.4%; 95% CI, 18.9%-22.0%) were completed within their planned timeframe, and 1166 trials (45.9%; 95% CI, 43.9%-47.8%) met their prespecified enrollment target. The median delay among completed trials was 12.2 months (IQR, 5.1-24.3 months) or 66.7% (IQR, 30.1%-135.8%) longer than planned. Among completed trials that did not meet their prespecified enrollment target, the median recruiting shortfall was equivalent to 31.0% (IQR, 12.7%-55.5%) of the planned study sample. A total of 546 trials (21.5%; 95% CI, 19.9%-23.1%) were discontinued. The median time to discontinuation was 26.4 months (IQR, 15.2-45.7 months), and the median recruiting shortfall among discontinued trials was equivalent to 92.7% (IQR, 65.0%-100.0%) of the trial’s prespecified enrollment target.Conclusions and RelevanceThis cross-sectional study found that delayed completion, recruiting shortfalls, and untimely discontinuation were common among surgical trials. These findings highlight the importance of ensuring that investigators and funders do not overestimate the feasibility of planned trials.

Thirty-day readmission following total knee arthroplasty (TKA) is an important outcome influencing the quality of patient care and health system efficiency. The aims of this study were (1) to ascertain the clinical importance of established risk factors for 30-day readmission risk and give clinicians the opportunity to suggest and discuss novel risk factors and (2) to evaluate consensus on the importance of these risk factors. This study was conducted in two stages: a modified Delphi survey followed by a focus group. Orthopaedic surgeons and anaesthetists involved in the care of TKA patients completed an anonymous survey to judge the clinical importance of risk factors selected from a systematic review and meta-analysis and to suggest other clinically meaningful risk factors, which were then discussed in a focus group designed using elements of nominal group technique. Eleven risk factors received a majority (≥50%) vote of high importance in the Delphi survey overall, and six risk factors received a majority vote of high importance in the focus group overall. Lack of consensus highlighted the fact that this is a highly complex problem which is challenging to predict and which depends heavily on risk factors which may be open to interpretation, difficult to capture, and dependent upon personal clinical experience, which must be tailored to the individual patient.

Many embedded systems such as digital cameras, digital radios, high-resolution printers, cellular phones, etc., involve a heavy use of signal processing and are thus based on digital signal processors (DSPs). DSPs such as the TMS320C2x and the DSP5600x have irregular data paths that typically result due to application specific needs (such as chaining multiply-accumulate operations, etc.). Efficient code generation for such embedded DSP processors is a challenging problem. The stringent requirements such as tight memory constraints and fast response time result in the need for a compact and efficient code. In this paper, we address the problem of generating a compact and efficient code for embedded DSP processors. Most of the DSP instruction set architectures (ISAs) feature intrainstruction parallelism (IIP), enabling individual operations to be executed in parallel by generating a complex instruction. A reduction in generated code size and improved performance can be achieved by exploiting this parallelism present in such ISAs. In this paper, we present a code restructuring technique to fully exploit this parallelism through maximal utilization of the complex instructions present in the instruction set. We formulate this as a maximal benefit code restructuring problem, which is to derive the arrangement of statements to maximally exploit IIP without violating data dependencies. This problem is equivalent to the precedence constrained Hamiltonian path problem for directed acyclic graphs and the traveling salesman problem in general, both of which are NP-hard. In this paper, we present an optimal algorithm to solve the problem. We have implemented this optimal algorithm in a compiler targeted to generate code for the TMS320C25 DSP. We tested our framework on a number of benchmarks and found that the performance of the generated code (measured in dynamic instruction cycle counts) improves by as much as 9.9% with an average of 4%. The average code-size reduction over code compiled without exploiting parallelism is 2.9%. We also studied the effect of loop unrolling on the available IIP. An on-chip instruction cache can be effectively utilized by unrolling loops such that generated code fully occupies the memory. The benefit is reduction in dynamic instruction count due to the higher number of complex instructions generated. We found that by unrolling loop by four times to fit available on-chip instruction cache, the dynamic instruction counts reduce by as much as 9.9 %.