When clinically indicated, the choice of performing a total knee arthroplasty (TKA) vs a unicompartmental knee arthroplasty (UKA) is dictated by patient and surgeon preferences. Increased understanding of surgical morbidity may enhance this shared decision-making process. This study compared 30-day risk-adjusted outcomes in TKA vs UKA using a national database. We analyzed data from the National Safety and Quality Improvement Program database, for patients who received TKA or UKA between 2014-2018. The main outcomes were blood transfusion, operation time, length of stay, major complication, minor complication, unplanned reoperation, and readmission. Comparisons of odds of the outcomes of interest between TKA and UKA patients were analyzed using multivariate regression models accounting for confounders. We identified 274,411 eligible patients, of whom 265,519 (96.7%) underwent TKA, while 8892 (3.3%) underwent UKA. Risk-adjusted models that compared perioperative and postoperative outcomes of TKA and UKA showed that the odds of complications such as blood transfusion (adjusted odds ratio [aOR], 19.74; 95% confidence interval [CI]: 8.19-47.60), major (aOR, 1.87; 95% CI: 1.27-2.77) and minor complications (aOR, 1.43; 95% CI: 1.14-1.79), and readmission (aOR, 1.41; 95% CI: 1.16-1.72) were significantly higher among patients who received TKA than among those who received UKA. In addition, operation time (aOR, 7.72; 95% CI: 6.72-8.72) and hospital length of stay (aOR, 1.11; 95% CI: 1.05-1.17) were also higher among the TKA recipients compared to those who received UKA. UKA is associated with lower rates of adverse perioperative outcomes compared to TKA. Clinical indications and surgical morbidity should be considered in the shared-decision process

The purpose of this study was to examine trends in diabetes-related hospitalizations over the period 2010 to 2019 using Nationwide Inpatient Sample (NIS) to facilitate informed policies regarding diabetes-related prevention and management. Between 2010 and 2019, there were 304 million hospitalizations above 18 years of age, of which 78 million were diabetes-associated hospitalizations. The overall population-adjusted diabetes hospitalizations significantly increased from 3079.0 to 3280.8 per 100,000 US population (relative increase, 6.6%, Ptrend < 0.028). Age-stratified analysis showed that hospitalizations significantly increased for 18–29 years (relative increase, 7.8%, Ptrend < 0.001) while age- and gender-stratified analysis showed that diabetes hospitalization significantly increased for 18–29-year males (relative increase, 18.1%, Ptrend < 0.001). Total hospitalization charge increased from 97.5 billion USD in 2010 to 132.0 billion USD in 2019 (relative increase, 35.4%, Ptrend < 0.001). Our study’s findings suggest that diabetes-associated hospitalizations will continue to increase in the future because recent evidence indicates a reappearance of diabetes complications. It is important to screen, prevent, and control diabetes at a younger age based on the trends observed in our study.

HIV/AIDS is a leading cause of mortality and morbidity worldwide. In spite of successful interventions and treatment protocols, an HIV vaccine would be the ultimate prevention and control strategy. Ever since identification of HIV/AIDS, there have been meticulous efforts for vaccine development. The specific aim of this paper is to review recent vaccine efficacy trials and associated advancements and discuss the current challenges and future directions. Recombinant DNA technologies greatly facilitated development of many viral products which were later incorporated into vectors for effective vaccines. Over the years, a number of scientific approaches have gained popularity and include the induction of neutralizing antibodies in late 1980s, induction of CD8 T cell in early 1990s, and combination approaches currently. Scientists have hypothesized that stimulation of right sequences of somatic hypermutations could induce broadly reactive neutralizing antibodies (bnAbs) capable of effective neutralization and viral elimination. Studies have shown that a number of host and viral factors affect these processes. Similarly, eliciting specific CD8 T cells immune responses through DNA vaccines hold future promises. In summary, future studies should focus on the continuous fight between host immune responses and ever-evasive viral factors for effective vaccines.

Phase I studies are used to estimate the dose-toxicity profile of the drugs and to select appropriate doses for successive studies. However, literature on statistical methods used for phase I studies are extensive. The objective of this review is to provide a concise summary of existing and emerging techniques for selecting dosages that are appropriate for phase I cancer trials. Many advanced statistical studies have proposed novel and robust methods for adaptive designs that have shown significant advantages over conventional dose finding methods. An increasing number of phase I cancer trials use adaptive designs, particularly during the early phases of the study. In this review, we described nonparametric and algorithm-based designs such as traditional 3 + 3, accelerated titration, Bayesian algorithm-based design, up-and-down design, and isotonic design. In addition, we also described parametric model-based designs such as continual reassessment method, escalation with overdose control, and Bayesian decision theoretic and optimal design. Ongoing studies have been continuously focusing on improving and refining the existing models as well as developing newer methods. This study would help readers to assimilate core concepts and compare different phase I statistical methods under one banner. Nevertheless, other evolving methods require future reviews.

The pathophysiology of stoke involves many complex pathways and risk factors. Though there are several ongoing studies on stroke, treatment options are limited, and the prevalence of stroke is continuing to increase. Understanding the genomic variants and biological pathways associated with stroke could offer novel therapeutic alternatives in terms of drug targets and receptor modulations for newer treatment methods. It is challenging to identify individual causative mutations in a single gene because many alleles are responsible for minor effects. Therefore, multiple factorial analyses using single nucleotide polymorphisms (SNPs) could be used to gain new insight by identifying potential genetic risk factors. There are many studies, such as Genome-Wide Association Studies (GWAS) and Phenome-Wide Association Studies (PheWAS) which have identified numerous independent loci associated with stroke, which could be instrumental in developing newer drug targets and novel therapies. Additionally, using analytical techniques, such as meta-analysis and Mendelian randomization could help in evaluating stroke risk factors and determining treatment priorities. Combining SNPs into polygenic risk scores and lifestyle risk factors could detect stroke risk at a very young age and help in administering preventive interventions.