Comparative Analysis of 30-Day Readmission, Reoperation, and Morbidity between Posterior Cervical Decompression and Fusion Performed in Inpatient and Outpatient Settings.

STUDY DESIGN: A retrospective cohort study. PURPOSE: To compare 30-day readmission, reoperation, and morbidity for patients undergoing posterior cervical decompression and fusion (PCDF) in inpatient vs. outpatient settings. OVERVIEW OF LITERATURE: PCDF has recently been increasingly performed in outpatient settings, often utilizing minimally invasive techniques. However, literature evaluating short-term outcomes for PCDF is scarce. Moreover, no currently large-scale database studies have compared short-term outcomes between PCDF performed in the inpatient and outpatient settings. METHODS: Patients who underwent PCDF from 2005 to 2018 were identified using the National Surgical Quality Improvement Program database. Regression analysis was utilized to compare primary outcomes between surgical settings and evaluate for predictors thereof. RESULTS: We identified 8,912 patients. Unadjusted analysis revealed that outpatients had lower readmission (4.7% vs. 8.8%, p =0.020), reoperation (1.7% vs. 3.8%, p =0.038), and morbidity (4.5% vs. 11.2%, p <0.001) rates. After adjusting for baseline differences, readmission, reoperation, and morbidity no longer statistically differed between surgical settings. Outpatients had lower operative time (126 minutes vs. 179 minutes) and levels fused (1.8 vs. 2.2) (p <0.001). Multivariate analysis revealed that age (p =0.008; odds ratio [OR], 1.012), weight loss (p =0.045; OR, 2.444), and increased creatinine (p <0.001; OR, 2.233) independently predicted readmission. The American Society of Anesthesiologists (ASA) classification of ≥3 predicted reoperation (p =0.028; OR, 1.406). Rehabilitation discharge (p <0.001; OR, 1.412), ASA-class of ≥3 (p =0.008; OR, 1.296), decreased hematocrit (p <0.001; OR, 1.700), and operative time (p <0.001; OR, 1.005) predicted morbidity. CONCLUSIONS: The 30-day outcomes were statistically similar between surgical settings, indicating that PCDF can be safely performed as an outpatient procedure. Surrogates for poor health predicted negative outcomes. These results are particularly important as we continue to shift spinal surgery to outpatient centers. This importance has been highlighted by the need to unburden inpatient sites, particularly during public health emergencies, such as the coronavirus disease 2019 pandemic.

Old drugs, new tricks: leveraging known compounds to disrupt coronavirus-induced cytokine storm.

A major complication in COVID-19 infection consists in the onset of acute respiratory distress fueled by a dysregulation of the host immune network that leads to a run-away cytokine storm. Here, we present an in silico approach that captures the host immune system's complex regulatory dynamics, allowing us to identify and rank candidate drugs and drug pairs that engage with minimal subsets of immune mediators such that their downstream interactions effectively disrupt the signaling cascades driving cytokine storm. Drug-target regulatory interactions are extracted from peer-reviewed literature using automated text-mining for over 5000 compounds associated with COVID-induced cytokine storm and elements of the underlying biology. The targets and mode of action of each compound, as well as combinations of compounds, were scored against their functional alignment with sets of competing model-predicted optimal intervention strategies, as well as the availability of like-acting compounds and known off-target effects. Top-ranking individual compounds identified included a number of known immune suppressors such as calcineurin and mTOR inhibitors as well as compounds less frequently associated for their immune-modulatory effects, including antimicrobials, statins, and cholinergic agonists. Pairwise combinations of drugs targeting distinct biological pathways tended to perform significantly better than single drugs with dexamethasone emerging as a frequent high-ranking companion. While these predicted drug combinations aim to disrupt COVID-induced acute respiratory distress syndrome, the approach itself can be applied more broadly to other diseases and may provide a standard tool for drug discovery initiatives in evaluating alternative targets and repurposing approved drugs.