Risk Factors for Thirty-Day Readmission Following Lumbar Surgery: A Meta-Analysis.

OBJECTIVE: Thirty-day readmission is one of the common complications after lumbar surgery. More 30-day readmission increases the total hospitalization, economic burden, and physical pain of patients, delays the progress of postoperative rehabilitation, and even lead to die. Therefore, it is necessary to analyze the risk factors of 30-day readmission following lumbar surgery. METHODS: We searched for all the clinical trials published from the establishment of the database to May 1, 2022 through the Cochrane Library, Web of Science, Embase, and PubMed. Data including age, American Society of Anesthesiology physical status class, preoperative hematocrit (Hct), diabetes mellitus (DM), current smoker, chronic obstructive pulmonary disease (COPD), length of hospital stay (LHS), operation time, and surgical site infection (SSI) were extracted. We used Review Manager 5.4 for data analysis. RESULTS: Six studies with 30,989 participants were eligible for this meta-analysis. The analysis revealed that there were statistically significant differences in the age (95% confidence interval [CI]: -3.35-2.90, P < 0.001), preoperative Hct (95% CI: 0.75-1.33, P < 0.001), DM (95% CI: 0.56-0.74, P < 0.001), COPD (95% CI: 0.38-0.58, P < 0.001), operation time (95% CI: -35.54-16.18, P < 0.001), LHS (95% CI: -0.54-0.50, P < 0.001), and SSI (95% CI: 0.02-0.03, P < 0.001) between no readmission and readmission groups. In terms of the American Society of Anesthesiology physical status class and current smoker, there was no significant effect on the 30-day readmission (P = 0.16 and P = 0.35 respectively). CONCLUSIONS: Age, preoperative Hct, DM, COPD, operation time, LHS, and SSI are the danger factors of 30-day readmission following lumbar surgery.

Analysis of N6-Methyladenosine RNA Methylation Regulators in Diagnosis and Distinct Molecular Subtypes of Ankylosing Spondylitis.

The most frequent internal modification in eukaryotic mRNA is N6-methyladenosine (m6A). However, what we know about the m6A regulators in Ankylosing spondylitis (AS) is still limited. In our study, eight distinct m6A regulators were selected utilizing Differentially Expressed Gene (DEG) analysis of the Gene Expression Omnibus GSE73754 dataset for making comparisons between AS (Ankylosing spondylitis) and non-AS patients. The random forest model and the nomogram model were used to screen the eight candidate m6A regulators and evaluate their prediction accuracy for the occurrence of AS. Furthermore, based on the selected m6A regulators, the AS patients were divided into two subgroups, and we applied principal component analysis algorithms to calculate their m6A score and evaluate the m6A patterns. Our findings revealed that patients in cluster A were linked to activated CD4 T cell immunity and activated CD8 T cell immunity. With its major contributions in the area of immunology, our research in m6A patterns may benefit the future diagnosis and treatment strategies of AS.