Utility of monocyte distribution width in the differential diagnosis between simple and complicated diverticulitis: a retrospective cohort study.

BACKGROUND: Colonic diverticulitis is a leading cause of abdominal pain. The monocyte distribution width (MDW) is a novel inflammatory biomarker with prognostic significance for coronavirus disease and pancreatitis; however, no study has assessed its correlation with the severity of colonic diverticulitis. METHODS: This single-center retrospective cohort study included patients older than 18 years who presented to the emergency department between November 1, 2020, and May 31, 2021, and received a diagnosis of acute colonic diverticulitis after abdominal computed tomography. The characteristics and laboratory parameters of patients with simple versus complicated diverticulitis were compared. The significance of categorical data was assessed using the chi-square or Fisher's exact test. The Mann-Whitney U test was used for continuous variables. Multivariable regression analysis was performed to identify predictors of complicated colonic diverticulitis. Receiver operator characteristic (ROC) curves were used to test the efficacy of inflammatory biomarkers in distinguishing simple from complicated cases. RESULTS: Of the 160 patients enrolled, 21 (13.125%) had complicated diverticulitis. Although right-sided was more prevalent than left-sided colonic diverticulitis (70% versus 30%), complicated diverticulitis was more common in those with left-sided colonic diverticulitis (61.905%, p = 0.001). Age, white blood cell (WBC) count, neutrophil count, C-reactive protein (CRP) level, neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and MDW were significantly higher in the complicated diverticulitis group (p < 0.05). Logistic regression analysis indicated that the left-sided location and the MDW were significant and independent predictors of complicated diverticulitis. The area under the ROC curve (AUC) was as follows: MDW, 0.870 (95% confidence interval [CI], 0.784-0.956); CRP, 0.800 (95% CI, 0.707-0.892); NLR, 0.724 (95% CI, 0.616-0.832); PLR, 0.662 (95% CI, 0.525-0.798); and WBC, 0.679 (95% CI, 0.563-0.795). When the MDW cutoff was 20.38, the sensitivity and specificity were maximized to 90.5% and 80.6%, respectively. CONCLUSIONS: A large MDW was a significant and independent predictor of complicated diverticulitis. The optimal cutoff value for MDW is 20.38 as it exhibits maximum sensitivity and specificity for distinguishing between simple and complicated diverticulitis The MDW may aid in planning antibiotic therapy for patients with colonic diverticulitis in the emergency department.

Screening of Potential Biomarkers in the Peripheral Serum for Steroid-Induced Osteonecrosis of the Femoral Head Based on WGCNA and Machine Learning Algorithms.

BACKGROUND: Steroid-induced osteonecrosis of the femoral head (SONFH) has produced a substantial burden of medical and social experience. However, the current diagnosis is still limited. Thus, this study is aimed at identifying potential biomarkers in the peripheral serum of patients with SONFH. METHODS: The expression profile data of SONFH (number: GSE123568) was acquired from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) in SONFH were identified and used for weighted gene coexpression network analysis (WGCNA). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to investigate the biological functions. The protein-protein interaction (PPI) network and machine learning algorithms were employed to screen for potential biomarkers. Gene set enrichment analysis (GSEA), transcription factor (TF) enrichment analysis, and competing endogenous RNA (ceRNA) network were used to determine the biological functions and regulatory mechanisms of the potential biomarkers. RESULTS: A total of 562 DEGs, including 318 upregulated and 244 downregulated genes, were identified between SONFH and control samples, and 94 target genes were screened based on WGCNA. Moreover, biological function analysis suggested that target genes were mainly involved in erythrocyte differentiation, homeostasis and development, and myeloid cell homeostasis and development. Furthermore, GYPA, TMCC2, and BPGM were identified as potential biomarkers in the peripheral serum of patients with SONFH based on machine learning algorithms and showed good diagnostic values. GSEA revealed that GYPA, TMCC2, and BPGM were mainly involved in immune-related biological processes (BPs) and signaling pathways. Finally, we found that GYPA might be regulated by hsa-miR-3137 and that BPGM might be regulated by hsa-miR-340-3p. CONCLUSION: GYPA, TMCC2, and BPGM are potential biomarkers in the peripheral serum of patients with SONFH and might affect SONFH by regulating erythrocytes and immunity.