Construction and Validation Study of a Model for Predicting the Risk of Pulmonary Complications in Elderly Patients with Multiple Rib Fractures.

Objective: Given the high incidence of pulmonary complications and poor prognosis in patients with multiple rib fractures, we have developed a risk prediction model for pulmonary complications in patients with MRF. In order to identify the high-risk groups prone to pulmonary complications as early as possible, we will intervene in advance and provide targeted interventions to improve patients' quality of life and disease prognosis. Methods: The prospective cohort study design scheme was used to collect data information based on the hospital's electronic medical record system. The constructed cohort included 314 cases, and the validation cohort included 119 patients with MRF. The risk prediction model for pulmonary complications in patients with MRF was established using the backward screening method and multivariate logistic regression analysis. The predictive quality and clinical utility of the model were assessed using AUC, sensitivity, specificity, calibration curves, and clinical decision curves. Results: Seven predictors were finally included after multivariate logistic regression analysis: age, smoking history, diabetes mellitus, presence of other fracture combinations, serum albumin, treatment modality, and presence of underlying lung disease. The construction of the cohort yielded an AUC of 0.928 (95% CI 0899-0.956; P < .001) for the present model, with a sensitivity of 81.2% and a specificity of 76.8%, while the external validation cohort yielded an AUC of 0.942 (95% CI 0.900-0.983; P < .001), with a sensitivity of 76.7% and a specificity of 78.4%, and the H-L chi-squared tests all showed P > .05. Conclusions: The column-line diagram model of pulmonary complications in patients with MRF constructed in this study showed good discriminative and calibration performance in both internal and external validation, which is helpful for clinicians to identify individuals at high risk of pulmonary complications as early as possible, and thus can be recommended for clinical use.

Influence of lymphadenectomy on survival and recurrence in patients with early-stage epithelial ovarian cancer: a meta-analysis.

BACKGROUND: This meta-analysis aimed to evaluate the effectiveness of lymphadenectomy on survival and recurrence in patients with early-stage epithelial ovarian cancer (eEOC). METHODS: Relevant studies were searched from four online databases. Hazard ratios (HRs) with 95% confidence intervals (CIs) or risk ratios (RRs) with 95% CIs were used to evaluate the effects of lymphadenectomy on overall survival (OS), progression-free survival (PFS), and recurrence rates. A subgroup analysis was performed to explore the sources of heterogeneity, followed by sensitivity and publication bias assessments. RESULTS: Fourteen articles involving 22,178 subjects were included. Meta-analysis revealed that lymphadenectomy was significantly associated with improved OS (HR = 0.72; 95% CI:0.61, 0.84; P < 0.001), improved PFS (HR = 0.74; 95% CI: 0.67, 0.80; P < 0.001), and reduced recurrence rates (RR = 0.72; 95% CI: 0.60, 0.85; P < 0.001). Subgroup analysis showed that factors including area, histology, and source of the control group were significantly related to improved OS and PFS in patients with eEOC. Sensitivity analysis showed that the combined results were stable and reliable, and no significant publication bias was observed. CONCLUSIONS: Patients with eEOC can benefit from lymphadenectomy, with improved survival outcomes (OS and PFS) and a lower recurrence rate.

Integrated bioinformatics analysis for differentially expressed genes and signaling pathways identification in gastric cancer.

Background: Gastric cancer (GC) has a high mortality rate in cancer-related deaths worldwide. Currently, the pathogenesis of gastric cancer progression remains unclear. Here, we identified several vital candidate genes related to gastric cancer development and revealed the potential pathogenic mechanisms using integrated bioinformatics analysis. Methods: Two microarray datasets from Gene Expression Omnibus (GEO) database integrated. Limma package was used to analyze differentially expressed genes (DEGs) between GC and matched normal specimens. DAVID was utilized to conduct Gene ontology (GO) and KEGG enrichment analysis. The relative expression of OLFM4, IGF2BP3, CLDN1 and MMP1were analyzed based on TCGA database provided by UALCAN. Western blot and quantitative real time PCR assay were performed to determine the protein and mRNA levels of OLFM4, IGF2BP3, CLDN1 and MMP1 in GC tissues and cell lines, respectively. Results: We downloaded the expression profiles of GSE103236 and GSE118897 from the Gene Expression Omnibus (GEO) database. Two integrated microarray datasets were used to obtain differentially expressed genes (DEGs), and bioinformatics methods were used for in-depth analysis. After gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichments analysis, we identified 61 DEGs in common, of which the expression of 34 genes were elevated and 27 genes were decreased. GO analysis displayed that the biological functions of DEGs mainly focused on negative regulation of growth, fatty acid binding, cellular response to zinc ion and calcium-independent cell-cell adhesion. KEGG pathway analysis demonstrated that these DEGs mainly related to the Wnt and tumor signaling pathway. Interestingly, we found 4 genes were most significantly upregulated in the DEGs, which were OLFM4, IGF2BP3, CLDN1 and MMP1. Then, we confirmed the upregulation of these genes in STAD based on sample types. In the final, western blot and qRT-PCR assay were performed to determine the protein and mRNA levels of OLFM4, IGF2BP3, CLDN1 and MMP1 in GC tissues and cell lines. Conclusion: In our study, using integrated bioinformatics to screen DEGs in gastric cancer could benefit us for understanding the pathogenic mechanism underlying gastric cancer progression. Meanwhile, we also identified four significantly upregulated genes in DEGs from both two datasets, which might be used as the biomarkers for early diagnosis and prevention of gastric cancer.

Dietary iron intake predicts all-cause and cardiovascular mortality in patients with diabetes.

BACKGROUND: Limited data exists on the link between dietary iron intake and mortality in diabetes. Our investigation aimed to explore how dietary iron intake correlates with overall and cause-specific mortality in diabetic individuals. METHODS: This analysis encompassed 5970 participants with diabetes from the National Health and Nutrition Examination Survey spanning 1999 to 2014. Baseline data were collected through surveys and examinations, with mortality status tracked via National Death Index records until December 31, 2015. Cox proportional hazard models were utilized to calculate hazard ratios (HR) and 95% confidence intervals (CI) for mortality from various causes, including cardiovascular disease (CVD) and cancer. RESULTS: The average iron intake among the cohort was 14.1 ± 7.4 mg daily, with an average participant age of 61.3 and 3059 (51.3%) male adults. Over 41,425 person-years of follow-up, 1497 deaths were recorded. Following adjustments for multiple variables, an iron intake between 11.1 and 14.4 mg was associated with the lowest risk of all-cause mortality (HR 0.83 [0.70, 0.99], P < 0.05) compared to the reference group (<8.3 mg). Analysis of dose-response curves revealed an L-shaped pattern in men and a J-shaped pattern in women concerning the relationship between iron intake and all-cause mortality. CONCLUSIONS: Our findings suggest a nonlinear association between dietary iron intake and all-cause mortality in individuals with diabetes. Specifically, higher iron intake may increase all-cause mortality risk in men, while potentially exert a protective effect in women.

Serum osmolality was non-linearly associated with the risk of all-cause and cardiovascular mortality in patients with diabetes.

AIMS: This study aimed to evaluate the relationship between both low and high osmolarity and the risk of all-cause and cause-specific mortality in diabetic population. METHODS: All participants were included from the National Health and Nutrition Examination Survey 1999-2014. Baseline serum osmolality was determined from laboratory tests and cause of death from national death records. HRs and 95% CIs for all-cause mortality and cardiovascular mortality in diabetes were estimated using Cox proportional regression analysis. The non-linear relationship was explored using restricted cubic splines regression. RESULTS: Among 7622 individuals with diabetes, 1983 (12.4%) died during a total of 3.26 thousand person-years of follow-up. Compared with the reference category (281-284 mmol/kg), the multivariable-adjusted HRs and 95% CIs for all-cause mortality were 1.27 (1.16-1.40; p<0.001) in the lowest osmolality category (<201 mmol/kg) and 1.18 (1.09-1.28; p<0.001) in the highest osmolality category (>312 mmol/kg). Restricted cubic splines results showed that serum levels of osmolality had a U-shaped association with the risk of all-cause mortality, and L-shaped relationship with the risk of cardiovascular death. CONCLUSIONS: Both low osmolality and high osmolality were predictive of increased all-cause mortality in patients with diabetes, supporting a U-shaped relationship. Also, a lower serum osmolality increased the risk of cardiovascular mortality.

The carcinogenic complex lncRNA DUXAP8/EZH2/LSD1 accelerates the proliferation, migration and invasion of colorectal cancer.

PURPOSE: To elucidate the potential role of long non-coding RNA (lncRNA) DUXAP8 in the malignant progression of colorectal cancer (CRC) and its possible molecular mechanism. METHODS: The expression level of lncRNA DUXAP8 in CRC tissues and matched paracancerous tissues was detected by quantitative real-time polymerase chain reaction (qRT-PCR). Meanwhile, its level in CRC patients with different tumor sizes and tumor grades was determined. The regulatory effects of DUXAP8 on the behaviors of CRC cells were evaluated by cell counting kit-8 (CCK-8), 5-Ethynyl-2'- deoxyuridine (EdU) and Transwell assay. The interaction between LSD1, EZH2 and DUXAP8 was evaluated by RNA-protein interactions and RIP assay. Linear regression analyses were conducted to examine the correlation between DUXAP8 and LSD1, EZH2. RESULTS: LncRNA DUXAP8 was upregulated in CRC tissues and cell lines. Its level remained higher in CRC with larger tumor size or higher tumor grade. Knockdown of DUXAP8 suppressed the proliferative, migratory and invasive abilities of DLD-1 and SW480 cells. Both RF classifier and SVM classifier predicted the pronounced accuracies of LSD1 and EZH2. RIP assay further demonstrated the interaction between DUXAP8 and LSD1, EZH2. Knockdown of LSD1 or EZH2 could attenuate the proliferative rate of CRC cells. Moreover, the mRNA levels of LSD1 and EZH2 were positively correlated with DUXAP8 in CRC. CONCLUSIONS: LncRNA DUXAP8 accelerates the malignant progression of CRC via positively regulating EZH2 and LSD1.