This study aimed to evaluate the predictive value of long non-coding RNA (lncRNA) antisense non-coding RNA in the INK4 locus (ANRIL) for atrial fibrillation (AF) patients with ischemic stroke and investigate its correlation with risk factors, functional outcome, and prognosis.
This study assesses the high risk factors of residue or relapse after conization of cervical intraepithelial neoplasia. Literature on high risk factors of residue or relapse after conization of cervical intraepithelial neoplasia from January 2006 to June 2011 were selected from the Pubmed Database, Elsevier Database, Chinese Biomedicine Database and Chinese Journal Full-text Database of China National Knowledge Internet (CNKI). Software RevMan 4. 2 provided by Cochrane collaboration network was used in the statistical analysis of the data. According to the inclusion criteria, 10 essays were retrieved, including 348 cases in case groups and 1,608 cases in control groups. Information about residue or relapse after conization, incisal edge, HIV infection after six months of surgery, age, menopause status was obtained through the above method. Meta-analysis showed that positive surgical margin groups had a higher residual or recurrence rate than negative surgical margin groups after conization; groups where glands were involved had a higher residual or recurrence rate than non-involved glands groups after conization; positive HR-HPV infection after six months of conization groups had higher residual or recurrence rates than negative HR-HPV infection groups; 50 years or older groups had higher residual or recurrence rate than under 50 year-old groups after conization; postmenopausal groups had higher residual or recurrence rate than premenopausal groups. Menopause, 50 years old or older, gland involvement, positive surgical margin and HR-HPV infection after six months are high risk factors of residue or relapse after α - β conization of CIN.
Normal B lymphocyte function and antibody secretion during inflammation can provide critical protection for the host. We aimed to synthesize existing evidence to explore whether circulating B cells and plasma immunoglobulin M (IgM) levels were associated with survival during sepsis.PubMed, Embase, ISI Web of Knowledge, Cochrane Central Register of Controlled Trials were systematically searched. Studies with data on circulating B cells and plasma IgM levels within the initial 24 hours after sepsis onset were selected.A total of 11 studies were qualified for inclusion in this systematic review and meta-analysis with a total of 829 patients with sepsis and/or septic shock. Number of circulating B cells was similar between septic patients and health controls (SMD = -1.81, 95% CI: -4.15, 0.54; P = 0.13, I2 = 99%), while it was significantly reduced in sepsis survivors versus sepsis non-survivors (SMD = -0.60, 95% CI: -0.87, -0.32; P < 0.0001, I2 = 0%). Concentration of plasma IgM level was significantly decreased in septic patients as compared with healthy controls. Also, the plasma IgM level was significantly lower in sepsis survivors versus sepsis non-survivors.A poor prognostic survival outcome was observed for patients with decreased circulating B cells as well as IgM levels within the initial 24 h after sepsis onset.
Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive solid tumors in the digestive system. A greater understanding of the pathogenesis of PDAC may facilitate the search for new therapeutic targets. Guanine nucleotide‐binding protein subunit gamma‐12 (GNG12) belongs to the G protein family and participates in the modulation of the inflammatory signaling cascade. However, the cancer‐related function and clinical relevance of GNG12 in PDAC have not previously been reported. Here, we investigated the clinical significance of GNG12 in PDAC using the Oncomine web tool, the gene expression profiling interactive analysis tool and tissue microarray (TMA). GNG12 expression was observed to be higher in PDAC patient specimens than in nontumor pancreatic tissues, and high expression of GNG12 was associated with poor prognosis. We subsequently show that GNG12 promotes pancreatic cancer cell growth in vivo and in vitro , as evaluated using 3‐(4,5‐dimethylthiazol‐2‐yl)‐5‐(3‐carboxymethoxyphenyl)‐2‐(4‐sulfophenyl)‐2H‐tetrazolium, inner salt assays, colony formation assays and a xenograft mouse model. Furthermore, our results suggest that GNG12 activates nuclear factor‐κB signaling and modulates the immune response. Collectively, our findings suggest that GNG12 may be suitable as a new prognosis‐related biomarker and a promising target for treatment of pancreatic cancer.
Abstract Background: Sepsis-associated encephalopathy (SAE) is associated with systemic inflammation caused by sepsis. It is estimated that a majority of sepsis patients develop severe acute effects (SAE) during their stay in the intensive care unit (ICU), and a significant number of survivors have persistent cognitive impairment even after they have recovered from the illness. The aim of this study was to develop a useful predictive nomogram for patients with ICU sepsis and screen for SAE risk factors. Methods: We conducted a retrospective cohort study using the Medical Information Mart for Intensive Care IV (MIMIC-IV) database, defining SAE as a Glasgow Coma Scale (GCS) score of ≤15 or delirium. We randomly divided patients into training and validation cohorts, and used least absolute shrinkage and selection operator (LASSO) regression modeling to optimize feature selection. The independent risk factors were determined through a multivariable logistic regression analysis, and a prediction model was built. Nomogram performance was evaluated using the area under the receiver operating characteristic curve (AUC), calibration plots, Hosmer-Lemeshow test, decision curve analysis (DCA), net reclassification improvement (NRI) and integrated discrimination improvement (IDI). Results: Among 4476 sepsis patients screened, 2781 (62.1%) developed SAE. In-hospital mortality was higher in the SAE group than in the non-SAE group (9.5% vs 3.7% p<0.001). A number of variables were screened, such as the patient's age, gender, BMI on the first day of admission, the mean arterial pressure, the body temperature, the platelet count, the sodium level, and the use of midazolam. The variables that were assessed encompassed the patient's age, gender, BMI upon admission, initial mean arterial pressure, body temperature, platelet count, sodium level, utilization of midazolam, and SOFA score. These were used to construct and validate a nomogram. Comparisons between the nomogram's AUC, NRI, IDI, and DCA with those of the conventional SOFA score in conjunction with delirium revealed superior performance. The nomogram's calibration plots and the results of the Hosmer-Lemeshow test indicated accurate calibration. Enhanced NRI and IDI values demonstrated that our scoring system surpassed traditional diagnostic approaches. Furthermore, the DCA curve indicated favorable clinical applicability of the nomogram. Conclusion: This study identified independent risk factors for the development of SAE in sepsis patients and used them to construct a predictive model. The findings of this study can provide a clinical reference for the early diagnosis of SAE in patients.
Objective This study aimed to develop and validate a nomogram to predict the risk of sepsis in non-traumatic subarachnoid hemorrhage (SAH) patients using data from the MIMIC-IV database. Methods A total of 803 SAH patients meeting the inclusion criteria were randomly divided into a training set (563 cases) and a validation set (240 cases). Independent prognostic factors were identified through forward stepwise logistic regression, and a nomogram was created based on these factors. The discriminative ability of the nomogram was assessed using the area under the receiver operating characteristic curve (AUC) and compared with the SOFA score. The model’s consistency was evaluated using the C-index, and the improvement in performance over the SOFA score was calculated using integrated discrimination improvement (IDI) and net reclassification improvement (NRI). Results Five independent predictive factors were identified through LASSO regression analysis: mechanical ventilation, hyperlipidemia, temperature, white blood cell count, and red blood cell count. The AUC of the nomogram in the training and validation sets were 0.854 and 0.824, respectively, both higher than the SOFA score. NRI and IDI results indicated that the nomogram outperformed the SOFA score in identifying sepsis risk. Calibration curves and the Hosmer-Lemeshow test demonstrated good calibration of the nomogram. Decision curve analysis showed that the nomogram had higher net benefit in clinical application. Conclusion The nomogram developed in this study performed excellently in predicting the risk of sepsis in SAH patients, surpassing the traditional SOFA scoring system, and has significant clinical application value.
'/%3e%3cuse xlink:href='%23a' transform='rotate(144 450 300)'/%3e%3cuse xlink:href='%23a' transform='rotate(216 450 300)'/%3e%3cuse xlink:href='%23a' transform='rotate(288 450 300)'/%3e%3c/svg%3e)
'/%3e%3cuse xlink:href='%23a' transform='rotate(23.036 .093 25.536)'/%3e%3cuse xlink:href='%23a' transform='rotate(45.87 1.273 16.18)'/%3e%3cuse xlink:href='%23a' transform='rotate(69.945 .996 12.078)'/%3e%3cuse xlink:href='%23a' transform='rotate(20.66 -19.689 31.932)'/%3e%3c/svg%3e)
'%3e%3cg id='b'%3e%3cpath id='a' stroke='%23000' stroke-width='2' d='M-6-25H6m-12 3H6m-12 3H6'/%3e%3cuse xlink:href='%23a' y='44'/%3e%3c/g%3e%3cpath stroke='%23fff' d='M0 17v10'/%3e%3ccircle r='12' fill='%23cd2e3a'/%3e%3cpath fill='%230047a0' d='M0-12A6 6 0 0 0 0 0a6 6 0 0 1 0 12 12 12 0 0 1 0-24z'/%3e%3c/g%3e%3cg transform='rotate(-123.69)'%3e%3cuse xlink:href='%23b'/%3e%3cpath stroke='%23fff' d='M0-23.5v3M0 17v3.5m0 3v3'/%3e%3c/g%3e%3c/svg%3e)