Analysis of Risk Factors for Surgical Treatment of Acute Female Pelvic Inflammatory Disease.

AIM: To investigate the incidence and high-risk factors associated with the surgical treatment of acute female pelvic inflammatory disease (PID). METHODS: A retrospective analysis was conducted on all inpatients diagnosed with acute female PID, encompassing conditions such as endometritis, salpingitis, tubo-ovarian abscess, ovarian abscess, and pelvic peritonitis, at Dongyang Hospital of Wenzhou Medical University from January 2013 to December 2021. Patients were categorized into two groups: the surgery group (n = 58) and the non-surgery group (n = 399), based on the necessity of surgical intervention (refer to Materials and Methods for surgical indications). Collected data included patient demographics (age, body mass index (BMI)), comorbidities (hypertension, diabetes mellitus), initial laboratory findings upon admission (white blood cell count, absolute neutrophil count, hemoglobin, platelet count, blood urea nitrogen/creatinine, prothrombin time (PT), international normalized ratio (INR), fibrinogen, albumin), surgical records, and postoperative pathology. Univariate and multivariate logistic regression analyses were conducted to ascertain the risk factors associated with the surgical treatment of acute female PID. RESULTS: Out of 457 hospitalized patients with acute female PID, 58 cases (12.7%) required surgical intervention. Univariate and multivariate logistic regression analyses indicated that advancing age correlated with an increased likelihood of surgical intervention in women with acute PID (odds ratio (OR) = 1.052, 95% Confidence Interval (CI) 1.022-1.082, p = 0.001). Additionally, lower serum albumin levels upon admission were associated with a heightened risk of surgery (OR = 0.913, 95% CI 0.859-0.970, p = 0.003), while elevated fibrinogen levels amplified the risk of surgical intervention in these patients (OR = 1.193, 95% CI 1.008-1.411, p = 0.04). CONCLUSIONS: Elderly women diagnosed with acute PID, especially those presenting with abscess formation, should undergo prompt surgical intervention if they display high-risk factors such as low albumin levels and elevated fibrinogen levels upon admission.

Case report: Solitary fibrous tumor of the paracervical uterus combined with vaginal wall adenocarcinoma.

Background: Solitary fibrous tumors are rare mesenchymal tumors that typically occur in the pleura. Solitary fibrous tumors of the uterine cervix are uncommon. We report the first case of a patient who underwent total hysterectomy for vaginal wall adenocarcinoma and was found to have a concurrent solitary fibrous tumor in the paracervical-uterus. Case presentation: A 51-year-old woman was admitted to our hospital due to contact bleeding. A gynecological examination revealed nodules of 3.0 × 1.0 cm on the vaginal wall, and a colposcopy with biopsy revealed adenocarcinoma of the vaginal wall. After the recommended staging examinations, the patient underwent total hysterectomy, double adnexectomy, pelvic lymph node dissection, and vaginal wall resection. During surgery, a nodule measuring approximately 2 × 2 cm was found in the middle of the mass in the left paracervical region. Subsequent postoperative histopathological examination confirmed an solitary fibrous tumor of the uterine cervix with adenocarcinoma of the vaginal wall. The patient was followed up for 46 months after hospitalization, and no recurrence or distant metastases were observed. Conclusion: In rare cases, solitary fibrous tumors may form large masses in the cervical or vaginal wall. They can easily be misdiagnosed as benign or malignant cervical tumors before and during surgery. Postoperative pathology and immunohistochemistry are helpful for diagnosis. Most solitary fibrous cervical tumors are benign, occasionally with low malignant potential, and surgical treatment is feasible and effective.

New online dynamic nomograms to predict recurrence-free and overall survival after resection of endometrial cancer: a single-institution retrospective cohort study.

PURPOSE: The significant global burden of endometrial cancer (EC) and the challenges associated with predicting EC recurrence indicate the need for a dynamic prediction model. This study aimed to propose nomograms based on clinicopathological variables to predict recurrence-free survival (RFS) and overall survival (OS) after surgical resection for EC. METHODS: This single-institution retrospective cohort study included patients who underwent surgical resection for EC. Web-based nomograms were developed to predict RFS and OS following resection for EC, and their discriminative and calibration abilities were assessed. RESULTS: This study included 289 patients (median age, 56 years). At a median follow-up of 51.1 (range, 4.1-128.3) months, 13.5% (39/289) of patients showed relapse or died, and 10.7% (31/289) had non-endometrioid tumors (median size: 2.8 cm). Positive peritoneal cytology result (hazard ratio [HR], 35.06; 95% confidence interval [CI], 1.12-1095.64; P = 0.0428), age-adjusted Charlson comorbidity index (AACCI) (HR, 52.08; 95% CI, 12.35-219.61; P < 0.001), and FIGO (Federation of Gynecology and Obstetrics) stage IV (HR, 138.33; 95% CI, 17.38-1101.05; P < 0.001) were predictors of RFS. Similarly, depth of myometrial invasion ≥ 1/2 (HR, 1; 95% CI, 0.46-2.19; P = 0.995), AACCI (HR, 93.63; 95% CI, 14.87-589.44; P < 0.001), and FIGO stage IV (HR, 608.26; 95% CI, 73.41-5039.66; P < 0.001) were predictors of OS. The nomograms showed good predictive capability, positive discriminative ability, and calibration (RFS: 0.895 and OS: 0.891). CONCLUSION: The nomograms performed well in internal validation when patients were stratified into prognostic groups, offering a personalized approach for risk stratification and treatment decision-making.

Differences of characteristics, influencing factors, and treatment effects on the survival in patients with first and second primary cervical cancer.

To explore the characteristics, influencing factors, and effect of different treatments on the survival in patients with first primary cervical cancer (CC) and second primary CC. Data of 33,934 eligible patients with CC were extracted from the Surveillance, Epidemiology, and End Results (SEER) database in 2004-2015. We also included 176 patients with CC from the Affiliated Dongyang Hospital of Wenzhou Medical University. Univariate and multivariate Cox proportional hazard models were used to screen the potential influencing factors associated with the survival in patients with hazard ratios (HRs) and 95 % confidence intervals (CIs). Subgroup analyses of age, American Joint Committee on Cancer (AJCC) stages, tumor grades and histologic types were conducted to explore the association between different treatments and survival in different populations. The 5-year mortality was 43.08 % for patients with first primary CC and that was 58.13 % for patients with second primary CC. We found that the relationships between age, histologic type, tumor grade, tumor size, AJCC tumor-node-metastasis (TNM) stage, surgery, chemotherapy, radiotherapy and the first primary CC and second primary CC were different (all P < 0.05). Additionally, the results of subgroup analyses indicated that the choice of surgery, chemotherapy, and radiotherapy should be adjusted according to the different health conditions of the patients. In conclusion, the causal relationship between characteristics, influencing factors, and treatments and survival in patients with primary CC diagnosed as different time periods are needed further exploration.

Effects of peripheral blood neutrophil/lymphocyte ratio levels and their changes on the prognosis of patients with early cervical cancer.

Although some studies have reported on the levels and clinical significance of peripheral blood neutrophil/lymphocyte ratio (NLR) in cervical cancer, the role of NLR levels and their changes preoperatively and postoperatively in early cervical cancer remain unclear. Our analyses explored the preoperative and postoperative NLR in 203 patients with stage I-IIA cervical cancer and evaluated the relationship between NLR changes, clinicopathological characteristics, and patient prognosis. The cut-off preoperative and postoperative NLR values were determined using receiver operating characteristic curve analysis. Preoperative NLR correlated with age, menopausal status, tumor size, and vascular infiltration, whereas postoperative NLR correlated with tumor differentiation. Patients with cervical cancer with a high preoperative NLR had significantly shorter overall survival (OS) and progression-free survival (PFS) than other patients, whereas PFS was significantly lower in the high postoperative NLR group. When comparing postoperative and preoperative NLR values, we observed a significantly higher rate of increase in postmenopausal patients and those without vascular infiltration than that among premenopausal patients and those with vascular infiltration. However, no clear difference in prognosis was observed between the groups with increased and decreased NLR. Therefore, a high peripheral blood NLR may predict a poor prognosis in patients with early cervical cancer. The effect of NLR changes on the prognosis of patients with cervical cancer requires further verification in multicenter studies.

Case report: Superficial cervicovaginal myofibroblastoma of the cervix with endometrial carcinoma.

Introduction: A superficial cervical vaginal myofibroblastoma is a rare mesenchymal tumor, originating from the superficial stroma of the vagina and cervix. This study reports a patient, who was diagnosed with endometrioid carcinoma and a concomitant benign superficial cervicovaginal myofibroblastoma. Case presentation: A 53-year-old female with endometrial carcinoma was admitted to the Department of Gynecology of our hospital. She had a history of breast cancer on May 23, 2010, and took toremifene citrate for 41 months. Radical resection of the endometrial carcinoma was performed at our hospital. Based on the pathological findings, she was postoperatively diagnosed with endometrial adenocarcinoma with superficial cervical vaginal myofibroblastoma. The patient continued receiving postoperative breast cancer treatment. She underwent follow-up for 23 months. No recurrence or metastasis of the endometrial cancer or superficial cervical vaginal myofibroblastoma was observed. Conclusion: There were similarities between superficial cervical vaginal myofibroblastoma and other mesenchymal tumors of the female genital tract. Superficial cervical vaginal myofibroblastomas have a good prognosis, and the combination of tissue morphology and immunohistochemistry helped establish a definitive diagnosis.

Ordinal Pattern: A New Descriptor for Brain Connectivity Networks.

Brain connectivity networks based on magnetic resonance imaging (MRI) or functional MRI (fMRI) data provide a straightforward way to quantify the structural or functional systems of the brain. Currently, there are several network descriptors developed for representing and analyzing brain connectivity networks. However, most of them are designed for unweighted networks, regardless of the valuable weight information of edges, or do not take advantage of the ordinal relationship of weighted edges (even though they are designed for weighted networks). In this paper, we propose a new network descriptor (i.e., ordinal pattern that contains a sequence of weighted edges) for brain connectivity network analysis. Compared with previous network properties, the proposed ordinal patterns cannot only take advantage of the weight information of edges but also explicitly model the ordinal relationship of weighted edges in brain connectivity networks. We further develop an ordinal pattern-based learning framework for brain disease diagnosis using resting-state fMRI data. Specifically, we first construct a set of brain functional connectivity networks, where each network is corresponding to a particular subject. We then develop an algorithm to identify ordinal patterns that frequently appear in brain connectivity networks of patients and normal controls. We further perform discriminative ordinal pattern selection and extract feature representations for subjects based on the selected ordinal patterns, followed by a learning model for automated brain disease diagnosis. Experimental results on both Alzheimer's Disease Neuroimaging Initiative and attention deficit hyperactivity disorder-200 data sets demonstrate that our method outperforms the several state-of-the-art approaches in the tasks of disease classification and clinical score regression.

Network-based classification of ADHD patients using discriminative subnetwork selection and graph kernel PCA.

BACKGROUND: Attention Deficit Hyperactivity Disorder (ADHD) is one of the most prevalent behavioral disorders in childhood and adolescence. Recently, network-based diagnosis of ADHD has attracted great attentions due to the fact that ADHD disease is related to not only individual brain regions but also the connections among them, while existing methods are hard to discover disorder patterns related with several brain regions. NEW METHOD: To overcome this drawback, a discriminative subnetwork selection method is proposed to directly mine those frequent and discriminative subnetworks from the whole brain networks of ADHD and normal control (NC) groups. Then, the graph kernel principal component (PCA) is applied to extract features from those discriminative subnetworks. Finally, support vector machine (SVM) is adopted for classification of ADHD and NC subjects. RESULTS: We evaluate the performances of our proposed method using the ADHD200 dataset, which contains 118 ADHD patients and 98 normal controls. The experimental results show that our proposed method can achieve a very high accuracy of 94.91% for ADHD vs. NC classification. Moreover, our proposed method can also discover the discriminative subnetworks as well as the discriminative brain regions, which are helpful for enhancing our understanding of ADHD disease. COMPARISON WITH EXISTING METHOD(S): The accuracy of our proposed method is 9.20% higher than those of the state-of-the-art methods. CONCLUSIONS: A lot of experiments in ADHD200 dataset show that, our proposed method can improve the performance significantly comparing to the state-of-the-art methods.