Computational methods to predict and enhance decision-making with biomedical data.

The proposed research applies machine learning techniques to healthcare applications. The core ideas were using intelligent techniques to find automatic methods to analyze healthcare applications. Different classification and feature extraction techniques on various clinical datasets are applied. The datasets include: brain MR images, breathing curves from vessels around tumor cells during in time, breathing curves extracted from patients with successful or rejected lung transplants, and lung cancer patients diagnosed in US from in 2004-2009 extracted from SEER database. The novel idea on brain MR images segmentation is to develop a multi-scale technique to segment blood vessel tissues from similar tissues in the brain. By analyzing the vascularization of the cancer tissue during time and the behavior of vessels (arteries and veins provided in time), a new feature extraction technique developed and classification techniques was used to rank the vascularization of each tumor type. Lung transplantation is a critical surgery for which predicting the acceptance or rejection of the transplant would be very important. A review of classification techniques on the SEER database was developed to analyze the survival rates of lung cancer patients, and the best feature vector that can be used to predict the most similar patients are analyzed

Serum thyroid stimulating hormone, total and free T4 during the neonatal period: Establishing regional reference intervals

Context: Congenital hypothyroidism (CH), the most common etiology of preventable mental retardation in children, is estimated to be more prevalent among Asian population. Aims: Since thyroid function tests (TFTs) varied among different ages and geographical regions, in this study, the neonatal thyroid reference intervals in a healthy neonatal population is determined for the first time in Iran. Settings and Design: A cross-sectional study performed on 246 healthy term newborns aged between 2 days and 1 month. Materials and Methods: Blood samples were obtained by venipuncture from all subjects. The median, 2.5 th , 5 th , 95 th , and 97.5 th percentile of serum thyroid-stimulating hormone (TSH), as well as the total and free T4 were assessed among different age groups. Statistical Analysis Used: Predictive Analytics Software (PASW Statistics 18) was used for the analysis. Results: Serum TSH, total and free T4 concentration peaked in 5 th to 7 th days of life, continued over 2 weeks, then decreased and started reaching to adult reference range. A significant negative correlation between age and serum concentration of TSH (P = 0.02), total T4 (P = 0.01) and free T4 (P = 0.01) was found. Conclusion: This study yielded fairly different values for TFTs compared compared values found in other countries and also different from values reported for laboratory kits we used. These differences were assumed to be due to variations in ethnicity, age, and laboratory methods used. Due to the lack of international standardization, conducting multicenter studies helps in making a more precise evaluation of thyroid status in neonates

Problems in Diagnosis and Treatment of Retrorectal Tumors: Our Experience in 50 Patients

Retrorectal tumors are rare lesions in adults, which remains a difficult diagnostic and management problem. The purpose of this study was to evaluate the results of surgical management of retrorectal tumors in our institution. In a retrospective study, a consecutive series of patients who underwent surgical excision of a retrorectal tumor were identified from a database. Medical records, radiology, pathology reports and surgical approach were checked retrospectively. The data was analyzed using SPSS statistical software (version 18). From 50 patients, 24 were male, and 26 were female with the mean age of 41.7 years. The origin of mass was congenital in 46% (23 cases) and neurogenic in 14% (7 patients), bone origin in 12% (6 cases) and miscellaneous in 24% (12 cases). In total, 56.7% (21 cases) were malignant. Surgical approaches included laparotomy in 11 cases, the sacral approach in 17 cases, the anterior-posterior approach in 14 cases and one case through abdomino-sacral approach. The mean follow-up was 56.7 (10-277) month. Ten patients died due to extensive metastases with a mean survival of 46.6 (1-158) months. Primary urethrorectal tumors are very rare. Successful treatment of these tumors requires careful clinical evaluation and expertise in pelvic surgery

Status of immunity against PVB19 in HIV-infected patients according to CD4 + cell count, and antiretroviral therapy regimen groups

Background: Human Parvovirus B19 (PVB19) is among the aetiology of aplastic crisis in human immunodeficiency virus (HIV)-infected patients. Several studies have indicated the importance of an infection agent in bringing about complications in immuno-compromised patients. The current study aims to determine the seroprevalence of IgM and IgG antibodies to PVB19 among HIV-positive patients and its association with clinical and epidemiological factors. Materials and Methods: In a case control study, 90 HIV-positive patients were compared with 90 sex and age matched healthy controls in terms of anti-PVB19 IgG and IgM along with other primary clinical and laboratory features. Results: The overall prevalence of positive anti-PVB19 IgG among HIV patients and controls were 81.1% and 28.9%, respectively (P < 0.001). None of the subjects showed positive results for anti-PVB19 IgM. Patients with CD4 + cell count <200 showed higher seroprevalence of positive anti-PVB19 IgG which did not reach statistically significant. However, anti-PVB19 IgG seropositivity differed significantly between HIV patients on different regimens of antiretroviral therapy (ART) (P < 0.05). Conclusion: Immunity against PVB19 is more prevalent among HIV-positive patients compared to healthy controls. However, positive HIV status is not associated with acute PVB19 infection. The presence of anti-PVB19 IgG does not necessarily protect the body from further complications like anaemia. Given the results of the study, AIDS patients are recommended to undergo screening for parvovirus antibody in order to prevent complications like aplastic anaemia

Epidemiological study of suicidal patients referred to Kowsar Hospital in Semnan

Introduction: Suicide is one of the public health challenges which affect the individual, family, and even society. Because of the fact that accurate data collection on suicide attempts in different population areas is necessary, this study was conducted to determine the epidemiological and demographic characteristics of suicidal patients in Semnan, Iran. Materials and Methods: The present descriptive-retrospective study was performed on the clinical files of 809 suicidal patients referred to Kowsar Hospital in Semnan during 2015–2018. Using a checklist, biographical information, and marital status, suicide methods, physical diseases, previous psychiatric diseases, causes of suicide, and outcomes of suicide were collected, and then, the data were analyzed using EXCEL software. Results: Out of 809 subjects, 27% had a history of chronic psychiatric diseases, 1% of the statistical population (12 people) died, and 99% of the people (797 people) survived. The prevalence of suicide attempts was higher among women, single people, housewives, and people in the age group of 18–24 years. Family issues have been cited as the cause of 495 cases (61%) of suicide attempts in our study. Conclusion: Since suicide attempts are more common among young single women because of family issues, this important issue should be given more attention by health policy makers in Semnan province

Euglycemic diabetic ketoacidosis and COVID‐19 management in a term pregnant patient; a case report

Abstract In this case report, we report a Covid‐19 infected female patient with gestational diabetes mellitus with primary manifestation of ketoacidosis at term pregnancy and discuss the management challenges with euglycemia and a high ketone burden

Bladder cancer prognosis using deep neural networks and histopathology images

Background: Recent studies indicate that bladder cancer is among the top 10 most common cancers in the world (Saginala et al. 2022). Bladder cancer frequently reoccurs, and prognostic judgments may vary among clinicians. As a favorable prognosis may help to inform less aggressive treatment plans, classification of histopathology slides is essential for the accurate prognosis and effective treatment of bladder cancer patients. Developing automated and accurate histopathology image analysis methods can help pathologists determine the prognosis of patients with bladder cancer. Materials and methods: In this study, we introduced Bladder4Net, a deep learning pipeline, to classify whole-slide histopathology images of bladder cancer into two classes: low-risk (combination of PUNLMP and low-grade tumors) and high-risk (combination of high-grade and invasive tumors). This pipeline consists of four convolutional neural network (CNN)-based classifiers to address the difficulties of identifying PUNLMP and invasive classes. We evaluated our pipeline on 182 independent whole-slide images from the New Hampshire Bladder Cancer Study (NHBCS) (Karagas et al., 1998; Sverrisson et al., 2014; Sverrisson et al., 2014) collected from 1994 to 2004 and 378 external digitized slides from The Cancer Genome Atlas (TCGA) database (https://www.cancer.gov/tcga). Results: The weighted average F1-score of our approach was 0.91 (95% confidence interval (CI): 0.86–0.94) on the NHBCS dataset and 0.99 (95% CI: 0.97–1.00) on the TCGA dataset. Additionally, we computed Kaplan–Meier survival curves for patients who were predicted as high risk versus those predicted as low risk. For the NHBCS test set, patients predicted as high risk had worse overall survival than those predicted as low risk, with a log-rank p-value of 0.004. Conclusions: If validated through prospective trials, our model could be used in clinical settings to improve patient care