Radiation-induced diarrhea is frequently observed during pelvic radiotherapy. This study was performed to determine the ability of a probiotic containing live lactobacillus acidophilus plus bifidobacterium bifidum to reduce the incidence of radiation-induced diarrhea in locally advanced cervical cancer patients.

Background. The identification of risk factors for in utero and intrapartum transmission of human immunodeficiency virus type 1 (HIV-1) is crucial to the design and understanding of preventive interventions.

The most common cause of long-term disability and death in young adults is a traumatic brain injury. The decision for surgical intervention for craniotomy is dependent on the injury type and the patient's neurologic exam. The potential subtypes of intracranial hemorrhage that may necessitate surgical intervention include subdural hemorrhage, epidural hemorrhage, and intraparenchymal hemorrhage. We proposed a novel automatic method for segmenting the hemorrhage subtypes on a CT scan by integrated CT scan with bone window as input of a deep learning model. Brain CT scans were collected from adult patients and annotated regions of subdural hemorrhage, epidural hemorrhage, and intraparenchymal hemorrhage by neuroradiologists. Their raw DICOM images were preprocessed by two different window settings i.e., subdural and bone windows. The collected CT scans were divided into two datasets namely training and test datasets. A deep-learning model was modified to segment regions of each hemorrhage subtype. The model is a three-dimensional convolutional neural network including four parallel pathways that process the input at different resolutions. It was trained by a training dataset. After the segmentation result was produced by the deep-learning model, it was then improved in the post-processing step. The size of the segmented lesion was considered, and a region-growing algorithm was applied. We evaluated the performance of the proposed method on the test dataset. The method reached the median Dice similarity coefficients higher than 0.37 for each hemorrhage subtype. The proposed method demonstrates higher Dice similarity coefficients and improved segmentation performance compared to previously published literature.

Background: Delirium in traumatic brain injury (TBI) is common, may be predictable, and has a multifaceted symptom complex. This study aimed to examine: 1) the sum score of Glasgow Coma Scale (GCS) and if its component scores could predict delirium in TBI patients, and 2) the prominent symptoms and their courses over the first days after TBI. Methods: TBI patients were recruited from neurosurgical ward inpatients. All participants were hospitalized within 24 hours after their TBI. Apart from the sum score of GCS, which was obtained at the emergency department (ED), the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, diagnostic criteria for delirium were applied daily. The severity of delirium symptoms was assessed daily using the Delirium Rating Scale – Revised-98 (DRS-R-98). Results: The participants were 54 TBI patients with a mean GCS score of 12.7 (standard deviation [SD] =2.9). A total of 25 patients (46.3%) met the diagnosis of delirium and had a mean age of 36.7 years (SD =14.8). Compared with 29 non-delirious patients, 25 delirious patients had a significantly lower mean GCS score (P=0.04), especially a significantly lower verbal component score (P=0.03). Among 18 delirious patients, four symptoms of the DRS-R-98 cognitive domain (orientation, attention, long-term memory, and visuospatial ability) were moderate symptoms (score ≥2) at the first day of admission. After follow-up, three cognitive (orientation, attention, and visuospatial ability) and two noncognitive symptoms (lability of affect and motor agitation) rapidly resolved. Conclusion: Almost half of patients with mild to moderate head injuries may develop delirium in the first 4 days after TBI. Those having a low GCS score, especially the verbal component score, at the ED were likely to have delirium in this period. Most cognitive domains of delirium described in the DRS-R-98 were prominent within the first 4 days of TBI with delirium. Three cognitive and two noncognitive symptoms of delirium decreased significantly.