Delayed Bladder Perforation Resulting From Large Bladder Stone and Gluteal Abscess Caused by Pelvic Plate Loosening: A Case Report.

Delayed bladder injuries resulting from screw or plate loosening, following pelvic ring fractures are rare, and this complication could be prevented. A 63-year-old woman presented with dysuria and lower abdominal pain, 13 years after the open fixation of a pelvic injury. Computed tomography revealed a 5-cm bladder stone and two migrated screws. Six months after the stone was removed, an abscess was noted over the left gluteal region. During the removal of the screw and abscess debridement, we accidentally observed that the anterior pelvic bridge plate had eroded into the bladder and had multiple bladder stones attached. After the involved hardware was removed, the abscess was debrided and the bladder was repaired. The patient did not have further urinary tract infections or urinary symptoms. In patients with pelvic ring fractures, we recommend placing the bridge plate on the superior side of the pubic symphysis to reduce the risk of bladder perforation in the event of plate or screw loosening. When a patient with a history of pelvic fixation presents with symptoms such as urinary tract infections, bladder stones, or even an abscess around the gluteal region, possible bladder perforation caused by the loosening of plates or screws should be considered.

Application of machine learning and natural language processing for predicting stroke-associated pneumonia.

Background: Identifying patients at high risk of stroke-associated pneumonia (SAP) may permit targeting potential interventions to reduce its incidence. We aimed to explore the functionality of machine learning (ML) and natural language processing techniques on structured data and unstructured clinical text to predict SAP by comparing it to conventional risk scores. Methods: Linked data between a hospital stroke registry and a deidentified research-based database including electronic health records and administrative claims data was used. Natural language processing was applied to extract textual features from clinical notes. The random forest algorithm was used to build ML models. The predictive performance of ML models was compared with the A2DS2, ISAN, PNA, and ACDD4 scores using the area under the receiver operating characteristic curve (AUC). Results: Among 5,913 acute stroke patients hospitalized between Oct 2010 and Sep 2021, 450 (7.6%) developed SAP within the first 7 days after stroke onset. The ML model based on both textual features and structured variables had the highest AUC [0.840, 95% confidence interval (CI) 0.806-0.875], significantly higher than those of the ML model based on structured variables alone (0.828, 95% CI 0.793-0.863, P = 0.040), ACDD4 (0.807, 95% CI 0.766-0.849, P = 0.041), A2DS2 (0.803, 95% CI 0.762-0.845, P = 0.013), ISAN (0.795, 95% CI 0.752-0.837, P = 0.009), and PNA (0.778, 95% CI 0.735-0.822, P < 0.001). All models demonstrated adequate calibration except for the A2DS2 score. Conclusions: The ML model based on both textural features and structured variables performed better than conventional risk scores in predicting SAP. The workflow used to generate ML prediction models can be disseminated for local adaptation by individual healthcare organizations.

[The nursing experience of caring for a sexual assault victim].

The more advancements in technology, the more temptations there are for teenagers on the Internet. Despite satisfying the fancies of juveniles, the Internet predisposes them to many kinds of danger. In this article, a seventeen-year-old girl met a net pal on the Internet, went out with him out of curiosity, and was sexual assaulted. The Roy's adaptation model was applied to the victim. Further, all data were collected by observation and conversation in the emergency room, during routine outpatient follow-up and through phone conversations from April, 27, 2006 to June, 1, 2006. Sleep pattern disturbance, situational low self-esteem, impaired social interaction, and Rape-trauma syndrome were diagnosed after nursing assessment. In accordance with these diagnoses, individualized nursing implementation was performed, including encouraging her to express herself, listening to her patiently, and providing her with support as well as social welfare resources. Finally, the victim was assisted not only to overcome the dark shadow of her assault but to develop a positive attitude and set a new goal through the cooperation of her family, our medical group, and herself. This nursing experience may provide some helpful information for us to share in caring for such cases.