RESUMEN
Urethral duplication is a very rarely observed congenital anomaly, mostly affecting the males. This case report highlights the management of two patients diagnosed with Type II A, Y-type urethral duplication. An 11-year-old boy was diagnosed with Type II A of Y-type urethral duplication, where the dorsal urethra was completely hypoplastic, and the ventral urethra was communicating with rectum. After the failure of a single-stage inner preputial pedicled tube urethroplasty, a perineoscrotal flap urethroplasty was done, and at present, the patient is waiting for the 2nd stage of surgery. Case 2 is a 14-year-old boy diagnosed with Type II A2, Y-type urethral duplication, where the dorsal urethra at proximal part was hypoplastic with normal caliber of penile urethra, and the ventral urethra was communicating with rectum. The boy was treated with end-to-end urethroplasty, and good surgical outcome was observed. The purpose of this case report is to discuss the management of unusual form of Y-type urethral duplication by staging the surgical procedure.
RESUMEN
BACKGROUND: Patient stratification is a critical task in clinical decision making since it can allow physicians to choose treatments in a personalized way. Given the increasing availability of electronic medical records (EMRs) with longitudinal data, one crucial problem is how to efficiently cluster the patients based on the temporal information from medical appointments. In this work, we propose applying the Temporal Needleman-Wunsch (TNW) algorithm to align discrete sequences with the transition time information between symbols. These symbols may correspond to a patient's current therapy, their overall health status, or any other discrete state. The transition time information represents the duration of each of those states. The obtained TNW pairwise scores are then used to perform hierarchical clustering. To find the best number of clusters and assess their stability, a resampling technique is applied. RESULTS: We propose the AliClu, a novel tool for clustering temporal clinical data based on the TNW algorithm coupled with clustering validity assessments through bootstrapping. The AliClu was applied for the analysis of the rheumatoid arthritis EMRs obtained from the Portuguese database of rheumatologic patient visits (Reuma.pt). In particular, the AliClu was used for the analysis of therapy switches, which were coded as letters corresponding to biologic drugs and included their durations before each change occurred. The obtained optimized clusters allow one to stratify the patients based on their temporal therapy profiles and to support the identification of common features for those groups. CONCLUSIONS: The AliClu is a promising computational strategy to analyse longitudinal patient data by providing validated clusters and by unravelling the patterns that exist in clinical outcomes. Patient stratification is performed in an automatic or semi-automatic way, allowing one to tune the alignment, clustering, and validation parameters. The AliClu is freely available at https://github.com/sysbiomed/AliClu.
Asunto(s)
Algoritmos , Análisis por Conglomerados , Registros Electrónicos de Salud , Humanos , Estudios Longitudinales , Factores de TiempoRESUMEN
Complications following supracondylar fracture of humerus are well-known. Pre- and post-operative complications have been documented in the literature. Neurovascular injury due to fracture fragments following this type of fracture is described. Iatrogenic brachial artery during surgical treatment of this fracture is unknown to the literature. So we report a rare case of iatrogenic brachial artery injury during pinning of supracondylar fracture of humerus and try to create awareness to the surgeons that such injuries can occur with improper operative techniques.