RESUMEN
Background: The increasing incidence and prevalence of breast malignancies have led to increasing numbers of surgical interventions performed on the axilla and breast, including axillary lymph node dissection (ALND), sentinel lymph node biopsy (SLNB), and mastectomy. The risk of postoperative complications, like breast cancer-related lymphoedema (BCRL), can have significant deleterious cosmetic and quality of life effects. National guidelines and cancer councils publish recommendations to avoid skin puncturing procedures, such as venepuncture and intravenous (IV) cannulation, on arms ipsilateral to the surgical site to prevent BCRL occurrence. The initial trials that established a link between BCRL and skin puncture were conducted in the 1950s and 1960s; the evolution of surgical management of breast cancer has likely led to large decreases in complication rates. Methods: Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, four databases were systematically searched for relevant articles. Eleven relevant articles were identified for inclusion in the final analysis. Updated Australian and New Zealand College of Anaesthetists & Faculty of Pain Medicine (ANZCA) guidelines were included in the analysis following their publication after the initial search had been completed. Results: The overall quality and quantity of evidence in this field is sufficient to conclude that skin puncturing procedures on ipsilateral arms should not be avoided in patients with previous breast or axillary surgery. The highest-quality and most recent available evidence does not support an association between BCRL and skin puncturing procedures. Policies and practices that advocate avoiding skin puncture procedures to prevent BCRL may lead to delays in clinical care. The 2023 ANZCA guidelines recommend against avoiding affected arms for peripheral access and suggest the removal of institutional policies preventing this practice. Conclusions: In patients that have undergone breast surgery or axillary procedures, venous access procedures can be safely performed on the ipsilateral arm. The evidence does not support overarching restrictions on using the ipsilateral arm without pre-existing lymphoedema.
RESUMEN
Similarity-based search of sequence collections is a core task in bioinformatics, one dominated for most of the genomic era by exact and heuristic alignment-based algorithms. However, even efficient heuristics such as BLAST may not scale to the data sets now emerging, motivating a range of alignment-free alternatives exploiting the underlying lexical structure of each sequence. In this paper, we introduce two supervised approaches-SuperVec and SuperVecX-to learn sequence embeddings. These methods extend earlier Representation Learning (RepL) based methods to include class-related information for each sequence during training. Including class information ensures that related sequence fragments have proximal representations in the target space, better reflecting the structure of the domain. We show the quality of the embeddings learned through these methods on (i) sequence retrieval and (ii) classification tasks. We also propose an hierarchical tree-based approach specifically designed for the sequence retrieval problem. The resulting methods, which we term H-SuperVec or H-SuperVecX, according to their respective use of SuperVec or SuperVecX, learn embeddings across a range of feature spaces based on exclusive and exhaustive subsets of the class labels. Experiments show that the proposed methods perform better for retrieval and classification tasks over existing (unsupervised) RepL-based approaches. Further, the new methods are an order of magnitude faster than BLAST for the database retrieval task, supporting hybrid approaches that rapidly filter the collection so that only potentially relevant records remain. Such filtering of the original database allows slower but more accurate methods to be executed quickly over a far smaller dataset. Thus, we may achieve faster query processing and higher precision than before.