Outcomes of Breast Conserving Surgery With Immediate Vicryl‐Mesh Insertion: Is It Safe And Effective?

Although breast-conserving surgery (BCS) has become a standard for breast-cancer surgery with improved cosmetic outcomes, there have been many attempts to achieve superior results. Vicryl-mesh insertion, one such method, is a simple technique involving a relatively short period of time. However, doubts regarding its safety and efficacy remain. Therefore, we attempted to analyze the aesthetic outcomes, patient satisfaction, and safety with respect to Vicryl mesh. From May 2007 to March 2009, 38 patients underwent BCS with immediate Vicryl-mesh insertion at Ewha Womans University Mokdong Hospital, Seoul, Korea. In the same period, 31 patients who underwent BCS for breast cancer were randomly selected as a control group. Five patients who underwent BCS with Vicryl-mesh insertion were excluded because they were lost to follow-up shortly after surgery. Retrospective analysis of patient records and oral interviews were performed. We analyzed patients' overall satisfaction, postoperative satisfaction with breast shape, pain, and postoperative complications in the two groups. The mean age, body mass index, follow-up period, specimen size, and ratio of benign to malignant tumors did not differ significantly between the two groups. With regard to tumor location, more tumors were in the upper and lower inner portions of the breast among patients who underwent BCS with Vicryl mesh. There were no significant differences in overall satisfaction or satisfaction with breast shape (p > 0.05), but differences in pain scores were significant (p = 0.016). In terms of the complication rate, four cases with complications (11.8%) were observed in the Vicryl-mesh group and no complications in the BCS-only group. Vicryl-mesh insertion showed a higher complication rate and no cosmetic gain. Therefore, we believe that Vicryl-mesh insertion should be performed carefully. In addition, studies involving many more cases and longer follow-up periods are needed.     

Evaluation of burn severity in vivo in a mouse model using spectroscopic optical coherence tomography

Clinical management of burn injuries depends upon an accurate assessment of the depth of the wound. Current diagnostic methods rely primarily on subjective visual inspection, which can produce variable results. In this study, spectroscopic optical coherence tomography was used to objectively evaluate burn injuries in vivo in a mouse model. Significant spectral differences were observed and correlated with the depth of the injury as determined by histopathology. The relevance of these results to clinical burn management in human tissues is discussed.OCIS codes: (170.6510) Spectroscopy, tissue diagnostics; (110.4500) Optical coherence tomography     

Automatically Detecting Failures in Natural Language Processing Tools for Online Community Text

Background

The prevalence and value of patient-generated health text are increasing, but processing such text remains problematic. Although existing biomedical natural language processing (NLP) tools are appealing, most were developed to process clinician- or researcher-generated text, such as clinical notes or journal articles. In addition to being constructed for different types of text, other challenges of using existing NLP include constantly changing technologies, source vocabularies, and characteristics of text. These continuously evolving challenges warrant the need for applying low-cost systematic assessment. However, the primarily accepted evaluation method in NLP, manual annotation, requires tremendous effort and time.

Objective

The primary objective of this study is to explore an alternative approach—using low-cost, automated methods to detect failures (eg, incorrect boundaries, missed terms, mismapped concepts) when processing patient-generated text with existing biomedical NLP tools. We first characterize common failures that NLP tools can make in processing online community text. We then demonstrate the feasibility of our automated approach in detecting these common failures using one of the most popular biomedical NLP tools, MetaMap.

Methods

Using 9657 posts from an online cancer community, we explored our automated failure detection approach in two steps: (1) to characterize the failure types, we first manually reviewed MetaMap’s commonly occurring failures, grouped the inaccurate mappings into failure types, and then identified causes of the failures through iterative rounds of manual review using open coding, and (2) to automatically detect these failure types, we then explored combinations of existing NLP techniques and dictionary-based matching for each failure cause. Finally, we manually evaluated the automatically detected failures.

Results

From our manual review, we characterized three types of failure: (1) boundary failures, (2) missed term failures, and (3) word ambiguity failures. Within these three failure types, we discovered 12 causes of inaccurate mappings of concepts. We used automated methods to detect almost half of 383,572 MetaMap’s mappings as problematic. Word sense ambiguity failure was the most widely occurring, comprising 82.22% of failures. Boundary failure was the second most frequent, amounting to 15.90% of failures, while missed term failures were the least common, making up 1.88% of failures. The automated failure detection achieved precision, recall, accuracy, and F1 score of 83.00%, 92.57%, 88.17%, and 87.52%, respectively.

Conclusions

We illustrate the challenges of processing patient-generated online health community text and characterize failures of NLP tools on this patient-generated health text, demonstrating the feasibility of our low-cost approach to automatically detect those failures. Our approach shows the potential for scalable and effective solutions to automatically assess the constantly evolving NLP tools and source vocabularies to process patient-generated text.     

Dynamic obstruction induced by systolic anterior motion of the mitral valve in a volume-depleted left ventricle: an unexpected cause of acute heart failure in a patient with chronic obstructive pulmonary disease

Systolic anterior motion (SAM) of the mitral valve (MV) and left ventricular outflow tract (LVOT) dynamic obstruction (DO) typically occur in hypertrophic cardiomyopathy; however, they can appear in an apparently normal heart in association with changes in cardiac loading conditions and/or hyperdynamic left ventricular (LV) performance. Meanwhile, chronic obstructive pulmonary disease (COPD) can impair LV filling by elevating pulmonary vascular resistance. The authors report a case of transient acute heart failure caused by LVOT DO resulting from SAM of the MV in a severely volume-depleted LV in a patient with acute COPD exacerbation.     

Injuries Among School-aged Children of Immigrants

In response to a dearth of research on injuries among children of immigrants, this study examined child injury rates by immigrant generation. We used generalized estimating equations and nationally representative data to estimate injury risk for school-aged children of immigrants of different generations compared to children of native, US-born parents. After controlling for multiple other factors including socioeconomic status, citizenship, and children’s general health, both 1st and 2nd generation school-aged children had significantly lower odds of having injuries compared to children of natives. Additional analyses also found lower odds of injuries among 1st and 2nd generation children relative to children of natives that persisted in both lower- and higher-income families. The findings suggest that 1st and 2nd generation immigrant families possess factors that protect children from injury independent of socioeconomic status. Policy and program development would benefit from a clearer understanding of these protective factors.