Editor: Deborah Sesok-Pizzini, MD, MBA, chief medical officer, Labcorp Diagnostics, Burlington, NC, and adjunct professor, Department of Clinical Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia.
Reassessment of the impact and significance of social media on pathology
August 2024—Social media, including websites and platforms such as Facebook, Instagram, and X (formerly Twitter), are a dominant way to consume news and entertainment and have significant societal impact. Social media use in medicine, including pathology, is widespread and has been associated with numerous benefits. The medical industry generally has encouraged the professional use of social media, despite its potential harm. The approaches of various medical disciplines to social media have included support for early adoption, publication of how-to guides, enthusiastic backing by professional organizations, and formulation of guidelines to temper usage. The authors conducted a study to identify motivating forces and premises that underpin physicians’ adoption of social media for professional uses. They also sought to characterize how the intended use of social media in medicine for professional purposes intersected with the properties of social media platforms (SMPs). The authors reviewed literature that described professional social media use in pathology and other medical specialties, which they obtained via relevant keyword searches in PubMed, Google Scholar, Dimensions, and Web of Science. They also examined the business, technology, and social sciences literature and high-quality gray literature—that is, newspapers, books, and blogs—that addressed questions in relation to social media adoption for professional use. The authors then examined domains or aspects of social media use, including professional recognition, enhancement of Internet discourse, educational use, scientific communication, and medical professionalism. They showed that positive aspects of social media include its ability to connect physicians of different disciplines, provide a window into their workings, supply useful broadcast tools, and foster a sense of community. They also determined that the pathology social media community should be commended for focusing on education and a welcoming attitude toward trainees and for carefully and thoughtfully avoiding the polarization and activism noted in some other specialties. The authors identified six major premises as motivators of professional social media use: (1) Trainees and pathologists stand to make significant gains from participating in SMPs. (2) Professional participation in SMPs adds to the richness of social media. (3) Social media communication is not much different from scientific communication and can sometimes take its place. (4) Social media generates advantages through opportunities for networking. (5) Physician and trainee careers can remain unimpacted by the activism and controversy that trend on social media. (6) Medical professionalism must evolve to accommodate the needs of a physician workforce using social media. The authors showed that the harms of using social media in a professional capacity have not been fully addressed in medical literature and that a change in direction and the creation of new communication platforms would benefit the social media community. They noted that medical literature generally views social media use favorably and advocates for it. When the authors examined social media use outside of medicine, they encountered evidence and opinions that were more widely critical of adopting it. The authors concluded that after reviewing their premises, physicians should not withdraw from an online presence. However, they suggested that physicians should lead the charge in creating social media venues that best suit their professional needs.
Chen SJT, Samuelson MI, Rajan A. A reassessment of the impact and significance of social media to pathology. Arch Pathol Lab Med. 2024;148:613–622.
Correspondence: Dr. Anand Rajan at anand-rajand@uiowa.edu
Use of flow cytometry to detect and quantify Babesia species intraerythrocytic parasites
Babesiosis is an infectious disease caused by a parasite of the genus Babesia. It is primarily transmitted through tick vectors (Ixodes scapularis) after being acquired from mammalian reservoirs. Babesia can also be transmitted by blood transfusion, but this is less common. Human infections are primarily associated with B. microti, B. cenatorum, B. duncani, B. divergens, and M01-type Babesia species. B. microti is the most common species in the United States, and 95 percent of these cases occur in the Northeast or Upper Midwest regions. The diagnosis of babesios is primarily based on clinical evidence and risk factors, such as travel to endemic areas or a recent tick bite. Microscopic examination of thick and thin Giemsa-stained blood films is the gold standard for detecting and quantifying the Babesia parasite and diagnosing babesiosis. Molecular methods are limited in their ability to quantify percent parasitemia, which is needed to monitor treatment efficacy. Babesia serology testing is not recommended for diagnosing acute infection. Recent studies have shown that automated fluorescence flow cytometry (FLC) is a potential alternative for detecting and quantifying Plasmodium parasites. The authors conducted a study to apply the novel FLC method to detecting and quantifying Babesia parasites in venous blood and compare results to light microscopy and molecular polymerase chain reaction methods. They used an automated hematology analyzer (Sysmex XN-31) to detect and quantify B. microti-infected RBCs from residual venous blood samples (n=250; Babesia positive, n=170; Babesia negative, n=80). Qualitative and quantitative machine learning algorithms were developed for the analysis because automated instrument software is not available for diagnosing Babesia. The authors compared the results of the FLC-based analysis to the gold standard light microscopy test and molecular-based tests to determine performance characteristics. The results showed that the FLC machine learning models, when applied to the Babesia-infected samples, had an area under the curve (AUC) of 0.956 (sensitivity of 95.9 percent and specificity of 83.3 percent) relative to polymerase chain reaction. In evaluating the valid scattergrams, the qualitative model had an AUC of 1.0 (sensitivity and specificity of 100 percent), while the quantitative model demonstrated an AUC of 0.986 (sensitivity of 94.4 percent and specificity of 100 percent). The authors demonstrated in this study that the Sysmex XN-31 analyzer can detect and quantify Babesia-infected RBCs in a rapid automated fashion. They noted that several samples resulted in indeterminant status and these low-level parasitemia samples could not be quantified directly. The authors concluded that a combination of quantitative and qualitative data-analysis methods could be used to diagnose Babesia in most of the samples analyzed. This study focused on the clinical utility of this method but not on key performance indicators, such as precision, accuracy, and reproducibility, all of which need to be considered in future studies.
Vanderboom PM, Misra A, Rodino KG, et al. Detection and quantification of Babesia species intraerythrocytic parasites by flow cytometry. Am J Clin Pathol. 2024;161:451–462.
Correspondence: Dr. Andrew P. Norgan at norgan.andrew@mayo.edu