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Rationale & Objective: While the use of telemedicine has increased dramatically across disciplines, patient perspectives on telemedicine related to chronic kidney disease are not well understood. We systematically reviewed qualitative studies on patients with chronic kidney disease as well as those with kidney transplant to better understand these patients' perspectives related to telemedicine. Study Design: Qualitative meta-analysis. Setting & Participants: Pre-dialysis chronic kidney disease and kidney transplant patients that used telemedicine. Selection Criteria for Studies: English language studies published in the year 2000 and beyond that investigated patient perspectives in a qualitative manner. Works that were not qualitative or did not focus on provider-patient interactive modes of telemedicine were excluded. Data Extraction: 375 articles were pulled from PubMed, Embase, and Academic Science Premier. After filtering, 8 final articles were selected. These articles were critically appraised for quality and were used in the final analysis. Analytical Approach: We used a grounded theory approach to develop a codebook to systematically review each of the selected articles through a qualitative meta-analysis of the included literature. Results: Telemedicine was seen by patients to have notable strengths as well as weaknesses. These characteristics can be organized into 4 primary themes (autonomy, logistics, privacy/confidentiality, and trust). Within each primary theme, we identified subthemes. Universally, all articles included the subtheme "fewer trips to the health care facility" as a beneficial factor of telemedicine within the primary theme "logistics." A majority (6 of 8) of the articles included positive patient perspectives on the primary theme "autonomy" in terms of telemedicine promoting the subtheme of "engagement." Patients' views on telemedicine were mixed regarding the primary themes of "privacy/confidentiality" and "trust" related to telemedicine. Limitations: Lack of provider perspectives, non-English studies, and studies published before the year 2000. Articles published after the start of data extraction were also not included. Conclusions: Telemedicine should continue to be offered to patients with chronic kidney disease and kidney transplant patients to facilitate access. Additional research should focus on ways to decrease negative factors experienced by some patients such as difficulty using the technology.

Telemedicine is the ability to do medical visits using technology such as telephone and video calls. For this study, we researched the experiences and perspectives of patients with chronic kidney disease or kidney transplant, who often require complex, coordinated care. We found 8 articles on this topic from 6 different countries and analyzed the text of these publications to see if there were any common themes across the articles. We found 4 major themes: autonomy, logistics, privacy/confidentiality, and trust. Within each of these themes, there were positive and negative connotations to telemedicine. Overall, we feel that telemedicine should continue to be available for interested patients, and more research should be done to remove barriers to telemedicine.

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In our rapidly expanding landscape of artificial intelligence, synthetic data have become a topic of great promise and also some concern. This review aimed to provide pathologists and laboratory professionals with a primer on the role of synthetic data and how it may soon shape the landscape within our field. Using synthetic data presents many advantages but also introduces a milieu of new obstacles and limitations. This review aimed to provide pathologists and laboratory professionals with a primer on the general concept of synthetic data and its potential to transform our field. By leveraging synthetic data, we can help accelerate the development of various machine learning models and enhance our medical education and research/quality study needs. This review explored the methods for generating synthetic data, including rule-based, machine learning model-based and hybrid approaches, as they apply to applications within pathology and laboratory medicine. We also discussed the limitations and challenges associated with such synthetic data, including data quality, malicious use, and ethical bias/concerns and challenges. By understanding the potential benefits (ie, medical education, training artificial intelligence programs, and proficiency testing, etc) and limitations of this new data realm, we can not only harness its power to improve patient outcomes, advance research, and enhance the practice of pathology but also become readily aware of their intrinsic limitations.

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BACKGROUND: Opioid overdoses in the USA have increased to unprecedented levels. Administration of the opioid antagonist naloxone can prevent overdoses. OBJECTIVE: This study was conducted to reveal the pharmacoepidemiologic patterns in naloxone prescribing to Medicaid patients from 2018 to 2021 as well as Medicare in 2019. DESIGN: Observational pharmacoepidemiologic study SETTING: US Medicare and Medicaid naloxone claims INTERVENTION: The Medicaid State Drug Utilisation Data File was utilised to extract information on the number of prescriptions and the amount prescribed of naloxone at a national and state level. The Medicare Provider Utilisation and Payment was also utilised to analyse prescription data from 2019. OUTCOME MEASURES: States with naloxone prescription rates that were outliers of quartile analysis were noted. RESULTS: The number of generic naloxone prescriptions per 100 000 Medicaid enrollees decreased by 5.3%, whereas brand naloxone prescriptions increased by 245.1% from 2018 to 2021. There was a 33.1-fold difference in prescriptions between the highest (New Mexico=1809.5) and lowest (South Dakota=54.6) states in 2019. Medicare saw a 30.4-fold difference in prescriptions between the highest (New Mexico) and lowest states (also South Dakota) after correcting per 100 000 enrollees. CONCLUSIONS: This pronounced increase in the number of naloxone prescriptions to Medicaid patients from 2018 to 2021 indicates a national response to this widespread public health emergency. Further research into the origins of the pronounced state-level disparities is warranted.

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Chronic rhinosinusitis (CRS) is a common, yet underreported and understudied manifestation of upper respiratory disease in people with cystic fibrosis (CF). Recently developed standard of care guidelines for the management of CF CRS suggest treatment of upper airway disease may ameliorate lower airway disease. We sought to determine whether changes to sinus microbial community diversity and specific taxa known to cause CF lung disease are associated with increased respiratory disease and inflammation. We performed 16S rRNA gene sequencing, supplemented with cytokine analyses, microscopy, and bacterial culturing, on samples from the sinuses of 27 adults with CF CRS. At each study visit, participants underwent endoscopic paranasal sinus sampling and clinical evaluation. We identified key drivers of microbial community composition and evaluated relationships between diversity and taxa with disease outcomes and inflammation. Sinus community diversity was low, and the composition was unstable, with many participants exhibiting alternating dominance between Pseudomonas aeruginosa and staphylococci over time. Despite a tendency for dominance by these two taxa, communities were highly individualized and shifted composition during exacerbation of sinus disease symptoms. Exacerbations were also associated with communities dominated by Staphylococcus spp. Reduced microbial community diversity was linked to worse sinus disease and the inflammatory status of the sinuses (including increased interleukin-1ß [IL-1ß]). Increased IL-1ß was also linked to worse sinus endoscopic appearance, and other cytokines were linked to microbial community dynamics. Our work revealed previously unknown instability of sinus microbial communities and a link between inflammation, lack of microbial community diversity, and worse sinus disease. IMPORTANCE Together with prior sinus microbiota studies of adults with CF chronic rhinosinusitis, our study underscores similarities between sinus and lower respiratory tract microbial community structures in CF. We show how community structure tracks with inflammation and several disease measures. This work strongly suggests that clinical management of CRS could be leveraged to improve overall respiratory health in CF. Our work implicates elevated IL-1ß in reduced microbiota diversity and worse sinus disease in CF CRS, suggesting applications for existing therapies targeting IL-1ß. Finally, the widespread use of highly effective cystic fibrosis transmembrane conductance regulator (CFTR) modulator therapy has led to less frequent availability of spontaneous expectorated sputum for microbiological surveillance of lung infections. A better understanding of CF sinus microbiology could provide a much-needed alternative site for monitoring respiratory infection status by important CF pathogens.

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Pseudomonas aeruginosa notoriously adapts to the airways of people with cystic fibrosis (CF), yet how infection-site biogeography and associated evolutionary processes vary as lifelong infections progress remains unclear. Here we test the hypothesis that early adaptations promoting aggregation influence evolutionary-genetic trajectories by examining longitudinal P. aeruginosa from the sinuses of six adults with CF. Highly host-adapted lineages harbored mutator genotypes displaying signatures of early genome degradation associated with recent host restriction. Using an advanced imaging technique (MiPACT-HCR [microbial identification after passive clarity technique]), we find population structure tracks with genome degradation, with the most host-adapted, genome-degraded P. aeruginosa (the mutators) residing in small, sparse aggregates. We propose that following initial adaptive evolution in larger populations under strong selection for aggregation, P. aeruginosa persists in small, fragmented populations that experience stronger effects of genetic drift. These conditions enrich for mutators and promote degenerative genome evolution. Our findings underscore the importance of infection-site biogeography to pathogen evolution.

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BACKGROUND: The Ki-67 index is important for grading neuroendocrine tumors (NETs) in cytology. However, different counting methods exist. Recently, augmented reality microscopy (ARM) has enabled real-time image analysis using glass slides. The objective of the current study was to compare different traditional Ki-67 scoring methods in cell block material with newer methods such as ARM. METHODS: Ki-67 immunostained slides from 50 NETs of varying grades were retrieved (39 from the pancreas and 11 metastases). Methods with which to quantify the Ki-67 index in up to 3 hot spots included: 1) "eyeball" estimation (EE); 2) printed image manual counting (PIMC); 3) ARM with live image analysis; and 4) image analysis using whole-slide images (WSI) (field of view [FOV] and the entire slide). RESULTS: The Ki-67 index obtained using the different methods varied. The pairwise kappa results varied from no agreement for image analysis using digital image analysis WSI (FOV) and histology to near-perfect agreement for ARM and PIMC. Using surgical pathology as the gold standard, the EE method was found to have the highest concordance rate (84.2%), followed by WSI analysis of the entire slide (73.7%) and then both the ARM and PIMC methods (63.2% for both). The PIMC method was the most time-consuming whereas image analysis using WSI (FOV) was the fastest method followed by ARM. CONCLUSIONS: The Ki-67 index for NETs in cell block material varied by the method used for scoring, which may affect grade. PIMC was the most time-consuming method, and EE had the highest concordance rate. Although real-time automated counting using image analysis demonstrated inaccuracies, ARM streamlined and hastened the task of Ki-67 quantification in NETs.

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