Eye disease in kidney transplantation: Clinical challenges in a unique patient population.

Eye disease is common among kidney transplant recipients, and their management is challenging. Chronic kidney disease is associated with ocular complications, both independently and in the context of various systemic disorders. In addition, chronic immunosuppression predisposes kidney transplant recipients to an array of long-term ocular issues. This may be broadly categorized into infections, malignancies, and other immunosuppression-specific side effects. The interdependence of kidney disease, transplant pharmacotherapy, and ocular health, therefore, requires a multispecialty approach. Although the kidney transplant population has grown along with the burden of associated oculopathies, systematic guidelines targeting this patient group are lacking. This evidenced-based narrative review summarizes the pertinent issues that may present in the ophthalmic and optometric clinical settings, with emphasis on collaborative management and directions for future research.

Open Source Software for Automatic Subregional Assessment of Knee Cartilage Degradation Using Quantitative T2 Relaxometry and Deep Learning.

OBJECTIVE: We evaluated a fully automated femoral cartilage segmentation model for measuring T2 relaxation values and longitudinal changes using multi-echo spin-echo (MESE) magnetic resonance imaging (MRI). We open sourced this model and developed a web app available at https://kl.stanford.edu into which users can drag and drop images to segment them automatically. DESIGN: We trained a neural network to segment femoral cartilage from MESE MRIs. Cartilage was divided into 12 subregions along medial-lateral, superficial-deep, and anterior-central-posterior boundaries. Subregional T2 values and four-year changes were calculated using a radiologist's segmentations (Reader 1) and the model's segmentations. These were compared using 28 held-out images. A subset of 14 images were also evaluated by a second expert (Reader 2) for comparison. RESULTS: Model segmentations agreed with Reader 1 segmentations with a Dice score of 0.85 ± 0.03. The model's estimated T2 values for individual subregions agreed with those of Reader 1 with an average Spearman correlation of 0.89 and average mean absolute error (MAE) of 1.34 ms. The model's estimated four-year change in T2 for individual subregions agreed with Reader 1 with an average correlation of 0.80 and average MAE of 1.72 ms. The model agreed with Reader 1 at least as closely as Reader 2 agreed with Reader 1 in terms of Dice score (0.85 vs. 0.75) and subregional T2 values. CONCLUSIONS: Assessments of cartilage health using our fully automated segmentation model agreed with those of an expert as closely as experts agreed with one another. This has the potential to accelerate osteoarthritis research.

Donor-derived Cell-free DNA: Advancing a Novel Assay to New Heights in Renal Transplantation.

Despite advances in transplant immunosuppression, long-term renal allograft outcomes remain suboptimal because of the occurrence of rejection, recurrent disease, and interstitial fibrosis with tubular atrophy. This is largely due to limitations in our understanding of allogeneic processes coupled with inadequate surveillance strategies. The concept of donor-derived cell-free DNA as a signal of allograft stress has therefore rapidly been adopted as a noninvasive monitoring tool. Refining it for effective clinical use, however, remains an ongoing effort. Furthermore, its potential to unravel new insights in alloimmunity through novel molecular techniques is yet to be realized. This review herein summarizes current knowledge and active endeavors to optimize cell-free DNA-based diagnostic techniques for clinical use in kidney transplantation. In addition, the integration of DNA methylation and microRNA may unveil new epigenetic signatures of allograft health and is also explored in this report. Directing research initiatives toward these aspirations will not only improve diagnostic precision but may foster new paradigms in transplant immunobiology.

Precision Medicine in Kidney Transplantation: Just Hype or a Realistic Hope?

Desirable outcomes including rejection- and infection-free kidney transplantation are not guaranteed despite current strategies for immunosuppression and using prophylactic antimicrobial medications. Graft survival depends on factors beyond human leukocyte antigen matching such as the level of immunosuppression, infections, and management of other comorbidities. Risk stratification of transplant patients based on predisposing genetic modifiers and applying precision pharmacotherapy may help improving the transplant outcomes. Unlike certain fields such as oncology in which consistent attempts are being carried out to move away from the "error and trial approach," transplant medicine is lagging behind in implementing personalized immunosuppressive therapy. The need for maintaining a precarious balance between underimmunosuppression and overimmunosuppression coupled with adverse effects of medications calls for a gene-based guidance for precision pharmacotherapy in transplantation. Technologic advances in molecular genetics have led to increased accessibility of genetic tests at a reduced cost and have set the stage for widespread use of gene-based therapies in clinical care. Evidence-based guidelines available for precision pharmacotherapy have been proposed, including guidelines from Clinical Pharmacogenetics Implementation Consortium, the Pharmacogenomics Knowledge Base National Institute of General Medical Sciences of the National Institutes of Health, and the US Food and Drug Administration. In this review, we discuss the implications of pharmacogenetics and potential role for genetic variants-based risk stratification in kidney transplantation. A single score that provides overall genetic risk, a polygenic risk score, can be achieved by combining of allograft rejection/loss-associated variants carried by an individual and integrated into practice after clinical validation.

Phenotyping severity of patient-centered outcomes using clinical notes: A prostate cancer use case.

INTRODUCTION: A learning health system (LHS) must improve care in ways that are meaningful to patients, integrating patient-centered outcomes (PCOs) into core infrastructure. PCOs are common following cancer treatment, such as urinary incontinence (UI) following prostatectomy. However, PCOs are not systematically recorded because they can only be described by the patient, are subjective and captured as unstructured text in the electronic health record (EHR). Therefore, PCOs pose significant challenges for phenotyping patients. Here, we present a natural language processing (NLP) approach for phenotyping patients with UI to classify their disease into severity subtypes, which can increase opportunities to provide precision-based therapy and promote a value-based delivery system. METHODS: Patients undergoing prostate cancer treatment from 2008 to 2018 were identified at an academic medical center. Using a hybrid NLP pipeline that combines rule-based and deep learning methodologies, we classified positive UI cases as mild, moderate, and severe by mining clinical notes. RESULTS: The rule-based model accurately classified UI into disease severity categories (accuracy: 0.86), which outperformed the deep learning model (accuracy: 0.73). In the deep learning model, the recall rates for mild and moderate group were higher than the precision rate (0.78 and 0.79, respectively). A hybrid model that combined both methods did not improve the accuracy of the rule-based model but did outperform the deep learning model (accuracy: 0.75). CONCLUSION: Phenotyping patients based on indication and severity of PCOs is essential to advance a patient centered LHS. EHRs contain valuable information on PCOs and by using NLP methods, it is feasible to accurately and efficiently phenotype PCO severity. Phenotyping must extend beyond the identification of disease to provide classification of disease severity that can be used to guide treatment and inform shared decision-making. Our methods demonstrate a path to a patient centered LHS that could advance precision medicine.

The potassium regulator patiromer affects serum and stool electrolytes in patients receiving hemodialysis.

Hyperkalemia is a common and an important cause of death in maintenance hemodialysis patients. Here we investigated the effect of patiromer, a synthetic cation exchanger, to regulate potassium homeostasis. Serum and stool electrolytes were measured in 27 anuric patients with hyperkalemia receiving hemodialysis (mainly 2 mEq/L dialysate) during consecutive two weeks of no-treatment, 12 weeks of treatment with patiromer (16.8g once daily), and six weeks of no treatment. The serum potassium decreased from a mean of 5.7 mEq/L pre-treatment to 5.1 mEq/L during treatment and rebounded to 5.4 mEq/L post-treatment. During the treatment phase, serum calcium significantly increased (from 8.9 to 9.1 mg/dL) and serum magnesium significantly decreased (from 2.6 to 2.4 mg/dL) compared to pre-treatment levels. For each one mEg/L increase in serum magnesium, serum potassium increased by 1.07 mEq/L. Stool potassium significantly increased during treatment phase from pre-treatment levels (4132 to 5923 µg/g) and significantly decreased post-treatment to 4246 µg/g. For each one µg/g increase in stool potassium, serum potassium significantly declined by 0.05 mEq/L. Stool calcium was significantly higher during the treatment phase (13017 µg/g) compared to pre-treatment (7874 µg/g) and post-treatment (7635 µg/g) phases. We estimated that 16.8 g of patiromer will increase fecal potassium by 1880 µg/g and reduce serum potassium by 0.5 mEq/L. Thus, there is a complex interaction between stool and blood potassium, calcium and magnesium during patiromer treatment. Long term consequence of patiromer-induced changes in serum calcium and magnesium remains to be studied.

Assistive technology solutions for aiding travel of pedestrians with visual impairment.

This work systematically reviews the assistive technology solutions for pedestrians with visual impairment and reveals that most of the existing solutions address a specific part of the travel problem. Technology-centered approach with limited focus on the user needs is one of the major concerns in the design of most of the systems. State-of-the-art sensor technology and processing techniques are being used to capture details of the surrounding environment. The real challenge is in conveying this information in a simplified and understandable form especially when the alternate senses of hearing, touch, and smell have much lesser perception bandwidth than that of vision. A lot of systems are at prototyping stages and need to be evaluated and validated by the real users. Conveying the required information promptly through the preferred interface to ensure safety, orientation, and independent mobility is still an unresolved problem. Based on observations and detailed review of available literature, the authors proposed that holistic solutions need to be developed with the close involvement of users from the initial to the final validation stages. Analysis reveals that several factors need serious consideration in the design of such assistive technology solutions.

Acute disseminated intravascular coagulation following surgical resection of a myeloid sarcoma in a 57-year-old male.

Myeloid sarcoma is a rare extramedullary tumour consisting of immature myeloid cells. It can arise at any anatomical location and often develops in the bowel. This report describes a case of severe acute disseminated intravascular coagulation (DIC) with multi-organ failure occurring in a 57-year-old man with chronic myelomonocytic leukaemia during bowel resection for newly diagnosed adenocarcinoma of the sigmoid colon. Histopa thology however revealed a differentiating myeloid sarcoma encompassing a well-differentiated adenocarcinoma. This is the first documented case of acute DIC to be triggered following surgical manipulation of myeloid sarcoma.

Mesothelin and kidney function--analysis of relationship and implications for mesothelioma screening.

PURPOSE: Malignant mesothelioma (MM) carries a poor prognosis and remains a major public health issue in many countries. Outcomes may be improved with earlier detection and this justifies screening the at-risk asbestos-exposed population. Soluble mesothelin is a potential biomarker for MM, but it has been observed to be elevated in patients with reduced kidney function. Defining the relationship between mesothelin concentrations and kidney function will allow more accurate interpretation of this assay. MATERIALS AND METHODS: A cross-sectional study consisting of 144 patients with chronic kidney disease (CKD) was conducted at Sir Charles Gairdner Hospital and Royal Perth Hospital in Western Australia. Only patients with CKD stages II-V were recruited while those with a history of renal transplant, dialysis, or malignancy were excluded. Serum and urine mesothelin and creatinine concentrations were determined. RESULTS: There were 33, 49, 31 and 31 patients in CKD stages II, III, IV and V, respectively recruited. Serum mesothelin increased significantly with increasing serum creatinine (p<0.0001), and worsening stage of CKD (p<0.0001). A significant correlation between urine mesothelin to creatinine ratio and serum mesothelin concentration was detected (p=0.002). No significant difference was found in urine mesothelin to creatinine ratios across the four CKD stage groups. CONCLUSION: Serum mesothelin concentration is elevated in individuals with renal impairment. Renal function should therefore be taken into account during interpretation of this assay.