Citations

ObjectiveTo compare the diagnostic performance of an artificial intelligence deep learning system with that of expert neuro‐ophthalmologists in classifying optic disc appearance.MethodsThe deep learning system was previously trained and validated on 14,341 ocular fundus photographs from 19 international centers. The performance of the system was evaluated on 800 new fundus photographs (400 normal optic discs, 201 papilledema [disc edema from elevated intracranial pressure], 199 other optic disc abnormalities) and compared with that of 2 expert neuro‐ophthalmologists who independently reviewed the same randomly presented images without clinical information. Area under the receiver operating characteristic curve, accuracy, sensitivity, and specificity were calculated.ResultsThe system correctly classified 678 of 800 (84.7%) photographs, compared with 675 of 800 (84.4%) for Expert 1 and 641 of 800 (80.1%) for Expert 2. The system yielded areas under the receiver operating characteristic curve of 0.97 (95% confidence interval [CI] = 0.96–0.98), 0.96 (95% CI = 0.94–0.97), and 0.89 (95% CI = 0.87–0.92) for the detection of normal discs, papilledema, and other disc abnormalities, respectively. The accuracy, sensitivity, and specificity of the system's classification of optic discs were similar to or better than the 2 experts. Intergrader agreement at the eye level was 0.71 (95% CI = 0.67–0.76) between Expert 1 and Expert 2, 0.72 (95% CI = 0.68–0.76) between the system and Expert 1, and 0.65 (95% CI = 0.61–0.70) between the system and Expert 2.InterpretationThe performance of this deep learning system at classifying optic disc abnormalities was at least as good as 2 expert neuro‐ophthalmologists. Future prospective studies are needed to validate this system as a diagnostic aid in relevant clinical settings. ANN NEUROL 2020;88:785–795

AbstractCoronavirus disease 2019 (COVID-19) has affected millions of people across the world but disproportionately and severely affects persons with metabolic disorders such as obesity, diabetes mellitus, and hypertension. In this brief review, we discuss the pathways of immune dysregulation that may lead to severe COVID-19 in persons with metabolic conditions.

AbstractBackgroundIn nerve allograft development, currently used subjective histological scoring systems to evaluate nerve structure in experimental studies are not uniform and have not been validated.The aim of this study was to describe and validate a simple, fast and inexpensive method to compare structural properties of nerve allografts on a histological level.Materials and methodsA total of 113 histological sections of rat (sciatic nerves) and human peripheral nerve segments (thoracodorsal and long thoracic nerve for motor and sural for sensory nerve) treated with various decellularization protocols were analyzed. Slides were stained with Hematoxylin & Eosin (H&E), Toluidine Blue and Laminin. A subjective scoring system using a 5‐point scale was used to score each nerve section by four independent researchers. For validation of this score both inter‐ and intra‐rater reliability were calculated using the Intraclass Correlation Coefficient (ICC).ResultsOverall, an excellent correlation between the different observers was found for the Toluidine Blue (ICC = 0.919, 95% CI: 0.891–0.941), H&E (ICC = 0.9, 95% CI: 0.865–0.927) and Laminin staining (ICC = 0.897, 95% CI: 0.860–0.926). Intra‐rater reliability was good for all three staining techniques (ICC >0.8).ConclusionThis study demonstrates the validity of this simple scoring system to evaluate nerve structure after different processing protocols. All three evaluated staining techniques can reliably be used for both rat and human nerve tissue. We believe this method is suitable to compare different processing techniques to create processed nerve allografts, especially when the average scores of multiple raters are used.

Abstract Despite the widespread clinical use of dynamic susceptibility contrast (DSC) MRI, DSC-MRI methodology has not been standardized, hindering its utilization for response assessment in multicenter trials. Recently, the DSC-MRI Standardization Subcommittee of the Jumpstarting Brain Tumor Drug Development Coalition issued an updated consensus DSC-MRI protocol compatible with the standardized brain tumor imaging protocol (BTIP) for high-grade gliomas that is increasingly used in the clinical setting and is the default MRI protocol for the National Clinical Trials Network. After reviewing the basis for controversy over DSC-MRI protocols, this paper provides evidence-based best practices for clinical DSC-MRI as determined by the Committee, including pulse sequence (gradient echo vs spin echo), BTIP-compliant contrast agent dosing (preload and bolus), flip angle (FA), echo time (TE), and post-processing leakage correction. In summary, full-dose preload, full-dose bolus dosing using intermediate (60°) FA and field strength-dependent TE (40–50 ms at 1.5 T, 20–35 ms at 3 T) provides overall best accuracy and precision for cerebral blood volume estimates. When single-dose contrast agent usage is desired, no-preload, full-dose bolus dosing using low FA (30°) and field strength-dependent TE provides excellent performance, with reduced contrast agent usage and elimination of potential systematic errors introduced by variations in preload dose and incubation time.

The coronavirus disease 2019 (COVID-19) pandemic has disrupted all aspects of clinical care, including cancer clinical trials. In March 2020, ASCO launched a survey of clinical programs represented on its Cancer Research Committee and Research Community Forum Steering Group and taskforces to learn about the types of changes and challenges that clinical trial programs were experiencing early in the pandemic. There were 32 survey respondents; 14 represented academic programs, and 18 represented community-based programs. Respondents indicated that COVID-19 is leading programs to halt or prioritize screening and/or enrollment for certain clinical trials and cease research-only visits. Most reported conducting remote patient care where possible and remote visits and monitoring with sponsors and/or contract research organizations (CROs); respondents viewed this shift positively. Numerous challenges with conducting clinical trials were reported, including enrollment and protocol adherence difficulties with decreased patient visits, staffing constraints, and limited availability of ancillary services. Interactions with sponsors and CROs about modifying trial procedures were also challenging. The changes in clinical trial procedures identified by the survey could serve as strategies for other programs attempting to maintain their clinical trial portfolios during the COVID-19 pandemic. Additionally, many of the adaptations to trials made during the pandemic provide a long-term opportunity to improve and transform the clinical trial system. Specific improvements could be expanded use of more pragmatic or streamlined trial designs, fewer clinical trial–related patient visits, and minimized sponsor and CRO visits to trial programs.

Inspired by the ABIM Foundation's Choosing Wisely® campaign, the “Things We Do for No Reason™” (TWDFNR) series reviews practices that have become common parts of hospital care but may provide little value to our patients. Practices reviewed in the TWDFNR series do not represent “black and white” conclusions or clinical practice standards but are meant as a starting place for research and active discussions among hospitalists and patients. We invite you to be part of that discussion.

Abstract We evaluated the joint associations between a new 313-variant PRS (PRS313) and questionnaire-based breast cancer risk factors for women of European ancestry, using 72 284 cases and 80 354 controls from the Breast Cancer Association Consortium. Interactions were evaluated using standard logistic regression and a newly developed case-only method for breast cancer risk overall and by estrogen receptor status. After accounting for multiple testing, we did not find evidence that per-standard deviation PRS313 odds ratio differed across strata defined by individual risk factors. Goodness-of-fit tests did not reject the assumption of a multiplicative model between PRS313 and each risk factor. Variation in projected absolute lifetime risk of breast cancer associated with classical risk factors was greater for women with higher genetic risk (PRS313 and family history) and, on average, 17.5% higher in the highest vs lowest deciles of genetic risk. These findings have implications for risk prevention for women at increased risk of breast cancer.

Background: Steatotic grafts are increasingly being used for liver transplant (LT); however, the impact of graft steatosis on renal function has not been well described. Methods: A total of 511 allografts from Mayo Clinic Arizona and Minnesota were assessed. We evaluated post-LT acute kidney injury (AKI) patterns, perioperative variables and one-year outcomes for patients receiving moderately steatotic allografts (>30% macrovesicular steatosis, n = 40) and compared them to non-steatotic graft recipients. Results: Post-LT AKI occurred in 52.5% of steatotic graft recipients versus 16.7% in non-steatotic recipients (p < 0.001). Ten percent of steatotic graft recipients required new dialysis post-LT (p = 0.003). At five years, there were no differences for AKI vs. no AKI patient survival (HR 0.95, 95% CI 0.08–10.6, p = 0.95) or allograft survival (HR 1.73, 95% CI 0.23–13.23, p = 0.59) for those using steatotic grafts. Lipopeliosis on biopsy was common in those who developed AKI (61.0% vs. 31.6%, p = 0.04), particularly when the Model for End-Stage Liver Disease (MELD) was ≥20 (88.9%; p = 0.04). Lipopeliosis was a predictor of post-LT AKI (OR 6.0, 95% CI 1.1–34.6, p = 0.04). Conclusion: One-year outcomes for moderately steatotic grafts are satisfactory; however, a higher percentage of post-LT AKI and initiation of dialysis can be expected. Presence of lipopeliosis on biopsy appears to be predictive of post-LT AKI.