External Validation of the Percutaneous Renal Ablation Complexity Scoring System in Patients Undergoing Percutaneous Cryoablation or Microwave Ablation of Renal Tumors.

PURPOSE: To assess the ability of the Percutaneous Renal Ablation Complexity (P-RAC) scoring system to predict procedural complexity or adverse events (AEs) in adult patients undergoing percutaneous thermal ablation of renal tumors. MATERIALS AND METHODS: A retrospective review of 240 consecutive adult patients who underwent percutaneous thermal renal ablation from 2004 to 2018 was conducted. The P-RAC score was calculated for each renal tumor and procedural complexity recorded. A correlation coefficient was calculated for the P-RAC score and both the number of probes used and procedural duration. Receiver operating characteristic curves assessed the score's ability to predict the use of adjunctive techniques and/or major AEs, classified according to the Society of Interventional Radiology guidelines. RESULTS: For the entire cohort, there was a weak correlation between P-RAC scores and both the number of probes used (r = 0.31; P < .001) and procedural duration (r = 0.18; P = .03). When evaluating only patients treated with microwave ablation (MWA), no correlation between P-RAC scores and either the number of probes (P = .7) used or procedural duration (P = .4) was found. The area under the curve (AUC) for the P-RAC score to predict the use of adjunctive techniques was 0.55 and 0.53 for the entire cohort and MWA group, respectively. The AUC for the P-RAC score to predict major AEs was 0.70, 0.71, and 0.73 for the entire cohort, MWA group, and cryoablation group, respectively. CONCLUSIONS: The P-RAC scoring system is limited in its ability to predict percutaneous thermal renal tumor ablation procedural complexity, especially in patients treated with MWA. The scoring system may have a role in identifying patients at risk of major AEs.

Contact Tracing Apps: Lessons Learned on Privacy, Autonomy, and the Need for Detailed and Thoughtful Implementation.

The global and national response to the COVID-19 pandemic has been inadequate due to a collective lack of preparation and a shortage of available tools for responding to a large-scale pandemic. By applying lessons learned to create better preventative methods and speedier interventions, the harm of a future pandemic may be dramatically reduced. One potential measure is the widespread use of contact tracing apps. While such apps were designed to combat the COVID-19 pandemic, the time scale in which these apps were deployed proved a significant barrier to efficacy. Many companies and governments sprinted to deploy contact tracing apps that were not properly vetted for performance, privacy, or security issues. The hasty development of incomplete contact tracing apps undermined public trust and negatively influenced perceptions of app efficacy. As a result, many of these apps had poor voluntary public uptake, which greatly decreased the apps' efficacy. Now, with lessons learned from this pandemic, groups can better design and test apps in preparation for the future. In this viewpoint, we outline common strategies employed for contact tracing apps, detail the successes and shortcomings of several prominent apps, and describe lessons learned that may be used to shape effective contact tracing apps for the present and future. Future app designers can keep these lessons in mind to create a version that is suitable for their local culture, especially with regard to local attitudes toward privacy-utility tradeoffs during public health crises.

External Validation of the Renal Ablation-Specific (MC)2 Risk Scoring System in Predicting Complications from Percutaneous Renal Cryoablation.

PURPOSE: The (MC)2 score is a renal ablation-specific risk scoring system to predict major complications from percutaneous renal cryoablation (PRCA). However, it is untested in an external population of patients. The purpose of this study is to validate the ability of the (MC)2 score to predict major complications after PRCA in an external population. MATERIALS AND METHODS: Retrospective review of patients who underwent PRCA from 2004 to 2019. Patient demographics, medical histories, and tumor characteristics were collected. The (MC)2 score was calculated and patients were assigned to low risk (< 5), moderate risk (5-8) and high-risk (> 8) groups. Complications were recorded. Major complications were classified according to CIRSE guidelines. RESULTS: Two hundred and one patients [M = 116; F = 85; median age = 65 (range 27-90)] met inclusion criteria. Eleven patients (5.5%) developed major complications and 50 patients (24.9%) developed minor complications. Of patients with major complications, mean tumor diameter was 39 mm (± 10.4), seven patients (63.6%) had a central tumor, four patients (36.4%) had complicated diabetes, and one patient (9.1%) had a prior MI. Major complication rates were 2.1%, 14%, and 14.3% in the (MC)2 low risk, moderate risk, and high risk groups, respectively. The mean (MC)2 score for patients with major complications [6.2 (± 2.4)] was higher than the mean score for patients with minor complications [4.7 (± 2.4) (p = 0.07)] and no complications [3.9 (± 1.9) (p < 0.01)]. The area under the ROC curve to predict major complications was 0.78. CONCLUSION: The (MC)2 risk scoring system appropriately identifies patients at risk for major complications from PRCA in this external patient population.

Computational modeling of retinal hypoxia and photoreceptor degeneration in patients with age-related macular degeneration.

Although drusen have long been acknowledged as a primary hallmark of dry age-related macular degeneration (AMD) their role in the disease remains unclear. We hypothesize that drusen accumulation increases the barrier to metabolite transport ultimately resulting in photoreceptor cell death. To investigate this hypothesis, a computational model was developed to evaluate steady-state oxygen distribution in the retina. Optical coherence tomography images from fifteen AMD patients and six control subjects were segmented and translated into 3D in silico representations of retinal morphology. A finite element model was then used to determine the steady-state oxygen distribution throughout the retina for both generic and patient-specific retinal morphology. Oxygen levels were compared to the change in retinal thickness at a later time point to observe possible correlations. The generic finite element model of oxygen concentration in the retina agreed closely with both experimental measurements from literature and clinical observations, including the minimal pathological drusen size identified by AREDS (64 µm). Modeling oxygen distribution in the outer retina of AMD patients showed a substantially stronger correlation between hypoxia and future retinal thinning (Pearson correlation coefficient, r = 0.2162) than between drusen height and retinal thinning (r = 0.0303) indicating the potential value of this physiology-based approach. This study presents proof-of-concept for the potential utility of finite element modeling in evaluating retinal health and also suggests a potential link between transport and AMD pathogenesis. This strategy may prove useful as a prognostic tool for predicting the clinical risk of AMD progression.