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Background: Protein biomarkers have been broadly investigated in cerebrospinal fluid and blood for the detection of neurodegenerative diseases, yet a clinically useful diagnostic test to detect early, pre-symptomatic Alzheimer's disease (AD) remains elusive. We conducted this study to quantify Aβ40, Aβ42, total Tau (t-Tau), hyperphosphorylated Tau (ptau181), glial fibrillary acidic protein (GFAP) and neurofilament light chain (NfL) in eye fluids relative to blood. Methods: In this cross-sectional study we collected vitreous humor, aqueous humor, tear fluid and plasma in patients undergoing surgery for eye disease. All six biomarkers were quantitatively measured by digital immunoassay. Spearman and Bland–Altman correlation analyses were performed to assess the agreement of levels between ocular fluids and plasma. Results: Seventy-nine adults underwent pars-plana vitrectomy in at least one eye. Of the 79, there were 77 vitreous, 67 blood, 56 tear fluid, and 51 aqueous samples. All six biomarkers were quantified in each bio-sample, except GFAP and NfL in tear fluid due to low sample volume. All six biomarkers were elevated in vitreous humor compared to plasma samples. T-Tau, ptau181, GFAP and NfL were higher in aqueous than in plasma, and t-Tau and ptau181 concentrations were higher in tear fluid than in plasma. Significant correlations were found between Aβ40 in plasma and tears (r = 0.5; p = 0.019), t-Tau in plasma and vitreous (r = 0.4; p = 0.004), NfL in plasma and vitreous (r = 0.3; p = 0.006) and plasma and aqueous (r = 0.5; p = 0.004). No significant associations were found for Aβ42, ptau181 and GFAP among ocular fluids relative to plasma. Bland–Altman analysis showed aqueous humor had the closest agreement to plasma across all biomarkers. Biomarker levels in ocular fluids revealed statistically significant associations between vitreous and aqueous for t-Tau (r = 0.5; p = 0.001), GFAP (r = 0.6; p < 0.001) and NfL (r = 0.7; p < 0.001). Conclusion: AD biomarkers are detectable in greater quantities in eye fluids than in plasma and show correlations with levels in plasma. Future studies are needed to assess the utility of ocular fluid biomarkers as diagnostic and prognostic markers for AD, especially in those at risk with eye disease. [ABSTRACT FROM AUTHOR]

Background: The purpose of this research was to compare patient satisfaction between hybrid ophthalmology telemedicine and standard-of-care in-person visits. A retrospective, cross-sectional, case-control analysis of patient satisfaction based on survey data was used. Methods: Responses to the National Research Council Health Patient Survey were retrieved for randomly sampled hybrid ophthalmology telemedicine and in-person visits between March 11, 2020 and December 31, 2021 at a hospital-based eye clinic in Boston, Massachusetts. The primary outcome was based on the question "How likely would you be to recommend this provider to your family and friends?" (0-10 scale) with a score of 9 or 10 coded as satisfied. Two-sample t -tests, Pearson's chi-square tests, and bivariate logistic regressions were used to compare patient satisfaction scores between the hybrid and in-person cohorts. Demographic data, including age, sex, language, and self-reported race and ethnicity, were used as potential predictors of patient satisfaction in a multivariable logistic regression model. Results: There were 49 surveys from hybrid visits and 3,390 surveys from in-person visits. Hybrid visit patients reported high satisfaction scores without significant differences compared to in-person visit patients (hybrid 79% satisfied, in-person 82% satisfied, p  = 0.728). Age was significantly associated with satisfaction in the hybrid cohort with the 65+ age group reporting lower satisfaction (below 65 years 100% satisfied, 65+ years 60% satisfied, p  = 0.003). No association with age was observed in the in-person cohort. Conclusions: The hybrid ophthalmology telemedicine model can provide effective care without sacrificing patient satisfaction. Older patients may benefit from targeted interventions in future telemedicine models.

Objective: This study aims to establish an effective predictive model for predicting Xp11.2 translocation/TFE3 gene fusion renal cell carcinoma (TFE3-RCC) and develop optimal therapeutic strategies., Methods: Data from 4961 patients diagnosed with renal cell carcinoma at two medical centers in China were retrospectively analyzed. A cohort of 1571 patients from Zhejiang Provincial People's Hospital (Ra cohort) was selected to construct the model. Another cohort of 1124 patients from the Second Affiliated Hospital of Zhejiang Chinese Medical University was used for external validation (the Ha cohort). All patients with TFE3-RCC in both cohorts were included in the Ta cohort for the prognostic analysis. Univariate and multivariate binary logistic regression analyses were performed to identify independent predictors of the predictive nomogram. The apparent performance of the model was validated. Decision curve analysis was also performed to assess the clinical utility of the developed model. Factors associated with progression and prognosis in the Ta cohort were analyzed using the log-rank method, and Cox regression analysis and Kaplan-Meier survival curves were used to describe the effects of factors on prognosis and progression., Results: Univariate and multivariate logistic regression analyses demonstrated that age, sex, BMI, smoking, eosinophils, and LDL were independent predictors of TFE3-RCC. Therefore, a predictive nomogram for TFE3-RCC, which had good discriminatory power (AUC = 0.796), was constructed. External validation (AUC = 0.806) also revealed good predictive ability. The calibration curves displayed good consistency between the predicted and observed incidences of TFE3-RCC. Invasion of regional lymph nodes, tyrosine kinase inhibitors, and surgical methods were independent factors associated with progression. Tyrosine kinase inhibitors are independent prognostic factors., Conclusion: This study not only proposed a high-precision clinical prediction model composed of various variables for the early diagnosis of Xp11.2 translocation/TFE3 gene fusion renal cell carcinoma but also optimized therapeutic strategies through prognostic analysis.