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Purpose: To evaluate and compare the effectiveness of nearest neighbor (NN)- and variational autoencoder (VAE)-smoothing algorithms to reduce variability and enhance the performance of glaucoma visual field (VF) progression models. Design: Longitudinal cohort study. Subjects: 7150 eyes (4232 patients), with ≥ 5 years of follow-up and ≥ 6 visits. Methods: Vsual field thresholds were smoothed with the NN and VAE algorithms. The mean total deviation (mTD) and VF index rates, pointwise linear regression (PLR), permutation of PLR (PoPLR), and the glaucoma rate index were applied to the unsmoothed and smoothed data. Main Outcome Measures: The proportion of progressing eyes and the conversion to progression were compared between the smoothed and unsmoothed data. A simulation series of noiseless VFs with various patterns of glaucoma damage was used to evaluate the specificity of the smoothing models. Results: The mean values of age and follow-up time were 62.8 (standard deviation: 12.6) years and 10.4 (standard deviation: 4.7) years, respectively. The proportion of progression was significantly higher for the NN and VAE smoothed data compared with the unsmoothed data. VF progression occurred significantly earlier with both smoothed data compared with unsmoothed data based on mTD rates, PLR, and PoPLR methods. The ability to detect the progressing eyes was similar for the unsmoothed and smoothed data in the simulation data. Conclusions: Smoothing VF data with NN and VAE algorithms improves the signal-to-noise ratio for detection of change, results in earlier detection of VF progression, and could help monitor glaucoma progression more effectively in the clinical setting. Financial Disclosures: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

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Purpose: To develop a structural metascore (SMS) that combines measurements from different devices and expresses them on a single scale to facilitate their long-term analysis. Methods: Three structural measurements (Heidelberg Retina Tomograph II [HRT] rim area, HD-Cirrus optical coherence tomography [OCT] average retinal nerve fiber layer [RNFL] thickness, Spectralis OCT RNFL global thickness) were normalized on a scale of 0 to 100 and converted to a reference value. The resultant metascores were plotted against time. SMS performance was evaluated to predict future values (internal validation), and correlations between the average grades assigned by three clinicians were compared with the SMS slopes (external validation). Results: The linear regression fit with the variance approach, and adjustment to a Spectralis equivalent was the best-performing approach; this was denominated metascore. Plots were created for 3416 eyes of 1824 patients. The average baseline age (± standard deviation) was 69.8 (±13.9), mean follow-up was 11.6 (±4.7) years, and mean number of structural scans per eye was 10.0 (±4.7). The mean numbers of scans per device were 3.8 (±2.5), 5.0 (±2.9), and 1.3 (±3.0) for HRT, Cirrus, and Spectralis, respectively. The metascore slopes' median was -0.3 (interquartile range 1.1). Correlations between the average grades assigned by the three clinicians and the metascore slopes were -0.51, -0.49, and -0.69 for the first (structural measurement printouts alone), second (metascore plots alone), and third (printouts + metascore plots) series of gradings, respectively. The average absolute predictive ability was 7.63/100 (whereas 100 = entire normalized scale). Conclusions: We report a method that converts Cirrus global RNFL and HRT global rim area normalized measurements to Spectralis global RNFL equivalent values to facilitate long-term structural follow-up. Translational Relevance: Because glaucoma changes usually occur slowly, patients are often examined with different instruments during their follow-up, a method that "unifies" structural measurements provided by different devices, which could assist patients' longitudinal structural follow-up.

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PRCIS: We describe a method that provides rapid visualization of glaucomatous change in a 2-dimensional (2D) structural and functional (S/F) space. PURPOSE: To describe a method to visualize glaucomatous change in a 2D S/F space. DESIGN: This was a retrospective longitudinal observational study. SUBJECTS: Group I included 64 normal and 64 glaucomatous eyes used to develop the structural score. Group II included 957 glaucomatous eyes used to plot the structural-functional progression vectors. METHODS: Subjects were arranged in 2 groups. Group I was a cross-sectional group used to develop a structural score which were applied to longitudinal measurements of patients in group II for vectoral analysis. Visual field index was used as a functional score. Vectors were created for each eye to define structural (x) and functional (y) progression. The structural and functional components were calculated with linear models of optical coherence tomography scores and visual field index. The resultant vector and its confidence interval were plotted in 2D S/F space. MAIN OUTCOME MEASURES: Combined structural-functional glaucomatous progression. RESULTS: Group I included 64 normal and 64 glaucomatous eyes. We calculated 957 vectors (957 eyes of 582 OAG patients) in group II. The mean (±SD) follow-up period was 6.9 (±1.5) years and mean baseline mean deviation (MD) was -4.3 (±5.4). Preperimetric, mild, moderate, and severe groups included 159, 288, 299, and 211 eyes, respectively. Mean baseline MDs in these groups were 0.8, -1.0, -3.7, and -11.2 dB, and mean vector slopes were 0.88, 1.00, 1.98, and 2.69. CONCLUSION: We present a method that presents glaucoma progression in a 2D S/F space. This approach integrates a large amount of longitudinal numerical data and provides the clinician with a rapid and intuitive summary of the patient's glaucoma trajectory.

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BACKGROUND: Previous studies have suggested associations between trends of web searches and COVID-19 traditional metrics. It remains unclear whether models incorporating trends of digital searches lead to better predictions. OBJECTIVE: The aim of this study is to investigate the relationship between Google Trends searches of symptoms associated with COVID-19 and confirmed COVID-19 cases and deaths. We aim to develop predictive models to forecast the COVID-19 epidemic based on a combination of Google Trends searches of symptoms and conventional COVID-19 metrics. METHODS: An open-access web application was developed to evaluate Google Trends and traditional COVID-19 metrics via an interactive framework based on principal component analysis (PCA) and time series modeling. The application facilitates the analysis of symptom search behavior associated with COVID-19 disease in 188 countries. In this study, we selected the data of nine countries as case studies to represent all continents. PCA was used to perform data dimensionality reduction, and three different time series models (error, trend, seasonality; autoregressive integrated moving average; and feed-forward neural network autoregression) were used to predict COVID-19 metrics in the upcoming 14 days. The models were compared in terms of prediction ability using the root mean square error (RMSE) of the first principal component (PC1). The predictive abilities of models generated with both Google Trends data and conventional COVID-19 metrics were compared with those fitted with conventional COVID-19 metrics only. RESULTS: The degree of correlation and the best time lag varied as a function of the selected country and topic searched; in general, the optimal time lag was within 15 days. Overall, predictions of PC1 based on both search terms and COVID-19 traditional metrics performed better than those not including Google searches (median 1.56, IQR 0.90-2.49 versus median 1.87, IQR 1.09-2.95, respectively), but the improvement in prediction varied as a function of the selected country and time frame. The best model varied as a function of country, time range, and period of time selected. Models based on a 7-day moving average led to considerably smaller RMSE values as opposed to those calculated with raw data (median 0.90, IQR 0.50-1.53 versus median 2.27, IQR 1.62-3.74, respectively). CONCLUSIONS: The inclusion of digital online searches in statistical models may improve the nowcasting and forecasting of the COVID-19 epidemic and could be used as one of the surveillance systems of COVID-19 disease. We provide a free web application operating with nearly real-time data that anyone can use to make predictions of outbreaks, improve estimates of the dynamics of ongoing epidemics, and predict future or rebound waves.

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PURPOSE: To present a method that allows visualization of functional and structural change in 2-dimensional space. DESIGN: Retrospective, longitudinal, observational study. PARTICIPANTS: Patients from the Stein Eye Institute, UCLA from 1993 through 2017. METHODS: Patients were arranged into 2 cohorts. Cohort 1 was used to create a structural score for the horizontal axis of the structural-functional (S-F) 2-dimensional space. The visual field (VF) index was used for the vertical axis as the functional score. Cohort 2 was used to apply those scores for analysis of S-F progression with a combined vector. The first cohort included eyes with mild glaucoma (abnormal glaucoma hemifield test results, pattern standard deviation <0.05 on 2 examinations, or mean deviation [MD] >-5 dB) and normal control participants. The second cohort included all stages of open-angle glaucoma with ≥5 OCT retinal nerve fiber layer scans, ≥5 reliable visual field (VF) results, and follow-up of ≥4 years. MAIN OUTCOME MEASURES: Vectors were created for each eye to represent the trajectory of glaucoma progression over time. Each vector was defined by structural (x-axis) and functional (y-axis) components. The structural component was calculated with a linear model of Heidelberg Retina Tomograph (Heidelberg Engineering, Heidelberg, Germany) scores over time. The functional component was calculated with a linear model of VF measurements over time. The resultant vector and its confidence interval were plotted in 2-dimensional S-F space. Eyes were divided into severity stages based on baseline MD. A mean vector was calculated for each severity stage. RESULTS: We obtained 290 vectors from 290 eyes of 196 patients. The mean ± standard deviation follow-up period was 14.6±3.1 years. Average age was 58.6±8.8 years. Preperimetric, mild, moderate, and severe categories included 41, 89, 97, and 63 eyes, respectively. Mean baseline MDs were 0.8 dB, -0.95 dB, -3.57 dB, and -11.51 dB, respectively, and mean vector slopes for each severity categories were 0.79, 0.95, 1.95, and 2.08, respectively. Cook's distance removed 131 (7.1%) and 137 (7.4%) outliers from the structure and function regressions, respectively. CONCLUSIONS: We report a method to visualize the trajectory of a patient's glaucoma progression in a 2-dimensional S-F space. The slope of the trajectory of glaucoma progression is a function of the severity of the disease.

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Importance: Rates of visual field (VF) progression vary among patients with glaucoma. Knowing the rate of progression of individual patients would allow appropriately aggressive therapy for patients with high rates of visual loss and protect those with low rates from unnecessary therapy. Objective: To compare 3 pointwise methods of estimating the rate of VF progression in glaucoma. Design, Setting, and Participants: This retrospective, observational cohort study included 729 eyes of 567 consecutive patients with primary open-angle glaucoma who had at least 6 reliable VFs and at least 3 years of follow-up. One hundred seventy-six patients (257 eyes) were treated at a tertiary glaucoma center; in addition, data were collected from 391 participants (472 eyes) in the Advanced Glaucoma Intervention Study. Data were collected from May 1988 to November 2004 and analyzed from October 2018 to February 2019. Exposures: Estimates of VF progression were measured with guided progression analysis (GPA), pointwise linear regression (PLR), and the glaucoma rate index (GRI). A subgroup analysis was performed in a subset of patients with likely VF progression and likely VF stability. Main Outcomes and Measures: Proportion of VF series detected as progressing, estimates of false-positive proportions, time to detect progression, and agreement among measures. Results: Among the 567 patients included in the analysis, mean (SD) age was 65.6 (9.7) years, 300 (52.9%) were female, and 295 (52.0%) were white. The median baseline mean deviation was -6.7 (interquartile range [IQR], -11.6 to -3.5) dB; the median follow-up time, 8.9 (IQR, 7.3-10.4) years. The proportion of eyes labeled as progressing was 27.7% according to the GPA, 33.5% according to the PLR, and 52.9% according to the GRI; pairwise differences for GRI vs PLR were 20% (95% CI, 17%-23%); for GRI vs GPA, 25% (95% CI, 22%-29%); and for PLR vs GPA, 6% (95% CI, 3%-9%; P < .001 for all comparisons, McNemar test). The shortest median time to progression was with the GRI (8.8 [IQR, 2.4-10.5 years), compared with the GPA and PLR (both >16 years). The hazard ratio of VF progression for GRI vs PLR (reference) was 11.3 (95% CI, 9.2-13.7); for GRI vs GPA (reference), 18.1 (95% CI, 14.5-22.6); and for PLR vs GPA (reference), 1.5 (95% CI, 1.3-1.9; P < .001 for all comparisons, Cox proportional hazards regression). These results held in the subgroup with likely progression; the proportions of progressing eyes were 73.7% (115 of 156) for GPA, 81.4% (127 of 156) for PLR, and 92.9% (145 of 156) for GRI. Pairwise difference for GRI vs PLR was 11.5% (95% CI, 7.4%-17.6%; P < .001, McNemar test); for GRI vs GPA, 19.2% (95% CI, 12.6%-26.4%; P < .001, McNemar test); and for PLR vs GPA, 7.7% (95% CI, 0.3%-15.7%; P = .08, McNemar test). Conclusions and Relevance: These results suggest GRI can detect long-term VF progression in glaucoma earlier than PLR or GPA. Validation with prospective designs may strengthen the generalizability and value of this method.

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PURPOSE: To identify predictive factors for visual field (VF) fluctuation in glaucoma patients. DESIGN: Retrospective cohort study. PARTICIPANTS: A total of 1392 eyes (816 patients) with 6 or more VFs and 3 years or more of follow-up. METHODS: For each eye, the VF mean deviation (MD) and the pointwise sensitivities were regressed against time to model the series trend, and the root mean square error (RMSE) was estimated as a measure of variability. Potential predictors were selected with least absolute shrinkage and selection operator regression and included eye laterality, ethnicity, glaucoma type, intraocular pressure (IOP) fluctuation, baseline best corrected-visual acuity, intervening cataract or glaucoma surgery, length of follow-up, frequency of testing, baseline MD, rates of VF progression, and median false positive (FP) and false negative (FN) responses. MAIN OUTCOME MEASURES: Predictors of global and pointwise VF long-term fluctuation. RESULTS: In the global model, left eye (0.063 dB; P = 0.022), Asian descent (0.265 dB; P = 0.006), larger IOP fluctuation (0.051 dB; P < 0.001), intervening cataract surgery (0.090 dB; P = 0.023), longer follow-up (0.130 dB; P < 0.001), worse baseline MD (-0.145 dB; P < 0.001), faster VF decay rate (-0.090 dB; P < 0.001), and higher FP rate (0.145 dB; P < 0.001) and FN rate (0.220 dB; P < 0.001) were predictors of VF fluctuation. In the pointwise model, larger IOP fluctuation (0.039 dB; P = 0.022), longer follow-up (0.340 dB; P < 0.001), higher VF frequency (0.238 dB; P = 0.002), intervening glaucoma surgery (0.190 dB; P = 0.01), worse baseline MD (-0.535 dB; P < 0.001), faster VF decay rate (-0.340 dB; P < 0.001), and higher FP rate (0.255 dB; P < 0.001) and FN rate (0.395 dB; P < 0.001) were associated with increased fluctuation. The multivariable model explained 57% and 28% of the pointwise and global variances, respectively. CONCLUSIONS: This study identified novel predictors of VF fluctuation, and explains nearly 60% of the pointwise variance. In the presence of factors predictive of high fluctuation, increased frequency of testing and better analytics will help to identify VF progression more accurately.

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PURPOSE: To quantify visual field (VF) variability as a function of threshold sensitivity and location, and to compare weighted pointwise linear regression (PLR) with unweighted PLR and pointwise exponential regression (PER) for data fit and prediction ability. METHODS: Two datasets were used for this retrospective study. The first was used to characterize and estimate VF variability, and included a total of 4,747 eyes of 3,095 glaucoma patients with six or more VFs and 3 years or more of follow-up. After performing PER for each series, standard deviation of residuals was quantified for each decibel of sensitivity as a measure of variability. A separate dataset was used to test and compare unweighted PLR, weighted PLR, and PER for data fit and prediction, and included 261 eyes of 176 primary open-angle glaucoma patients with 10 or more VFs and 6 years or more of follow-up. RESULTS: The degree of variability changed as a function of threshold sensitivity with a zenith and a nadir at 33 and 11 dB, respectively. Variability decreased with eccentricity and was higher in the central 10° (P < 0.001). Differences among the methods for data fit were negligible. PER was the best model to predict future sensitivity values in the mid term and long term. CONCLUSIONS: VF variability increases with the severity of glaucoma damage and decreases with eccentricity. Weighted linear regression neither improves model fit nor prediction. PER exhibited the best prediction ability, which is likely related to the nonlinear nature of long-term glaucomatous perimetric decay. TRANSLATIONAL RELEVANCE: This study suggests that taking into account heteroscedasticity has no advantage in VF modeling.

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PURPOSE: To compare methods to assess visual field (VF) progression in glaucoma. METHODS: 4,950 VFs of 253 primary open angle-glaucoma patients were evaluated for progression with the following methods: clinical evaluation, guided progression analysis (GPA), mean deviation (MD), and visual field index (VFI) rates, Advanced Glaucoma Intervention Study (AGIS) and Collaborative Initial Glaucoma Treatment Study (CIGTS) scores, pointwise linear regression (PLR), permutation of PLR (PoPLR), and glaucoma rate index (GRI). A separate simulated series of longitudinal VFs was assessed with all methods except for GPA and clinical evaluation. RESULTS: The average (±SD) age of the patients at baseline was 65.4 (±11.5) years. The average (±SD) follow-up was 11.8 (±4.6) years, and the mean (±SD) number of VFs was 16.8 (±7.0). Proportion of series detected as progressing was 65% for PoPLR, 58% for GRI, 41% for GPA, 40% for PLR, 36% for CIGTS, 35% for clinicians, 31% for MD rate, 29% for AGIS, and 22% for VFI rate. Median times to detection of progression were 7.3 years for PoPLR, 7.5 years for GRI, 11 years for clinicians, 14 years for GPA, 16 years for PLR, 17 years for CIGTS, 19 years for AGIS, and more than 20 years for MD and VFI rates. In simulated VF series, GRI had the highest partial area under the receiver operator characteristic curve (0.040) to distinguish between glaucoma progression and aging/cataract decay, followed by VFI rate (0.028), MD rate (0.024), and PoPLR (0.006). CONCLUSIONS: GRI and PoPLR showed the highest proportion of series detected as progressing and shortest times to progression detection. GRI exhibited the best ability to detect progression in the simulated VF series. TRANSLATIONAL RELEVANCE: Knowledge of the properties of every method would allow tailoring application in both clinical and research settings.

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PURPOSE: To identify baseline and longitudinal risk factors for fast visual field (VF) decay in patients with open-angle glaucoma. DESIGN: Retrospective cohort study. METHODS: Patients with open-angle glaucoma with ≥6 VFs and ≥4 years of follow-up were included. VF decay rates were measured with the following methods: mean deviation (MD) rate, VF index (VFI) rate, and the Glaucoma Rate Index (GRI). The relationship between VF rates and clinical variables were investigated with linear mixed models. Logistic regression analysis was performed to determine which factors were associated with fast progression. RESULTS: A total of 1317 eyes of 745 patients with a mean (± SD) age of 63.3 (±10.9) years and a median (interquartile range) MD -2.4 (-0.7 to -5.6) dB at baseline were analyzed. The median (interquartile range) number of VFs was 12 (9 to 16), and mean follow-up duration was 11.5 (±3.7) years. Older age (P < .001), higher peak intraocular pressure (IOP) (P < .001), and glaucoma surgery during the study period (P < .001) were associated with faster rates of progression regardless of the method used. Worse baseline MD was associated with MD rate (P = .02), but neither with VFI rate (P = .37) nor GRI (P = .31); whereas pseudoexfoliative glaucoma was associated with faster rates of progression with MD (P = .008) and VFI (P = .01) rates, but not with GRI. Higher peak IOPs (P = .005) was a significant predictor for fast progression. CONCLUSION: In this cohort, older age, peak IOP, pseudoexfoliative glaucoma, and baseline MD were associated with the rate of glaucomatous VF worsening. Fast progressors had a higher peak IOP than non-fast progressors. The identification and appropriately aggressive treatment of fast progressors would reduce visual disability from glaucoma.

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PURPOSE: To test the hypothesis that cataract surgery slows the apparent rate of visual field (VF) decay in primary open-angle glaucoma patients compared with rates measured during cataract progression. DESIGN: Retrospective cohort study. METHODS: Consecutive open-angle glaucoma patients who underwent cataract surgery and who had ≥4 VFs and ≥3 years of follow-up before and after surgery were retrospectively reviewed. Mean deviation (MD) rate, visual field index (VFI) rate, pointwise linear regression (PLR), pointwise rate of change (PRC), and the Glaucoma Rate Index (GRI) were compared before and after cataract surgery. RESULTS: A total of 134 eyes of 99 patients were included. Median (interquartile range) follow-up was 6.5 (4.7-8.1) and 5.3 (4.0-7.3) years before and after cataract surgery, respectively. All intraocular pressure (IOP) parameters (mean IOP, standard deviation of IOP, and peak IOP) significantly improved (P < .001) after cataract surgery. All VF indices indicated an accelerated VF decay rate after cataract surgery: MD rate (-0.18 ± 0.40 dB/year vs -0.40 ± 0.62 dB/year, P < .001), VFI rate (-0.44% ± 1.09%/year vs -1.19% ± 1.85%/year, P < .001), GRI (-5.5 ± 10.8 vs -13.5 ± 21.5; P < .001), and PRC (-0.62% ± 2.47%/year before and -1.35% ± 3.71%/year after surgery; P < .001) and PLR (-0.20 ± 0.82 dB/year before and -0.42 ± 1.16 dB/year after surgery; P < .001) for all VF locations. Worse baseline MD and postoperative peak IOP were significantly associated with the postoperative VF decay rate and the change in the decay rate after cataract surgery. CONCLUSION: Although all IOP parameters improved after cataract surgery, VFs continued to progress. Cataract surgery does not slow the apparent rate of glaucomatous VF decay as compared to rates measured during the progression of the cataract.

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PURPOSE: This study assessed the effectiveness of the HIV/sexually transmitted infection/pregnancy prevention program, It's Your Game: Keep It Real (IYG). METHODS: IYG was implemented by classroom teachers in 24 urban middle schools from 2012 to 2015. Using a quasi-experimental design, each year we surveyed ninth-grade students in 10 high schools that were selected based on feeder patterns from project middle schools. We compared two groups of students (n = 4,562): (1) students whose middle school grade cohorts did not receive IYG ("No-IYG"), and (2) students whose middle school grade cohorts received IYG ("IYG"). Multilevel analyses examined differences between the two groups in the initiation of any type of sexual activity (oral, vaginal, or anal sex), presexual behaviors, and psychosocial mediators. RESULTS: Students in the IYG group were less likely to report initiation of sexual activity by ninth grade compared to students in the No-IYG group (odds ratio .77; 95% confidence interval .66-.90). The IYG group was significantly less likely to have engaged in presexual behaviors, including having been on a date, had a boyfriend/girlfriend, and touched or been touched on private body parts. The IYG group had better outcomes on 11 of 19 psychosocial variables, including knowledge; beliefs about abstinence, sex, friends' beliefs, norms, and behaviors; reasons for not having sex; personal limits; exposure to risky situations; self-efficacy; and quality of dating relationships. CONCLUSIONS: The results suggest that IYG, when implemented on a large scale by trained classroom teachers in urban public schools, had positive impacts on students' behaviors, beliefs, and knowledge.

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PURPOSE: To develop a method to measure the rate of glaucomatous visual field (VF) deterioration and to identify fast progressors. METHODS: Retrospective, longitudinal, observational study of 8486 eyes of 4610 glaucomatous patients with ≥6 VFs and ≥3 years of follow-up. A Glaucoma Rate Index (GRI) was calculated. VF locations were partitioned into exponential decay or exponential improvement models. A pointwise rate of change (PRC) was estimated with an exponential fit and expressed as the percent/year change of the age- and location-matched normal perimetric range, presented as a spatially conserved VF map. PRCs were summed and normalized with boundary rates set by simulated decaying and improving VF series on a scale of -100 to +100, respectively. RESULTS: A total of 89,704 VF examinations with 425,039 test location series was used. Median follow-up and number of VFs/eye were 9.7 years and 9 VFs, respectively. Initial and final mean deviations (±SD) were -4.2 (±5.2) and -5.7 (±6.4) dB. The proportions of test locations designated as decayed, improved, and unchanged were 13%, 4%, and 83%, respectively. Mean PRCs for decay, improvement, and no change were -3.7 (±4.7)%/y, 2.5 (±2.6)%/y, and -0.5 (±2.1)%/y, respectively. The number of eyes with negative and positive GRIs was 5802 (68%) and 2390 eyes (28%), respectively. The proportion of eyes defined as fast progressors was 6.8%. CONCLUSIONS: GRI provides a robust measure of glaucomatous VF change, operates without discontinuity over the entire perimetric range, and can be used to identify fast progressors. TRANSLATIONAL RELEVANCE: This study describes a novel method that can help the clinician to determine VF progression.

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In-depth interviews and focus group discussions were conducted to inform the development of an instrument to measure the health-related quality of life of children living with HIV. The QOL-CHAI instrument consists of four generic core scales of the "Pediatric Quality of Life Inventory" and two HIV-targeted scales-"symptoms" and "discrimination." A piloting exercise involving groups of children living with HIV and HIV-negative children born to HIV-infected parents provided evidence for the acceptable psychometric properties and usability of the instrument. It is expected that the QOL-CHAI can serve well as a brief, standardized, and culturally appropriate instrument for assessing health-related quality of life of Indian children living with HIV.

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Purpose: To test the hypothesis that vertical asymmetry in macular ganglion cell/inner plexiform layer (GCIPL) thickness can improve detection of early glaucoma. Methods: Sixty-nine normal eyes and 101 glaucoma eyes had macular imaging with spectral-domain optical coherence tomography (OCT; 200 × 200 cube). The resulting GCIPL thickness matrix was grouped into a 20 × 20 superpixel array and superior superpixels were compared to their inferior counterparts. A global asymmetry index (AI) was defined as the grand mean of the asymmetry ratios. To measure local asymmetry, the corresponding thickness measurements of three rows above and below the horizontal raphe were compared individually and in combinations. Global and local AIs were compared to the best-performing GCIPL thickness parameters with area under the receiver operating curves (AUC) and sensitivity/specificities. Results: Age or axial length did not influence AIs in normal subjects (P ≥ 0.08). Global and local AIs were significantly higher in the glaucoma group compared to normal eyes. Minimum (AUC = 0.962, 95% confidence interval [CI]: 0.936-0.989) and inferotemporal thickness (AUC = 0.944, 95% CI: 0.910-0.977; P = 0.122) performed best for detection of early glaucoma. The AUC for global AI was 0.851 (95% CI: 0.792-0.909) compared to 0.916 (95% CI: 0.874-0.958) for the best local AI. Combining minimum or inferotemporal GCIPL thickness and the best local AI led to higher partial AUCs (0.088 and 0.085, 90% specificity, P = 0.120 and 0.130, respectively) than GCIPL thickness measures. Conclusions: Macular vertical thickness asymmetry measures did not perform better than sectoral or minimum GCIPL thickness for detection of early glaucoma. Combining local asymmetry parameters with the best sectoral GCIPL thickness measures enhanced this task.

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PURPOSE: Helping children living with HIV (CLH) to attain an optimum quality of life is an important goal for HIV programs around the world. Our principal objectives were to determine the association of HIV infection with different domains of health-related quality of life (HRQoL) among 8- to 15-year-old CLH in India and to compare the HRQoL parameters between CLH and HIV-negative children born to HIV-infected parents ("HIV-affected"). We also assessed whether antiretroviral therapy (ART) and CD4 lymphocyte counts were associated with HRQoL among CLH. METHODS: Using the "Quality of Life (health-related) of Children Living with HIV/AIDS in India" instrument, we interviewed 199 CLH and 194 HIV-affected children from three districts of West Bengal, India. Participants were asked to quantify the difficulties faced by them in six HRQoL domains: physical, emotional, social, school functioning, symptoms, and discrimination. RESULTS: The mean age of the participants was 11.6 (SD ± 2.5) years. CLH, compared to HIV-affected children, had poorer scores on all HRQoL domains except 'discrimination.' Among CLH, there were no significant differences in HRQoL domain scores (except in the 'discrimination' domain) between ART-treated and -untreated groups. CD4 lymphocyte count was found to be a significant positive predictor of the 'symptom' scale score. CONCLUSIONS: In India, interventions for CLH mostly focus on biological disease. However, the current study revealed that HRQoL among CLH was much poorer than that of a socio-demographically comparable group. Culturally and developmentally appropriate psychosocial support measures for Indian CLH are urgently needed.

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AIMS: To explore the correlation of local macular ganglion cell/inner plexiform layer (GC/IPL) thickness measurements with sensitivity at individual test locations on the central 10-2 visual fields (VFs) in patients with glaucoma. METHODS: One hundred thirty-seven eyes of 125 patients with spectral domain optical coherence tomography (OCT) and 10-2 VFs were included. The exported thickness matrices (200×200) of GC/IPL measurements were centred on the fovea. Total deviation values at each test location were correlated with the 20 000 GC/IPL thickness measurements in the corresponding inferior or superior hemiretina, and areas of highest correlation were plotted. Macular structure-function relationships were also examined between six wedge-shaped GC/IPL sectors and the corresponding VF clusters. A multivariate model was built to identify the 10-2 VF test locations associated with each GC/IPL sector thickness. RESULTS: Average mean deviation on 10-2 VFs was -9.2±6.1 dB. The 10-2 VF test points demonstrated correlations with GC/IPL thickness in localised arcuate patterns mostly limited within the central 4.8×4.0 mm measurement ellipse (ρ=0.43-0.74, p<0.05 for all). Twenty-one test points of the 10-2 VF were the best predictors of sectoral GC/IPL thickness. Sectoral VF-OCT correlations were high (ρ=0.53-0.66, p<0.001) and did not significantly change after adjusting for retinal GC displacement (p>0.05). CONCLUSIONS: Macular OCT/VF relationships have localised arcuate characteristics in the central region of the macula. Given the overlapping nature of structure-function relationships, a smaller number of VF test locations may be used to summarise macular functional damage. TRIAL REGISTRATION NUMBER: NCT01742819.

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This analysis assessed patterns of sexual experience, the order in which behaviors were initiated, and associated factors, among Latino and African American ninth grade students (average age 15.2) who self-administered audio-computer-assisted surveys on netbooks in classes at 10 Los Angeles-area public high schools. Lifetime experiences with vaginal and oral sex were most common (19% and 16%, respectively); fewer reported anal sex (6%). Of the 23% reporting any sex, 91% fell into four categories: 36% reporting both oral and vaginal sex; 23% vaginal only; 18% all three; and 13% oral only. Most sexually experienced students (88%) initiated with vaginal or oral sex (46% vaginal, 33% oral, 9% both same day). No dominant pathway of sexual onset emerged for those reporting all three types of sex. We found no evidence that oral or anal sex substituted for or delayed vaginal sex. Males, those with a current partner, and those reporting multiple partners were more likely than others to report all three sexual behaviors versus vaginal only (odds ratios [ORs] 2.0, 1.5, 3.0; p = .02, .06, < .01, respectively). Although vaginal intercourse dominated their early sexual behavior, one-fifth of sexually experienced students reported anal intercourse, highlighting the need for specific prevention messages surrounding this higher-risk behavior.

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BACKGROUND AND PURPOSE: The National Institutes of Health (NIH) funds training programs to increase the numbers and skills of scientists who obtain NIH research grants, but few programs have been rigorously evaluated. The sizeable recent NIH investment in developing programs to increase the diversity of the NIH-funded workforce, implemented through the Diversity Program Consortium (DPC), is unusual in that it also funds a Consortium-wide evaluation plan, which spans the activities of the 10 BUilding Infrastructure Leading to Diversity (BUILD) awardees and the National Research Mentoring Network (NRMN). The purpose of this article is to describe the evaluation design and innovations of the BUILD Program on students, faculty, and institutions of the 10 primarily undergraduate BUILD sites. KEY HIGHLIGHTS OF THE PROJECT: Our approach to this multi-methods quasi-experimental longitudinal evaluation emphasizes stakeholder participation and collaboration. The evaluation plan specifies the major evaluation questions and key short- to long-term outcome measures (or Hallmarks of Success). The Coordination and Evaluation Center (CEC) embarked on a comprehensive evaluation strategy by developing a set of logic models that incorporate the Hallmarks of Success and other outcomes that were collaboratively identified by the DPC. Data were collected from each BUILD site through national surveys from the Higher Education Research Institute at UCLA (HERI), annual followup surveys that align with the HERI instruments, site visits and case studies, program encounter data ("tracker" data), and institutional data. The analytic approach involves comparing changes in Hallmarks (key outcomes) within institutions for biomedical students who participated versus those who did not participate in the BUILD program at each institution, as well as between institution patterns of biomedical students at the BUILD sites, and matched institutions that were not BUILD grantees. Case studies provide insights into the institutionalization of these new programs and help to explain the processes that lead to the observed outcomes. IMPLICATIONS: Ultimately, the results of the consortium-wide evaluation will be used to inform national policy in higher education and will provide relevant examples of institutional and educational programmatic changes required to diversify the biomedical workforce in the USA.

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IMPORTANCE: Identifying the course of glaucomatous visual field (VF) loss that progresses from normal to perimetric blindness is important for treatment and prognostication. OBJECTIVE: To model the process of glaucomatous VF decay over the entire perimetric range from normal to perimetric blindness. DESIGN, SETTING, AND PARTICIPANTS: A post hoc, retrospective analysis was performed using data from the Advanced Glaucoma Intervention Study and the UCLA (University of California, Los Angeles) Jules Stein Eye Institute Glaucoma Division. Patients with open-angle glaucoma and VFs obtained from reliable examinations (defined as <30% fixation losses, <30% false-positive rates, and <30% false-negative rates) were recruited. All tests were performed with standard automated perimetry and a 24-2 test pattern. Linear, exponential, and sigmoid regression models were used to assess the pattern of threshold sensitivity deterioration at each VF location as a function of time. Visual field locations of interest included those with a mean of the initial 2 sensitivities of 26 dB or greater and a less than 10-dB mean of the final 2 sensitivities. Root mean squared error (RMSE) was used to evaluate goodness of fit for each regression model. The error was defined as the difference between the sensitivities modeled by the function and the observed sensitivities. The Advanced Glaucoma Intervention Study was conducted from 1998 to 2006; the present post hoc analysis was conducted from March 1, 2014, to March 1, 2015. MAIN OUTCOMES AND MEASURES: The RMSE of the residuals (fitted minus observed values) for the 3 regression models was used to evaluate goodness of fit. RESULTS: A total of 798 eyes from 583 patients (mean [SD] age, 64.7 [10.7] years; 301 [51.6%] women) who had more than 6 years of follow-up and underwent more than 10 VF examinations were included in this analysis. Mean (SD) follow-up time was 8.7 (2.2) years, and each eye had a mean of 15.2 (4.9) VF tests. For the VF locations with an initial sensitivity of 26 dB or greater and final sensitivity of less than 10 dB (309 locations), the sigmoid best-fit regression model had the lowest RMSE in 248 (80.3%) of the locations, the exponential function in 39 (12.6%), and the linear function in 22 (7.1%). The means (SDs) of RMSE were sigmoid, 4.1 (1.9); exponential, 6.0 (1.5); and linear 5.8 (1.6). CONCLUSIONS AND RELEVANCE: Pointwise sigmoid regression had a better ability to fit perimetric decay into a subset of locations that traverse the entire range of perimetric measurements from near normal to near perimetric blindness compared with linear and exponential functions. These results support the concept that the measured behavior of glaucomatous VF loss to perimetric blindness is nonlinear and that its course of deterioration may change with the course of disease.