A Diagnostic Calculator for Detecting Glaucoma on the Basis of Retinal Nerve Fiber Layer, Optic Disc, and Retinal Ganglion Cell Analysis by Optical Coherence Tomography

Purpose: The purpose of this study was to develop and validate a multivariate predictive model to detect glaucoma by using a combination of retinal nerve fiber layer (RNFL), retinal ganglion cell-inner plexiform (GCIPL), and optic disc parameters measured using spectral-domain optical coherence tomography (OCT). Methods: Five hundred eyes from 500 participants and 187 eyes of another 187 participants were included in the study and validation groups, respectively. Patients with glaucoma were classified in five groups based on visual field damage. Sensitivity and specificity of all glaucoma OCT parameters were analyzed. Receiver operating characteristic curves (ROC) and areas under the ROC (AUC) were compared. Three predictive multivariate models (quantitative, qualitative, and combined) that used a combination of the best OCT parameters were constructed. A diagnostic calculator was created using the combined multivariate model. Results: The best AUC parameters were: inferior RNFL, average RNFL, vertical cup/disc ratio, minimal GCIPL, and inferior-temporal GCIPL. Comparisons among the parameters did not show that the GCIPL parameters were better than those of the RNFL in early and advanced glaucoma. The highest AUC was in the combined predictive model (0.937; 95% confidence interval, 0.911–0.957) and was significantly (P = 0.0001) higher than the other isolated parameters considered in early and advanced glaucoma. The validation group displayed similar results to those of the study group. Conclusions: Best GCIPL, RNFL, and optic disc parameters showed a similar ability to detect glaucoma. The combined predictive formula improved the glaucoma detection compared to the best isolated parameters evaluated. The diagnostic calculator obtained good classification from participants in both the study and validation groups.

Pathways to quiescence: SHARDS view on the star formation histories of massive quiescent galaxies at 1.0 < z < 1.5

We present star formation histories (SFHs) for a sample of 104 massive (stellar mass M > 10^10 M_⊙) quiescent galaxies (MQGs) at z = 1.0–1.5 from the analysis of spectrophotometric data from the Survey for High-z Absorption Red and Dead Sources (SHARDS) and HST/WFC3 G102 and G141 surveys of the GOODS-North field, jointly with broad-band observations from ultraviolet (UV) to far-infrared (far-IR). The sample is constructed on the basis of rest-frame UVJ colours and specific star formation rates (sSFRs = SFR/Mass). The spectral energy distributions (SEDs) of each galaxy are compared to models assuming a delayed exponentially declining SFH. A Monte Carlo algorithm characterizes the degeneracies, which we are able to break taking advantage of the SHARDS data resolution, by measuring indices such as MgUV and D4000. The population of MQGs shows a duality in their properties. The sample is dominated (85 per cent) by galaxies with young mass-weighted ages, t_M t_M < 2 Gyr, short star formation time-scales, 〈τ〉 ∼ 60–200 Myr, and masses log(M/M_⊙) ∼ 10.5. There is an older population (15 per cent) with t_M t_M = 2–4 Gyr, longer star formation time-scales, 〈τ〉∼ 400 Myr, and larger masses, log(M/M_⊙) ∼ 10.7. The SFHs of our MQGs are consistent with the slope and the location of the main sequence of star-forming galaxies at z > 1.0, when our galaxies were 0.5–1.0 Gyr old. According to these SFHs, all the MQGs experienced a luminous infrared galaxy phase that lasts for ∼500 Myr, and half of them an ultraluminous infrared galaxy phase for ∼100 Myr. We find that the MQG population is almost assembled at z ∼ 1, and continues evolving passively with few additions to the population.