Development and validation of a clinical score to estimate progression to severe or critical state in Covid-19 pneumonia hospitalized patients

The prognosis of a patient with Covid-19 pneumonia is uncertain. Our objective was to establish a predictive model of disease progression to facilitate early decision-making. A retrospective study was performed of patients admitted with Covid-19 pneumonia, classified as severe (admission to the intensive care unit, mechanic invasive ventilation, or death) or non-severe. A predictive model based on clinical, analytical, and radiological parameters was built. The probability of progression to severe disease was estimated by logistic regression analysis. Calibration and discrimination (receiver operating characteristics curves and AUC) were assessed to determine model performance. During the study period 1,152 patients presented with Covid-19 infection, of whom 229 (19.9%) were admitted for pneumonia. During hospitalization, 51 (22.3%) progressed to severe disease, of whom 26 required ICU care (11.4); 17 (7.4%) underwent invasive mechanical ventilation, and 32 (14%) died of any cause. Five predictors determined within 24 hours of admission were identified: Diabetes, Age, Lymphocyte count, SaO2, and pH (DALSH score). The prediction model showed a good clinical performance, including discrimination (AUC 0.87 CI 0.81, 0.92) and calibration (Brier score = 0.11). In total, 0%, 12%, and 50% of patients with severity risk scores ≤5%, 6-25%, and >25% exhibited disease progression, respectively. A simple risk score based on five factors predicts disease progression and facilitates early decision-making according to prognosis.Carlos III Health Institute, Spain, Ministry of Economy and Competitiveness (SPAIN) and the European Regional Development Fund (FEDER)Instituto de Salud Carlos II

PREOPERATIVE VITREORETINAL INTERFACE ABNORMALITIES ON SPECTRAL DOMAIN OPTICAL COHERENCE TOMOGRAPHY AS RISK FACTOR FOR PSEUDOPHAKIC CYSTOID MACULAR EDEMA AFTER PHACOEMULSIFICATION

Abstract Purpose: We assessed the role of vitreoretinal interface status in the development of pseudophakic cystoid macular edema (PCME) after cataract surgery. Methods: Prospective cohort study in which 112 patients (112 eyes) scheduled for cataract surgery were selected at random to undergo spectral domain optical coherence tomography (OCT) within 1 week preoperatively and at 1 and 3 months postoperatively. Spectral domain OCT macular images included no vitreoretinal contact, focal and diffuse vitreomacular adhesion, focal and diffuse vitreomacular traction, epiretinal membrane, macular hole, and macular edema. Results: The incidence of PCME was 11.6% (13 eyes), all of them being diagnosed at 1 month, and 7 eyes resolved at 3 months. The only risk factor for PCME was detection of nonsurgical epiretinal membrane by spectral domain OCT before phacoemulsification, being developed in 5 of 16 eyes (χ = 0.08, odds ratio 4.53, 95% confidence interval 1.28-16.13). Other variables such as posterior vitreous detachment, subfoveal choroidal thickness, diabetes, or hypertension were not significantly associated with PCME. Conclusion: In this cohort, preoperative detection of epiretinal membrane by spectral domain OCT was a risk factor for PCME after cataract extraction. It is recommended to perform a spectral domain OCT before cataract surgery because the presence of an epiretinal membrane may be passed unnoticed by fundus examination

A comparative study between swedish interactive thresholding algorithm faster and swedish interactive thresholding algorithm standard in glaucoma patients

Purpose: to compare the results of the new strategy Swedish Interactive Thresholding Algorithm (SITA) Faster to the results of SITA Standard in patients with glaucoma. Methods: this was a cross-sectional study of 49 patients with glaucoma and previous experience with standard automated perimetry. Two consecutive tests were performed in random order, one with SITA Standard and another one with SITA Faster, in the studied eye of each patient. Comparisons were made for test time, mean deviation (MD), visual field index (VFI), and number of depressed points in pattern deviation map and total deviation map for every level of significance. Results: the average test time was 56% shorter with SITA Faster (P < 0.001). The intraclass correlation coefficient (ICC) for MD and VFI showed excellent agreement between both strategies, ICC = 0.98 (95% confidence interval [CI]: 0.96, 0.99) and ICC = 0.97 (95% CI: 0.95, 0.99), respectively. For the number of depressed points in total deviation map and pattern deviation map, ICC demonstrated good agreement with values between 0.8 and 0.95. Conclusions: our study shows that SITA Faster is a shorter test with strong agreement with SITA Standard parameters. These results suggest that SITA Faster could replace SITA Standard for glaucoma diagnosis