ObjectiveTo analyze pathogenic factors and etiological characteristics of suppurative endophthalmitis.MethodsA total of 531 consecutive patients (531 eyes) with suppurative endophthalmitis who were hospitalized in Qingdao Eye Hospital of Shandong Eye Institute from January 2006 to December 2015 were included in the study. Among them, 410 patients with 410 eyes were males (77.2%), 121 patients with 121 eyes were females (22.8%). The average age of the patients was 38.62±15.36 years. The relevant medical records were collected to analyze the pathogenic factors. Samples of aqueous humor, vitreous or other intraocular samples were taken under aseptic conditions for bacterial and fungal culture and in vitro drug sensitivity test.ResultsOcular trauma was the primary pathogenic factor of suppurative endophthalmitis (60.1%), other factors included postoperative endophthalmitis (19.0%), suppurative keratitis-related endophthalmitis (17.1%) and endogenous endophthalmitis (3.8%). Postoperative endophthalmitis mainly occured after cataract surgery. A total of 224 strains of organisms were isolated, among which the predominant organisms isolated were gram-positive bacteria (54.0%) and staphylococcus epidermidis was the most common (25.0%). The other pathogenic organisms were fungi (29.5%) and gram-negative bacteria (16.5%). Among the fungi, aspergillus (10.7%) was the dominant genus, followed by fusarium (9.8%). For gram-positive organisms, susceptibilities were vancomycin 97.4%, gatifloxacin 91.8%, fusidate acid 77.9% and levofloxacin 54.6%. For gram-negative organisms, susceptibilities were gatifloxacin 85.7%, levofloxacin 77.8%, tobramycin 71.4% and ceftazidime 62.5%. For fungal isolates, sensitivities were voriconazole 88.2% and amphotericin B 84.8%.ConclusionsOcular trauma is the main pathogenic factor of suppurative endophthalmitis, followed by postoperative endophthalmitis and suppurative keratitis-related endophthalmitis. Gram-positive bacteria are the major pathogenic organisms, especially staphylococcus epidermidis followed by fungal species, among which aspergillus and fusarium were the dominating pathogenic genus.
ObjectiveTo compare and observe the curative effect of different body positions after pars plana vitrectomy (PPV) combined with inert gas filling for rhegmatogenous retinal detachment (RRD). MethodsA retrospective clinical study. From October 2019 to September 2021, 192 eyes of 192 RRD patients who were diagnosed and received PPV combined with inert gas filling in Qingdao Eye Hospital of Shandong First Medical University were included in the study. Best corrected visual acuity (BCVA), intraocular pressure, ultra-wide-angle fundus photography, optical coherence tomography, and B-mode ultrasonography were performed in all affected eyes. The BCVA examination was performed using a standard logarithmic visual acuity chart, which was converted into logarithm of the minimum angle of resolution (logMAR) visual acuity during statistics. According to the post-operative position requirements, the affected eyes were divided into the face-down positioning group and the adjustable positioning group, with 97 eyes in 97 patients and 95 eyes in 95 patients, respectively. Age (Z=0.804), course of disease (Z=－0.490), eye type (χ2=0.175), logMAR BCVA (Z=－0.895), intraocular pressure (Z=0.178), lens status (χ2=1.090), number of detached clocks (Z=0.301) and macular involvement (χ2=0.219), number of holes (Z=－1.051) and number of lower holes (χ2=0.619) were compared, there was no significant difference (P＞0.05). The gender composition ratio was compared, and the difference was statistically significant (χ2=5.341, P＜0.05). The follow-up time after surgery was more than 3 months. The retinal reattachment rate in one operation, the improvement of BCVA and the incidence of complications were observed. The independent sample Mann-Whitney test was used for the comparison of continuous variables between groups; the χ2 test was used for the comparison of categorical variables. ResultsIn the face-down positioning group and the adjustable positioning group, retinal reattachment in one operation was performed in 92 (94.8%, 92/97) and 89 (93.7%, 89/95) eyes, respectively; logMAR BCVA was 0.45±0.34, 0.41±0.21. There was no significant difference in the retinal reattachment rate in one operation (χ2=0.120, P=0.729) and logMAR BCVA (Z=－0.815, P=0.416) between the two groups. After surgery, the intraocular pressure increased in 11 (11.3%, 11/97) and 5 (5.3%, 5/95) eyes in the face-down positioning group and the adjustable positioning group, respectively; the secondary epimacular membrane was 2 (2.1%, 2/97), 3 (3.2%, 3/95) eyes. There was no significant difference in the incidence of elevated intraocular pressure and secondary epimacular membrane between the two groups after surgery (χ2=2.320, 0.227; P=0.128, 0.634). ConclusionIt is safe and effective to adopt adjustable positioning after PPV combined with inert gas filling for RRD, which is equivalent to the effect of face-down positioning.
ObjectiveTo observe the diagnostic value of six classification intelligent auxiliary diagnosis lightweight model for common fundus diseases based on fundus color photography. MethodsA applied research. A dataset of 2 400 color fundus images from Nanjing Medical University Eye Hospital and Zhejiang Mathematical Medical Society Smart Eye Database was collected, which was desensitized and labeled by a fundus specialist. Of these, 400 each were for diabetic retinopathy, glaucoma, retinal vein occlusion, high myopia, age-related macular degeneration, and normal fundus. The parameters obtained from the classical classification models VGGNet16, ResNet50, DenseNet121 and lightweight classification models MobileNet3, ShuffleNet2, GhostNet trained on the ImageNet dataset were migrated to the six-classified common fundus disease intelligent aid diagnostic model using a migration learning approach during training as initialization parameters for training to obtain the latest model. 1 315 color fundus images of clinical patients were used as the test set. Evaluation metrics included sensitivity, specificity, accuracy, F1-Score and agreement of diagnostic tests (Kappa value); comparison of subject working characteristic curves as well as area under the curve values for different models. ResultCompared with the classical classification model, the storage size and number of parameters of the three lightweight classification models were significantly reduced, with ShuffleNetV2 having an average recognition time per sheet 438.08 ms faster than the classical classification model VGGNet16. All 3 lightweight classification models had Accuracy > 80.0%; Kappa values > 70.0% with significant agreement; sensitivity, specificity, and F1-Score for the diagnosis of normal fundus images were ≥ 98.0%; Macro-F1 was 78.2%, 79.4%, and 81.5%, respectively. ConclusionThe intelligent assisted diagnosis of common fundus diseases based on fundus color photography is a lightweight model with high recognition accuracy and speed; the storage size and number of parameters are significantly reduced compared with the classical classification model.