Objective To construct and verify an early prediction model for visual benefit of diabetic macular edema(DME)after anti-vascular endothelial growth factor(VEGF)treatment based on clinical data,optical coherence tomo-graphy angiography(OCTA),serum brain tissue aquaporin-4(AQP4)mRNA and total bilirubin(TBIL)levels.Methods A total of 480 patients(480 eyes)with DME treated in the First People's Hospital of Zigong City from October 2021 to March 2024 were selected and divided into a modeling set(320 cases)and a validation set(160 cases)at a ratio of 2∶1.According to the visual benefit after anti-VEGF treatment,patients in the modeling set were further divided into a benefit group(80 cases)and a non-benefit group(240 cases).The baseline data of the two groups of patients were collected,and the factors influencing visual benefits in DME patients after anti-VEGF treatment were analyzed.An early prediction model was constructed and validated both internally and externally.Results The inter-group comparison results showed that the diabetes duration in the non-benefit group was longer than that in the benefit group(P＜0.05).The proportion of smokers,the best corrected visual acuity(BCVA),the minimum resolution angle(logMAR)vision,hemoglobin A1c(HbAlc)and AQP4 mRNA levels were higher in the non-benefit group than those in the benefit group(all P＜0.05).The foveal retinal deep capillary plexus blood flow density(DCP-VD),central macular thickness(CMT),and TBIL levels were lower in the non-benefit group than those in the benefit group(all P＜0.05).The least absolute shrinkage and selection operator(LAS-SO)-Logistic regression analysis showed that the factors influencing visual benefit in DME patients after anti-VEGF treat-ment were CMT,BCVA(logMAR),HbAlc,AQP4 mRNA levels,foveal DCP-VD,and TBIL levels.The predictive risk con-sistency index of the nomogram model constructed based on the above-mentioned influencing factors for visual benefit pre-diction after anti-VEGF treatment was 0.844.The receiver operating characteristic(ROC)curve showed that the area un-der the ROC curve(AUC)of the model was 0.844(95％ CI:0.797-0.891)in the modeling set and 0.898(95％ CI:0.847-0.949)in the validation set.The decision analysis curve showed that when the high-risk threshold of the modeling set ranged between 0 and 82％ and that of the validation set ranged between 0 and 100％,the model could bring net clinical benefits.Conclusion CMT,BCVA(logMAR),HbAlc,AQP4 mRNA levels,foveal DCP-VD,and TBIL levels are the fac-tors influencing visual benefit in DME patients after anti-VEGF treatment.The visual benefit prediction model constructed based on these factors has high accuracy and stability,and can be used as an effective tool for clinical prediction of visual benefit after treatment.

Objective To construct and verify an early prediction model for visual benefit of diabetic macular edema(DME)after anti-vascular endothelial growth factor(VEGF)treatment based on clinical data,optical coherence tomo-graphy angiography(OCTA),serum brain tissue aquaporin-4(AQP4)mRNA and total bilirubin(TBIL)levels.Methods A total of 480 patients(480 eyes)with DME treated in the First People's Hospital of Zigong City from October 2021 to March 2024 were selected and divided into a modeling set(320 cases)and a validation set(160 cases)at a ratio of 2∶1.According to the visual benefit after anti-VEGF treatment,patients in the modeling set were further divided into a benefit group(80 cases)and a non-benefit group(240 cases).The baseline data of the two groups of patients were collected,and the factors influencing visual benefits in DME patients after anti-VEGF treatment were analyzed.An early prediction model was constructed and validated both internally and externally.Results The inter-group comparison results showed that the diabetes duration in the non-benefit group was longer than that in the benefit group(P＜0.05).The proportion of smokers,the best corrected visual acuity(BCVA),the minimum resolution angle(logMAR)vision,hemoglobin A1c(HbAlc)and AQP4 mRNA levels were higher in the non-benefit group than those in the benefit group(all P＜0.05).The foveal retinal deep capillary plexus blood flow density(DCP-VD),central macular thickness(CMT),and TBIL levels were lower in the non-benefit group than those in the benefit group(all P＜0.05).The least absolute shrinkage and selection operator(LAS-SO)-Logistic regression analysis showed that the factors influencing visual benefit in DME patients after anti-VEGF treat-ment were CMT,BCVA(logMAR),HbAlc,AQP4 mRNA levels,foveal DCP-VD,and TBIL levels.The predictive risk con-sistency index of the nomogram model constructed based on the above-mentioned influencing factors for visual benefit pre-diction after anti-VEGF treatment was 0.844.The receiver operating characteristic(ROC)curve showed that the area un-der the ROC curve(AUC)of the model was 0.844(95％ CI:0.797-0.891)in the modeling set and 0.898(95％ CI:0.847-0.949)in the validation set.The decision analysis curve showed that when the high-risk threshold of the modeling set ranged between 0 and 82％ and that of the validation set ranged between 0 and 100％,the model could bring net clinical benefits.Conclusion CMT,BCVA(logMAR),HbAlc,AQP4 mRNA levels,foveal DCP-VD,and TBIL levels are the fac-tors influencing visual benefit in DME patients after anti-VEGF treatment.The visual benefit prediction model constructed based on these factors has high accuracy and stability,and can be used as an effective tool for clinical prediction of visual benefit after treatment.

OBJECTIVE: To observe the clinical treatment effectiveness of Clarithromycin combined with nasal glucocorticoids for chronic rhinosinusitis (CRS). METHOD: Clarithromycin was 0.25 g a day (the first two weeks was 0.25 g twice a day) and topical Triamcinolone Acetonide Acetate nasal spray was (220 microg/d) once a day. Fifty-six patients were enrolled in our research. Twenty-six patients of CRS without nasal polyps was treated for 12 to 28 weeks (average 16.62 weeks). Thirty patients of CRS with nasal polyps was treated for 12 to 33 weeks (average 20.03 weeks) after polypectomy. The patients' symptom were evaluated through Sino-Nasal Outcome Test 20 (SNOT-20) scale. Meanwhile sinus CT were evaluated by Lund-Mackey system before and after operation. RESULT: The score of CT scan was significantly decreased to 2.83 +/- 1.86 (t = 11.41, P < 0.01) in the CRS with nasal polyps group and to 2.43 +/- 1.91 (t = 12.86, P < 0.01) in the CRS without nasal polyps group after treatment. Recovery rate of CRS with nasal polyps group was 43.3% and of CRS without nasal polyps group was 50.0% with CT images. The self assessments of treatment efficiency was coincident with CT image in the two groups. CONCLUSION The treatment with Long term use of low dosage oral macrolide Clarithromycin combined with nasal steroid on CRS was efficacy. Polypectomy ,large dose antibiotic and steroid used in intraoperative period could significant improve the treatment efficiency of CRS with nasal polyps.
Adolescent ; Adult ; Aged ; Chronic Disease ; Clarithromycin ; administration & dosage ; therapeutic use ; Drug Therapy, Combination ; Female ; Humans ; Male ; Middle Aged ; Nasal Polyps ; drug therapy ; Rhinitis ; drug therapy ; Sinusitis ; drug therapy ; Treatment Outcome ; Triamcinolone Acetonide ; administration & dosage ; therapeutic use ; Young Adult