Combined treatment of submacular hemorrhage with low-dose subretinal recombinant tissue plasminogen activator and intravitreal conbercept.

BACKGROUND: Pars Plana Vitrectomy (PPV) combined with subretinal injection of low-dose recombinant tissue plasminogen activator (rt-PA) and intravitreal injection of Conbercept as a novel therapy for submacular hemorrhage (SMH) requires evaluation. METHODS: In a retrospective interventional clinical study, 14 eyes of 14 patients with SMH underwent PPV along with rt-PA (subretinal) and Conbercept (intravitreal) injections. The main outcomes included best-corrected visual acuities (BCVAs), degrees of blood displacement, and adverse events. All patients completed at least 6-month follow-up visits. RESULTS: Mean BCVAs significantly improved at 7 days (22.29 ± 15.35), 1 month (30.71 ± 16.42), 3 months (38.29 ± 13.72), 4 months (38.86 ± 14.15), and 6 months (41.21 ± 14.91) post-treatment compared to baseline (16.36 ± 13.97) (F = 12.89, P = 0.004). The peak improvement in BCVAs occurred at 6 months postoperatively. The procedure effectively eliminated subfoveal hemorrhages in all eyes, with clots removal and absorption occurring within one month and complete regression by 3-month follow-up visits. Postoperatively, two cases of AMD resulted in discoid scars on the fundus. No instances of rt-PA-related retinal toxicity were observed during the follow-up period. CONCLUSION: The combined approach of PPV with low-dose rt-PA and anti-VEGF shows promise in enhancing both vision and anatomical structure in SMH therapy. Individualized treatment plans tailored to the primary disease should be developed to optimize visual prognoses. TRIAL REGISTRATION: Retrospectively registered No.ChiCTR2100053034. Registration date: 10/11/2021.

Performance of deep learning for detection of chronic kidney disease from retinal fundus photographs: A systematic review and meta-analysis.

OBJECTIVE: Deep learning has been used to detect chronic kidney disease (CKD) from retinal fundus photographs. We aim to evaluate the performance of deep learning for CKD detection. METHODS: The original studies in CKD patients detected by deep learning from retinal fundus photographs were eligible for inclusion. PubMed, Embase, the Cochrane Library, and Web of Science were searched up to October 31, 2022. The Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool was used to assess the risk of bias. RESULTS: Four studies enrolled 114,860 subjects were included. The pooled sensitivity and specificity were 87.8% (95% confidence interval (CI): 61.6% to 98.3%), and 62.4% (95% CI: 44.9% to 78.7%). The area under the curve (AUC) was 0.864 (95%CI: 0.769, 0.986). CONCLUSION: Deep learning based on retinal fundus photographs has the ability to detect CKD, but it currently has a lot of room for improvement. It is still a long way from clinical application.

Acupoint injection for nonspecific chronic low back pain: A protocol of systematic review.

OBJECTIVE: The aim of this study was to evaluate the effect of acupuncture injection therapy for the patients with nonspecific chronic low back pain (CLBP) systematically. METHODS: Four English online databases and 4 Chinese online databases will be researched systematically from their inception to December 31, 2018. Reference management software, Endnote X7, will be used to manage and screen the records. After removing the duplicate records, 2 independent reviewers will select the studies that meet the inclusion criteria. "Risk of table" recommend by Cochrane Handbook for Systematic Reviews of Interventions will be used to judge the quality of the included records. All data will be extracted by 1 reviewer and checked by another reviewer. Any disagree will be addressed via consulting a third reviewer in the above processes. Microsoft Excel will be used to manage and convert data if necessary. The missing data will be obtained via emailing the original authors of included studies. Review Manager (RevMan5.3) will be used to perform the data synthesis if enough data were collected. Otherwise, only the qualitative analysis will be performed. Based on the heterogeneity results, fixed-effect model or random-effect model will be used to estimate the overall effect of acupuncture injection therapy for patients with nonspecific CLBP. Meta-regression and subgroup analysis will be also performed to explore the sources of heterogeneity. If there are enough records included, the publish bias will be assessed by funnel plot. All procedures will be strictly performed in accordance with the Cochrane Handbook for Systematic Reviews of Interventions. CONCLUSION: This review will offer clinical evidence of acupuncture injection therapy for the patients with nonspecific CLBP. PROSPERO RESEARCH REGISTRATION IDENTIFYING NUMBER: CRD42019119158.