{"doi":"10.1167/iovs.66.14.45","title":"Macular Deep Capillary Plexus Ischemia as a Biomarker for Identifying Referable Diabetic Retinopathy","abstract":"Purpose: To evaluate deep capillary plexus (DCP) ischemia measured on 3 × 3-mm macular optical coherence tomography angiography (OCTA) as a biomarker for referable diabetic retinopathy (refDR). Methods: In this cross-sectional study, we analyzed 290 eyes from 193 patients with diabetes and varying severity but without macular edema. Averaged macular OCTA images were processed to calculate a range of OCTA metrics, including geometric perfusion deficits (GPDs). Each OCTA metric was evaluated for its ability to discriminate refDR using (1) an OCTA-only generalized estimating equation logistic model and (2) a model combining the metric with clinical covariates (age, sex, diabetes duration, hemoglobin A1c, and hypertension). Accuracy was quantified by the area under the curve (AUC), and model-to-model differences (ΔAUC) were evaluated using 1000-iteration cluster-bootstrap resampling. Internal validity and calibration of the best-performing OCTA-only model were assessed using subject-wise fivefold cross-validation and the Brier score. Results: Among 10 OCTA metrics, GPDs in the DCP (GPD-DCP) achieved the highest standalone discrimination (AUC = 0.913; 95% confidence interval, 0.879-0.947) and significantly improved the model with clinical covariates (AUC increase from 0.865 to 0.934; ΔAUC = +0.070; P = 0.002). At clinically relevant thresholds, GPD-DCP achieved 95% sensitivity with 63.5% specificity, as well as 95% specificity with 63.2% sensitivity. Subject-wise cross-validation confirmed robust performance (mean [SD] AUC = 0.919 [0.034]), with excellent calibration (Brier score = 0.115). Conclusions: GPD-DCP offers excellent, well-calibrated discrimination of refDR and significantly improves risk stratification when combined with standard clinical factors, supporting its use for screening and risk assessment.","journal":"Investigative Ophthalmology & Visual Science","year":2025,"id":527545,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":3,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.7713,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1375313,"name":"Ke Zhuang","orcid":null,"position":1,"is_corresponding":false},{"id":409026,"name":"Amani A. Fawzi","orcid":"0000-0002-9568-3558","position":2,"is_corresponding":false},{"id":1374723,"name":"Shinji Kakihara","orcid":"0000-0002-8433-8169","position":0,"is_corresponding":true}],"reference_count":35,"raw_metadata":null,"created_at":"2026-07-19T02:50:39.280101Z","pmid":"41251524","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}