Diabetic Erectile Dysfunction: Erectile Reserve and Treatment-Response Heterogeneity
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Baoguang Huang1, Tianning Li1, Jingshang Wang2
1Department of Traditional Chinese Medicine, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing Maternal and Child Health Care Hospital, Beijing, China.
Abstract:
Diabetic erectile dysfunction (DIED) is a clinically important complication of diabetes that affects sexual health, quality of life, and broader vascular-neural risk. Although nitric oxide (NO)-cyclic guanosine monophosphate signaling provides the physiologic basis for phosphodiesterase type 5 (PDE5) inhibitor therapy, DIED is not adequately explained by a single downstream vasodilatory defect. This mechanism-oriented narrative review uses treatment-response heterogeneity as its organizing problem and integrates clinical syntheses, human tissue or ex vivo evidence, animal and cellular studies, omics, network pharmacology, and Traditional Chinese medicine-related evidence within an explicit evidence hierarchy. We propose erectile reserve as a candidate conceptual and phenotyping framework, not as a validated clinical score, biomarker, or diagnostic category. Candidate determinant domains include baseline erectile-function severity, neurogenic reserve, vascular/NO-related reserve, structural reserve, systemic disease burden, and treatment-exposure modifiers. These domains should be treated as possible predictors or modifiers, whereas response after an optimized PDE5 inhibitor trial is an outcome endpoint. PDE5 inhibitors remain the best-established symptomatic pharmacologic option, but apparent nonresponse requires assessment of dose, timing, stimulation, adherence, adverse effects, interactions, hormonal contributors, and psychosexual context. Huoxue Tongluo-related evidence remains predominantly preclinical, mechanistic, and hypothesis-generating and should not be interpreted as evidence of established DIED-specific clinical efficacy. Future work should prospectively test whether parsimonious reserve domains add predictive value beyond routine clinical variables and improve patient-relevant treatment selection.
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