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Pattern-based clinical recognition of diabetes-associated mucormycosis: an evidence mapping study integrating symptom
Qiongfang Zhang1, Ze Fang1, Hailing Zeng1
1Zhongjiang People's Hospital, Zhongjiang, China.
Background:
Diabetic-associated mucormycosis is a rapidly progressive and life-threatening opportunistic infection with high mortality. Early recognition remains challenging due to heterogeneous clinical presentations and the lack of structured characterization of symptom patterns. This study aimed to systematically map clinical features and develop a pattern-based recognition framework for diabetic-associated mucormycosis.
Methods:
A comprehensive literature search was conducted in PubMed, Web of Science, and Embase from database inception to March 2026. Case reports and case series involving diabetic patients with confirmed mucormycosis were included. Case-level data were extracted and analyzed using an evidence mapping approach. Clinical presentation clusters were defined based on infection sites, and symptom distributions, imaging features, and diagnostic pathways were descriptively synthesized.
Results:
A total of 66 studies comprising 97 cases were included. Rhino-orbito-cerebral mucormycosis (ROCM) was the predominant presentation (68.0%), followed by pulmonary infection (14.4%). Symptom patterns demonstrated a distinct structure characterized by intra-cluster aggregation and inter-cluster separation. ROCM was associated with a concentrated pattern of visual and craniofacial manifestations, whereas pulmonary cases were dominated by respiratory symptoms. Importantly, diagnostic pathways exhibited a symptom-driven structure, in which clinical presentation guided sampling strategies and influenced diagnostic methods. Based on these findings, a structured framework linking presentation clusters, symptom combinations, and diagnostic pathways was established.
Conclusions:
Diabetic-associated mucormycosis appears to exhibit relatively structured clinical presentation patterns within the published literature. The proposed pattern-based recognition framework provides a descriptive and hypothesis-generating synthesis of clinical presentation patterns and diagnostic pathways in diabetic-associated mucormycosis. This framework may help inform future research and contribute to a more structured understanding of clinical recognition patterns in high-risk populations.
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