Algorithm-based approach to the management of rhino-maxillary mucormycosis: part II of a two-part study

Rhino-maxillary mucormycosis (RMM) is an aggressive, life-threatening fungal infection associated with substantial morbidity and mortality. While early diagnosis is universally advocated, robust quantitative evidence delineating how defined diagnostic delays influence objective clinical outcomes remains scarce. This study aimed to quantify the relationship between diagnostic timing and treatment outcomes in RMM and to develop a protocol-driven multidisciplinary algorithm to standardize management.

This retrospective case series analyzed patients diagnosed and treated for RMM at the Otolaryngology and Oral and Maxillofacial Surgery clinics of Beni-Suef University between November 2019 and December 2021. Data extraction and statistical analysis were conducted from June 2022 to January 2024. Diagnostic timing was categorized as early (4-7 days), late (8-10 days), or delayed (> 10 days). Primary outcomes included disease prognosis (regression, stabilization, progression, or death) and resolution pattern (favorable or unfavorable). Associations were evaluated using chi-square tests and Cramer's V, with statistical significance set at p < 0.05.

Thirty patients were included (mean age 56.53 ± 11.52 years; 60% male). Early diagnosis occurred in 40% of cases, late in 26.67%, and delayed in 33.33%. The overall survival rate was 83.33%. At final follow-up, disease regression was observed in 60% of patients, stabilization in 16.67%, and progression in 6.67%. A statistically significant association was identified between diagnostic timing and disease regression across follow-up intervals, most pronounced at the third postoperative month (χ² = 17.47, Cramer's V = 0.56, p = 0.008). Diagnostic timing was also significantly associated with a favorable resolution pattern at the third month (χ² = 15.77, Cramer's V = 0.75, p = 0.0004). This association was not statistically significant at six months (p = 0.87).

Diagnostic timing demonstrates a significant association with clinical outcomes in RMM. Earlier diagnosis correlates with higher rates of regression and favorable resolution patterns. Adoption of a structured diagnostic and management algorithm may facilitate early triage and coordinated multidisciplinary intervention, contributing to improved outcome standardization in oral and maxillofacial practice. Prospective validation in larger cohorts is warranted.