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Risk Factors of COVID-19 associated mucormycosis in Iranian patients: a multicenter study
BMC Infectious Diseases volume 24, Article number: 852 (2024)
Abstract
Background
To evaluate the demographic, clinical, and prognostic characteristics of patients diagnosed with COVID-19-associated mucormycosis (CAM) in Iranian patients.
Methods
This prospective observational study was conducted in 8 tertiary referral ophthalmology centers in different provinces of Iran during the fifth wave of the COVID-19 pandemic. All patients were subjected to complete history taking and comprehensive ophthalmological examination and underwent standard accepted treatment strategy based on the disease stage.
Results
Two hundred seventy-four CAM patients (most were males (150, 54.7%)) with a mean age of 56.8 ± 12.44 years were enrolled. Patients with a history of cigarette smoking (Adjusted Odds Ratio (AOR) = 4.36), Intensive Care Unit admission (ICU) (AOR = 16.26), higher stage of CAM (AOR = 2.72), and receiving endoscopic debridement and transcutaneous retrobulbar amphotericin B (AOR = 3.30) had higher odds of mortality. History of taking systemic corticosteroids during COVID-19 was significantly associated with reduced odds of mortality (AOR = 0.16). Generalized Estimating Equations analysis showed that the visual acuity of deceased patients (LogMAR: 3.71, 95% CI: 3.04–4.38) was worse than that of patients who were discharged from the hospital (LogMAR: 2.42, 95% CI: 2.16–2.68) (P < 0.001).
Conclusions
This study highlights significant risk factors for mortality in patients with CAM, such as cigarette smoking, ICU admission, advanced CAM stages, receiving transcutaneous retrobulbar amphotericin B and worser visual acuity. Conversely, a history of systemic corticosteroid use during COVID-19 was linked to reduced mortality. These findings underscore the critical need for early identification and targeted interventions for high-risk CAM patients to improve clinical outcomes.
Introduction
Mucormycosis is an opportunistic angioinvasive fungal infection. This organ and life-threatening disease is caused by a group of molds named mucoromycetes from the Mucorales order [1]. Mucormycosis was historically considered an uncommon infection worldwide, with an estimated annual incidence ranging from 0.005 to 1.7 per million population in different regions prior to the COVID-19 pandemic [2, 3]. In Iran, mucormycosis was considered a rare opportunistic infection, with a reported incidence of 0.62 cases per 100,000 population over a six-year period from 2011 to 2016 [4]. However, during the pandemic, based on a systematic review and meta-analysis of 958 COVID-19-associated Mucormycosis (CAM) cases the nations with the highest number of CAM cases overall were India (543/958, 57%), Iran (103/958, 11%), Egypt (61/958, 6%), France (33/958, 3%), and Türkiye (30/958, 3%) [5].
Although mucormycosis was known as a rare opportunistic infection in Iran [4, 6], CAM surged throughout the fifth wave of COVID-19 at the end of 2021 summer [7, 8]. Various underlying conditions and predisposing factors related to mucormycosis development were known, including uncontrolled diabetes, use of systemic corticosteroids, broad-spectrum antibiotic therapy, immunosuppressive therapy, and immunodeficiency state [9]. In addition to these known risk factors, several important possible related factors for the development of mucormycosis in SARS-CoV-2 infected patients have been proposed; COVID-19 infection mediates mucosal immunity impairment, endothelial cell dysfunction, hypoxic media, immune response defects, hyperinflammatory cytokine release, iron metabolism imbalance and higher ferritin and free iron levels, and metabolic acidosis, which all facilitate the fungal entrance and proliferation [8, 10,11,12,13,14,15]. Furthermore, hospitalization due to COVID-19 and the accepted treatment strategies (supplemental oxygen therapy, systemic corticosteroids, and targeted immunosuppressant) would also increase this probability [1]. It seems that a possible explanation for specific geographic distribution can be related to the different environmental and ecological co-factors related to CAM [7, 8, 16, 17].
This study aimed to comprehensively evaluate the demographic, clinical, and prognostic characteristics of patients diagnosed with CAM.
Methods
Study setting and ethical approval
A multicenter prospective observational study was conducted from September 1 to December 31, 2021, corresponding with the fifth wave of the COVID-19 pandemic. Patients were evaluated and followed during their hospitalization until either discharge or death.
This collaborative study (CAM-IR) recruited patients from eight tertiary referral ophthalmology centers across Iran (Fig. 1). The study was conducted under the provisions of the Helsinki Declaration. The study protocol was approved by the Institute Ethics Committee of Isfahan University of Medical Sciences (IR.MUI.MED.REC.1400.572) (11–10-2021), and it was registered at ClinicalTrials.gov (identifier, NCT05097664) (23–10-2021). Written informed consent was obtained from all participants or legal guardians to participate in the study. All data recruited from the patients were anonymized.
Participants and case definitions
Consecutive patients were recruited, including men and women without any age limit who were diagnosed with proven CAM, according to diagnostic nasal endoscopy findings, radiologic manifestations, and demonstration of fungi in the tissue or sterile body fluids of the patient by either direct microscopic visualization of broad ribbon-like aseptate hyphae or isolation of Mucorales in the clinical setting of concurrent or recent COVID-19 infection as 12 weeks after SARS-CoV-2 infection. The rhino-orbital-cerebral mucormycosis (ROCM) term refers to the whole range of the disease, from the limited sino-nasal invasion to the involvement of the rhino, orbits, and cerebrum [11]. Concurrent or recent COVID-19 infection could be diagnosed via any one of the following: reverse transcription polymerase chain reaction (RT-PCR) test on naso-oropharyngeal swabs, rapid antigen test, or computed tomography (CT) chest scores in the absence of a positive RT-PCR test in a clinically relevant symptomatic case.
Patients with mucormycosis without association to COVID-19, those with proven non-mucor fungal infections, non-ROCM patients, patients with acute or severely ill conditions that prevent them from ophthalmic examination, participants with incompatible clinical assessment or doubtful diagnosis, and patients who refused to participate in the study were excluded.
Study protocol and data gathering
The data was collected using a structured checklist, which was designed in seven sections: 1- Demographic data, 2- Past medical/social history, 3- COVID-19 disease characteristics, 4- CAM disease characteristics, 5- Details of comprehensive ophthalmic examination findings and ocular features of CA-ROCM, 6- MRI and CT imaging findings, 7- Follow-up details and outcome. Enrolled patients underwent ophthalmological examination, including visual acuity, slit-lamp bio-microscopy of anterior and posterior segments, and intraocular pressure assessment (IOP). To evaluate paranasal sinuses (PNS), a computerized tomography (CT) scan was performed. Magnetic resonance imaging (MRI) with contrast was performed for cases based on their clinical indication and stages to evaluate the disease extension to the orbit and brain.
Patients were staged as 1– involvement of nasal mucosa; 2– involvement of paranasal sinuses; 3–involvement of the orbit; 4– involvement of the central nervous system (CNS) [18].
Intravenous liposomal amphotericin B 5 mg/kg body weight was given to all the patients with proven CAM and was stopped when the disease regressed. Also, sino-nasal debridement/functional endoscopic sinus surgery (FESS) was conducted for them. Orbital exenteration was recommended per individual cases with advanced orbital involvement. Transcutaneous retrobulbar amphotericin B (TRAMB) with a concentration of 3.5 mg/ml was administered to the candidate patients at the physician's discretion.
Statistical analysis
Frequency distribution tables (number and percentage) were used to report categorical variables, and mean ± SD (standard deviation) and median with range were used to report quantitative ones. The normality of the data distribution was checked using the Shapiro–Wilk test (results not shown). T-tests (or Mann–Whitney U test) were used to compare numerical variables between discharged and expired patients as the main outcome in this study. The Chi-Square test evaluated the independence of each categorical explanatory variable and outcome. To illustrate the relationship between any factors of interest with the death of patients, adjusted odds ratio (AOR) were calculated and reported as point and interval estimations with a 95% confidence interval through multiple logistic regression. To select the variables, first, for each explanatory variable, simple logistic regression models were fitted on data to determine the P value for the marginal relationship of each with the outcome. Then, all variables with a liberal P value (< 0.2) were entered into the multiple logistic regression model [19]. The interpretation was based on the model extracted by the backward method using the likelihood ratio test. We also used Firth method as a penalized maximum likelihood estimator applying Stata software (Stata/MP 17.0 for windows, StataCorp LLC) using the firthlogit command to reduce the bias in the parameter estimates, especially for rare events. The Generalized Estimating Equations (GEE) model was used to compare the eyes in two groups considering the dependence of one person's eyes (number and percentage). The two groups were “expired patients” and “who were discharged from hospitals” and the response variable was “Death”. A P value less than 0.05 was considered significant.
The primary outcome measure was mortality, focusing on factors influencing death before discharge. Secondary outcomes included a range of clinical, demographic, and treatment-related factors, such as demographics, past medical history, COVID-19 characteristics, CAM clinical presentations, imaging findings, and specific treatment methods.
Results
Demographic data and medical profile
Of 302 suspected cases of mucormycosis from eight referral ophthalmology centers, 274 patients with proven CAM presented in ROCM were enrolled in the study (Fig. 1). The average follow-up time for patients during hospitalization was 23.3 ± 13.8 days.
The mean age of the patients was 56.83 ± 12.44 years, and the male gender was more prevalent (54.7%). The geographic distribution and sex ratio of the included cases from each center are shown in Fig. 2.
The patient's demographics and past medical, surgical, and habitual history are summarized in Table 1. Diabetes mellitus was the most common ailment among the patients (82.8%), followed by cardiovascular disease (44.5%). Of 227 diabetic patients, 158 (69.6%) were known cases, and 6.2% presented concomitant diabetic ketoacidosis (DKA) at the time when CAM was diagnosed (Table 1).
COVID-19 characteristics
COVID-19 characteristics of the patients are summarized in Table 2. A positive SARS-CoV-2 RT-PCR test was present in 217 patients (79.2%). Most included patients were not vaccinated against SARS-CoV-2 (70.8%), and only 9.1% were vaccinated with two doses. The mean interval between COVID-19 infection and the diagnosis of CAM was 25.2 ± 30.22 days. The hospital admission rate due to COVID-19 disease was 79.6% (218 patients), of which 10.6% had been admitted to the ICU. Supplemental oxygen was administered for 68.2% of the cases, and 19 (6.9%) patients underwent mechanical ventilation. Of the patients, 94.5% had mild or moderate lung involvement due to COVID-19 infection, and 73.7% had been treated with systemic corticosteroids.
Clinical characteristics, imaging findings, and the used treatment method
Facial pain (47.4%), facial swelling (38.3%), and nasal discharge (32.5%) were the three most common primary complaints of patients with a proven diagnosis in the setting of COVID-19 (Table 3). Ptosis (58%), periorbital swelling (46%), and nasal congestion (40.5%) were the most prevalent clinical signs and symptoms (Fig. 3). An altered state of consciousness was seen in 24 (8.8%) cases (Fig. 3). Among 225 evaluated cases, the most affected paranasal sinus determined by CT scan findings was the ethmoid sinus (75.2%), followed by the maxillary sinus (70.8%) (Table 3). Cavernous sinus involvement was seen in 19 patients (15%) who underwent MRI. Stage 3 of the CA-ROCM disease was more common (52.5%). All patients were treated with intravenous liposomal amphotericin B and sino-nasal debridement/FESS. Moreover, transcutaneous retrobulbar amphotericin B (TRAMB) was performed in 94 (34.3%) cases, and 28 patients (10.2%) underwent orbital exenteration.
Ocular and periocular clinical presentations
Although most of the patients had ocular involvement (92.3%), only 17 (6.7%) of them had binocular involvement (Table 4). The mean LogMAR best corrected visual acuity (BCVA) of the affected eyes was 2.77 ± 2.02. Extraocular movement restriction and the frozen eye were developed in 72.8% of eyes. From 254 affected eyes that were evaluated for relative afferent pupillary defect (RAPD), the defect was present in 157 (61.8%) eyes (Table 4). The most common ocular finding on slit-lamp biomicroscopy was chemosis (36.7%). Fundoscopy examination showed that 63 (23.3%) and 10 (3.7%) of the affected eyes had atrophic discs and optic disc swelling, respectively. CA-ROCM-associated microvascular event (central retinal artery occlusion (CRAO), Central retinal vein occlusion (CRVO), and Branch Retinal Vein Occlusion (BRVO)) was present in 45 eyes (Table 4).
Mortality analysis
The reports from different centers showed that 30 patients (10.9%) had expired before hospital discharge. Our results revealed significant differences in Diabetes Mellitus (DM) onset (P = 0.003), SARS-CoV-2 RT-PCR test result (P = 0.001), care setting due to COVID-19 infection (P = 0.006), lung involvement percentage (P = 0.004), systemic corticosteroid use in the treatment strategy of COVID-19 disease (P = 0.002), stage of CAM (P < 0.001), the used treatment method for CA-ROCM patients (P = 0.003), and ocular involvement (P = 0.002) among patients who discharged from hospital and who expired (Table 5).
Unadjusted effects of risk factors on mortality in patients with CAM using simple logistic regression model and penalized maximum likelihood estimator are shown in Table 6. The penalized maximum likelihood estimator analysis revealed a significant association between patients with history of DM (P = 0.01) new onset DM (P = 0.003), cigarette smoking (P = 0.02), positive SARS-CoV-2 RT-PCR test (P = 0.002), ICU admission (P = 0.006), taking systemic corticosteroids (P = 0.003), stage of the CAM (P < 0.001), orbital exenteration (P = 0.005) and TRAMB treatment (P = 0.004), and bilateral ocular involvement (P = 0.003) with the mortality during hospitalization (Table 6).
The results of the adjusted effects of risk factors on mortality in patients with CAM using a multiple logistic regression model and penalized maximum likelihood estimator are summarized in Table 7. Patients with a history of cigarette smoking (AOR = 4.36, 95% CI: 1.37–13.92), who were admitted to ICU due to COVID-19 infection (AOR = 16.26, 95% CI: 2.13–123.76) compared to the outpatient setting, higher stage of CAM (AOR = 2.72, 95% CI: 1.17–6.31), who underwent endoscopic debridement and TRAMB injection (AOR = 3.30, 95% CI: 1.10–9.90) compared to the patients who just underwent endoscopic debridement, had upper odds for death before discharge from hospital. History of taking systemic corticosteroids during COVID-19 was significantly associated with reduced odds of mortality (AOR = 0.16, 95% CI: 0.06–0.42) (Table 7). Also, GEE analysis showed that the visual acuity of deceased patients (LogMAR: 3.71, 95% CI: 3.04–4.38) was worse than that of patients who were discharged from the hospital (LogMAR: 2.42, 95% CI: 2.16–2.68) (P < 0.001).
Discussion
This study revealed a mortality rate of about 11% in patients diagnosed with CAM. Factors contributing to increased odds of death included a history of cigarette smoking, ICU admission, higher CAM stage, specific treatment methods, and ocular involvement.
Although different studies elucidated various mortality rates among CAM patients (14%—37%) [10, 20,21,22], the pooled prevalence of all-cause mortality was reported as 24% [23]. However, the mortality rate during hospitalization of the cases in our study was 10.9%. According to the literature, it could be said that the survival rate of patients with mucormycosis associated with Covid-19 is higher than that of patients with other concomitant diseases (oncohematological and uncontrolled diabetes mellitus) [24]. A study on 49 patients that followed them up for six months reported that 81.8% of the non-survivors, were older than 60 years old, 90.9% had intracranial involvement, and all had HBA1C > 8.0% [21]. In a similar pattern to our result, a retrospective case–control study on 73 CAM cases, which have been followed up for 30 days at minimum, showed no significant differences in age, gender, vaccination status, DM presence, remdesivir, and tocilizumab use among survivors and non-survivors [25]. Patients with malignancies, hematological disorders, or poorly controlled diabetes may have a more compromised immune status, predisposing them to poorer outcomes with invasive fungal infections like mucormycosis.
In contrast, COVID-19 can lead to immune dysregulation and increase susceptibility to opportunistic infections like mucormycosis. However, the underlying immune deficit may be less severe or variable compared to conditions like advanced malignancies or long-standing uncontrolled diabetes. In opposition to some studies [25, 26], our study elucidated considerable differences in corticosteroid usage and treatment methods among patients discharged from hospitals and patients who expired. Although the univariate analysis in a systematic review and meta-analysis on 851 non-COVID-19 associated mucormycosis cases elucidated DM and corticosteroid use as substantial mortality-associated factors, those lost significance in multivariate analysis [27]. While glucocorticosteroids are a known risk factor for invasive mycoses, their role in the treatment of severe COVID-19 has been pivotal in managing the hyperinflammatory response associated with the disease. In our study, we observed that the history of systemic corticosteroid use during COVID-19 was significantly associated with reduced odds of mortality. However, it is important to note that we did not have data on the effect of steroids on survival as all patients had started steroid treatment before the study period. This finding contrasts with the established risk of corticosteroids contributing to the development of mucormycosis, suggesting that while steroids may mitigate the severe effects of COVID-19, their dosing and duration need careful consideration to avoid predisposing patients to invasive fungal infections like mucormycosis. Further research is necessary to delineate the balance between their therapeutic benefits and potential risks in this context.
COSMIC study [10] elucidated that mortality and disease progression were considerably higher in stage 3c or worse when compared to stage 3b or better. Likewise, the results of our study demonstrated that patients with higher ROCM stages had a significantly higher mortality ratio. A review study on CAM cases from 18 countries reported higher mortality rates in case of CNS involvement among ROCM patients [22]. A multicenter study on 287 CAM and non-COVID-19-associated mucormycosis patients showed that higher age, cerebral involvement, and ICU admission were associated with higher mortality odds ratios at six weeks [28]. Our results confirmed that expired patients had lower visual acuity at the time of CAM diagnosis than those discharged from hospitals. The multiple logistic regression suggested that higher stage of CAM, treatments in the setting of ocular involvement, bilateral ocular involvement, and history of cigarette smoking and ICU admission due to COVID-19 could be considered as possible mortality-associated factors. Our findings regarding the potential relationship between cigarette smoking, severity of COVID-19 illness, and mortality from mucormycosis aligns with existing evidence demonstrated that smoking is known to impair lung function and increase susceptibility to respiratory infections like COVID-19 [29]. Smokers have been reported to have higher rates of severe COVID-19 illness and mortality compared to non-smokers [30]. Therefore, it is plausible that in this study, cigarette smoking may have predisposed patients to more severe COVID-19 illness, requiring ICU admission, and consequently increased the risk of mortality from the subsequent mucormycosis infection.
Secondary outcomes findings revealed that diabetes mellitus emerged as the predominant underlying condition, reflecting the high prevalence of this comorbidity in the study population. The exploration of COVID-19 characteristics brought to light a substantial positive rate for SARS-CoV-2 RT-PCR, emphasizing the association between mucormycosis and recent COVID-19 infection. Noteworthy was the observation that most patients had not received vaccination against SARS-CoV-2. ROCM clinical presentations showcased facial pain, swelling, and nasal discharge as common complaints, while ocular signs such as ptosis and periorbital swelling were highly prevalent. Imaging findings demonstrated ethmoid sinus involvement as the most common, and cavernous sinus involvement was observed in a relatively low percentage of cases. The majority of patients were classified as Stage 3 ROCM. Ocular involvement was prevalent in 92.3% of patients, with only 6.7% experiencing binocular issues. The 72.8% exhibited extraocular movement restriction, and frozen eyes were observed. Relative afferent pupillary defect (RAPD) was present in 61.8% of evaluated eyes. Chemosis was the most common ocular finding in slit-lamp biomicroscopy. Fundoscopy revealed atrophic discs in 23.3% and optic disc swelling in 3.7% of affected eyes. Microvascular events (CRAO, CRVO, BRVO) occurred in a minority of cases.
On average, CAM patients in our study were in the sixth decade of life, similar to other studies [10]. However, male predominance in our study was less (54.7%) than in other studies (71 to 73%) [10, 22]. The latest meta-analysis on a total of 3718 CAM patients [23] revealed DM as the most frequent underlying disease among these patients (89%) and reported that the pooled prevalence of systemic corticosteroid use in the treatment setting of COVID-19 disease was 79%, which all are consistent with our results (82.8% and 73.7%, respectively). According to the literature on non-COVID-19-associated [24] and CAM, the mean age of the patients and the existence of DM and corticosteroid use are quite similar in both groups. Lately, a case–control study confirmed the role of DM and corticosteroid use in CAM infection [31]. The inflammatory state and reduced immune response during hyperglycemic status that is intensified via SARS-CoV-2, the increased expression of GRP-78 (glucose-regulated protein 78) on epithelial and endothelial cells in response to increased glucose concentration and ketone bodies, and the increased free iron level that is intensified by ketoacidosis in COVID-19 patients altogether lead to a suitable environment for angioinvasion, hematogenous spread, and proliferation of mucormycosis [1, 9, 22, 32, 33]. Also, utilizing systemic corticosteroids in the treatment strategy of COVID-19 infection results in hyperglycemic media and the cytokine storm through the inflammatory state, providing a suitable condition for the fungi [9]. Impairment of immune function against mucormycosis caused by corticosteroids could increase the infection risk [22].
[21, 34]. Although the mean duration from COVID-19 infection to the CAM diagnosis (about 25 days) among the included patients is comparable with the data (25.6 days) from a recent systematic review [35], some other studies reported lower intervals [10, 36]. Most patients had mild or moderate lung involvement due to COVID-19 infection; this may state that CAM occurs more frequently in patients with less COVID-19 severity, which is suggested by another study [22].
In concurrence with our study, the most common presenting symptoms reported by a cross-sectional study on 270 CA-ROCM patients and a prospective study on 49 CA-ROCM patients were facial/periorbital pain and swelling [21, 37]. A systematic review and meta-analysis on 2,312 proven CAM patients reported headache (54%), periorbital swelling/pain (53%), facial swelling/pain (43%), ophthalmoplegia (42%), proptosis (41%), and nasal discharge/congestion (36%), decreased or loss of vision (31%), ptosis (28%), dental pain or loosened teeth (25%), palatal discoloration or ulcers (22%) as common symptoms [38], which are almost consistent with our study.
Consistent with other studies, the most commonly involved paranasal sinuses among CAM patients were ethmoid and maxillary sinuses [39, 40]. Mucormycosis usually starts from the maxillary sinus, extends to the ethmoid or sphenoid, and can invade the orbit through ethmoid foramina or splitting lamina papyracea [9].
Orbital involvement among CAM patients in our study (92.3%) was higher compared to a meta-analysis conducted on 3718 patients (61%) [23]. Also, in a study on 2826 probable/ possible/ proven ROCM Indian patients, orbital involvement among the patients was reported at 72% [10]. Consistent with other studies [34, 37], ptosis, periorbital edema, periocular pain/tenderness, ophthalmoplegia, and proptosis are common ocular and periocular signs and symptoms among CAM patients. Of 35 involved eyes in a cross-sectional study, retinal artery occlusion and disc edema were observed in 23% and 11%, respectively [34]. In another study on 49 CAM patients [21], the observed keratopathy, CRAO, and CRVO rates were reported at 24.49%, 4.08%, and 2.04%, respectively.
In this study, the number of patients who expired was 30 (11%), while the number of patients who were discharged was 244 (89%). Unbalanced data in a relatively small sample size reduces the statistical power of the tests. Therefore, it is necessary to interpret the results with caution due to this limitation.
Conclusion
This study sheds light on the intricate clinical landscape of CAM, emphasizing the significant mortality risk in affected individuals. By identifying key factors associated with increased odds of death, our findings contribute valuable insights for clinicians managing CAM cases. The comprehensive characterization of demographic features, clinical presentations, and treatment outcomes enhances our understanding of this complex pathology in the context of the COVID-19 pandemic. These insights may inform future clinical strategies and public health measures to improve outcomes for individuals grappling with CAM.
Availability of data and materials
The data sets generated for this study are available at reasonable request to the corresponding authors.
Abbreviations
- COVID-19:
-
Coronavirus Disease 2019
- CAM:
-
COVID-19-associated Mucormycosis
- CAM-IR:
-
COVID-19-associated Mucormycosis in Iranian Patients
- RT-PCR:
-
Reverse Transcription Polymerase Chain Reaction
- CT:
-
Computed Tomography
- IOP:
-
Intraocular Pressure
- PNS:
-
Paranasal Sinuses
- MRI:
-
Magnetic Resonance Imaging
- ROCM:
-
Rhino-orbital-cerebral Mucormycosis
- CA-ROCM:
-
COVID-19 -associated Rhino-orbital-cerebral Mucormycosis
- FESS:
-
Sino-nasal Debridement/functional Endoscopic Sinus Surgery
- TRAMB:
-
Transcutaneous Retrobulbar Amphotericin B
- RAPD:
-
Relative Afferent Pupillary Defect
- BCVA:
-
Best Corrected Visual Acuity
- CRAO:
-
Central Retinal Artery Occlusion
- CRVO:
-
Central Retinal Vein Occlusion
- BRVO:
-
Branch Retinal Vein Occlusion
- GEE:
-
Generalized Estimating Equations
- OR:
-
Odd Ratio
- DM:
-
Diabetes Mellitus
- GRP-78:
-
Glucose-regulated Protein 78
- ICU:
-
Intensive Care Unit
References
García-Carnero LC, Mora-Montes HM. Mucormycosis and COVID-19-Associated Mucormycosis: Insights of a Deadly but Neglected Mycosis. J Fungi (Basel). 2022;8(5).
Jeong W, Keighley C, Wolfe R, Lee WL, Slavin MA, Kong DCM, et al. The epidemiology and clinical manifestations of mucormycosis: a systematic review and meta-analysis of case reports. Clin Microbiol Infect. 2019;25(1):26–34.
Prakash H, Chakrabarti A. Global Epidemiology of Mucormycosis. J Fungi (Basel). 2019;5(1).
Vaezi A, Moazeni M, Rahimi MT, de Hoog S, Badali H. Mucormycosis in Iran: a systematic review. Mycoses. 2016;59(7):402–15.
Özbek L, Topçu U, Manay M, Esen BH, Bektas SN, Aydın S, et al. COVID-19-associated mucormycosis: a systematic review and meta-analysis of 958 cases. Clinical Microbiology and Infection. 2023.
Dolatabadi S, Ahmadi B, Rezaei-Matehkolaei A, Zarrinfar H, Skiada A, Mirhendi H, et al. Mucormycosis in Iran: A six-year retrospective experience. Journal de Mycologie Médicale. 2018;28(2):269–73.
Chamola V, Mohammadi R, Nair H, Goyal A, Patel A, Hassija V, et al. COVID-19-associated mucormycosis: A review of an emergent epidemic fungal infection in the era of COVID-19 pandemic. Journal of Research in Medical Sciences. 2022;27(1):57.
Pourazizi M, Hakamifard A, Peyman A, Mohammadi R, Dehghani S, Tavousi N, et al. COVID-19 associated mucormycosis surge: A review on multi-pathway mechanisms. Parasite Immunol. 2024;46(1): e13016.
Mahalaxmi I, Jayaramayya K, Venkatesan D, Subramaniam MD, Renu K, Vijayakumar P, et al. Mucormycosis: An opportunistic pathogen during COVID-19. Environ Res. 2021;201: 111643.
Sen M, Honavar SG, Bansal R, Sengupta S, Rao R, Kim U, et al. Epidemiology, clinical profile, management, and outcome of COVID-19-associated rhino-orbital-cerebral mucormycosis in 2826 patients in India - Collaborative OPAI-IJO Study on Mucormycosis in COVID-19 (COSMIC), Report 1. Indian J Ophthalmol. 2021;69(7):1670–92.
Singh AK, Singh R, Joshi SR, Misra A. Mucormycosis in COVID-19: A systematic review of cases reported worldwide and in India. Diabetes Metab Syndr. 2021;15(4): 102146.
Narayanan S, Chua JV, Baddley JW. Coronavirus Disease 2019-Associated Mucormycosis: Risk Factors and Mechanisms of Disease. Clin Infect Dis. 2022;74(7):1279–83.
Houshmand H, Abounoori M, Ghaemi R, Bayat S, Houshmand G. Ten-year-old boy with atypical COVID-19 symptom presentation: a case report. Clinical Case Reports. 2021;9(1):304–8.
Zahedi M, Yousefi M, Abounoori M, Malekan M, Tajik F, Heydari K, et al. The interrelationship between liver function test and the coronavirus disease 2019: a systematic review and meta-analysis. Iranian Journal of Medical Sciences. 2021;46(4):237.
Vastani ZF, Ahmadi A, Abounoori M, Ardeshiri MR, Masoumi E, Ahmadi I, et al. Interleukin‐29 profiles in COVID‐19 patients: Survival is associated with IL‐29 levels. Health Science Reports. 2022;5(2).
Pourazizi M, Mohammadi R, Abtahi-Naeini B. COVID-19 associated mucormycosis and anbarnesa: concerning about important source of spores. Iran J Public Health. 2022;51(1):223.
Pourazizi M, Eshraghi B, Azad R, Afshar K, Mohammadbeigy I. Father-Son COVID-19-associated mucormycosis: Important role of genetic susceptibility in combination with environmental factors. Clinical case reports. 2022;10(9): e6312.
Honavar SG. Code Mucor: Guidelines for the Diagnosis, Staging and Management of Rhino-Orbito-Cerebral Mucormycosis in the Setting of COVID-19. Indian J Ophthalmol. 2021;69(6):1361–5.
Vakhitova ZI, Alston-Knox CL. Non-significant p-values? Strategies to understand and better determine the importance of effects and interactions in logistic regression. PLoS ONE. 2018;13(11): e0205076.
Pal P, Singh B, Singla S, Kaur R. Mucormycosis in COVID-19 pandemic and its neurovascular spread. Eur Arch Otorhinolaryngol. 2022;279(6):2965–72.
Yadav H, Sen S, Nath T, Mazumdar S, Jain A, Verma P, et al. Analysis of COVID-19-associated rhino-orbital-cerebral mucormycosis patients in a tertiary care center in Northern India. Indian J Ophthalmol. 2022;70(6):2163–8.
Hoenigl M, Seidel D, Carvalho A, Rudramurthy SM, Arastehfar A, Gangneux JP, et al. The emergence of COVID-19 associated mucormycosis: a review of cases from 18 countries. Lancet Microbe. 2022.
Zobairy H, Salem MM, Ghajarzadeh M, Mirmosayyeb O, Mirsalehi M, Diabetes mellitus and other underlying conditions in patients with coronavirus disease,. associated rhino-orbito-cerebral mucormycosis: a systematic review and meta-analysis. J Laryngol Otol. 2019;2022:1–11.
Jeong W, Keighley C, Wolfe R, Lee WL, Slavin MA, Kong DCM, et al. The epidemiology and clinical manifestations of mucormycosis: a systematic review and meta-analysis of case reports. Clin Microbiol Infect. 2019;25(1):26–34.
Choksi T, Agrawal A, Date P, Rathod D, Gharat A, Ingole A, et al. Cumulative Mortality and Factors Associated With Outcomes of Mucormycosis After COVID-19 at a Multispecialty Tertiary Care Center in India. JAMA Ophthalmol. 2022;140(1):66–72.
Khostelidi S, Zaytsev V, Vartanyan S, Nikitin N, Evtukh G, Gilalov M, et al. Mucormycosis in patients with COVID-19 in Russia: the results of a prospective multi-center study. Jurnal Infektologii. 2022:116–27.
Jeong W, Keighley C, Wolfe R, Lee WL, Slavin MA, Chen SC, et al. Contemporary management and clinical outcomes of mucormycosis: A systematic review and meta-analysis of case reports. Int J Antimicrob Agents. 2019;53(5):589–97.
Patel A, Agarwal R, Rudramurthy SM, Shevkani M, Xess I, Sharma R, et al. Multicenter Epidemiologic Study of Coronavirus Disease-Associated Mucormycosis. India Emerg Infect Dis. 2021;27(9):2349–59.
Vardavas CI, Nikitara K. COVID-19 and smoking: A systematic review of the evidence. Tob Induc Dis. 2020;18:20.
Reddy RK, Charles WN, Sklavounos A, Dutt A, Seed PT, Khajuria A. The effect of smoking on COVID-19 severity: A systematic review and meta-analysis. J Med Virol. 2021;93(2):1045–56.
Arora U, Priyadarshi M, Katiyar V, Soneja M, Garg P, Gupta I, et al. Risk factors for Coronavirus disease-associated mucormycosis. J Infect. 2022;84(3):383–90.
Chao CM, Lai CC, Yu WL. COVID-19 associated mucormycosis - An emerging threat. J Microbiol Immunol Infect. 2022;55(2):183–90.
Rudrabhatla PK, Reghukumar A, Thomas SV. Mucormycosis in COVID-19 patients: predisposing factors, prevention and management. Acta Neurol Belg. 2022;122(2):273–80.
Arora R, Goel R, Khanam S, Kumar S, Shah S, Singh S, et al. Rhino-Orbito-Cerebral-Mucormycosis During the COVID-19 Second Wave in 2021 - A Preliminary Report from a Single Hospital. Clin Ophthalmol. 2021;15:3505–14.
SeyedAlinaghi S, Karimi A, Barzegary A, Pashaei Z, Afsahi AM, Alilou S, et al. Mucormycosis infection in patients with COVID-19: A systematic review. Health Sci Rep. 2022;5(2): e529.
Muthu V, Rudramurthy SM, Chakrabarti A, Agarwal R. Epidemiology and Pathophysiology of COVID-19-Associated Mucormycosis: India Versus the Rest of the World. Mycopathologia. 2021;186(6):739–54.
Hada M, Gupta P, Bagarhatta M, Tripathy K, Harsh A, Khilnani K, et al. Orbital magnetic resonance imaging profile and clinicoradiological correlation in COVID-19-associated rhino-orbital-cerebral mucormycosis: A single-center study of 270 patients from North India. Indian J Ophthalmol. 2022;70(2):641–8.
Watanabe A, So M, Mitaka H, Ishisaka Y, Takagi H, Inokuchi R, et al. Clinical Features and Mortality of COVID-19-Associated Mucormycosis: A Systematic Review and Meta-Analysis. Mycopathologia. 2022;187(2–3):271–89.
Eshraghi B, Hosseini NS, Mohammadi R, Abtahi SHR, Ramezani-Majd A, Azad R, Pourazizi M. From Bilateral Periorbital Necrotic Wound to Fungal Brain Abscess: A Complicated Case of COVID-19-Associated Mucormycosis. Case Rep Infect Dis. 2022;14(2022):3821492. https://doi.org/10.1155/2022/3821492.
Desai SM, Gujarathi-Saraf A, Agarwal EA. Imaging findings using a combined MRI/CT protocol to identify the “entire iceberg” in post-COVID-19 mucormycosis presenting clinically as only “the tip.” Clin Radiol. 2021;76(10):784.e27-e33.
Acknowledgements
This study was supported by Isfahan University of Medical Sciences (Grant number: 1400251). Figures for the manuscript are prepared, avoiding any copyright infringement, using ProCreate (version 4.0.8) vector-based tools based on the scientific review of the literature to depict every detail in an evidence-based way.
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B.E. contributed to the conceptualization and design of the work, supervised, gathered data, and substantially revised the manuscript; M.P. contributed to the conceptualization and design of the work, administered and supervised the project, and substantially revised the manuscript; B.K., M.Y.K., M.B.K., R.N., K.S., G.K., and M.P., contributed to the conceptualization and design of the work, gathered data, and revised the manuscript; A.F. contributed to data validation and interpretation, drafted the manuscript and substantially revised it. R.M. contributed to the interpretation of the data and revised the manuscript; N.S.H. contributed to the data visualization and revised the manuscript; M.M. and P.N. contributed to data analysis and revised the manuscript; H.G., P.G.B, Z.Z., S.K., S.J., M.F., M.V., M.M., M.J., A.M.R, F.S., V.M., A.K., A.S., S.M.J.S., M.E.R., M.A., and F.E., contributed to data gathering, and revised the manuscript. All authors approved the submitted manuscript.
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The study was conducted under the provisions of the Helsinki Declaration. The study protocol was approved by the Institute Ethics Committee of Isfahan University of Medical Sciences (IR.MUI.MED.REC.1400.572) (11/10/2021), and it was registered at ClinicalTrials.gov (identifier, NCT05097664). Written informed consent was obtained from all participants or legal guardians to participate in the study. All data recruited from the patients were anonymized.
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Eshraghi, B., Khademi, B., Mirmohammadkhani, M. et al. Risk Factors of COVID-19 associated mucormycosis in Iranian patients: a multicenter study. BMC Infect Dis 24, 852 (2024). https://doi.org/10.1186/s12879-024-09755-6
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DOI: https://doi.org/10.1186/s12879-024-09755-6