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 » Results
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 Table of Contents    
SYSTEMATIC REVIEW AND META-ANALYSIS
Year : 2021  |  Volume : 53  |  Issue : 6  |  Page : 499-510
 

COVID-19–associated rhino-orbital-cerebral mucormycosis: A systematic review, meta-analysis, and meta-regression analysis


1 Department of Ophthalmology, Government Medical College and Hospital, sector 32, Chandigarh, India
2 Department of Pharmacology, PGIMER, Chandigarh, India
3 Department of Management Studies, IIT Madras, Chennai, Tamil Nadu, India
4 Department of Pharmacology, Central University of Punjab, Bathinda, Punjab, India
5 Scientist, Indian Pharmacopoeia Commission, Ghaziabad, Uttar Pradesh, India
6 Microbiology, B.P. Civil hospital, Nawgaon, Assam, India

Date of Submission28-Oct-2021
Date of Decision08-Dec-2021
Date of Acceptance14-Dec-2021
Date of Web Publication30-Dec-2021

Correspondence Address:
Prof. Bikash Medhi
Department of Pharmacology, PGIMER, Chandigarh
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/ijp.ijp_839_21

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 » Abstract 


BACKGROUND: Till now, no meta-analysis is available to address the clinical profile, risk factors, different interventions, and outcomes among COVID-19–associated rhino-orbito-cerebral mucormycosis (C-ROCM) cases.
MATERIALS AND METHODS: Eight literature databases were screened using appropriate keywords from November 1, 2019, to June 30, 2021. The objectives were to analyze the clinical and microbiological profile, risk factor/comorbidity, intervention, and outcome. “R-metafor package” was used for analysis.
RESULTS: A total of 23 studies were included. The mean age of presentation of C-ROCM was 54.6 years. The most common presentation was ptosis (72.7%), lid edema (60.6%), proptosis (60.6%), ophthalmoplegia (57.3%), loss of vision (53.7%), facial edema (34.7%), and nasal-blockage (11.8%). Evidence of intracranial spread was seen in 42.8% of cases. Rhizopus was the most common fungus (57.1%) isolated in fungal culture. Among C-ROCM patients, diabetes was the commonest comorbid condition, and the use of corticosteroids related to COVID-19 treatment was the most common risk factor (85.75%). Compared to controlled diabetics, C-ROCM was significantly higher among uncontrolled diabetics (odds ratio [OR] 0.15, 95% confidence interval [C.I.] 0.041–0.544, P = 0.0010). However, no significant association was seen between C-ROCM and COVID-19 severity (OR 0.930, 95% C.I. 0.212–4.087, P = 0.923). For treatment, amphotericin-B was the most common antifungal drug used which was followed by surgical options. However, mortality was high (prevalence 0.344, 95% C.I. 0.205–0.403) despite treatment.
CONCLUSION: Although local rhino-orbito symptoms were the first to appear, rapid intracranial extension was seen in a significant number of C-ROCM cases. Uncontrolled diabetes and excessive use of corticosteroid were the most common risk factors present among the C-ROCM cases. High index clinical suspicion is imperative (specifically among COVID-19 patients with diabetes), and routine screening may be helpful.


Keywords: COVID-19–associated mucormycosis, cerebral, COVID-19, mucormycosis, orbital, rhino, rhino-orbito-cerebral mucormycosis, SARS CoV-2


How to cite this article:
Bhattacharyya A, Sarma P, Kaur H, Kumar S, Bhattacharyya J, Prajapat M, Prakash A, Sharma S, Reddy DH, Thota P, Bansal S, Gautam BS, Medhi B. COVID-19–associated rhino-orbital-cerebral mucormycosis: A systematic review, meta-analysis, and meta-regression analysis. Indian J Pharmacol 2021;53:499-510

How to cite this URL:
Bhattacharyya A, Sarma P, Kaur H, Kumar S, Bhattacharyya J, Prajapat M, Prakash A, Sharma S, Reddy DH, Thota P, Bansal S, Gautam BS, Medhi B. COVID-19–associated rhino-orbital-cerebral mucormycosis: A systematic review, meta-analysis, and meta-regression analysis. Indian J Pharmacol [serial online] 2021 [cited 2022 Sep 28];53:499-510. Available from: https://www.ijp-online.com/text.asp?2021/53/6/499/334358

#Indicate first author FNx01Indicate Corresponding Author Both Anusuya Bhattacharyya and Phulen Sarma Contributed Equally to the Manuscript. Hence Combined First Author





 » Introduction Top


Fungal infections are being recognized as important secondary infections among patients with COVID-19.[1],[2] Pre-existing comorbidities, injudicious use of corticosteroids and antimicrobials, and lapses in infection control practices contributed to opportunistic fungal infection in COVID-19 cases.[3] Common systemic fungal infections reported among COVID-19 population are candidemia, invasive aspergillosis, and mucormycosis.[4],[5] COVID-19–associated mucormycosis (CAM) is gaining significant attention across the globe.[6],[7] The general population incidence of mucormycosis is low (0.005–1.7/million populations); however, a surge of increases in the number of cases has been reported in recent COVID-19 pandemic.[8]

In immunocompetent patients, the incidence of opportunistic infections is low in the maxillofacial region, which may be attributed to its high vascularity. However, mucormycosis is especially important in this region as they colonize in the nasal mucosa and invade the local defense mechanisms in this area and can lead to invasive infections.[9] Rhino-orbito-cerebral mucormycosis (ROCM) represents the most common form of mucormycosis involving the maxillofacial and orbital region, which may further spread intracranially in its advanced stage and is reported among COVID-19 patients.[10] Critically ill patients on oxygen therapy, mechanical ventilation, and prolonged intensive care unit stay are known risk factors of mucormycosis, especially C-ROCM patients,[10] and high rate of mortality was seen among those with intra-cranial extension.

Although ROCM is very much relevant in the context of COVID-19, and few systematic reviews have addressed this issue, till now, no meta-analysis is available to address the demographic and clinical profile, risk factors, impact of different interventions, and outcomes among C-ROCM cases. In this context, the current systematic review and meta-analysis was undertaken to address these knowledge gaps.


 » Materials and Methods Top


This meta-analysis was undertaken and reported in accordance with “Preferred Reporting Items for Systematic Review and Meta-Analysis guidelines”[11] (PRISMA) (PROSPERO registration I.D. CRD42021262943).

Objectives

Primary objectives

  1. Clinical and demographic profile of C-ROCM patients
  2. Microbiological profile of C-ROCM cases
  3. Association between presence of risk factor/comorbidity and occurrence of C-ROCM
  4. Evaluation of different intervention used in ROCM and their outcome (treatment success, treatment failure, and death).


Secondary objectives

  1. Association between C-ROCM and diabetes (prevalence of diabetes among C-ROCM; both controlled and uncontrolled diabetes mellitus [DM])
  2. Association of mortality and DM in C-ROCM
  3. Association between C-ROCM and COVID-19 severity.


Inclusion criteria

  1. Studies including diagnosed/confirmed mucormycosis patients, as defined by “Revision and Update of the Consensus Definitions of Invasive Fungal Disease From the European Organization for Research and Treatment of Cancer and the Mycoses Study Group Education and Research Consortium”[12] of all age groups associated with concurrent or post-COVID-19 infection
  2. All types of observational study (prospective, retrospective, cohort, etc.) and case series reporting C-ROCM were included in our meta-analysis.


Exclusion criteria

  1. Case reports, guidelines, consensus, editorials, and review articles were excluded from our meta-analysis.


Study population

  1. Confirmed ROCM patients[12] including all age groups concurrent or post-COVID-19 C-ROCM.


Definitions

  • COVID-19 severity: COVID-19 severity definitions were adopted according to the World Health Organization “Therapeutics and COVID-19: living Guideline”[13] and patients were categorized into critical, severe, and nonsevere COVID-19 categories.[13]
  • Confirmed ROCM: Confirmed C-ROCM cases was defined according to the guidelines set by “Revision and Update of the Consensus Definitions of Invasive Fungal Disease From the European Organization for Research and Treatment of Cancer and the Mycoses Study Group Education and Research Consortium”[12]
  • Treatment success: Defined as response to treatment, i.e., stabilization of disease and disease-free patient[14]
  • Treatment failure: Death/mortality or progression of disease (showing radiological or clinical progression).[14]


Literature search and screening of articles

Eight literature databases were searched, i.e., PubMed, EMBASE, Google Scholar, Web of Science, Scopus, MedRxiv, BioRxiv, and SSRN from November 1, 2019, to June 30, 2021. Keywords used for data search were “Mucormycosis,” rhino, orbital, cerebral, ROCM, CAM, COVID-19, SARS CoV-2 without language restriction [detailed search strategy is given in [Supplementary Table 1]]. With completion of detailed search, duplicates were removed following which two authors (AB and PS) screened the articles/studies using the title and the abstracts of the study as predefined by the inclusion and exclusion criteria, following which full text of the relevant article was further evaluated for inclusion of our meta-analysis by using predefined inclusion and exclusion criteria. Any discrepancy among authors was resolved by consulting with BM.

Data extraction

PS and AB independently extracted the data directly from full-length articles into structured tables. Collected data consisted of study country of origin, study type, risk factor or comorbidity, laboratory parameters, anatomic location of infection, diagnostic method, clinical manifestation, details of therapy used (antibiotic, steroid, antifungal use, surgery, etc.), and outcome of treatment (clinical and radiological response, laboratory parameters, hospital stay, treatment success and mortality etc.). In case of any study where our studied outcome parameters were not reported, corresponding authors were contacted for data via e-mail.

Quality assessment

The “methodological quality assessment” of the observational studies was assessed using “Newcastle–Ottawa Scale,”[15] and “risk of bias (ROB)” was assessed under three domains, i.e., selection, comparability, and outcome.[16] For assessing the quality of case series, scale mentioned by Murad et al.[17] was used (ROB domain evaluated: selection, ascertainment, causality, and reporting). Two investigators PS and AB independently evaluated the ROB of all the included studies. BM was consulted to solve the issue in case any discrepancy. Only high-quality studies were included in the meta-analysis.

Publication bias

”Publication bias” was evaluated by constructing a funnel plot and “Egger's regression test.”[18]

Statistical analysis

For single-group dichotomous data, pooled proportion/prevalence with 95% confidence interval (C.I.) was calculated. In case of dichotomous data having two groups, log odds ratio (OR) with 95% C.I. was used as a measure of association. In case of continuous data, for single-group analysis, pooled mean with 95% C.I. was calculated, and for two groups, mean difference with 95% C.I. was calculated. I2 and Chi2 statistics were used to assess heterogeneity.[19] In case of high heterogeneity (>50%), “random-effect model” was used for the analysis, else a “fixed-effect model” was used.[20] For the meta-analysis, “R software with Metafor Package”, R Foundation for Statistical Computing, Vienna, Austria” was used. Data conversion to different formats was done as per Wan et al., 2014.[21] Proportion was obtained as a ratio of total sample size. For prevalence, it was multiplied by 100.

Exploration of heterogeneity

For significantly high heterogeneity (>50%), etiology of high heterogeneity was investigated using “subgroup and meta-regression analysis.” Meta regression was conducted in case where the confounding variable was reported in 10 or more studies.[22]

Subgroup analysis

”Subgroup analysis” was done on the basis of study design (i.e., prospective vs. retrospective) and on the basis of studies including only severe and critical category COVID-19 population versus studies including COVID-19 population of all severity category.

Meta regression

Many factors (e.g., age, sex, comorbid condition, and therapy) may influence the mortality associated with C-ROCM.[23] In this context, “a meta-regression analysis” was done to observe the effect of these confounders on the final result, especially in the outcome of the disease (mortality).


 » Results Top


Details of included studies

After searching eight literature databases, we identified 827 articles. After removing duplicates, 615 studies were obtained, which were carried forward for further screening using title and abstract. Full-text screening was done for 67 relevant articles, out of which 23 studies fulfilling “predefined inclusion/exclusion criteria” were finally included in the systematic review and meta-analysis. The majority of included studies were from India (14 studies[6],[7],[24],[25],[26],[27],[28],[29],[30],[31],[32],[33],[34]) followed by 4 studies from Egypt,[35],[36],[37],[38] 1 from Iran,[39] 1 from Turkey,[14] 1 from Chile,[40] 1 from French[41] and 1 from the Netherlands.[42] Among all these included articles, 4 were preprint[31],[33],[34],[41] [detailed characteristics of included studies showed in [Supplementary Table 2] and [Supplementary Figure 1] shows PRISMA flow diagram].

Publication bias

The Egger's test shows no evidence of publication bias with P = 0.633. [Supplementary Figure 2].

Primary objective

Demographic profile of patients with COVID-19–associated rhino-orbito-cerebral mucormycosis

Mean age at presentation

A total of 17 studies[6],[7],[14],[25],[26],[27],[29],[31],[32],[34],[35],[37],[39],[40],[41],[42],[43] reported mean age of presentation of C-ROCM. The mean age of presentation of C-ROCM was 54.6 years (95% C.I. 44–65, I2 = 99%, random-effect model) [Figure 1]. In the pooled data, it was seen that Bayram et al.[14] and Diwakar et al.[31] reported extremes of age group (mean age 73 years and 12 years, respectively) as compared to other studies. Hence, a sensitivity analysis was conducted by excluding these two studies; however, the mean age of presentation remained similar (56.8 years [95% C.I. 54–58]) and heterogeneity reduced to 50% (I2 = 50%, fixed-effect model) [Supplementary Figure 3].
Figure 1: Mean age at presentation in C-ROCM patients

Click here to view


Sex ratio

Males were the more frequently affected gender (17 studies,[6],[7],[14],[24],[25],[26],[27],[28],[29],[31],[33],[34],[35],[37],[39],[40],[42],[43] prevalence 0.784, 95% C.I. 0.721–0.846, I2 = 28.96%, fixed-effect model).

Clinical presentation of COVID-19–associated rhino-orbito-cerebral mucormycosis population

Mean time period of presentation of C-ROCM from the time of COVID-19 diagnosis was 20 days (10 studies,[7],[14],[14],[26],[29],[34],[35],[40],[42],[43] 95% C.I. 15–24 days) [Supplementary Figure 4]. There was no significant difference in odds of occurrence of ROCM among patients with concurrent COVID-19 infection versus post-COVID-19 infection (7 studies,[6],[26],[28],[29],[30],[37],[42] OR [log scale] 0.306, 95% C.I. 0.042–2.246, P = 0.244, I2 = 79.46%, random-effect model) [Supplementary Figure 5].

Regarding ocular presentation, unilateral involvement was commonest, while bilateral ocular involvement was reported only in small number of patients (2/12, i.e., 16.7%, single study[37]). The most common ocular presentations were lid edema (9 studies,[25],[26],[29],[31],[34],[35],[37],[39],[43] prevalence 0.606, 95% C.I. 0.385–0.826), proptosis (8 studies,[14],[26],[29],[35],[37],[38],[39],[43] prevalence 0.606, 95% C.I. 0.385–0.826), ophthalmoplegia (8 studies,[14],[29],[30],[31],[35],[37],[38],[43] prevalence 0.573, 95% C.I. 0.395–0.751), loss of vision (10 studies,[6],[14],[25],[26],[27],[28],[29],[35],[38],[39] prevalence 0.537, 95% C.I. 0.282–0.793), facial edema (6 studies,[29],[34],[35],[37],[39],[43] prevalence 0.347, 95% C.I. 0.216–0.477), and ptosis (4 studies,[14],[26],[29],[39] prevalence 0.727, 95% C.I. 0.534–0.920). Pupil involvement was reported by 3 studies[14],[26],[31] (prevalence 0.581, 95% C.I. 0.362–0.801), while optic nerve involvement was reported by 2 studies[34],[35] (prevalence 0.230, 95% C.I. 0.031–0.430). Rare but vision-threatening presentations included panophthalmitis (single study,[35] n = 7, unilateral in 4/7 and bilateral in 1/7), endophthalmitis (single study,[14] 6/11, 54.5%), orbital compartment syndrome (single study,[35] 1 out of 7, 14.2%), and central retinal artery occlusion (single study,[27] 6 out of 10, 60%).

Regarding rhino/nasal presentation the most common presenting features reported were nasal blockage (2 studies,[29],[39] n = 25, overall 3 out of 25, prevalence 0.118, 95% C.I. −0.008–0.244), black nasal discharge (single study,[29] n = 5, 2 out of 5), and epistaxis (2 studies,[25],[29] n = 15, 3 out of 15).

Palatal involvement was also reported by few studies (3 studies,[26],[28],[29] n = 21, overall 13 out of 21, prevalence 0.575, 95% C. I. 0.162–0.989). “Classic black Eschar” has been reported in small number of patients (single study,[28] n = 23, 9 out of 23), and bleeding gum (single study,[25] n = 10, 1 out of 10) has also been reported as infrequent presentation [detail clinical presentation and their prevalence in C-ROCM patients is summarized in [Table 1]].
Table 1: Pooled prevalence of proportion of various clinical presentations described among COVID-19-associated rhino-orbito-cerebral mucormycosis patient population

Click here to view


Radiological involvement

Radiological investigation, especially computed tomography (CT) scan and magnetic resonane imaging (MRI), has been used as a diagnostic tool to evaluate the extent of involvement of mucormycosis infection almost all the authors. Our meta-analysis showed the most common involvement to be rhino-orbital involvement (8 studies,[7],[14],[26],[28],[31],[37],[39],[43] prevalence 0.708, 95% C.I. 0.539–0.877), followed by sinonasal involvement (4 studies,[24],[38],[39],[43] prevalence 0.549, 95% C.I. −0.013–1.11) and intracranial involvement (13 studies,[6],[7],[14],[24],[25],[26],[27],[28],[29],[32],[35],[37],[39] prevalence 0.428, 95% C.I. 0.297–0.560). Involvement of orbital apex (2 studies,[14],[34] prevalence 0.257, 95% C.I. −168–0.882) and cavernous sinus was seen in small number of patients (8 studies,[26],[29],[30],[31],[32],[37],[38],[39] prevalence 0.403, 95% C.I. 0.22–0.595).

Regarding paranasal sinus involvement, “ethmoid sinus” was the most common paranasal sinus involved which was reported to be 80% (n = 10, 8 out of 10) by Arjun et al.,[34] 90.9% (n = 11, 10 out of 11) by Bayram et al.,[14] and 100% (n = 23, 23 out of 23) by Sharma et al.[28] Pansinusitis was seen in 60% (n = 5, 3 out of 5) by Nehara et al.,[29] 77.4% (n = 31, 24 out of 31) by Ravani et al.,[30] 90.9% (n = 11, 10 out of 11) by Bayram et al.,[14] and 100% (n = 6, 6 out of 6) patients by Sen et al.[26] Pakdel et al.[39] reported that the most common sinus involvement was pansinusitis in their study population.

Regarding orbital involvement, isolated orbital involvement was seen in 13% of cases (n = 15, 2 out of 15) by Pakdel et al.[39] Extraocular muscle involvement was seen in 19.35% of cases (n = 31, 6 out of 31) and orbital cellulitis in 61.29% (n = 31, 19 out of 31) by Ravani et al.[30] Subperiosteal abscess was seen in 5.6% of patients (n = 36, 2 out of 36) by El-Kholy et al.[38]

Regarding intracranial involvement, transverse and sigmoid sinus thrombosis was seen in 2.7% (n = 36, 1 out of 36), temporal lobe abscess in 2.7% (n = 36, 1 out of 36), encephalitis in 5.4% (n = 36, 2 out of 36), and central retinal artery thrombosis in 5.4% (n = 36, 2 out of 36) by El-Kholy et al.[38] Cavernous sinus thrombosis was seen in 60% (n = 5, 3 out of 5) patients by Nehara et al.[29] and 3.22% (n = 31, 3 out of 31) by Ravani et al.[30] Internal carotid artery thrombosis was seen in 6.45% (n = 31, 2 out of 31) and 16.7% (n = 25, 4 out of 25) by Ravani et al.[30] and Fouad et al.,[37] respectively. Brain infarct was seen in 20% (n = 5, 1 out of 5) patients by Nehara et al.[29] while cerebral abscess was seen in 16.7% (n = 25, 4 out of 25) population by Fouad et al.;[37] meningitis was seen in 8% (n = 25, 2 out of 25) by Joshi et al.;[32] 5th nerve involvement in 4% (n = 25, 1 out of 25) patients; and black turbinate sign in 32% cases (n = 25, 8 out of 25) in a single study.[32]

Very small number of studies reported pulmonary involvement and disseminated form of mucormycosis in C-ROCM patients. Buil et al.[42] reported bilateral consolidations in 25% patients (n = 4, 1 out of 4) and pulmonary cavities and a reversed halo-sign in 25% patients (n = 4, 1 out of 4). Rabagliati et al.[40] reported pulmonary cavitations in 6.25% (n = 16, 1 out of 16), pulmonary nodules in 6.25% (n = 16, 1 out of 16), both cavitations and nodule in 6.25% (n = 16, 1 out of 16), pleural effusion in 12.5% (n = 16, 2 out of 16), and pneumothorax and bullas in 12.5% patients (n = 16, 2 out of 16). Patel et al.[7] reported pulmonary involvement in 8.6% (n = 187, 16 out of 187) of C-ROCM patients. Sebastian et al.[43] reported bilateral nonlobar ground-glass opacities with septal thickening in 66.6% (N = 3, 2 out of 3); fibroparenchymal scarring in 33.3% (N = 3, 2 out of 3); subpleural fibrotic bands in the left lower lobe in 33.3% (N = 3, 2 out of 3), and pericardial effusion in 33.3% patients (N = 3, 2 out of 3). Dissemination of mucormycosis has been reported in 25% by Buil et al.[42] (N = 4, 1 out of 4) and 2.1% by Patel et al.[7] (n = 187, 4 out of 187) in their study population [Table 1].

Details of COVID-19 laboratory parameter

Very few studies reported laboratory parameters in the C-ROCM cases. Gangneux et al.[41] in their study population of invasive fungal infection reported that 64.2% (n = 57) patients presented lymphopenia at the time of first presentation. Bayram et al.[14] in their study population of C-ROCM patients reported that there was increased level of D-dimer (mean 1362.4 ± 468.9 μg/L, n = 11).

Microbiological profile of COVID-19–associated rhino-orbito-cerebral mucormycosis

Rhizopus species were the most common fungal species identified among positive fungal culture (7 studies,[27],[29],[31],[36],[40],[42],[43] prevalence 0.571, 95% C.I. 0.3–0.84). Mixed fungal growth was seen in 8.1% growth (6 studies,[6],[7],[26],[38],[42],[43] prevalence 0.081, 95% C.I. −0.007–0.169). Bacterial coinfection has been reported by 2 studies[26],[40] (prevalence 0.316, 95% C.I. 0.053–0.580).

Association of risk factor/co-morbidity for the occurrence of COVID-19–associated rhino-orbito-cerebral mucormycosis

Comorbidity

Diabetes mellitus

Diabetes is one of the most important comorbidities among C-ROCM patients. Pooled proportion of diabetes among C-ROCM patients were 0.79 (19 studies,[6],[7],[14],[25],[26],[27],[28],[29],[31],[32],[33],[34],[35],[37],[39],[40],[41],[42],[43] 95% C.I. 0.686–0.895). Mean duration of diabetes at the time of diagnosis of C-ROCM was 5.9 year as reported by Sen et al.[26] (n = 6) while 4.4 years by Ravani et al.[30] (n = 31) and 12.1 years by Bayram et al.[14] n = 11). Mean HBA1C at time of presentation was varied as reported by different authors (7–15 mg/dl by Satish et al.,[24] n = 15; 6.5 mg/dl by Sharma et al.,[28] n = 25; 7.57 mg/dl by Ravani et al.,[30] n = 31; 9.7 mg/dl by Fouad et al.,[37] n = 12; and 10.2 gm/dl by Arjun et al.,[34] n = 12). Average fasting blood sugar at presentation is reported by single study[26] as 222.5 mg/dl (n = 6).

Other comorbidities

Apart from DM, other comorbidities that were prevalent among C-ROCM population were hypertension (12 studies,[14],[25],[26],[28],[29],[34],[35],[39],[40],[41],[43] prevalence 0.435, 95% C.I. 0.340–0.530), chronic kidney disease (9 studies,[7],[14],[25],[28],[30],[34],[35],[37],[43] prevalence 0.114, 95% C.I. 0.032–0.196), hematological malignancy (5 studies,[7],[14],[37],[39],[42] prevalence 0.066, 95% C.I. −0.012–0.144), coronary artery disease (3 studies,[14],[26],[43] prevalence 0.235, 95% C.I. 0.052–0.419), acute renal failure (3 studies,[14],[28],[43] prevalence 0.058, 95% C.I. −0.016–0.132) and ischemic heart disease (3 studies,[25],[35],[37] prevalence 0.125, 95% C.I. −0.01–0.26).

Other rare comorbidities reported were atrial fibrillation (single study,[14] prevalence 9%, total population [n = 11]), chronic renal failure 36% (single study,[14] n = 11), hypothyroidism 10% (single study,[25] n = 10), hyperthyroidism 9% (single study,[14] n = 11), chronic liver disease 10% (single study,[25] n = 10), chronic obstructive pulmonary disease 9% (single study,[14] n = 11), and obesity 25% (single study,[42] n = 4).

Risk factors of C-ROCM

A significant proportion of C-ROCM patients in our study population received corticosteroid therapy as part of COVID-19 treatment protocol (proportion 0.857, 14 studies,[6],[7],[14],[25],[26],[27],[28],[29],[32],[33],[34],[39],[42],[43] 95% C.I. 0.784–0.930). Mean duration of steroid use related to COVID-19 was reported by single study[14] (n = 11) as 8 days while another study[32] reported to be average 10–14 days (n = 25). Total corticosteroid dose equivalent received due to COVID-19 was reported to be 84 mg (cumulative dose of dexamethasone equivalent = 84 mg [18–1343 mg]) by single study[7] (n = 187).

Few studies reported use of mechanical ventilation as another risk factor. Pooled data showed that proportion of patients received mechanical ventilation as part of COVID-19 treatment protocol to be 0.454 (4 studies,[27],[29],[32],[43] 95% C.I. −0.048–0.956). Similarly, use of supplemental oxygen has been reported as another risk factor by Mishra et al.[25] (40% patients, n = 10) and Arjun et al.[34] (80% patients, n = 10). Median worst PaO2/FiO2 for each patient was reported to be 124 (range 57–476) in the population as reported by Rabagliati et al. in their study population (N = 16, single study[40]).

Arjun et al.[34] also reported use of broad-spectrum antibiotic as risk factor of occurrence of C-ROCM in their study population (90%, n = 10). No data were available regarding use of iron chelating in any of the included studies.

Intervention and outcomes analysis

Antifungal therapy

Amphotericin B was the mainstay of systematic as well as local antifungal therapy used in all studies. Pooled result showed that the proportion of C-ROCM patients receiving amphotericin B was 0.930 (14 studies,[6],[7],[14],[25],[26],[27],[28],[29],[30],[31],[32],[34],[35],[39],[42],[43] 95% C.I. 0.873–0.987) among which proportion of liposomal amphotericin B given was 0.902 (12 studies,[6],[7],[14],[25],[26],[27],[28],[29],[30],[31],[34],[42],[43] 95% C.I. 0.825–0.978). Apart from intravenous form, proportion of patients receiving intraorbital amphotericin B was 0.506 (4 studies,[14],[26],[28],[31] 95% C.I. −0.048–1.062), by intravitreal route in 54.5% of patients (in patients with with C-ROCM associated panophthalmitis, single study[14]). Voriconazole (2 studies,[26],[43] proportion 0.206, 95% C.I. −0.054–0.467) and posaconazole were another antifungals used in the management of ROCM cases although very few studies reported.

Other concomitant therapeutic treatments given were broad-spectrum antibiotics (100% patients single study,[43] n = 3), tocilizumab (10% cases, 1 study,[25] n = 10), vasopressor (100% patients, single study,[43] n = 3) and intravenous (I.V.) dexamethasone (2 studies[14],[27] 100% patients, n = 21).

Surgical treatment

In C-ROCM cases, 70.9% cases were required mechanical debridement of para nasal sinus (13 studies,[14],[24],[25],[26],[27],[28],[29],[30],[32],[34],[35],[37],[43] proportion 0.709, 95% C.I. 0.587–0.832) while “functional endoscopic sinus surgery” was possible in 71.2% cases (4 studies,[6],[25],[26],[27] proportion 0.712, 95% C.I. 0.416–1.007). Orbital decompression was done in 10% cases[25] (single study, n = 10) while exenteration was done in 21.2% patients (10 studies,[6],[24],[25],[26],[27],[28],[29],[31],[32],[37] proportion 0.212, 95% C.I. 0.092–0.333). Other surgeries performed were maxillectomy in 34.6% patients (3 studies,[6],[25],[27] n = 37, 95% C.I. 0.004–0.688), ethmoidectomy in 10% (single study,[25] n = 10), and craniotomy in 10% patients (single study,[25] n = 10).

Outcome analysis

Overall treatment success was seen in 60.8% patients [15 studies,[6],[7],[14],[24],[25],[27],[28],[29],[34],[35],[37],[39],[42],[43] 95% C.I. 0.470–0.745, [Figure 2]a], while continued intracranial spread was seen despite treatment in 42.8% ROCM patients (13 studies,[6],[7],[14],[24],[25],[27],[28],[29],[32],[35],[37],[39] 95% C.I. 0.297–0.560). Treatment failure/mortality was seen in 34.4% of cases [15 studies,[6],[7],[14],[24],[25],[26],[27],[28],[29],[34],[35],[37],[39],[42],[43] 95% C.I. 0.205–0.483, [Figure 3]a], with mean time to death found to be 19 days (3 studies,[29],[35],[42] n = 16, 95% C.I. 3–35 days).
Figure 2: (a) Treatment success in C-ROCM population, (b) subgroup analysis of treatment success in C-ROCM patients based on severity of COVID-19

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Figure 3: (a) Treatment failure/mortality in C-ROCM population, (b) subgroup analysis treatment failure/mortality based on severity of COVID-19

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In the pooled result, high heterogeneity was seen while analyzing “treatment success” and “treatment failure” as indicated by I2 84% and 88% respectively [Figure 2]a and [Figure 3]a. To explore the etiology of “high heterogeneity,” we conducted “subgroup analysis” on the basis of “studies including “only severe and critical COVID-19 population” versus studies including “patients of all severity category of COVID-19” and study design (prospective vs. retrospective study). The high heterogeneity was not explained by subgroup analysis on the basis of COVID-19 severity [Figure 2]b and [Figure 3]b. However, while doing subgroup analysis based on study design (prospective vs. retrospective study), very less heterogeneity was seen among prospective studies as compared to retrospective studies both in mortality and treatment success [Supplementary Figure 6] and [Supplementary Figure 7].

Association between occurrence of C-ROCM and diabetic control

Prevalence of diabetes among C-ROCM cases was found to be 23.1% in controlled versus 68.5% in uncontrolled DM patients (11 studies,[6],[14],[26],[26],[27],[28],[29],[31],[32],[37],[42],[43] OR 0.150, 95% C.I. 0.041–0.544, I2 = 64.5%, random-effect model, P = 0.001), indicating significant association between uncontrolled DM with C-ROCM patients [Figure 4].
Figure 4: Association of controlled versus uncontrolled DM for occurrence of C-ROCM

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Association between C-ROCM and COVID-19 severity

No significant difference was found with regard to occurrence of C-ROCM and COVID-19 severity (nonsevere vs. severe-to-critical COVID-19, 8 studies,[24],[25],[27],[28],[29],[38],[39],[42] OR 0.930, 95% C.I. 0.212–4.087, I2 = 74%, random-effect model, P = 0.923) [Supplementary Figure 8].

Meta regression

We evaluated the effect of different covariates on the incidence of occurrence of C-ROCM associated mortality in “univariate meta regression model.” Covariates that were reported in 10 or more studies were evaluated. The covariates evaluated were diabetes, age, male sex, liposomal amphotericin B treatment, and mechanical debridement. Among all these, only mechanical debridement has significant impact on mortality (i.e., protective effect as indicated by negative correlation, −0.004 P = 0.002) [Supplementary Table 3] and [Supplementary Figure 9]. All other covariates did not show significant correlation with ROCM-associated mortality.


 » Discussion Top


This systematic review and meta-analysis provides the global scenario of C-ROCM, its epidemiology, clinical presentation, and microbiological spectrum, which became a matter of concern due to sudden rise of mucormycosis/black fungus cases in the whole world parallel to ongoing COVID-19 pandemic.

Our meta-analysis showed that occurrence C-ROCM was more prevalent in elderly population with a mean age of presentation of 54.6 years and male gender being commonly affected. The lag period between COVID-19 diagnosis and diagnosis of ROCM was found to be average of 20 days (95% C.I. 15–24 days).

The most common presenting feature in C-ROCM was proptosis (60.6%), lid edema (60.7%), ophthalmoplegia (57.3%), loss of vision (53.7%), facial edema (34.7%), and ptosis (4 studies, 72.7%). Involvement of palate was not uncommon (35.6%). Rare occurrence of panophthalmitis (n = 4/7) and endophthalmitis[14],[35] (6/11) is also being reported as sight-threatening complication though in very few studies. Although intracranial dissemination was frequently seen owing to the contiguous spread, pulmonary involvement[7],[40],[42],[43] (21/210) or dissemination to other organs was very rare[7],[42] (5/191).

CT scan and MRI remain the most common radiological tool for diagnosis, evaluation of the extent of disease, and monitoring of response to treatment.[6],[26],[28] Rhino-orbital involvement was the most common (70.8%) presentation followed by sinonasal (54.9%) and cerebral involvement (42.8%). Cavernous sinus involvement was seen in 40.7% patients. Ethmoid sinus was the single most common paranasal sinus involved[14],[28],[30],[34] (80% by Arjun et al.[34] [n = 10], 90.9% by Bayram et al.[14] [n = 11], and 100% involvement reported by Sharma et al.[28] [n = 23]).

Rhizopus species were the most common species identified (57.1%) in total ROCM patients in our meta-analysis.

Diabetes was the most common comorbid condition in C-ROCM patients (79%). After diabetes, the most common associated comorbidities found among C-ROCM patients were hypertension (43.5%), coronary artery disease (23.5%), ischemic heart disease (12.5%), chronic kidney disease (11.4%), and hematological malignancy (6.6%).

Among other risk factors, 85.7% C-ROCM cases received corticosteroid; 12/20, i.e., 61%, received supplemental oxygen therapy;[25],[34] and 14/43, i.e., 45.4%, also received mechanical ventilation as part of COVID-19 therapy. One hypothesis says, increased use of corticosteroid as a part of COVID-19 treatment protocol served as exaggerating factor for glucose homeostasis which act as predisposing condition for the patients to opportunistic fungal infection.[6],[44],[45],[46] However, the dose of corticosteroid used as part of COVID-19 treatment protocol is not reported in maximum of the study. Use of broad-spectrum antibiotic as the risk factor is also reported by single study.[34]

In our meta-analysis, significant association (P = 0.001) was found between uncontrolled DM (68.5%) with C-ROCM patients as compared to controlled diabetes (23.1%). However, no association was seen between occurrence of COVID-19 severity and C-ROCM. Similarly, no significant difference was seen with respect to occurrence of C-ROCM among concurrent COVID-19 population versus post-COVID-19 population (OR 0.306, 95% C.I. 0.042–2.246, P = 0.244).

Alteration of iron metabolism occurs in severe COVID-19[44] and iron overload (excessive free iron seen in acidosis) are other established risk factors for opportunistic fungal infection.[47],[48] However, none of the included in our meta-analysis has reported or gave specific consideration in this aspect.

Antifungal therapy was the mainstay of treatment both as presumptive and postdiagnosis therapy, and I.V. amphotericin B (93%) has been started as definitive treatment in all of the included studies in our meta-analysis, while liposomal amphotericin B was given in 90% of patients. Amphotericin B was given by intraorbital route in case of orbital involvement by few authors (16/42, 50.5%) and intravitreal route in case of panophthalmitis (6/11, 54.5%, single study[14]); however, details of the antifungal susceptibility are not reported in maximum of the studies. The impact of liposomal amphotericin B needs further evaluation and newer antifungal option has to be taken into consideration.[49],[50],[51],[52],[53],[54],[55],[56],[57],[58],[59],[60]

Mechanical debridement was the commonly performed surgical procedure (70.9%) followed by maxillectomy (15/37, 34.6%), while exenteration was required in 21.2% patients. Less frequently performed surgeries were ethmoidectomy (1/10, i.e., 10%, single study[25]), orbital decompression (1/10, i.e., 10%, single study[25]), and craniotomy (1/10, i.e., 10%, single study[25]). Although complete removal of infected tissue by surgical debridement at the earliest in addition to antifungal therapy is recommended as definitive treatment modality in patients with C-ROCM, it is not possible in all the cases, especially in patients with advanced disease at presentation or due to fitness issue for general anesthesia in maximum of the studies, leading to higher mortality rate.

Regarding the treatment outcome, treatment success was seen in 59.8% patients while continued intracranial spread was seen in 30.9% and treatment failure/mortality was seen in as high as 37.3% of cases despite treatment. While exploring the source of high heterogeneity, in treatment success and treatment failure, no difference was seen while doing subgroup analysis based on studies including only severe and critical versus studies including all category COVID-19 population. On the other hand, study design (prospective vs. retrospective study) seems to explain high heterogeneity in our meta-analysis. On univariate analysis for possible correlation of comorbidity and risk factors, mechanical debridement shows significant impact on mortality in C-ROCM patients (i.e., protective effect as indicated by coefficient − 0.004, P = 0.002). Again requirement of only debridement indirectly indicates a less severe form of disease without intracranial extension and without requiring other more invasive therapy. The protective effect of debridement may thus be explained in a dual manner.

Strength and weakness

This current meta-analysis provides the most recent and largest overview of the C-ROCM worldwide, which is the first meta-analysis published in this regard also. However, limited data regarding laboratory parameter of C-ROCM patients are available.


 » Conclusion Top


Our meta-analysis showed that occurrence C-ROCM was more prevalent in elderly population and among males with the most common presenting feature being loss of vision, proptosis, lid edema, ophthalmoplegia, facial edema, and ptosis. Although intracranial dissemination was frequently seen, pulmonary involvement or dissemination to other organs was very rare. CT scan and MRI remain the most common radiological tool for diagnosis and for evaluation of the extent of disease. KOH positivity for Mucor species was seen in 62% patients while 59.3% culture was positive for Mucor, Rhizopus species was the most common species to be identified (44.8%). 67.7% of the population had concomitant diabetes and 85.7% cases received corticosteroid as part of COVID-19 therapy. Compared to controlled DM, the incidence of ROCM was higher among patients with uncontrolled DM. However, no association was seen between COVID-19 severity and occurrence of ROCM. Amphotericin B, more specifically liposomal amphotericin B, was a mainstay of therapy along with other surgical management options. However, despite treatment, mortality/treatment failure was seen in 37.3% of cases.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.


























 » Supplementary References Top


  1. Satish D, Joy D, Ross A, Balasubramanya. Mucormycosis coinfection associated with global COVID-19: A case series from India. Int J Otorhinolaryngol Head Neck Surg 2021;7:815-20.
  2. Mishra N, Mutya VS, Thomas A, Girish Rai G , Reddy B , Mohanan AA, et al. A case series of invasive mucormycosis in patients with COVID-19 infection. Int J Otorhinolaryngol Head Neck Surg 2021;7:867-70.
  3. Sen M, Lahane S, Lahane TP, Parekh R, Honavar SG. Mucor in a viral land: A tale of two pathogens. Indian J Ophthalmol 2021;69:244-52.
  4. Sarkar S, Gokhale T, Choudhury SS, Deb AK. COVID-19 and orbital mucormycosis. Indian J Ophthalmol 2021;69:1002-4.
  5. Moorthy A, Gaikwad R, Krishna S, Hegde R, Tripathi KK, Kale PG, et al. SARS-CoV-2, uncontrolled diabetes and corticosteroids An unholy trinity in invasive fungal infections of the maxillofacial region? A retrospective, multi-centric analysis. J Maxillofac Oral Surg 2021;20:1-8.
  6. Sharma S, Grover M, Bhargava S, Samdani S, Kataria T. Post coronavirus disease mucormycosis: A deadly addition to the pandemic spectrum. J Laryngol Otol 2021;135:442-7.
  7. Nehara HR, Puri I, Singhal V, Ih S, Bishnoi BR, Sirohi P. Rhinocerebral mucormycosis in COVID-19 patient with diabetes a deadly trio: Case series from the north-western part of India. Indian J Med Microbiol 2021;39:380-3.
  8. Ravani SA, Agrawal GA, Leuva PA, Modi PH, Amin K. Rise of the phoenix: Mucormycosis in COVID-19 times. Indian J Ophthalmol 2021;69:1563-8.
  9. Diwakar J, Samaddar A, Konar SK, Dattatraya M, Emma M, Veenakumari BN, et al. First Report of COVID-19-Associated Rhino-Orbito-Cerebral Mucormycosis in Pediatric patients with Type 1 Diabetes Mellitus. Rochester, NY: Social Science Research Network; 2021. Available from: https://papers.ssrn.com/abstract=3863080. [Last accessed on 2021 Jul 24].
  10. Gangneux JP, Dannaoui E, Fekkar A, Edouard LC, Francoise B, Nicolas P, et al. High Prevalence of Fungal Infections in Mechanically Ventilated COVID-19 Patients in the ICU: The French Multicenter MYCOVID Study. Rochester, NY: Social Science Research Network; 2021. Available from: https://papers.ssrn.com/abstract=3858565. [Last accessed on 2021 Jul 24].
  11. Buil JB, van Zanten AR, Bentvelsen RG, Rijpstra TA, Goorhuis B, van der Voort S, et al. Case series of four secondary mucormycosis infections in COVID-19 patients, the Netherlands, December 2020 to May 2021. Euro Surveill 2021;26:2100510.
  12. Fouad YA, Abdelaziz TT, Askoura A, Saleh MI, Mahmoud MS, Ashour DM, et al. Spike in rhino-orbital-cerebral mucormycosis cases presenting to a tertiary care center during the COVID-19 pandemic. Front Med (Lausanne) 2021;8:645270.
  13. El-Kholy NA, El-Fattah AM, Khafagy YW. Invasive fungal sinusitis in post COVID-19 patients: A new clinical entity. Laryngoscope 2021;131:2652-8.
  14. Ismaiel WF, Abdelazim MH, Eldsoky I, Ibrahim AA, Alsobky ME, Zafan E, et al. The impact of COVID-19 outbreak on the incidence of acute invasive fungal rhinosinusitis. Am J Otolaryngol 2021;42:103080.
  15. Ashour MM, Abdelaziz TT, Ashour DM, Askoura A, Saleh MI, Mahmoud MS. Imaging spectrum of acute invasive fungal rhino-orbital-cerebral sinusitis in COVID-19 patients: A case series and a review of literature. J Neuroradiol 2021;48:319-24.
  16. Rabagliati R, Rodríguez N, Núñez C, Huete A, Bravo S, Garcia P. COVID-19-associated mold infection in critically ill patients, Chile. Emerg Infect Dis 2021;27:1454-6.
  17. Bayram N, Ozsaygılı C, Sav H, Tekin Y, Gundogan M, Pangal E, et al. Susceptibility of severe COVID-19 patients to rhino-orbital mucormycosis fungal infection in different clinical manifestations. Jpn J Ophthalmol 2021;65:515-25.
  18. Joshi AR, Muthe MM, Patankar SH, Athawale A, Achhapalia Y. CT and MRI findings of invasive mucormycosis in the setting of COVID-19: Experience from a single center in India. AJR Am J Roentgenol 2021;217:1431-2.
  19. 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;27:2349-59.
  20. Muley P, Chitguppi R, Jambure R. Proposal for a Novel Grading System for Rhino-Maxillary Mucormycosis Based on the Analysis of 30 Cases. Rochester, NY: Social Science Research Network; 2021. Available from: https://papers.ssrn.com/abstract=3854282. [Last accessed on 2021 Jul 24].
  21. Pakdel F, Ahmadikia K, Salehi M, Tabari A, Jafari R, Mehrparvar G, et al. Mucormycosis in patients with COVID-19: A cross-sectional descriptive multicentre study from Iran. Mycoses 2021;64:1238-52.
  22. Arjun R, Felix V, Niyas VKM, Kumar MAS, Krishnan RB, Mohan V, Ansar A, Gautaam S, Lalitha S. COVID-19 associated Rhino-orbital Mucormycosis: a Single Centre Experience of Ten Cases. QJM. 2021 Jun 28:hcab176. doi: 10.1093/qjmed/hcab176. Epub ahead of print. PMID: 34181023.
  23. Sebastian SK, Kumar VB, Gupta M, Sharma Y. Covid Assossiated Invasive Fungal Sinusitis. Indian Journal of Otolaryngology and Head and Neck Surgery. 2021 Feb:1-4. doi: 10.1007/s12070-021-02471-6. PMID: 33649716; PMCID: PMC7905418.




 
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