Clinico-Epidemiologic Characteristics of Patients Reported in the Mycotic Infections in COVID-19 Registry

Rohan Maini Internal Medicine, Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, New York;

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Neha Saini Internal Medicine, Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, New York;

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Kranti Bhavana ENT, All India Institute of Medical Sciences, Patna, India;

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Bhartendu Bharti ENT, All India Institute of Medical Sciences, Patna, India;

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Shweta Walia Opthamology, Maharaja Yeshwantrao Hospital, Indore, India;

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Neetu Kori Opthamology, Maharaja Yeshwantrao Hospital, Indore, India;

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Sushila Kataria Medanta Institute of Medicine and Research, Delhi, India;

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Pooja Sharma Medanta Institute of Medicine and Research, Delhi, India;

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Vikas Deswal Medanta Institute of Medicine and Research, Delhi, India;

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Kavya Atluri Department of Bioinformatics, University of California, Los Angeles, California;

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Yatin Sethi ENT, Venkateshwara Hospital, Dwarka, New Delhi, Delhi;

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Charuta Mandke Opthalmology, HinduHrudaySamrat Balasaheb Thackarey Medical College, Mumbai, India;

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Mayank Chansoria Emergency Medicine, Netaji Subhash Chandra Bose Medical College, Jabalpur, India;

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Sumit Rawat Microbiology, Bundelkhand Medical College, Sagar, India;

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Rajani Bhat Consultant Pulmonologist, Bangalore, India;

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Ameet Dravid Infectious Diseases, Noble Hospital, Pune, India;

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Chandan Baranwal ENT, Nepal Mediciti Hospital, Karyabinayak, Nepal;

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Nirmal Sarkar Pulmonology and Chest Medicine, Sarkari Kormochari Hospital, Dhaka, Bangladesh

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Sunit Jariwala Internal Medicine, Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, New York;

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Yoram Puius Internal Medicine, Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, New York;

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Shitij Arora Internal Medicine, Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, New York;

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for the MUNCO Registry
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for the MUNCO Registry

ABSTRACT.

We update results from the Mycotic Infections in COVID-19 (MUNCO) Registry, May–September 2021. Data collection from May to September 2021 yielded 728 cases from India, Nepal, Bangladesh, Thailand, and the United States. The cases consisted of mostly mucormycosis (97.6%), primarily rhinocerebral, and were analyzed to investigate clinical characteristics associated with negative outcomes. Patients were mostly diabetic (85%) and male (76%), with significant mortality (11.7%). All patients received treatment of coronavirus disease 2019 (COVID-19) as well as antifungal treatment. The crude mortality rate was 11.3% for mucormycosis and 22.7% formixed infections. This study demonstrates the utility of online databases in the collection of high-caliber data.

INTRODUCTION

The coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 has been associated with secondary fungal infections, notably mucormycosis, aspergillosis, and candidiasis.1 To identify clinical characteristics associated with poor outcomes of COVID-19–associated mycoses, we previously established the Mycotic Infections in COVID-19 (MUNCO) Registry,2 which accumulated 65 cases of Coronavirus-associated mucormycosis in India and South Asia in close to real time. We present here updated data describing 728 cases, now including mucormycosis, aspergillosis, and candidiasis.

METHODS

As previously described,2 cases were solicited through social media and contacts at participating hospitals and entered into a deidentified, secure electronic database at https://www.covidmucor.com using REDCap.3 Mycoses were based on the judgment of the clinician entering the data and included all patients with histopathologically confirmed infection. The primary outcome was in-hospital mortality. Secondary outcomes were measured at the time of COVID-19 diagnosis and included hospital admission, length of admission, intensive care unit (ICU) admission, oxygen requirement, incomplete recovery, and vision loss. Incomplete recovery was defined as continued treatment at day 42, interrupted treatment, palatal perforation, stroke, or paralysis.

RESULTS

The 728 cases were collected from May to September 2021 during predominance of the B.1.617.2 lineage (Delta variant). Cases were reported from India, Bangladesh, Thailand, and Nepal, and one came from the United States (Supplemental Figure 1).

Table 1 shows demographics and clinical characteristics of the cases, mostly CAM. Median age and body mass index were similar across all fungal isolates. Patients were predominantly male and unvaccinated, with either uncontrolled or newly diagnosed diabetes. The major fungal infection was mucormycosis (97.6%), and the sites most often involved with any fungal infection were sinuses (95.6%), eyes (58.1%), and brain (18.1%). Inflammatory marker levels were similar across all isolates.

Table 1

Demographics and clinical characteristics of patients with COVID-19–associated mycoses

Patient Characteristics Mucormycosis

(N = 711)*
Aspergillus

(N = 27)*
Candida

(N = 14)*
Mixed

(N = 22)*
Patient demographics
 Age, years (N = 728)
  Median 51 56 57 55
  2–25 10 (1.4) 0 (0) 0 (0) 0 (0)
  26–50 322 (45) 10 (37) 6 (42) 9 (40)
  51–75 371 (52) 15 (55) 5 (35) 11 (50)
  76–87 8 (1) 2 (7.4) 3 (21) 2 (9)
 Sex
  Male 545 (76) 19 (70) 9 (64) 17 (77)
  Female 165 (23) 8 (29) 5 (35) 5 (22)
 BMI, kg/m2 (N = 721)
  Average 24.0 23.8 23.9 24.4
  14–25 464 (65) 14 (51) 9 (64) 13 (59)
  25–30 183 (25) 8 (29) 5 (35) 8 (36)
  30–40 36 (5) 0 (0) 0 (0) 1 (4.5)
  > 40 2 (0.2) 0 (0) 0 (0) 0 (0)
Comorbidities (N = 676)
 Diabetes 607 (85) 27 (100) 12 (85) 20 (90)
  Controlled 158 (22) 5 (18.5) 0 (0) 3 (13)
  Uncontrolled 342 (48) 19 (70.3) 11 (78) 16 (72)
  New diagnosis 102 (14) 2 (7.4) 0 (0) 1 (9)
  DKA 20 (2.8) 1 (3.7) 0 (0) 1 (9)
 Prior long-term steroid 70 (9) 2 (7.4) 0 (0) 2 (9)
 Asthma/COPD 16 (22) 0 (0) 1 (7) 0 (0)
 IVDU 3 (0.4) 3 (11) 0 (0) 2 (9)
 HIV 3 (0.4) 0 (0) 0 (0) 0 (0)
 Transplant 8 (1) 0 (0) 0 (0) 0 (0)
 Cancer 3 (0.4) 0 (0) 0 (0) 0 (0)
 Other 171 (24) 9 (33) 10 (71) 12 (54)
Vaccination status (N = 711)
 Vaccinated 109 (15) 5 (18) 3 (21) 6 (27)
  COVISHIELD 93 (13) 4 (14.8) 2 (14) 5 (22)
  COVAXIN 13 (1.8) 0 (0) 1 (7) 1 (9)
  Single dose 83 (11) 1 (3.7) 2 (14) 4 (18)
  Double dose 25 (3) 3 (11) 1 (7) 2 (9)
 Unvaccinated 602 (84) 22 (81) 11 (78) 16 (72)
Site of involvement (N = 709)
 Sinus 667 (93.8) 10 (37) 1 (7.1)
 Ophthalmic 408 (57.4) 4 (14.8) 1 (7.1)
 Cerebral 128 (18) 0 (0) 0 (0)
 Pulmonary 17 (2.4) 1 (3.7) 3 (21.4)
 Gastrointestinal 10 (1.4) 1 (3.7) 0 (0)
 Cutaneous 8 (1.1) 0 (0) 0 (0) 0
Mean C-reactive protein (normal < 3 mg/L) 74.8 45.1 67.6 71.5
Mean ferritin (normal 12–1,300 ng/mL) 605 575.6 753 1,060

= not available; BMI = body mass index; COPD = chronic obstructive pulmonary disease; DKA = diabetic ketoacidosis.

Values are expressed as n (%) unless otherwise indicated.

Totals may add up to more than 100% because of coinfection by multiple fungi.

Totals may add up to more than 100% because of infection at multiple sites.

The average time between diagnosis of COVID-19 and fungal infection was 24.5 days. A total of 438 patients (60.8%) were hospitalized for COVID-19 or related indications for a mean of 12.8 days, and 107 patients (24.9%) were admitted to the ICU (Table 2). The Aspergillus group had the longest length of stay. Although most patients did not require oxygen, 87 (12.6%) required a high-flow nasal cannula, 68 (9.9%) required a non-rebreather, and 25 (3.6%) required a ventilator.

Table 2

Treatments and outcomes of patients with COVID-19–associated mycoses

Treatment data Mucor

(N = 711)*
Aspergillus

(N = 27)*
Candida

(N = 14)*
Mixed

(N = 22)*
COVID-19 treatment
 Favipiravir 163 (22.9) 10 (37) 6 (42.9) 11 (50)
 Remdesivir 266 (37.4) 17 (63) 12 (85.7) 15 (68.2)
 Corticosteroid 539 (75.8) 25 (92.6) 14 (100) 20 (90.9)
 Budesonide 30 (4.2) 4 (14.8) 3 (21.4) 3 (13.6)
 Doxycycline 281 (39.5) 7 (25.9) 2 (14.3) 6 (27.3)
 Azithromycin 288 (40.5) 8 (29.6) 2 (14.3) 5 (22.7)
 Ivermectin 271 (38.1) 12 (44.4) 2 (14.3) 10 (45.5)
 Tocilizumab 16 (2.3) 0 (0) 1 (7.1) 1 (4.5)
 Itolizumab 2 (0.28) 0 (0) 0 (0) 1 (4.5)
 Zinc 471 (66.2) 11 (40.7) 9 (64.3) 12 (54.5)
 Other 73 (10.3) 2 (7.4) 3 (21.4) 2 (9.1)
Steroids
 Dexamethasone 290 (40.8) 8 (29.6) 6 (42.9) 6 (27.3)
 Prednisone 37 (5.2) 3 (11.1) 1 (7.1) 4 (18.2)
 Methylprednisolone 218 (30.7) 14 (51.9) 8 (57.1) 12 (54.5)
Antifungal treatment
 Amphotericin B 642 (90.3) 20 (74.1) 8 (57.1) 17 (77.3)
 Posaconazole 426 (59.9) 13 (48.1) 9 (64.3) 13 (59.1)
 Isavuconazole 27 (3.8) 4 (14.8) 1 (7.1) 5 (22.7)
 Surgery 466 (65.5) 17 (63) 8 (57.1) 15 (68.2)
 Voriconazole 9 (1.3) 1 (3.7) 5 (35.7) 2 (9)
Amphotericin treatment
 Amphotericin B deoxycholate 62 (8.7) 7 (25.9) 4 (28.6) 10 (45.5)
 Liposomalamphotericin B 604 (85) 17 (63) 7 (50) 14 (63.6)
 Amphotericin B lipid complex 113 (15.9) 1 (3.7) 4 (28.6) 5 (22.7)
Hospital course
 Hospitalized 423 (59.5) 21 (77.8) 14 (100) 17 (77.3)
 Length of hospital admission, days 12.5 19.6 20.3 19.1
 Intensive care unit admission 98 (13.8) 9 (33.3) 9 (64.3) 7 (31.8)
Level of oxygen requirement
 High-flow nasal cannula 82 (11.5) 4 (14.8) 4 (28.6) 3 (13.6)
 Continuous positive airway pressure 6 (0.84) 1 (3.7) 0 (0) 0 (0)
 Bilevel positive airway pressure 23 (3.2) 4 (14.8) 3 (21.4) 3 (13.6)
 Ventilator 24 (3.4) 2 (7.4) 2 (14.3) 3 (13.6)
 Extracorporeal membrane oxygenation 7 (0.98) 0 (0) 0 (0) 0 (0)
 Hudson mask 103 (14.5) 2 (7.4) 1 (7.1) 2 (9.1)
 Nasal prongs 133 (18.7) 4 (14.8) 1 (7.1) 5 (22.7)
 Non-rebreather 65 (9.1) 7 (25.9) 6 (42.9) 5 (22.7)
 No oxygen required 297 (41.8) 6 (22.2) 1 (7.1) 4 (18.2)
Outcome after treatment
 Incomplete recovery 345 (48.5) 11 (40.7) 4 (28.6) 4 (18.2)
 Full recovery 264 (37.1) 11 (40.7) 8 (57.1) 13 (59.1)
 Death 83 (11.7) 3 (11.1) 2 (14.3) 5 (22.7)
 Lost to follow-up 18 (2.5) 1 (3.7) 0 (0) 0 (0)
 Vision loss 243 (34.2) 7 (25.9) 3 (21.4) 7 (31.8)

Values are expressed as n (%) unless otherwise indicated.

Totals may add up to more than 100% because of coinfection by multiple fungi.

Totals may add up to more than 100% because use of multiple treatment modalities.

All patients received both COVID-19 treatment and antifungal treatment (Table 2). For COVID-19 treatment, 556 patients (81.3%) received corticosteroids, 476 (69.6%) received zinc, 292 (42.7%) received azithromycin, 283 (41.4%) received doxycycline, and 274 (40.1%) received ivermectin. The distribution of antifungal therapy is detailed in Table 2.

Overall, the crude mortality rate was 11.3% for mucormycosis and 22.7% for mixed infections. No deaths occurred in the Aspergillus and candida groups. Full recovery was seen in 252 patients with mucormycosis (36.5%), 2 (18.2%) with Aspergillus, 1 (25%) with candida, and 13 (59.1%) with a mixed isolate. Vision loss was seen in a third of the patients but was not seen in the candida group.

DISCUSSION

This much larger study validates the utility of an online registry to obtain high-quality data about a large number of cases in close to real time. Analysis showed confirmation of many known characteristics of COVID-19–associated mycoses: mostly mucormycosis (primarily rhinocerebral), with high morbidity and mortality2,4; increased representation of patients with diabetes and male sex1,2,4; a high incidence of hypertension (17.2%), as seen in studies of Covid-19–associated pulmonary aspergillosis5; and high corticosteroid use that likely increased the risk for fungal infections.6 This lends credence to other findings that deserve further study, such as the use of zinc, which possibly predisposed these patients to fungal infections.7

This large sample, which included cases from five countries, shows that COVID-19–related mycoses are not limited to India. Although mucormycosis has dominated recently published studies, this paper also describes fungal infections such as Aspergillus and candida underlying COVID-19.

Study limitations were previously described2: self-reporting resulting in unmeasured bias and missing cases. Furthermore, there was no control group without COVID-19 for comparison.

Further studies might investigate the burden of fungal infections in various nosocomial settings and equipment. Because much of this information was collected before vaccination was widely available in the countries studied, further studies could compare secondary mycotic infections in vaccinated and unvaccinated patients.

The goal of this study was to establish a global online registry that allows providers anywhere to report COVID-associated fungal infections in real time. The large sample size will allow further analysis of clinical characteristics associated with poor outcomes.

Supplemental Materials

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ACKNOWLEDGMENTS

The American Society of Tropical Medicine and Hygiene has waived the Open Access fee for this article due to the ongoing COVID-19 pandemic.

REFERENCES

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    Baddley JW et al., 2021. Coronavirus disease 2019–associated invasive fungal infection. Open Forum Infect Dis. 8: ofab510.

  • 2.

    Arora S et al., 2021. Online registry of COVID-19–associated mucormycosis cases, India, 2021. Emerg Infect Dis 27: 29632965.

  • 3.

    Harris PA , Taylor R , Thielke R , Payne J , Gonzalez N , Conde JG , 2009. Research electronic data capture (REDCap)—a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform 42: 377381.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 4.

    Singh AK , Singh R , Joshi SR , Misra A , 2021. Mucormycosis in COVID-19: a systematic review of cases reported worldwide and in India. Diabetes Metab Syndr 15: 102146.

  • 5.

    Kuehn BM , 2020. Pulmonary fungal infections affect patients with COVID-19. JAMA 324: 2248.

  • 6.

    Nicolas FE , Murcia L , Navarro E , Navarro-Mendoza MI , Perez-Arques C , Garre V , 2020. Mucorales species and macrophages. J Fungi (Basel) 6: 94.

  • 7.

    Staats CC , Kmetzsch L , Schrank A , Vainstein MH , 2013. Fungal zinc metabolism and its connections to virulence. Front Cell Infect Microbiol 3: 65.

Author Notes

Address correspondence to Yoram Puius or Shitij Arora, Department of Internal Medicine, Montefiore Medical Center, NW651, 111 E 210TH STREET, BRONX, NY 10467. E-mails: ypuius@montefiore.org or sharora@montefiore.org

These authors contributed equally to this work.

Financial support: S. J. receives support for access to REDCap from the Einstein-Montefiore Institute for Clinical and Translational Research (grant no. UL1TR002556-06).

Disclosure: This study was approved by the Institutional Review Board of the Albert Einstein College of Medicine (approval no. 2021-13086) and ethics boards of the author-affiliated hospitals, where applicable.

Authors’ addresses: Rohan Maini, Neha Saini, and Sunit Jariwala, Yoram Puius, and Shitij Arora, Internal Medicine, Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, NY, E-mails: rohanm@proton.me, nehas@proton.me, sunitj@proton.me, ypuius@montefiore.org, and sharora@montefiore.org. Kranti Bhavana and Bhartendu Bharti, Internal Medicine, All India Institute of Medical Sciences, Patna, Bihar, India, E-mails: krantib@proton.me and bhartendub@proton.me. Shweta Walia and Neetu Kori, Internal Medicine, Maharaja Yashwantrao Hospital, Indore, India, E-mails: shwetaw@proton.me and neetuk@proton.me. Sushila Kataria, Pooja Sharma, and Vikas Deswal, Internal Medicine, Medanta Hospital and Research Center, Delhi, India, E-mails: sushilak@proton.me, poojas@proton.me, and vikasd@proton.me. Kavya Atluri, Department of Bioinformatics, University of California, Los Angeles, CA, E-mail: katluri12@gmail.com. Yatin Sethi, Department of ENT, Venkateshwara Hospital, Delhi, India, E-mail: dryatinsethi@gmail.com. Charuta Mandke, HinduHrudaySamrat Balasaheb Thackarey Medical College, Mumbai, India, E-mail: charutam@proton.me. Mayank Chansoria, Internal Medicine, Netaji Subhash Chandra Bose Medical College and Hospital, Jabalpur, India, E-mail: mayankc@proton.me. Sumit Rawat, Internal Medicine, Bundelkhand Medical College, Sagar, India, E-mail: sumitk@proton.me. Rajani Bhat, Consultant Pulmonologist, Sagar, India, E-mail: rajanib@proton.me. Ameet Dravid, Internal Medicine, Noble Hospital, Pune, India, E-mail: dravida@proton.me. Chandan Baranwal, Internal Medicine, Nepal Mediciti Hospital, Karyabinayak, Nepal, E-mail: chandanb@proton.me. Nirmal Sarkar, Internal Medicine, Sarkari Kormochari Hospital, Dhaka, Bangladesh, E-mail: nirmals@proton.me.

  • 1.

    Baddley JW et al., 2021. Coronavirus disease 2019–associated invasive fungal infection. Open Forum Infect Dis. 8: ofab510.

  • 2.

    Arora S et al., 2021. Online registry of COVID-19–associated mucormycosis cases, India, 2021. Emerg Infect Dis 27: 29632965.

  • 3.

    Harris PA , Taylor R , Thielke R , Payne J , Gonzalez N , Conde JG , 2009. Research electronic data capture (REDCap)—a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform 42: 377381.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 4.

    Singh AK , Singh R , Joshi SR , Misra A , 2021. Mucormycosis in COVID-19: a systematic review of cases reported worldwide and in India. Diabetes Metab Syndr 15: 102146.

  • 5.

    Kuehn BM , 2020. Pulmonary fungal infections affect patients with COVID-19. JAMA 324: 2248.

  • 6.

    Nicolas FE , Murcia L , Navarro E , Navarro-Mendoza MI , Perez-Arques C , Garre V , 2020. Mucorales species and macrophages. J Fungi (Basel) 6: 94.

  • 7.

    Staats CC , Kmetzsch L , Schrank A , Vainstein MH , 2013. Fungal zinc metabolism and its connections to virulence. Front Cell Infect Microbiol 3: 65.

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