Abstract
We aimed to compare the demography, clinical profile, histopathology, fungal culture, radiology, surgery performed, medical therapy and outcomes of patients with acute invasive fungal sinusitis seen during the first and second waves of the COVID-19 pandemic by retrospectively reviewing their case records. Of 238 patients, 43(18.1%) presented during the first wave and 195(81.9%) during the second wave. Patients seen during the first wave were older (p = 0.04) and more likely to have visual impairment (p = 0.004), frozen eye (p = 0.012), altered sensorium (p = 0.007) and stage 3 disease (p = 0.03). Those seen during the second wave were more often COVID-19 positive and had newly diagnosed diabetes mellitus (p = 0.04)and stage 1 disease (p = 0.03). Most patients had a positive culture for Rhizopus species during both waves. Histopathology showed broad aseptate hyphae in all patients but angioinvasion was seen more often during the first wave (p = 0.04). The majority of patients were treated with endoscopic+/- open debridement followed by intravenous amphotericin B and oral posaconazole. While the overall survival rate was similar (first wave 65.1%; second wave 79%; p = 0.106), mortality after discharge was greater during the first wave (11.6% vs 1.5%; p = 0.001). Mortality was higher in patients with stage 3 disease (p = 0.003). Significant differences in clinical presentation, histopathology, radiological stage of disease and post-discharge survival were noted between the two waves of the COVID-19 pandemic, the causes for which were multi-factorial.
Keywords: COVID-19, Endoscopic sinus surgery, Invasive fungal sinusitis, Mucormycosis, Outcomes
Introduction
Acute invasive fungal sinusitis (AIFS), of which mucormycosis is the most common form, is a rapidly progressive, angioinvasive, potentially fatal condition chiefly affecting diabetics and immunocompromised patients. In the pre-pandemic era, when the estimated incidence of mucormycosis in India was 140 per million, in the Western world it was 0.2 to 95 per million [1]. The recent Covid pandemic caused a sharp increase in cases in India, initially during the first wave, and later, with an even greater explosion, during the second wave [2]. This, effectively escalated the prevalence of the disease to 7000 per million in India, about 50 times that of the pre- COVID-19 era [3].
The first wave which began in March 2020 in India, peaked in mid-September with the highest single-day spike of 97,894 new cases recorded on September 16, 2020 [4]. The emergence of more transmissible and virulent double and triple mutant variants like the delta virus (B.1.617.2 lineage) resulted in the onset of the second wave [5]. The second wave showed a steep rise in COVID-19 positive and mostly younger patients along with the emergence of many newly diagnosed diabetics [6]. A sharp increase in the number of patients with AIFS was also seen [7–11].
The putative risk factors reported for the sudden escalation of AIFS during the COVID-19 pandemic included the indiscriminate use of steroids [9, 12–14], COVID-19 induced dysregulated immune response [9, 13], uncontrolled diabetes [9, 12, 13, 15], and prolonged hospital stay with need of supplemental oxygen and artificial ventilation [10, 15]. High serum glucose and ferritin levels due to uncontrolled diabetes mellitus in the setting of a hypoxic, acidic medium was the ideal milieu for the development of mucormycosis. This, along with SARS-CoV-2- induced decreased phagocytic activity facilitated a rapid increase in the cases of AIFS. A number of socioeconomic, epidemiological and medical factors served to further increase the burden of disease in the country [15].
Previous reports have focused on patients seen either during the first wave alone [12, 16–22] or during the second wave alone [6–11, 14]. Two reports from India combined patients seen during both waves of the pandemic [23, 24]. Even as we evaluated and treated these patients, we noticed several similarities but also distinct differences in the epidemiology, clinical presentation and outcomes between patients seen during the first and second wave of the pandemic. In the present study, therefore, we hypothesized that there were significant differences in the epidemiology, presentation and outcome of patients with AIFS seen during the first and second wave of the COVID-19 pandemic at our hospital.
Materials and Methods
Study Design
This was a retrospective, observational study which included all patients diagnosed with AIFS during the first and second waves of the COVID-19 pandemic in a tertiary care hospital in South India. Patients who presented during the first wave (March 2020 to March 2021) were compared against those who presented during the second wave (April 2021- August 2021). Details regarding demography, comorbidities, COVID-19 status, prior treatment history, clinical presentation, endoscopic findings, biochemical parameters, radiology, microbiology, histopathology, treatment details and outcomes at the time of discharge and at last follow up were collected from patient records.
Study Subjects and Diagnosis
Patients with AIFS showed a wide variety of presenting symptoms and signs and occasionally underwent extensive neurological or ocular evaluation before referral to an otolaryngologist. However, in the vast majority, AIFS was suspected when a patient presented with headache, facial pain and/or ocular/palatal/nasal symptoms. The diagnosis was confirmed when biopsy from any suspicious area, after detailed ENT examination, revealed invasive fungal disease on histopathology. A positive fungal smear for Mucorales species on a KOH preparation was diagnosed when broad aseptate fungal hyphae with wide angled branching was seen. Likewise, Aspergillus species were identified when slender, septate fungal hyphae with acute angled branching were seen. Fungal culture results were obtained within 1 to 3 weeks of biopsy. Mixed fungal sinusitis was diagnosed on histopathological examination by the presence of two or more types of fungal sinusitis identified in the same histological specimen as described before [25].
At presentation patients were advised contrast enhanced CT scan of the paranasal sinuses. Contrast enhanced MRI scanning was done in those with suspected orbital/intracranial/deep skull base extension. Patients also underwent laboratory testing of random blood sugar, HbA1C, D dimer, LDH and serum ferritin levels to assess for diabetes, thrombotic tendency and acute fungal infection.
Treatment
Surgical
The protocol followed by us during the COVID-19 pandemic to fast-track patients for early diagnosis has been described before [26]. Patients underwent endoscopic sinusotomy with sampling of all sinuses and debridement of all sinuses with unhealthy tissue, irrespective of whether there was clinicoradiological involvement of the sinus. This was similar to the protocol followed by us in the pre-pandemic era [22, 27]. Debridement of extraparanasal sinus disease extension into the premaxillary, retromaxillary areas, anterior orbit, alveolus and palate was also performed where indicated. Based on disease extension, alveolectomy, palatectomy or partial or total maxillectomy was performed. Orbital debridement or exenteration or excision of brain abscess were done in consultation with ophthalmology and neurosurgery colleagues. As far as possible, all primary surgery was undertaken at the same sitting. Revision surgery was performed, when indicated, for patients with residual or progressive disease.
Medical
Antifungal drugs were commenced as soon as the fungal smear and preliminary urgent histopathology reports/frozen section reports arrived. Patients were administered intravenous amphotericin B for a period of about 2 weeks with monitoring of renal function. This was followed by oral posaconazole tablets in most cases for a minimum period of 3 months with further prolongation of treatment if the patient’s condition warranted it.
Institutional Review Board Approval
Approval was obtained from the Institutional Review Board and Ethics committee of Christian Medical College, Vellore for the conduct of the study (IRB No. 14,178).
Statistical Analysis
Descriptive statistics were used to report baseline demography. Frequencies and percentages were calculated for categorical variables. Means with standard deviation were calculated for continuous variables. Categorical variables were compared between the patients seen during the first wave and the second wave and p value obtained using Chi-square test and Fisher’s exact test. All tests were two-sided at α = 0.05 level of significance. All analyses were done using Statistical Package for Social Sciences (SPSS) software Version 21.0 (Armonk, NY: IBM Corp).
Results
Invasive fungal sinusitis was diagnosed in 43 and 195 patients seen during the first and second waves respectively.
Demography (Table 1)
Table 1.
Comparison of demographical variables between first and second wave
| Demographic variable | First wave (%) n = 43 |
Second wave (%) n = 195 |
p |
|---|---|---|---|
| Age(years); Mean ± SD | 54.07 ± 10.16 | 50.25 ± 12.86 | 0.038 |
| Sex | 0.094 | ||
| Male | 36 (83.7) | 139 (71.3) | |
| Female | 7 (16.3) | 56 (28.7) | |
| Type of DM | 0.311 | ||
| Type 1 | 1 (2.3) | 1 (0.5) | |
| Type 2 | 41 (95.4) | 182 (93.3) | |
| Newly diagnosed DM | 6 (14.0) | 57 (29.2) | 0.040 |
| Hypertension | 17 (39.5) | 65 (33.3) | 0.439 |
| Chronic kidney disease | 4 (9.3) | 9 (4.6) | 0.260 |
| Immunosuppressive therapy or haematological malignancy | 2 (4.7) | 6 (3.1) | 0.604 |
| COVID-19 positive | 27 (62.8) | 161 (82.6) | 0.006 |
| COVID-19 stage | |||
| Treated at home | 1 (3.7) | 13 (8.1) | 0.809 |
| Hospitalized but no ICU care | 25 (92.6) | 138 (85.7) | |
| ICU care | 1 (3.7) | 10 (6.2) | |
|
Prior febrile illness (If COVID-19 negative) |
4 (25.0) | 16 (48.5) | 0.118 |
| Prior steroid treatment | 17 (39.5) | 130 (66.7) | 0.110 |
DM=diabetes mellitus; ICU=intensive care unit
Patients seen during the first wave were older (p = 0.04) and were more likely to be COVID-19 negative. In contrast, during the second wave there were more COVID-19 positive patients (p = 0.006) as well as a higher proportion of patients with newly diagnosed diabetes mellitus (p = 0.04).
Clinical (Table 2)
Table 2.
Clinical features of patients seen during both waves (n = 238)
| Variable | First wave (%) | Second wave (%) | p |
|---|---|---|---|
| Symptom duration (days) | |||
|
Median (IQR) (Min, Max) |
10.0 (4.0,21.0) (2,180) |
6.0 (3.0,10.0) (1,30) |
< 0.001 |
| Facial pain & swelling | 24 (55.8) | 157 (80.5) | 0.001 |
| Headache | 27 (62.8) | 104 (53.3) | 0.259 |
| Reduced sensation cheek | 21 (48.8) | 90 (46.2) | 0.750 |
| Visual disturbance | 0.004 | ||
| Reduced vision | 13 (30.2) | 24 (12.3) | |
| Total loss of vision | 11 (25.6) | 33 (16.9) | |
| Only light perception | 0 (0.0) | 10 (5.1) | |
| Periorbital swelling | 18 (41.9) | 85 (43.6) | 0.836 |
| Proptosis | 15 (34.9) | 60 (30.8) | `0.599 |
| Ptosis | 17 (39.5) | 68 (34.9) | 0.564 |
| Frozen eye | 19 (44.2) | 49 (25.1) | 0.012 |
| Nasal symptoms & signs | |||
| Nasal block/discharge | 11 (25.6) | 50 (25.6) | 1.000 |
| Epistaxis | 4 (9.3) | 22 (11.3) | |
| Hyposmia/anosmia | 0 (0.0) | 2 (1.0) | |
| Right nasal endoscopy | 1.000 | ||
| Normal nasal mucosa | 4 (9.3) | 17 (8.7) | |
| Mucopus nasal cavity | 8 (18.6) | 38 (19.5) | |
| Edematous/polypoid mucosa | 19 (44.2) | 70 (35.9) | |
| Black eschar | 3 (6.1) | 15 (7.7) | |
| Slough | 11 (25.6) | 11 (5.6) | |
| Unhealthy, necrotic mucosa | 26 (60.5) | 100 (51.3) | |
| No data | 0 (0.0) | 1 (0.5) | |
| Altered sensorium | 6 (14.0) | 7 (3.6) | 0.007 |
| Focal neurological deficit | 9 (20.9) | 24 (12.3) | 0.139 |
| Hemiparesis | 4 (9.3) | 4 (2.1) | 0.038 |
| 7th nerve palsy | 7 (16.3) | 16 (8.2) | 0.105 |
| Type of 7th nerve palsy | 0.318 | ||
| Lower motor neuron | 4 (57.1) | 13 (81.3) | |
| Upper motor neuron | 3 (42.9) | 3 (18.8) | |
| 6th nerve palsy | 2 (4.7) | 0 (0.0) | 0.032 |
| Dental | 0.906 | ||
| Loose tooth | 7 (16.3) | 38 (19.5) | |
| Oroantral fistula | 4 (9.3) | 10 (5.1) | |
| Toothache | 5 (11.6) | 23 (11.8) | |
| Palatal Involvement | 0.819 | ||
| Palatal ulcer | 8 (18.6) | 20 (10.2) | |
| Palatal perforation | 1 (2.3) | 3 (1.5) | |
| Pallor/discoloration | 2 (4.6) | 27 (13.8) | |
| Palatal bulge | 6 (13.9) | 20 (10.2) | |
| Skin | |||
| Congested | 0 (0.0) | 1 (0.5) | 0.452 |
| Black discoloration | 0 (0.0) | 1 (0.5) | |
| Ulceration | 1 (2.3) | 0 (0.0) |
The duration of symptoms was significantly shorter during the second wave (p < 0.001).
Orbital
Visual disturbances were more common during the first wave (p < 0.01) while facial pain and swelling were more common during the second wave (p = 0.001). Patients with frozen eye were also seen more frequently during the first wave (p = 0.01).
Neurological
Overall, neurological symptoms and signs were more common during the first wave than the second (p = 0.01). A significantly greater proportion of patients had altered sensorium (p < 0.01), hemiparesis (p = 0.04) and 6th nerve palsy (p = 0.03) during the first wave.
Nasal Symptoms and Signs
Only about one-third of patients during both waves complained of nasal symptoms, the commonest being nasal obstruction/ discharge (25.6%) and epistaxis (10.9%). Most patients had either unhealthy, necrotic mucosa (29%) or edematous, polypoid mucosa (16.8%) with mucopus (8%) on endoscopy. Normal nasal mucosa was seen equally during both waves.
Dental and Palatal Symptoms and Signs
Palatal discoloration (12.2%) followed by palatal ulcer (11.8%) and loose tooth (18.9%) and toothache (11.8%) were the most common manifestations of palatal and dental involvement respectively during both waves. No significant differences were seen between both waves in terms of either dental (p = 0.91) or palatal (p = 0.82) involvement.
Mycology (Table 3)
Table 3.
Comparison of mycology and histopathology results between the two waves
| Variable | First wave (%) | Second wave (%) | p |
|---|---|---|---|
| Positive fungal smear | 30 (69.8) | 159 (81.5) | 0.197 |
| Aseptate | 28/30 (93.3) | 158/159 (99.4) | 0.066 |
| Septate | 5/30 (16.7) | 31/159 (19.5) | 0.717 |
| Positive fungal culture | 21 (48.8) | 124 (63.6) | 0.073 |
| Zygomycetes | 1.000 | ||
| Rhizopus | 20/21 (95.2) | 110/124 (88.7) | |
| Mucor | 0 (0.0) | 1/124 (0.8) | |
| Other Zygomycetes and Scedosporium species | 0 (0.0) | 3/124 (2.4) | |
| Aspergillus | 1.000 | ||
| A. Flavus | 1/21 (4.8) | 12/124 (9.7) | |
| A. Fumigatus | 0 (0.0) | 3/124 (2.4) | |
| Aspergillus species | 0 (0.0) | 1/124 (0.8) | |
|
Other Aspergillus(name) A.terreus A.niger |
2/21 (9.5) 1 1 |
6/124 (4.8) 1 5 |
|
| Fungal coinfection | 3/21 (14.3) | 24/124 (19.4) | 0.766 |
| Frozen section | N = 18 | N = 59 | |
| Positive | 12 (66.7) | 48 (81.4) | 0.206 |
| Histopathology | N = 42 | N = 192 | |
| Broad aseptate hyphae | 42 (100.0) | 192 (100.0) | NA |
| Septate hyphae | 6 (14.3) | 41 (21.4) | 0.300 |
| Angioinvasion | 40 (95.2) | 159 (82.8) | 0.041 |
| Mixed fungal sinusitis | 25 (59.5) | 84 (43.8) | 0.063 |
| Bone invasion | 36 (83.7) | 157 (80.5) | 0.627 |
| Two different fungi | 6 (13.9) | 28 (14.3) | 0.945 |
| Candida | 0 (0.0) | 8 (4.1) | 0.177 |
| Mixed fungal sinusitis | 25(59.5) | 84(43.8) | 0.063 |
| AIFS + Fungus ball | 6(24) | 32 (38.1) | |
| AIFS + CGFS | 21(84) | 68 (81) | |
| AIFS + CIFS | 0 | 5(6) |
CGFS=chronic granulomatous fungal sinusitis; CIFS=chronic invasive fungal sinusitis
Fungal smear and culture were more often positive during the second wave, although the difference was not significant. Rhizopus species was cultured almost equally during both waves. Other Zygomycetes like Absidia and Zygomycete species were cultured from one patient each during the second wave alone. One patient had a positive culture for Scedosporium species during the second wave. A positive culture for Aspergillus species was infrequently seen (17.2% overall).
Histopathology (Table 3)
One patient during the first wave and 3 patients during the second wave did not have biopsy of the specimen and diagnosis was based on clinical features along with fungal smear and culture results. Broad aseptate hyphae were identified on hematoxylin-eosin stain or fungal stain in all patients who underwent biopsy during both waves. No significant differences were found on histopathology with respect to the prevalence of septate fungal hyphae (p = 0.300) during both waves.
Although bone invasion was seen equally during both the waves, angioinvasion was seen more frequently during the first wave (95.2%) than the second wave (82.8%) (p = 0.04). No significant difference was found in the prevalence of mixed fungal sinusitis during both waves (p = 0.063). A combination of AIFS and chronic granulomatous fungal sinusitis was the most common combination seen during both waves.
Laboratory Blood Test Results
No significant differences were found between mean HbA1c values, median serum ferritin levels, median D dimer levels and median LDH levels between both waves.
Radiology (Table 4)
Table 4.
Comparison of radiological findings between the first and second wave (n = 235)
| Variable | First wave (%) | Second wave (%) | p |
|---|---|---|---|
| Maxillary sinus involvement | 41 (95.3) | 188 (96.7) | 0.667 |
| Ethmoid sinus involvement | 39 (90.7) | 182 (93.3) | 0.519 |
| Sphenoid sinus involvement | 34 (79.1) | 146 (74.9) | 0.562 |
| Frontal sinus involvement | 25 (58.1) | 140 (71.8) | 0.079 |
| Bone erosion | 29 (67.4) | 97 (49.7) | 0.034 |
| Orbital fat stranding | 35 (81.4) | 135 (69.2) | 0.110 |
| Orbital apex involvement | 25 (58.1) | 71 (36.4) | 0.009 |
| Cavernous sinus involvement | 19 (44.2) | 55(29.7) | 0.053 |
| Cavernous sinus thickening/enhancement | 11 (25.6) | 49 (25.1) | |
| Cavernous sinus thrombosis | 8 (18.6) | 7 (3.6) | |
| Dural enhancement/thickening | 15 (34.9) | 53 (27.2) | 0.331 |
| Brain infarct | 8 (18.6) | 20 (10.3) | 0.131 |
| Internal carotid artery thrombosis | 7 (16.3) | 10 (5.1) | 0.011 |
| Temporal lobe abscess | 4 (9.3) | 9 (4.6) | 0.75 |
| Frontal lobe abscess | 1 (2.3) | 5 (2.5) | |
| Temporal lobe cerebritis | 1 (2.3) | 5 (2.5) | |
| Frontal lobe cerebritis | 0 (0.0) | 11 (5.6) | |
| Skull base/ PPF/ITF/NPX/PMR involvement | 39 (90.6) | 138 (70.8) | 0.007 |
| Neck space involvement | 8 (18.6) | 7 (3.6) | |
| Mastoid involvement | 3 (6.9) | 2 (1.0) | |
| Stage 1 disease | 2 (4.7) | 35 (17.9) | 0.030 |
| Stage 2 disease | 8 (18.6) | 45 (23.1) | 0.523 |
| Stage 3 disease | 33 (76.7) | 115 (59.0) | 0.030 |
PPF=pterygopalatine fossa;ITF=infratemporal fossa;NPX=nasopharynx; PMR=premaxillary region
Although sinus involvement was similar during both waves, cavernous sinus thrombosis (p = 0.05), orbital apex involvement (p = 0.009), internal carotid artery thrombosis (p = 0.01) and involvement of extracranial, extrasinus sites like premaxillary and retromaxillary spaces, deep neck spaces, skull base and nasopharynx (p = 0.007) were more commonly seen during the first wave. Bone erosion was also more commonly seen during the first wave (p = 0.03). There was a significantly higher proportion of patients with stage 3 disease during the first wave and stage 1 disease during the second wave (p = 0.03).
Surgical Management (Table 5)
Table 5.
Surgical procedures done during both waves
| Variable | First wave (%) n = 42 |
Second wave (%) n = 191 |
p |
|---|---|---|---|
| Total no. of surgeries (Mean, SD) | 2.6 (1.5) | 2.0 (1.2) | 0.044 |
| Prior surgery before presentation | 8 (19.0) | 25 (13.1) | 0.316 |
| Sinus surgery | N = 42 | N = 191 | 1.000 |
| Bilateral endoscopic sinonasal debridement | 42 (100.0) | 189 (98.9) | |
| Medial maxillectomy | 1 (2.4) | 7 (3.7) | |
| Sublabial approach | 6 (14.3) | 34 (17.8) | |
| Palate surgery | 20 (47.6) | 73 (38.2) | 0.260 |
| Unilateral inferior partial maxillectomy | 6 (14.3) | 36 (18.9) | |
| Bilateral inferior partial maxillectomy | 4 (9.5) | 6 (3.2) | |
| Unilateral total maxillectomy | 6 (14.3) | 23 (12.1) | |
| Bilateral total maxillectomy | 0 (0.0) | 0 (0.0) | |
| Palatine mucosa excision | 5 (11.9) | 11 (5.7) | |
| Palatectomy | 3 (7.1) | 7 (3.7) | |
| Alveolectomy | 1 (2.4) | 2 (1.1) | |
| Orbital surgery | 11 (26.2) | 28 (14.7) | 0.070 |
| Orbital exenteration | 8 (19.0) | 17 (8.9) | |
| Orbital debridement | 1 (2.4) | 11 (5.8) | |
| Dacryocystorhinostomy | 1 (2.4) | 0 (0.0) | |
| Intraorbital amphotericin B injection | 2 (4.8) | 0 (0.0) | |
| Other sites | 5 (11.9) | 43 (22.5) | 0.124 |
| Pterygopalatine fossa debridement | 2 (4.8) | 37 (19.5) | |
| Premaxillary area debridement | 2 (4.8) | 15 (7.9) | |
| Other osteomyelitis/abscess debridement | 1 (2.4) | 6 (3.2) | |
| Excision cutaneous fistula | 1 (2.4) | 0 (0.0) | |
| Cranial surgery | 5 (11.9) | 11 (5.8) | |
| Temporal craniotomy & abscess excision | 3 (7.1) | 1 (0.5) | 0.003 |
| Frontal craniotomy & abscess excision | 2 (4.8) | 0 (0.0) | 0.032 |
| Decompressive craniotomy | 1 (2.4) | 3 (1.6) | 0.714 |
| Frontal sinus debridement | 1 (2.4) | 7 (3.7) | 1.000 |
| Revision surgery at our hospital after primary surgery outside | 8 (19.1) | 26 (13.6) | 0.366 |
| Primary and revision surgery at our hospital | 7 (16.7) | 29 (15.2) | 0.810 |
| Type of revision surgery | |||
| Revision endoscopic sinonasal debridement | 1 (2.4) | 5 (2.6) | 1.000 |
| Temporal lobe abscess excision | 2 (4.7) | 1 (0.5) | 0.085 |
| Frontal lobe abscess excision | 1 (2.4) | 1 (0.5) | 0.329 |
| Frontal craniotomy& debridement | 1 (2.4) | 3 (1.6) | 0.714 |
| Pre-maxillary debridement | 2 (4.8) | 1 (0.5) | 0.085 |
| Orbital exenteration | 2 (4.8) | 5 (2.6) | 0.613 |
| Partial/total maxillectomy | 1 (2.4) | 17 (8.9) | 0.209 |
| Alveolar debridement | 0 (0.0) | 1 (0.5) | 0.638 |
| Zygoma debridement | 0 (0.0) | 1 (0.5) | 0.638 |
| Greater palatine artery ligation | 0 (0.0) | 1 (0.5) | 0.638 |
| Sphenopalatine artery ligation | 0 (0.0) | 1 (0.5) | 0.638 |
|
Duration from initial surgery(days) Median(IQR); (Min,Max) |
17.0 (7.0, 33.0); (5,62) | 26.5 (17.7, 50.5); (4,210) | 0.112 |
| Surgery for osteomyelitis | 4 (15.4) | 22 (18.4) | 0.702 |
One patient during the first wave and four patients during the second wave did not have surgery. These patients presented with stage 3 disease and were either too sick to undergo surgery and died within the hospital after commencing medical therapy (4 patients) or were taken home before treatment could be commenced (1 patient). The mean number of surgeries overall was 2.6 during the first wave and 2 during the second wave and this difference was statistically significant (p = 0.04). Of these, 19.1% of patients during the first wave and 13.6% of patients during the second wave had prior surgery outside our hospital before presentation.
Orbital exenteration was performed more frequently during the first wave (19%) than the second (8.9%) (p = 0.05). Both frontal (p = 0.03) and temporal craniotomy (p = 0.003) were also performed more frequently during the first than the second wave. Persistent symptoms or the onset of new symptoms resulted in the need for repeat imaging and revision surgery in 36 (15.5%) patients overall, 7 (16.7%) during the first wave and 29(15.2%) during the second wave.
Medical Therapy
Antifungals were administered to all except 2 patients (4.6%) during the first wave and 7 (3.6%) patients during the second wave. Overall, most patients received conventional amphotericin B for a period of 2 weeks followed by about 3 to 6 months of posaconazole. More patients received liposomal amphotericin B during the second wave (28% vs. 20%). A higher number of patients also received lipid complex amphotericin B during the second wave (31.9% vs. 2.5%). The total dose of amphotericin B given was slightly higher during the second wave (median dose = 1500 mg; range = 480 to 3000 mg) than the first (median dose = 722.5 mg (420 to 1962.5 mg). A significantly higher proportion of patients received posaconazole during the second wave (85.6%) than the first wave (74.4%) (p = 0.03).
Outcome (Table 6)
Table 6.
Comparison of outcome and follow up between the first and second wave
| Variable | First wave (%) | Second wave (%) | p |
|---|---|---|---|
| Outcome | N = 43 | N = 195 | |
|
Alive Dead Lost to follow-up |
28 (65.1) 11 (25.6) 4 (9.3) |
154 (79.0) 33 (16.9) 8 (4.1) |
0.106 |
| Adjusted outcome | N = 39 | N = 187 | |
|
Alive Dead |
28 (71.8) 11 (28.2) |
154 (82.3) 33 (17.7) |
0.130 |
| In hospital mortality | 6 (14.0) | 30 (15.4) | 0.813 |
| Causes of in-hospital mortality | |||
| Progressive AIFS | 6 (13.9) | 23 (11.8) | 0.796 |
| Sepsis | 5 (11.6) | 11 (5.6) | 0.177 |
| COVID-19 acute respiratory distress syndrome | 2 (4.6) | 11 (5.6) | 1.000 |
| Myocardial infarction | 0 (0.0) | 8 (4.1) | 0.357 |
| Progressive renal failure | 2 (4.6) | 1 (0.5) | 0.085 |
| Pulmonary embolism | 0 (0.0) | 2 (1.0) | 1.000 |
| Massive hemoptysis | 0 (0.0) | 1 (0.5) | 1.000 |
| Aspiration & hypoxia | 0 (0.0) | 1 (0.5) | 1.000 |
| Mortality after discharge | 5 (11.6) | 3 (1.5) | 0.001 |
| Causes of mortality after discharge | |||
| Progressive AIFS with intracranial extension | 3 (7.0) | 2 (1.0) | |
| Sepsis | 0 (0.0) | 1 (0.5) | |
| Myocardial infarction | 2 (4.6) | 0 (0.0) | |
|
Total follow up (months) Median (IQR); mean, mode, (range) |
11 (2,14); 9.43,2, (2,21) |
4 (3,4);4.40,3, (2,9) |
0.195 |
The overall survival rate was less for patients seen during the first wave (65.1%) compared to those seen during the second wave (79%) but this was not significant (p = 0.106). Four (9.3%) patients during the first wave and 8 (4.1%) during the second wave were lost to follow up. The adjusted survival rate after excluding those in whom there was no follow up was 71.8% during the first wave and 82.3% during the second wave. This was also not significant (p = 0.130).
The overall mortality rate was 25.6% during the first wave and 16.9% during the second wave. In – hospital mortality (within 2 weeks of admission) occurred in the majority who died (14% during the first wave and 15.4% during the second wave). Multi-cause mortality was seen in most patients seen during both waves. Mortality was higher in those patients who presented with stage 3 disease (p = 0.003). Mortality after discharge was significantly greater during the first wave (11.6%) than the second wave (1.5%) (p = 0.001).
Follow up
Follow up ranged from to 2 to 21 months with a mean of 9.43 months (median 11 months) during the first wave and 2 to 9 months with a mean of 4.40 months (median 4 months) during the second wave. Many patients did not continue antifungal therapy after discharge and had limited follow up because of government -imposed, nation-wide lockdown restrictions resulting in progressive disease despite temporary improvement during the time of admission.
Discussion
The results of our comparative study of cases of AIFS seen during both waves of the pandemic revealed distinct differences. We found that patients who presented during the first wave were older (p = 0.038). Similar results were noted in other series reporting the first wave [12, 21]. We also noted that new-onset diabetes mellitus was significantly more common during the second wave (29.2%) than the first (14%) (p = 0.04). While 28.6%, [8] 35.5% [7] and 63.2% [6] of patients with AIFS seen during the second wave in 3 series had new onset diabetes, few authors reported this phenomenon during the first wave [18, 19]. The rise in number of new-onset diabetics during the pandemic in India was probably because of the greater use of steroids either based on valid guidelines or random usage, often without even a proper prescription. Additionally, SARS –CoV-2 virus associated damage to the beta cells of the pancreas is yet another mechanism by which metabolic dysregulation leading to diabetes mellitus could have occurred [28].
The relatively later presentation of patients during the first wave (mean of 10 days) compared to the second wave (mean of 6 days) was significant (p < 0.001). The overall delayed presentation with more advanced disease during the first wave was due to a number of factors, not the least of which was the lack of access to medical care in many cases due to the government -imposed, nation-wide lockdown. There may have been a delay in diagnosis too because of a lack of sensitisation of general physicians as well as specialists like ophthalmologists and neurologists to the surge in cases and varied presentation of AIFS during the first wave as the disease was infrequently seen in the pre-pandemic era [1, 22, 27, 29]. Further, the common clinical presentation of facial pain and swelling, visual symptoms and headache and a relative paucity of nasal symptoms (about 1/3 of patients in both waves had nasal symptoms) led to patients being seen by specialties other than otorhinolaryngology first.
Evidence of a more aggressive form of disease during the first wave compared to the second was evident both histologically as well as clinicoradiologically in our series. While aseptate hyphae were seen in all patients whose tissues were examined histologically, angioinvasion was more evident on histopathology during the first wave than the second (p = 0.05). This is consistent with more aggressive disease due to late presentation. Clinically, a significantly greater proportion of patients had frozen eye (p = 0.01), altered sensorium (p < 0.01), hemiparesis (p = 0.04) and 6th nerve palsy (p = 0.03) during the first wave. In comparison, those authors reporting on cases seen only during the second wave reported that only 14.3% [8] and 4.8% [6] had CNS involvement clinically. Stage 3 disease was more common during the first wave (76.7%) than the second (59%; p = 0.04) in our series. Authors reporting only on cases seen during the first wave have reported 42% [22] to 66.7% [19] of cases having intracranial extension radiologically.
The successful management of mucormycosis requires a high index of clinical suspicion along with early imaging, debridement and institution of therapy [6, 26, 27, 29]. With the COVID-19 pandemic in the background, the need to perform emergency surgery with a coordinated effort from a multidisciplinary team including otorhinolaryngology, ophthalmology, infectious diseases, neurosurgery, critical care, microbiology, and pathology department was crucial. Our revised workflow practices during both waves of the pandemic greatly assisted in early diagnosis and successful management of these cases [26]. Most series report on early initiation of liposomal amphotericin B therapy [8, 12, 20–22]. In our series, most patients received conventional amphotericin B for at least 2 weeks. This shortened duration of therapy did not appear to affect outcomes, however, as a significantly greater proportion of patients who received amphotericin B were alive at last follow up (p = 0.001). Likewise, survival was higher in those who received posaconazole in our series (p < 0.001). Recently, the use of this protocol of short-duration amphotericin B followed by step down posaconazole tablets was shown to significantly reduce hospital stay and improve outcomes [30]. Many series did not report on the use of Posaconazole [8, 10, 12, 14].
Our survival rates for patients seen during the two waves showed slightly better survival among those patients seen during the second wave. This was similar to some reports of patients seen during the same period [12, 14, 18, 21, 22]. Improved survival rates during the second wave were most likely due to earlier identification of cases by medical personnel, presentation of patients at an earlier stage of disease because of greater awareness, early diagnosis and institution of antifungal therapy and early definitive surgery. Mortality after discharge was significantly greater during the first wave (11.6%) than the second wave (1.5%) (p = 0.001). Many patients did not continue antifungal therapy after discharge and had limited follow up (possibly because of pandemic restrictions of travel and access to medical care, particularly during the strict lockdown which occurred during the first wave alone) and this may have resulted in progressive disease despite improvement during the time of admission.
In conclusion, this study shows how in the presence of a viral pandemic, syndemics of AIFS can occur which can completely disable existing healthcare systems resulting in enormous mortality. Uncontrolled diabetes mellitus, whether pre-existing or of new- onset (secondary to COVID-19)can further predispose to AIFS. Application of a standard assessment and treatment protocol can greatly help towards improving outcomes.
Author Contributions
The contributions by the authors are Dr Regi Kurien: Conceptualization, Data curation, Methodology, Visualization, Writing – original draft, Writing – review & editing. Dr Lalee Varghese: Conceptualization, Data curation, Methodology, Visualization, Writing – original draft, Writing – review & editing. Dr Lisa Mary Cherian: Conceptualization, Data curation, Methodology, Visualization, Writing – review & editing. Dr Ranjeetha Racheal Inja: Data curation, Methodology, Visualization, Writing – review & editing. Dr Manu Thampi: Data curation, Methodology, Visualization, Writing – review & editing. Dr Stuti Chowdhary: Data curation, Methodology, Visualization, Writing – review & editing. Dr Rakesh.R. Bright: Data curation, Methodology, Visualization, Writing – review & editing. Dr Lisa Abraham: Data curation, Methodology, Visualization, Writing – review & editing. Dr Raga Panicker: Data curation, Methodology, Visualization, Writing – review & editing. Dr Nithya Rajendran: Data curation, Methodology, Visualization, Writing – review & editing. Dr Priya Ganesan: Data curation, Methodology, Visualization, Writing – review & editing. Dr. Shalini Sahu: Data curation, Methodology, Visualization, Investigation, Writing – review & editing. Dr Aparna: Data curation, Methodology, Visualization, Investigation, Writing – review & editing. Dr Abi Manesh: Data curation, Methodology, Visualization, Writing – review & editing. Dr. Jayanthi Peter: Data curation, Methodology, Visualization, Writing – review & editing. Dr Joy Sarojini Michael: Data curation, Methodology, Visualization, Investigation, Writing – review & editing. Dr Meera Thomas: Data curation, Methodology, Visualization, Investigation, Writing – review & editing. Ms Reka Karuppusami: Data curation, Methodology, Data analysis, Visualization, Investigation, Writing – review & editing. Dr. George M. Varghese: Data curation, Methodology, Visualization, Writing – review & editing. Dr Vedantam Rupa: Conceptualization, Data curation, Formal analysis, Methodology, Visualization, Writing – original draft, Writing – review & editing; corresponding author.
Funding
This study was not funded.
Declarations
Conflict of interest
There is no conflict of interest for any of the authors listed above.
Footnotes
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
References
- 1.Prakash H, Chakrabarti A. Global epidemiology of mucormycosis. J Fungi. 2019;5:26. doi: 10.3390/jof5010026. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Singh P (2021) Black fungus: here is a list of states with highest number of mucormycosis cases. Hindustan Times https://www.hindustantimes.com/india-news/black-fungus-states-with-highest-number-of-mucormycosis-cases-101621559394002.html, May 21 2021
- 3.Hussain S, Riad A, Singh A, et al. Global prevalence of COVID-19-Associated Mucormycosis (CAM): living systematic review and Meta-analysis. J Fungi. 2021;711:985. doi: 10.3390/jof7110985. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Press Information Bureau. Government of India. Ministry of Health and Family Welfare. India records more than 82,000 Recoveries for two days in a row (2021) 17 September, 2021: https://pib.gov.in/Pressreleaseshare.aspx?PRID=1655483
- 5.Venkatraja B, Srilakshminarayana G, Krishna Kumar B. The dominance of severe Acute Respiratory Syndrome Coronavirus 2 B.1.617 and its Sublineages and Associations with Mortality during the COVID-19 pandemic in India between 2020 and 2021. Am J Trop Med Hyg. 2021;106:142–149. doi: 10.4269/ajtmh.21-0812. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Dokania V, Gaikwad NS, Gite V, et al. Emergence of invasive fungal rhinosinusitis in recently recovered COVID-19 patients. Ann Otol Rhinol Laryngol. 2022;131:1202–1209. doi: 10.1177/00034894211060923. [DOI] [PubMed] [Google Scholar]
- 7.Arora U, Priyadarshi M, Katiyar V, et al. Risk factors for coronavirus disease-associated mucormycosis. J Infect. 2022;84:383–390. doi: 10.1016/j.jinf.2021.12.039. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Panwar P, Gupta A, Kumar A, Gupta B, Navriya SC. Mucormycosis in COVID Diabetic Patients: a horrifying Triad! Indian J Crit Care Med. 2021;25:1314–1317. doi: 10.5005/jp-journals-10071-24025. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Meher R, Wadhwa V, Kumar V, et al. COVID associated mucormycosis: a preliminary study from a dedicated COVID Hospital in Delhi. Am J Otolaryngol. 2022;43:103220. doi: 10.1016/j.amjoto.2021.103220. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Choksi T, Agrawal A, Date P, 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;140:66–72. doi: 10.1001/jamaophthalmol.2021.5201. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Singh A, Sikka K, Goel G, et al. Covid-19-associated rhino-orbito-cerebral mucormycosis (CAROM) in Delhi: demographics and risk factors in a single-centre consecutive cohort of 200 inpatients. Natl Med J India. 2022;35:132–137. doi: 10.25259/NMJI-35-3-132. [DOI] [PubMed] [Google Scholar]
- 12.Moorthy A, Gaikwad R, Krishna S, 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;20:418–425. doi: 10.1007/s12663-021-01532-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Narayanan S, Chua JV, Baddley JW. Coronavirus Disease 2019-Associated Mucormycosis: risk factors and mechanisms of Disease. Clin Infect Dis. 2022;74:1279–1283. doi: 10.1093/cid/ciab726. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Selarka L, Sharma S, Saini D, et al. Mucormycosis and COVID-19: an epidemic within a pandemic in India. Mycoses. 2021;64:1253–1260. doi: 10.1111/myc.13353. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.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;186:739–754. doi: 10.1007/s11046-021-00584-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Fouad YA, Abdelaziz TT, Askoura A, 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. doi: 10.3389/fmed.2021.645270. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.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;135:442–447. doi: 10.1017/S0022215121000992. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.El-Kholy NA, El-Fattah AMA, Khafagy YW. Invasive fungal sinusitis in Post COVID-19 patients: a New Clinical Entity. Laryngoscope. 2021;131:2652–2658. doi: 10.1002/lary.29632. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Sen M, Lahane S, Lahane TP, Parekh R, Honavar SG. Mucor in a viral land: a tale of two pathogens. Indian J Ophthalmol. 2021;69:244–252. doi: 10.4103/ijo.IJO_3774_20. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Pakdel F, Ahmadikia K, Salehi M, et al. Mucormycosis in patients with COVID-19: a cross-sectional descriptive multicentre study from Iran. Mycoses. 2021;64:1238–1252. doi: 10.1111/myc.13334. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Patel A, Agarwal R, Rudramurthy SM, et al. Multicenter epidemiologic study of Coronavirus Disease-Associated Mucormycosis, India. Emerg Infect Dis. 2021;27:2349–2359. doi: 10.3201/eid2709.210934. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Cherian LM, Varghese L, Rupa V, et al. Rhino-orbito-cerebral mucormycosis: patient characteristics in pre-COVID-19 and COVID-19 period. Rhinology. 2022;60:427–434. doi: 10.4193/Rhin22.099. [DOI] [PubMed] [Google Scholar]
- 23.Sen M, Honavar SG, Bansal R, 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;69:1670–1692. doi: 10.4103/ijo.IJO_1565_21. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Dave TV, Gopinathan Nair A, Hegde R, et al. Clinical presentations, Management and Outcomes of Rhino-Orbital-Cerebral mucormycosis (ROCM) following COVID-19: a multi-centric study. Ophthalmic Plast Reconstr Surg. 2021;37:488–495. doi: 10.1097/IOP.0000000000002030. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Rupa V, Thomas M. Different types of fungal sinusitis occurring concurrently: implications for therapy. Eur Arch Otorhinolaryngol. 2013;270:603–608. doi: 10.1007/s00405-012-2096-2. [DOI] [PubMed] [Google Scholar]
- 26.Kurien R, Varghese L, Cherian LM, et al. Revised workflow practices in the management of acute invasive fungal sinusitis during the coronavirus disease 2019 pandemic. J Laryngol Otol. 2022;136:1314–1319. doi: 10.1017/S0022215122001888. [DOI] [PubMed] [Google Scholar]
- 27.Malleshappa V, Rupa V, Varghese L, Kurien R. Avoiding repeated surgery in patients with acute invasive fungal sinusitis. Eur Arch Otorhinolaryngol. 2022;277:1667–1674. doi: 10.1007/s00405-020-05879-y. [DOI] [PubMed] [Google Scholar]
- 28.Müller JA, Groß R, Conzelmann C, et al. SARS-CoV-2 infects and replicates in cells of the human endocrine and exocrine pancreas. Nat Metab. 2021;3:149–165. doi: 10.1038/s42255-021-00347-1. [DOI] [PubMed] [Google Scholar]
- 29.Varghese L, Malleshappa V, Yadav BK, Kurien R, Rupa V. Risk factors and predictors of mortality in acute invasive fungal sinusitis - a single-institution experience. J Laryngol Otol. 2022;136:1320–1327. doi: 10.1017/S0022215122000755. [DOI] [PubMed] [Google Scholar]
- 30.Manesh A, Devasagayam E, Bhanuprasad K et al (2023) Short intravenous amphotericin B followed by oral posaconazole using a simple, stratified treatment approach for diabetes or COVID-19-associated rhino-orbito-cerebral mucormycosis: a prospective cohort study, clinical Microbiology and infection: S1198-743X(23)00295-1. 10.1016/j.cmi.2023.06.017 [DOI] [PMC free article] [PubMed]