Keywords
awareness - diabetes - epidemiology - patient education
Introduction
Mucormycosis (MCR) referred to as “black fungus” results from inhalation of fungal spores in patients with a weakened immune system.[1] The second wave of coronavirus disease 2019 (COVID-19) in India resulted in an unprecedented outbreak of MCR.
India has had the maximum disease load of MCR even in pre-COVID-19 times, although it remained largely unrecognized.[2] Rhino-orbitocerebral mucormycosis (ROCM) is the most common clinical form and diabetes mellitus (DM) is the biggest risk factor,[3] so much so that MCR has become a diabetes-defining illness.[4] It became a “notifiable disease” in May 2021.[2] India has a major global burden of uncontrolled diabetes.[5] It leads to mortality and morbidity associated with diabetes.[6] It increases the risk of COVID-19 infection and also complications. COVID-19, in turn, can induce acute-onset diabetes in some individuals with no history of diabetes.[7]
[8] India contributed to approximately 71% of the global cases of MCR in patients with COVID-19 based on published literature from December 2019, to the start of April 2021.[9] Diabetes has been identified as the most common comorbidity in COVID-19 patients in India.[10]
The patient partnership is desirable for optimal management of comorbidities, and health awareness for prevention and timely identification of potential disease complications. This became significant more so during the COVID-19 crisis wherein health infrastructure was overburdened.
Patients presenting early have MCR limited to the nose and paranasal sinuses and can be salvaged with antifungals accompanied by endoscopic surgery.[1]
[5] Owing to this, sound patient knowledge of predisposing risk factors and early symptom identification should lead to early detection and timely intervention, thereby improving patient outcomes.[5] The second wave of COVID-19 in India provided flourishing grounds for MCR.[9] Its association with COVID-19 is an entity demanding further research.
In the literature search, studies in various developing countries with a high diabetic burden reported awareness in less than half of their study participants and also highlighted the importance of patient awareness and their participation in the effective management of diabetes and prevention of its potential complications.[11]
[12] However, studies to assess awareness of MCR per se have been found lacking.[13]
Studies analyzing adverse health complications in diabetes revealed decreased incidence in patients where prevention and early detection of diabetes were practiced.[14]
However, studies evaluating the impact of awareness in MCR prevention among diabetic patients are deficient in literature.
In the present study, we aimed to provide a comprehensive assessment of MCR in the backdrop of COVID-19, to highlight the clinicoepidemiological profile, effect of health literacy on predisposing risk factors, and disease management in patients with COVID-19-associated mucormycosis (CAMCR), during the second wave of COVID-19 pandemic in India.
Materials and Methods
This cross-sectional study was conducted using a structured questionnaire in a tertiary care government hospital, during June-August 2021. Institutional ethics committee approval was obtained, IECHR-2021-50-S-R2, and the study was registered under Clinical Trial Registry of India, CTRI/2021/09/036452.
On the basis of a pilot study, 15 to 50% of patients had reasonable knowledge about various factors associated with CAMCR. Taking this value as reference, minimum required sample size with a 10% margin of error and 5% level of significance was 97 patients. To reduce the margin of error, total sample size taken was 100.
The formula used was:
N ≥ (p(1 -p))/(ME/zα)2
Where, Z
α = value of Z at a two-sided alpha error of 5%, ME = margin of error, and p = proportion of patients who had reasonable knowledge about various factors associated with the disease.
The inclusion criteria were microbiologically proven MCR, serologically confirmed cases of COVID-19, and age group of 18 to 70 years. Exclusion criteria were MCR not associated with COVID-19, other fungal infections, and patients on invasive ventilation. One-hundred study participants were randomly chosen patients, and written and informed consent obtained. They answered a questionnaire (with 38 questions) with input from his/her attendant, if and when required. All the answers were then verified through the file and other available records by an assessor who was one of the investigators of the study. The structured questionnaire was prepared by the investigators using the existing literature on the awareness and knowledge of patients about their comorbidities and their complications. This was reviewed by senior investigators of the institutional ethics committee and a statistical validation was obtained (Annexure 1). A pilot study was carried out and the questionnaire (Annexure 2) was subsequently modified according to the responses obtained by the participants, so as to optimally simplify the questions for laymen and remove any ambiguity. The questionnaire was bilingual (Hindi and English) with both verbal and written consent forms. Blood sugars were defined as “controlled” when blood sugar values were 80 to 140 mg/dL before meals and less than 200 mg/dL, 2 hours after meals.
Presentation with MCR was defined as “early,” when a patient presented to a clinician on noticing the symptoms of nasal cavity involvement.[5]
Awareness of symptoms of MCR was considered complete when being aware of red flag symptoms and considered incomplete if aware only of the advanced symptoms.[5] The assessor's response obtained following verification of health records, where ever available and applicable, was taken as the final response. In case of unavailability of records to verify a patient's response, the patient's response was documented and used in data analysis. In cases where neither the patient was able to recall nor the records were available to verify, the response was documented as “no records.”
Statistical Analysis
The data entry was done in a Microsoft Excel spreadsheet and the final analysis was done using the Statistical Package for Social Sciences (SPSS) software, IBM manufacturer, Chicago, United States, version 21.0. Percentages were calculated for descriptive statistics. For statistical significance, a p-value of less than 0.05 was considered.
The inter-kappa agreement analysis was done to ascertain the association between the responses obtained from the patient and from the assessors, thereby mitigating any potential recall bias at the patient's end and also verifying the completeness of the hospital record keeping. Kappa's score derived ranged from poor to very good (0.20–1.00).
Results
The study participants were constituted of 21% young adults (18–39 years of age), 48% middle-aged (40–59 years age), and 31% old adults (≥ 60 years of age). The mean age with CAMCR was 50.85 years (24–77 years). Male predilection was seen, forming 68% of the study population. 41% of patients had wage-earning jobs, and 29% were housewives. The majority of patients hailed from upper lower (34%) and lower-middle (30%) socioeconomic strata of modified Kuppuswamy classification[15] ([Table 1]). The most common anatomical site seen was rhino-orbital (73%; [Table 2]).
Table 1
Sociodemographic profile of study subjects
|
Sociodemographic characteristics
|
n (%)/ Mean ± SD
|
|
Age (years)
Young adults (18–39 years age), middle-aged adults (40–59 years age), old adults (≥ 60 years age).
|
50.86 ± 12.67
21%
48%
31%
|
|
Gender,
n = 100
|
|
Male
|
68%
|
|
Female
|
32%
|
|
Occupation,
n = 100
|
|
Blue collar
|
41%
|
|
Housewife
|
29%
|
|
White collar
|
16%
|
|
Business
|
9%
|
|
Farmer
|
59%
|
|
Socioeconomic status,
n = 100
|
|
Upper
|
2%
|
|
Upper middle
|
28%
|
|
Upper lower
|
34%
|
|
Lower middle
|
30%
|
|
Lower
|
6%
|
Abbreviation: SD, standard deviation.
Table 2
Clinical presentations
|
Clinical form, n = 100
|
|
Rhino
|
3
|
|
Cerebral
|
1
|
|
Rhinocerebral
|
2
|
|
Rhino-orbital
|
73
|
|
Rhino-orbital-pulmonary
|
10
|
|
Rhino-orbital-cerebral
|
11
|
The most common chronic medical condition encountered was DM, seen in 49% of patients, either alone or in combination with other comorbidities ([Table 3]). Sixty-two percent of the pre-existing diabetics in our study sample did not carry out regular blood sugar monitoring, while 38% did. Among the latter, 51% had uncontrolled blood sugars and in 18%, blood sugar was controlled. Moreover, 31% of patients were unaware of blood sugar values and also could not produce any health records ([Table 4]). Fifty-nine percent of study subjects received systemic steroids during COVID-19 illness. Twenty-nine percent subject were unaware and did not have health record-keeping regarding steroid use (Annexure 2).
Table 3
Chronic medical illness in study subjects
|
H/o Chronic medical illness, n = 100
|
%
|
|
DM1
|
1
|
|
DM2
|
33
|
|
DM2 + HTN
|
11
|
|
DM2 + HTN + CAD
|
1
|
|
DM2 + HTN + COAD
|
1
|
|
DM2 + HTN + HepC
|
1
|
|
DM2 + HTN + hypothyroid
|
2
|
|
HTN
|
5
|
|
Hypothyroid
|
1
|
|
No comorbidity
|
44
|
Abbreviations: CAD, coronary artery disease; COAD, chronic obstructive airway disease; DM1, diabetes mellitus type 1; DM2, diabetes mellitus type 2; Hep C, hepatitis C; HTN, hypertension.
Table 4
Blood sugar control among pre-existing diabetics
|
n = 49
|
%
|
|
Blood sugar controlled
|
18
|
|
Uncontrolled
|
51
|
|
No records
|
31
|
The association between COVID-19 disease severity and steroid treatment was assessed by Fisher's exact test ([Table 5]). It showed that 35% of study patients with mild COVID-19 disease were treated with systemic steroids. In addition, 45% of patients with mild disease were unaware and did not have health records to ascertain steroid treatment in them. The association showed a statistically significant p-value (0.001). In 47% of the study patients, blood sugar monitoring was done during COVID-19 illness with or without a history of steroid use. In 36%, no blood sugar monitoring was done and 17% patients were unaware and had no pertaining records (Annexure 2).
Table 5
Association of steroid treatment with disease severity
|
Steroid treatment
|
Mild (n = 40)
|
Moderate (n = 24)
|
Severe (n = 36)
|
Total
|
p-Value
|
|
No
|
8 (20%)
|
2 (8.33%)
|
2 (5.56%)
|
12 (12%)
|
0.001[a]
|
|
Yes
|
14 (35%)
|
16 (66.67%)
|
29 (80.56%)
|
59 (59%)
|
|
Don't know
|
18 (45%)
|
6 (25%)
|
5 (13.89%)
|
29 (29%)
|
|
Total
|
40 (100%)
|
24 (100%)
|
36 (100%)
|
100 (100%)
|
Abbreviation: COVID-19, coronavirus disease 2019.
a The association between COVID-19 disease severity and steroid treatment was assessed by Fisher's exact test and was statistically significant with p-value of 0.001.
Fifty-six percent of study subjects had fluctuating blood sugar levels during COVID-19 illness with or without steroid use. Nine percent of them had blood sugars in the normal range. Thirty-five percent of patients were unaware of the blood sugar values and had no health record-keeping (Annexure 2).
Mild and moderate COVID-19 illness was found in 40 and 24% of study subjects respectively, being severe in 36% (Annexure 2). Sixteen percent of the study subjects received only 1 dose of COVID-19 vaccination and 5% had received both doses.
The association between COVID-19 vaccination status and severity of COVID-19 disease was analyzed ([Table 6]). Of the unvaccinated, 32.91% had severe disease. In the fully vaccinated category (5 patients), two patients suffered severe disease. The association was clinically significant with a p-value of 0.009.
Table 6
Association of COVID-19 vaccination with the severity of COVID-19 illness
|
COVID-19 vaccination
|
Mild (n = 40)
|
Moderate (n = 24)
|
Severe (n = 36)
|
Total
|
p-Value
|
|
No
|
30(37.97%)
|
23(29.11%)
|
26(32.91%)
|
79(100%)
|
0.009
|
|
1 dose
|
8(50%)
|
0(0%)
|
8(50%)
|
16(100%)
|
|
2 doses
|
2(40%)
|
1(20%)
|
2(40%)
|
5(100%)
|
|
Total
|
40(40%)
|
24(24%)
|
36(36%)
|
100(100%)
|
Abbreviation: COVID-19, coronavirus disease 2019.
Of the unvaccinated study participants, 37.97% had a mild COVID-19 illness and 32.91% had a severe disease.
In the fully vaccinated category (5 patients), 2 patients suffered severe disease. The association was statistically significant with a p-value of 0.009.
Knowledge about the initial symptoms of MCR was lacking in 71% of subjects. Eleven percent had incomplete information about the red flag signs of MCR and were aware only of the symptoms of the advanced disease, while 18% reported awareness of red flag symptoms and signs of MCR (Annexure 2).
Eight percent of the subjects presented early with symptoms of MCR. Initiation of treatment within 5 to 10 days of symptom onset of MCR was done in 25% of the study patients (Annexure 2). A significant p-value (< 0.0001) and very good kappa score (0.896) in agreement analysis regarding the onset of symptoms and initiation of treatment for MCR ([Table 7]).
Table 7
Inter-rater kappa agreement between patient and assessor for the duration between mucormycosis symptom onset and initiation of treatment
|
Patient
|
Assessor
|
Total
|
p-Value
|
Kappa
|
|
0–5 D (n = 6)
|
5–10 D (n = 14)
|
10–15 D (n = 20)
|
15–20 D (n = 10)
|
20–30 D (n = 4)
|
30–40 D (n = 5)
|
40–50 D (n = 2)
|
|
0–5 D
|
6 (9.84%)
|
0 (0.00%)
|
0 (0.00%)
|
0 (0.00%)
|
0 (0.00%)
|
0 (0.00%)
|
0 (0.00%)
|
6 (9.84%)
|
<0.0001
|
0.896
|
|
5–10 D
|
0 (0.00%)
|
14 (22.95%)
|
1 (1.64%)
|
0 (0.00%)
|
0 (0.00%)
|
0 (0.00%)
|
0 (0.00%)
|
15 (24.59%)
|
|
10–15 D
|
0 (0.00%)
|
0 (0.00%)
|
19 (31.15%)
|
1 (1.64%)
|
0 (0.00%)
|
0 (0.00%)
|
0 (0.00%)
|
20 (32.79%)
|
|
15–20 D
|
0 (0.00%)
|
0 (0.00%)
|
0 (0.00%)
|
9 (14.75%)
|
1 (1.64%)
|
0 (0.00%)
|
0 (0.00%)
|
10 (16.39%)
|
|
20–30 D
|
0 (0.00%)
|
0 (0.00%)
|
0 (0.00%)
|
0 (0.00%)
|
3 (4.92%)
|
1 (1.64%)
|
0 (0.00%)
|
4 (6.56%)
|
|
30–40 D
|
0 (0.00%)
|
0 (0.00%)
|
0 (0.00%)
|
0 (0.00%)
|
0 (0.00%)
|
4 (6.56%)
|
1 (1.64%)
|
5 (8.20%)
|
|
40–50 D
|
0 (0.00%)
|
0 (0.00%)
|
0 (0.00%)
|
0 (0.00%)
|
0 (0.00%)
|
0 (0.00%)
|
1 (1.64%)
|
1 (1.64%)
|
|
Total
|
6 (9.84%)
|
14 (22.95%)
|
20 (32.79%)
|
10 (16.39%)
|
4 (6.56%)
|
5 (8.20%)
|
2 (3.28%)
|
61 (100.00%)
|
Inter-kappa agreement could be carried out in 61 patients, since the pertaining health records were not retrievable in remaining 39 patients.
A significant p-value (< 0.0001) was derived with a very good kappa score (0.896) in agreement with analysis regarding the onset of symptoms and initiation of treatment for mucormycosis.
The agreement analysis between patient and assessor for blood sugar monitoring ([Table 8]) and blood sugar control ([Table 9]) during COVID-19 illness and or while on steroid treatment showed a significant p-value (<0.001) and a very good kappa agreement (0.882 and 0.714 respectively). The analysis regarding the severity of COVID-19 illness ([Table 10]) was good (k= 0.798).
Table 8
Inter-rater kappa agreement between patient and assessor for blood sugar monitoring during COVID-19 illness/steroid use
|
Value of K
|
Strength of agreement
|
|
< 0.20
|
Poor
|
|
0.21–0.40
|
Fair
|
|
0.41–0.60
|
Moderate
|
|
0.61–0.80
|
Good
|
|
0.81–1.00
|
Very good
|
|
Patient
|
Assessor
|
Total
|
p-Value
|
Kappa
|
|
No (n = 16)
|
Yes (n = 17)
|
|
No
|
15 (45.45%)
|
0 (0.00%)
|
15 (45.45%)
|
<0.0001
|
0.882
|
|
Yes
|
1 (3.03%)
|
16 (48.48%)
|
17 (51.52%)
|
|
Can't Say
|
0 (0.00%)
|
1 (3.03%)
|
1 (3.03%)
|
|
Total
|
16 (48.48%)
|
17 (51.52%)
|
33 (100.00%)
|
Abbreviation: COVID-19, coronavirus disease 2019.
Inter-kappa agreement could be done for 33 patients since pertaining health records were not retrievable in the other 67 patients.
The agreement analysis between patient and assessor for blood sugar monitoring during COVID-19 illness and/or while on steroid treatment showed a significant p-value (<0.0001) and a very good value of kappa agreement (0.882).
Table 9
Inter-rater kappa agreement between patient and assessor for blood sugar control during COVID-19 illness/steroid use
|
Patient
|
Assessor
|
Total
|
p-Value
|
Kappa
|
|
No (n = 19)
|
Yes (n = 3)
|
|
No
|
16 (72.73%)
|
0 (0.00%)
|
16 (72.73%)
|
0.0002
|
0.61
|
|
Yes
|
1 (4.54%)
|
3 (13.64%)
|
4 (18.18%)
|
|
Can't say
|
2 (9.09%)
|
0 (0.00%)
|
2 (9.09%)
|
|
Total
|
19 (86.367%)
|
3 (13.64%)
|
22 (100.00%)
|
Abbreviation: COVID-19, coronavirus disease 2019.
Inter-kappa agreement could be carried out in 22 patients, since pertaining health records were not retrievable in the remaining 78 patients.
The agreement analysis between patient and assessor for blood sugar control during COVID-19 illness and/or while on steroid treatment showed a significant p-value (<0.0002) and a good value of kappa agreement 0.61.
Table 10
Inter-rater kappa agreement between patient and assessor for the severity of COVID-19 illness
|
Patient
|
Assessor
|
p-Value
|
Kappa
|
|
Mild (n = 24)
|
Moderate (n = 17)
|
Severe (n = 27)
|
Total
|
|
Mild
|
22
(32.35%)
|
5 (7.35%)
|
2 (2.94%)
|
29 (42.65%)
|
|
|
|
Moderate
|
1 (1.47%)
|
12 (17.65%)
|
0 (0.00%)
|
13 (19.12%)
|
|
|
|
Severe
|
0 (0.00%)
|
0 (0.00%)
|
25 (36.76%)
|
25 (36.76%)
|
< 0.0001
|
0.798
|
|
Can't say
|
1 (1.47%)
|
0 (0.00%)
|
0 (0.00%)
|
1 (1.47%)
|
|
|
|
Total
|
24
(35.29%)
|
17 (25.00%)
|
27 (39.71%)
|
68
(100.00%)
|
|
|
Abbreviation: COVID-19, coronavirus disease 2019.
Inter-kappa agreement could be carried in 68 patients, since pertaining health records were not retrievable in remaining 32 patients.
The agreement analysis regarding the severity illness of COVID-19 was obtained as good (k= 0.798).
Discussion
The study patients presenting with CAMCR were more commonly middle-aged, males, belonging to the upper-lower class of modified Kuppuswamy classification, doing wage-earning jobs. The most frequently involved anatomical site was rhino-orbital ([Tables 1], [2]). DM was the most common underlying illness ([Table 3]).
Studies have identified male predilection[2]
[16]
[17]
[18]
[19] and middle age group (45–55 years) as most commonly affected with MCR in pre-COVID-19 times similar to that for our patients with CAMCR,[16]
[17] as well as for other studies involving patients with CAMCR.[5]
[20]
Jeong et al in a global meta-analysis in non-COVID-19 times observed ROCM as the most common presentation, in 34% of patients.[11] Likewise, ROCM was also the most common clinical variant globally when associated with COVID-19 but in increasingly higher numbers, in 76%.[18] This was unlike in the pre-COVID-19 times wherein a disparate presentation was seen in the clinical distribution of MCR, with ROCM as the most common variant in developing countries,[2]
[17]
[20]
[21] but not the developed countries.[22]
Thus, we observed that the epidemiology and clinical form ([Table 2]) of patients with MCR in correlation with COVID-19 were similar to that for MCR in a pre-COVID-19 era in India.[2]
[3]
[22]
DM was identified as most common underlying disease in patients affected by MCR in pre-COVID-19 times globally[2] as well as in India.[17]
[19] Jeong et al in a large meta-analysis showed 40 versus 73.5% diabetics globally and in India, respectively, thus, highlighting a much higher prevalence of diabetes with MCR in India.[16] Bala et al prior to the COVID-19 pandemic observed DM to significantly increase the odds of contracting ROCM.[18] Although during COVID-19 pandemic, hyperglycemia due to pre-existing DM or new-onset diabetes has been studied as most important risk factor for CAMCR even in cases outside India.[19]
[20]
Retrospective studies in India on CAMCR[5]
[23]
[24] noted diabetes as the single major comorbidity with Bhanuprasad et al[24] observing diabetes in 97% of CAMCR patients, 40% of which were newly detected. This is in concordance with our findings amongst CAMCR patients ([Table 3]).
Patel et al[21] observed uncontrolled diabetes to be the most common underlying disease in 67 versus 60.4% in non-CAMCR and CAMCR, respectively. COVID-19 was the only underlying disease in 32.6% of CAMCR patients, comparable to 44% in our study ([Table 3]). This suggests a possibility of either new-onset diabetes with COVID-19 infection since it induces a diabetogenic state[4] and also increases the risk of associated complications. Furthermore, it may have likely worsened hyperglycemia in pre-existing but undiagnosed diabetics, thereby unmasking diabetes in them[7] which could have been in high number considering abysmal health awareness among Indian population.[6] Thus, DM continues to be the most common underlying illness in MCR both with and without association with COVID-19, with a higher prevalence of uncontrolled diabetes in CAMCR.
India is the diabetic capital of the world, not surprisingly considering dismal health literacy, and health access.[9] This is also reflected in our study with the fact that 62% of pre-existing diabetics were found not carrying out regular blood sugar monitoring. Furthermore, 51% of pre-existing diabetics had uncontrolled blood sugars, and 31% were both unaware of their glycemic control and also did not maintain health records ([Table 4]). Though hemoglobin A1c aids in better defining diabetes blood sugar control, it was available in the medical records for a few patients only and hence was not used. However, when available, it was found to be abnormal.
Another major risk factor identified is corticosteroid use, especially in diabetics resulting in complex immune dysregulation.[25]
[26] In pre-COVID-19 times, Skiada et al[22] noted MCR with corticosteroid use in 46% of patients. It was noted to be the most common predisposing factor in a meta-analysis by Jeong et al.[16] John et al[20] observed the use of systemic corticosteroids in 97.56% of patients with CAMCR. In our study, 59% of patients had been treated with steroids, while they were positive for COVID-19. Out of the 51 non-diabetics, 59% had received steroids for COVID-19. Twenty-nine percent of patients were neither aware of steroid use nor had records for the same.
However, 29% of patients had no awareness and also maintained no health records to provide information on steroid medication prescription (Annexure 2). The association between COVID-19 disease severity and steroid treatment was assessed and was statistically significant with p-value of 0.001([Table 5]).
We observed that 35% of patients with mild disease had been treated with systemic steroids. Furthermore, 45% of patients with mild COVID-19 illness had neither awareness nor documents pertaining to steroid use. These findings highlight the unwarranted and unrestrained use of steroids. COVID-19 scare and restricted access to a health facility during the COVID-19 crisis may have resulted in self-treatment with over-the-counter steroids.
In 47% of study subjects, blood sugar monitoring was carried out during COVID-19 illness with or without treatment with steroids. Seventeen percent of the patients were unaware and had no record-keeping to verify their glycemic monitoring. Furthermore, 56% of study subjects had fluctuating blood sugar levels during COVID-19 illness, while 9% of them had blood sugars in the normal range. Thirty-five percent of patients were unaware of the blood sugar values and had no health record-keeping (Annexure 2).
Our observations are corroborated by Gianchandani et al[27] who found very high blood sugar levels in CAMCR patients. The inter-kappa analysis on blood sugar monitoring during COVID-19 illness with or without treatment with systemic steroids shows a significant p-value and a very good kappa agreement (0.81–1.00; [Table 8]). This further signifies that the information obtained from patients was accurate and also a good record keeping as retrieved from the case sheets of the patients.
Mulakavalupil et al[28] showed that low-dose steroids with strict glycemic control completely eliminated risk of MCR in COVID-19. On assessing the disease severity, mild and moderate COVID-19 illness was found in 40 and 24% of subjects, respectively (Annexure 2).
Even mild COVID-19 can induce a proinflammatory milieu, which can further lead to lowering insulin sensitivity.[29] Prolonged hospitalization, broad-spectrum antibiotics, intensive care unit admission, intubation/mechanical ventilation, and surgery are usually seen with severe COVID-19 illness and associated with MCR.[30] Sixty percent of the study patients required hospitalization for a COVID-19 illness of which 30% remained hospitalized for 11 to 20 days.
Primary prevention in the form of vaccination remains the mainstay for mitigating the risks associated with COVID-19 in patients with DM.[31] Seventy-nine percent of the study participants were not vaccinated against COVID-19. A correlation between COVID-19 disease severity and vaccination status of the participants was studied and findings revealed that 33% of unvaccinated patients had severe disease, 38% had mild disease, and 29% had moderate disease. The association was statistically significant with a p-value of 0.009 ([Table 6]). COVID-19 vaccination has been shown to reduce the disease severity. In a retrospective, analysis by Li et al[32] on COVID-19 patients to estimate the effectiveness of vaccination in preventing disease progression, it was concluded that risk of pneumonia and severe disease was lower in fully vaccinated individuals than unvaccinated people. In a case–control study by Tenforde et al,[33] to ascertain the association between prior vaccination and hospitalization for COVID-19 and its progression, the authors concluded that the outcome of mechanical ventilation and death among the vaccinated was less likely. These findings are in concordance with the present study and suggest that the risk of developing severe COVID-19 disease is less with prior vaccination and thus complications like COVID-19-associated mucormycosis are also infrequent. Hence, mild disease does not require hospitalization or steroid treatment thereby immunosuppression and hospital-acquired infections are circumvented. Vaccination has a dual beneficial effect for COVID-19 disease on its severity as well as its further complications like COVID-19-associated MCR that were rampant during the second wave in India.
Average to poor sanitary surroundings during isolation and treatment period was reported by 58% of study subjects. Individuals who have recently recuperated from COVID-19 should ensure stringent personal hygiene.[34] Sixty-nine percent of patients reported wearing cloth protective masks and 9% used no masks, with 21% of patients using soiled masks (Annexure 2). The All India Institute of Medical Sciences had issued guidelines on MCR alerting the public on the alarming symptoms to be watched for to detect early disease.[35]
Seventy-one percent of the study participants had no knowledge and 11% had knowledge only about advanced stage symptoms and could not relate their initial symptoms to the disease ([Table 1]). In 18% of the aware cases, media through television and newspaper helped spread awareness. Only 6% of patients were alerted to the red flag signs of MCR by their clinicians. Thirty-two percent of patients reported face swelling including eyes as the initial symptom with nasal symptoms in only 11%. Hence, patients presenting with early disease limited to the nasal site were few (8%; Annexure 2).
Management for MCR was initiated in 25% of the patients within 5 to10 days of the symptom onset. Only in 8% of patients, management was initiated within 5 days of symptom onset. The agreement analysis shows a very good kappa score regarding the onset of symptoms and initiation of management of MCR, further nullifying a recall bias ([Table 7]).
A delay in the establishment of the diagnosis of MCR resulted in rapid disease progression thereby necessitating more aggressive treatment. Seventy-five percent of the study participants received both medical and surgical treatment by the time they answered the questionnaire (Annexure 2).
Strengthening efforts to enhance health awareness among the general public in various aspects of diabetes care is the key to keeping the associated threats in check. It is prudent to have early initiation of treatment of mucormycosis on strong clinical and radiological suspicion without waiting for tissue confirmation to enable improved outcomes in this rapidly progressive highly debilitating, fatal disease.
The present study having a questionnaire-based design had the limitations of being time-consuming, with participants getting disinterested at times, affecting the essence of the results obtained. Additionally, open-ended questions though few might have been difficult for less educated participants to answer. Other limitations specific to the study entailed records pertaining to the information on pre-existing illnesses, blood sugar charting, and management of MCR were incomplete and missing for so. Follow-up of the patients regarding outcome was not done; therefore, the underlying potential risk factors of the disease could not be correlated to the disease outcome.
The message to take home is that the health literacy of patients having a chronic disease like diabetes plays a key role in optimal control of comorbidity and preventing the associated complications. COVID-19 in its progression and severity affects immunocompromised patients with greater virulence. Hence, strengthening patient education and also health awareness in the general population is paramount to reducing complications entailing COVID-19 such as immunosuppression and MCR. In addition, vaccination against COVID-19 should be encouraged with the use of masks and social distancing should be actively practiced.
Conclusion
Clinicoepidemiological profile of COVID-19-associated MCR was found similar to that not associated with COVID-19, although diabetes was more commonly seen in patients with CAMCR in our study. Health literacy among diabetics had lacunae that resulted in impaired glycemic control. Additionally, awareness for blood sugar monitoring and control during COVID-19 illness with or without the use of steroids was mostly lacking. Knowledge of the “red flag” signs of MCR was incomplete, thereby hampering early disease recognition. Interventions to improve awareness amongst patients with diabetes should help in optimal glycemic control, and avoid potential complications including severe COVID-19 illness, MCR.
We conducted principal component analysis with Varimax rotation to divide the items into factors. The number of factors retained was derived by considering the magnitude of the eigenvalues, Kaiser's (1960) eigenvalues (> 1) rule, the proportion of variance extracted, item content, and the interpretability of the resulting factors. As for factor loading after the Varimax rotation, items with a factor loading less than 0.5 on all factors were excluded. We investigated the internal consistency by calculating Cronbach's alpha and by calculating item-total correlations for each factor that was identified with the factor analysis, and alpha greater than 0.70 was considered acceptable, and optimal item-total correlation was considered to be between 0.2 and 0.5.
Results from the factor analysis indicated that each factor accounts for approximately 40% of the variance. Cronbach's alpha coefficients for various questions in the questionnaire were greater than the accepted number of more than or equal to 0.70.
Calculation of internal consistency (Cronbach's alpha 0.703-0.834) and cross-validation provided evidence of reliability and lack of redundancy of items.
We found that the number of factors, the factor structure, and factors loadings were for the greater part comparable between the first randomly created subsample (n = 25) and the total sample (n =100).
Annexure 2: Patient questionnaire with responses
|
S No
|
Question
|
Possible answers
|
Replies obtained
|
|
1
|
How many days prior to developing symptoms of “Black fungus,” did you have COVID-19 or COVID-19 like illness? n = 100
|
0–10 days
|
33%
|
|
11–20 days
|
36%
|
|
21–30 days
|
18%
|
|
31–40 days
|
9%
|
|
> 40 days
|
4%
|
|
2
|
Where did you get treated for COVID-19? n = 100
|
Home
|
38%
|
|
Hospital
|
38%
|
|
Home +Hospital
|
24%
|
|
3
|
How was the overall hygiene of the place of stay while being isolated? n = 100
|
Good
|
42%
|
|
Average
|
50%
|
|
Poor
|
8%
|
|
4
|
How many days did you stay at a hospital/COVID-19 care center? n = 100
|
<10 days
|
23%
|
|
11–20 days
|
28%
|
|
21–30 days
|
9%
|
|
31–40 days
|
2%
|
|
NA
|
38%
|
|
5a
|
Were you treated with steroids like Dexona/ Predmet/Medrol/Wysolone, n = 100
|
Yes
|
59%
|
|
No
|
12%
|
|
No records
|
29%
|
|
5b
|
If yes, you took steroids, n= 59
|
As prescription
|
97%
|
|
As self-medication
|
3%
|
|
5c
|
If taken steroids as a prescription, prescribed for what duration? (n = 57)
|
<10 days
|
30%
|
|
>10 days
|
68%
|
|
No Records
|
2%
|
|
5d
|
If taken steroids as a prescription, took n = 57
|
More no. of days
|
1%
|
|
More than the prescribed dose
|
1%
|
|
More days+ More dose
|
1%
|
|
None
|
60%
|
|
No records
|
18%
|
|
NA
|
19%
|
|
6a
|
Was blood sugar monitored during COVID-19 illness with or without steroid use? n = 100
|
Yes
|
47%
|
|
No
|
36%
|
|
Don't know
|
17%
|
|
6b
|
Was the blood sugar controlled during COVID-19 illness with or without steroid use? n = 100
|
Normal range
|
9%
|
|
Fluctuating
|
56%
|
|
No records
|
35%
|
|
7a
|
Treatment prescribed for blood sugar control during COVID-19 illness with or without steroid use? n = 100
|
OHA
|
18%
|
|
OHA + insulin
|
17%
|
|
Insulin
|
29%
|
|
None
|
18%
|
|
No records
|
18%
|
|
7b
|
If OHAs were used then medication names? n = 35
|
Single drug
|
31%
|
|
Double drug
|
23%
|
|
Triple drug
|
6%
|
|
No records
|
40%
|
|
8
|
How severe was the illness? n = 100
|
Mild RR < 20, Spo2 > 93%
|
40%
|
|
Moderate RR 20-30, Spo2 > 90%
|
24%
|
|
Severe RR > 30, Spo2 < 90%
|
36%
|
|
9
|
What was the CTSS score if you remember, if the CT chest done? n = 100; CTSS score 7 or less (mild) n = 0; CTSS score 8–17 (moderate) n = 22; CTSS score 18 or more (severe) n = 11
|
10
|
3%
|
|
11
|
1%
|
|
12
|
4%
|
|
13
|
2%
|
|
14
|
3%
|
|
15
|
4%
|
|
16
|
2%
|
|
17
|
3%
|
|
18
|
3%
|
|
19
|
2%
|
|
20
|
1%
|
|
21
|
2%
|
|
22
|
1%
|
|
23
|
1%
|
|
24
|
1%
|
|
NA
|
36%
|
|
No records
|
31%
|
|
10a
|
Did you receive oxygen therapy? (n = 100)
|
Yes
|
56%
|
|
No
|
43%
|
|
Can't say
|
1%
|
|
10b
|
If yes, received at n = 56
|
Home
|
4%
|
|
Hospital
|
80%
|
|
Home +Hospital
|
16%
|
|
10c
|
Was the oxygen dry or moist? n = 56
|
Moist
|
80%
|
|
Dry
|
0%
|
|
Can't say
|
20%
|
|
10d
|
What type of humidification was used (hospital/home)? n = 56
|
Packaged water/RO water
|
19%
|
|
Distilled water
|
7%
|
|
Tap water
|
6%
|
|
Can't say
|
13%
|
|
NA
|
55%
|
|
11
|
Mode of oxygen therapy used? n = 56
|
Simple face mask
|
38%
|
|
Tight mask with straps (Bipap)
|
13%
|
|
Nasal prongs
|
5%
|
|
NA
|
44%
|
|
12
|
Any other treatment received?
|
Remdesivir
|
9%
|
|
Any other treatment
|
35%
|
|
No records
|
56%
|
|
13
|
For what duration was treatment taken for COVID-19, including hospital & home? n = 100
|
<7 days
|
22%
|
|
7–14 days
|
36%
|
|
15–30 days
|
34%
|
|
>30 days
|
8%
|
|
14
|
COVID-19 vaccination received? n = 100
|
1 dose
|
16%
|
|
2 doses
|
5%
|
|
Not vaccinated
|
79%
|
|
15a
|
Do you have pre-existing diabetes or any other disease for which you have been taking long term medication prior to COVID-19 illness? n = 100
|
Yes
|
56%
|
|
No
|
44%
|
|
15b
|
If yes please specify the disease DM/malignancy/HTN/thyroid disorder/CKD/ chemotherapy/immunosuppressants? n = 56
|
DM 1
|
1%
|
|
DM2
|
33%
|
|
DM2 + HTN
|
11%
|
|
DM2 + HTN + CAD
|
1%
|
|
DM2 + HTN + COAD
|
1%
|
|
DM2 + HTN + Hep c
|
1%
|
|
DM2 + HTN + Hypothyroid
|
1%
|
|
HTN
|
5%
|
|
Hypothyroid
|
1%
|
|
NA
|
45%
|
|
16
|
If pre-existing diabetes, what was the treatment taken? n = 49
|
OHA
|
35%
|
|
OHA + insulin
|
3%
|
|
Insulin
|
1%
|
|
None
|
10%
|
|
NA
|
51%
|
|
17a
|
Did you routinely check blood sugars prior to COVID-19 illness, n = 100
|
Yes
|
28%
|
|
No
|
72%
|
|
17b
|
If yes, how did you check? n = 28
|
Yes
|
57%
|
|
No
|
43%
|
|
17c
|
Did you routinely check blood sugars (in pre-existing diabetics), n = 49
|
Home yes
|
38%
|
|
Hospital care facility no
|
62%
|
|
18
|
Was blood sugar controlled? (blood sugar values: 80–140 mg/dL before meals and < 200 mg/dL, 2 hours after meals); n = 49
|
Yes
|
18.00%
|
|
No
|
51.00%
|
|
Can't say
|
31.00%
|
|
19
|
Did you experience any episodes of rapid heart rate, blurry vision, unconsciousness? n = 49
|
Yes
|
8%
|
|
No
|
83%
|
|
Can't say
|
9%
|
|
20a
|
Type of COVID-19 protection mask used? n = 100
|
Cloth
|
69%
|
|
Surgical
|
10%
|
|
N-95
|
9%
|
|
Combination
|
3%
|
|
No mask
|
9%
|
|
20b
|
How often was the mask changed/washed? n = 100
|
1-3 days
|
47%
|
|
4-6 days
|
24%
|
|
7-14 days
|
13%
|
|
>14 days
|
7%
|
|
NA
|
9%
|
|
20c
|
Was the oxygen mask changed on becoming soiled/wet? n = 100
|
Yes
|
71%
|
|
No
|
21%
|
|
NA
|
8%
|
|
21
|
Did you know about symptoms of black fungus? n = 100
|
Yes
|
18%
|
|
No
|
71%
|
|
Incomplete information
|
11%
|
|
22
|
If yes (complete or incomplete), source of information? n= 29
|
Television/newspaper
|
62%
|
|
Treating doctor
|
17.20%
|
|
Internet
|
13.70%
|
|
Family/Friends
|
6.89%
|
|
23
|
Were you alerted about the symptoms of mucormycosis before leaving the hospital? n = 100
|
Yes
|
6%
|
|
No
|
79%
|
|
NA
|
15%
|
|
24
|
Which symptoms did you notice first? n = 100
|
Face swelling
|
32%
|
|
Visual disturbances
|
12%
|
|
SO pain
|
12%
|
|
Nasal stuffiness
|
11%
|
|
Vision disturbances + SO pain
|
10%
|
|
Nasal discharge
|
7%
|
|
Pain in mandible
|
6%
|
|
Face numbness
|
5%
|
|
Blood in cough
|
2%
|
|
Nasal bleed
|
1%
|
|
Infraorbital pain
|
1%
|
|
cough/breathlessness
|
1%
|
|
25
|
After how many days of diagnosis of mucormycosis was the treatment started? n = 100
|
<5 days
|
8%
|
|
5–10 days
|
25%
|
|
10–15 days
|
25%
|
|
15–20 days
|
19%
|
|
20–30 days
|
9%
|
|
30–40 days
|
7%
|
|
40–50 days
|
5%
|
|
>50 days
|
2%
|
|
26
|
What mode of treatment are you being given for black fungus? n = 100
|
Medicine only
|
23%
|
|
Surgery only
|
2%
|
|
Both
|
75%
|
|
27
|
Are you satisfied with the treatment? n = 100
|
Satisfied
|
84%
|
|
Not satisfied
|
5%
|
|
Can't say
|
11%
|
Abbreviations: CAD, coronary artery disease; CKD, chronic kidney disease; COAD, chronic obstructive airway disease; COVID-19, coronavirus disease 2019; CTSS, CT Chest Severity Score; DM1, diabetes mellitus type 1; DM2, diabetes mellitus type 2; HTN, hypertension; NA, not available; OHA, Oral Hypoglycemic Agent; RO, reverse osmosis; RR, relative risk; SPO2, oxygen saturation; SO, supraorbital.
