Diabetic post-covid mucormycosis: A dermatoglyphic prediction

ABSTRACT

Aim:

To identify the characteristic pattern/parameter among diabetic post-covid mucormycosis patients which may further help in identifying such susceptible patients in a much earlier course of the disease.

Materials and Methods:

The study was done with 30 diabetic patients (21 males and 9 females) admitted in RIMS Ranchi during the second wave of Covid-19 for post-covid complications. Palm and fingerprint pattern was taken by ink and pad method to measure the qualitative and quantitative parameters.

Result:

Diabetic post-covid mucormycosis patients were found to have predominantly whorl pattern in males, loop in females, and C-line pattern absent in 36.6%. Proximal axial triradii with ulnar deviation was 76.6%. All the ridge counts (except ab ridge count of right hand) when compared with hypothesized value were found to be significant with P value (<0.005). None of the three angles measured were found to be significant.

Conclusion:

All the ridge counts (except ab ridge count of right hand) were found to be a reliable parameter for the diagnosis of diabetic post-covid mucormycosis. ATD angle known to be the most reliable parameter for diagnosis of diabetes mellitus in dermatoglyphics is found to be nonreliable with respect to diabetes post-covid mucormycosis.

Introduction

During the second wave of Covid-19, it was seen that there was a rise in morbidity and mortality among post-covid diabetic patients due to mucormycosis.[1] India being a diabetic capital of the world, was hit hard amounting around 8,848 cases according to the times of India of May 23, 2021.[2,3] Previous studies on mucormycosis have identified chronic corticosteroid use and diabetes-induced ketoacidosis as the two primary risk factors for the condition.[4,5] During Covid-19 times it was seen that there was a steep rise in mucormycosis cases which could be mainly because of 1) uncontrolled diabetes leading to ketoacidosis with increased ferritin level leading to impaired ability of phagocytes to move and kill the Mucorales, 2) the deferoxamine given to treat the increased ferritin level was by itself known to be an important growth factor for Mucorales, and lastly 3) the prolonged use of corticosteroids to avoid the need for oxygen and hospital admission in Covid-19 patients.[4,5,6] Globally, the prevalence of mucormycosis varied from 0.005 to 1.7 per million population, while its prevalence is nearly 80 times higher (0.14 per 1000) in India compared to developed countries, in a recent estimate for the year 2019–2020.[7]

Dermatoglyphics which is the study of epidermal ridge configuration on palm and planter region is known to develop by several genes as early as third month of intrauterine life. The pleiotrophic gene influencing both familial diseases and dermatoglyphic patterns could be used as a characteristic to predict a phenotype of a possible future illness.[8]

Early recognition of the disease and prompt initiation of treatment are essential for lifesaving management. Due to the challenges and complexity associated with early diagnosis and management of covid-associated mucormycosis, it would be best handled by a multidisciplinary team.[9] Several studies have been done around the globe on the dermatoglyphic pattern in patients with diabetes mellitus. This study is an attempt to identify the characteristic pattern/parameter among the post-covid mucormycosis diabetic patients which may further help in identifying such susceptible patients in a much earlier course of the disease.

Materials and Methods

An observational cross-sectional study was conducted after getting consent from the Institutional ethical committee on 30 diabetic patients (male 21 and female 9) admitted in the Department of ENT in RIMS Ranchi, Jharkhand from June 2021 to November 2021 for post-covid complications. Those fulfilling inclusion and exclusion criteria were given a summary of the research being conducted. History was taken from them regarding their demographic parameters, medical history, surgical history, family history, and Covid-19 history. Palmer and fingerprint of both hands were taken using ink and pad method as directed by Cummins and Midlow (1961).[3]

Initially, both hands were cleaned and then Koves’s duplicate ink was applied using an ink roller. With plane paper on a glass slab used for a firm surface, the palms and fingers were pressed on paper and hand raised from radial to ulnar side. Hand was washed using an ample amount of soap and water and then dried.

All the prints were scanned using a scanner and examined by three observers to measure the various parameters on a computer using MS paint and protractor. The mean of all the parameters obtained was noted and analyzed using Statistical Package for Social Sciences Version 25.[10] One sample Student t-test was used for quantitative analysis and Pearson’s Chi-square test was used for qualitative test.

Working definitions

1. Fingerprint: whorl, arches, and loop as shown in [Figure 2].

2. C-line pattern: the proximal fork of triradii direction was seen if it is ulnar deviated, radial deviated, proximally oriented, or absent

3. Axial triradi (AXT): (t) triradii close to the distal wrist crease, t’ triradii at level of distal border of thumb, t’’ triradii more distal to t”.

4. Axial triradii deviation (AXT-d): a vertical line drawn from the middle of proximal metacarpophalangeal joint crease of the ring finger to the distal wrist crease. The axial triradius which falls in the same alignment or on either side of the drawn line is named as central or deviated to the ulnar or radial side.[8]

5. Total finger ridge count (TFRC) and absolute finger ridge count (AFRC): TFRC represents the sum of the ridge count of all the fingers. A larger count is used in those fingers with more than one ridge count. In loops where there is only one triradii, there is one ridge count. In a whorl where there are two triradii, there are two ridge counts and here the higher count is used. In a double loop whorl, the counting is done from the triradii to the core that is nearer the triradii. AFRC is the sum of the ridge count of all fingers. The TFRC and AFRC are the same if no whorls are present. TFRC expresses the size of the pattern and AFRC reflects the pattern size as well as its intensity.[8]

6. Ridge count of palm A) ab ridge count: ridge count of the line joining triradii at the base of the index finger (a) to triradii at the base of the middle finger (b). B) bc ridge count: ridge count of the line joining (b) to triradii at the base of the ring finger (c). C) cd ridge count: ridge count of the line joining (c) to triradii at the base of the little finger (d).

7. Measurement of the angles of the palm ATD, TDA, and TAD angle: a point (t) as triradii near the distal wrist crease, join the points a, d, and t and measure the three angles.

Figure 2.

Dermatoglyphic pattern of the palm. a)- index finger triradii, b)- middle finger triradii, c)- ring finger triradii, d)- little finger triradii, t)- axial triradii, 1)- angle atd, 2)- angle tad, 3)- angle adt

Result

Interpretation

A Chi-square test for association was conducted between gender and AXT, AXT-d, and C-line pattern as shown in [Table 1]. There was statistically no significant association between gender and AXT (Chi-square value: 1.96 df: 1, P value:.161), gender and AXT-d (Chi-square value: 4.87 df: 2, P value: 0.087), gender and C-line pattern (Chi-square value: 0,653 df: 3, P value: 0,088). There was a moderately strong association between gender and AXT, AXT-d, and C-line pattern Cramer’s V being 0.181, 0.285, and 0.104.

Table 1.

Exhibiting the AXT, AXT-d, and C- Line pattern

Parameter	Male	female	Chi-square value	P
AXT
Proximal t	33	11
Middle t´	9	7	1.96	0.161
Distal t´´	0	0
AXT-d
ulnar	33	13
middle	9	3	4.87	0.087
radial	0	2
C-Line
ulnar	11	6
radial	10	3	0.653	0.88
proximal	6	2
absent	15	7

A Chi-square test for association was conducted between gender and AXT, AXT-d, and C-line pattern. There was statistically no significant association of AXT, AXT-d, and C-line pattern with gender (P value < 0.005).

Interpretation

The value of TFRC and AFRC was normally distributed as seen in Q-Q plot test of normality. A one sample t-test was applied to test whether the mean TFRC and mean AFRC of the present study differ from a hypothesized value. We observed that there was a statistically significant difference (P value < .005) in the mean TFRC and mean AFRC of my study from a hypothesized value as shown in [Table 2].

Table 2.

TFRC and AFRC

Parameter	Mean	SD	t	P
TFRC	58.28	12.44	−16.30	<.005
AFFC	61.10	11.95	−32.41	<.005

Interpretation

The value of ab, bc, and cd ridge count was normally distributed as seen in Q-Q plot test of normality. A one sample t-test was applied to test whether mean ab ridge count, mean bc ridge count, and mean cd ridge count of the present study differ from a hypothesized value. We observed that there was a statistically significant difference (P value < .005) in mean of ab ridge count (left), mean of bc ridge count (right and left), and mean of cd ridge count (right and left) of present study from a hypothesized value as shown in [Table 3].

Table 3.

ab, bc, cd ridge count

Parameter	Mean	SD	t	P
ab ridge count
right	33.9	6.78	1.75	0.09
left	38.3	6.89	4.76	0.00
bc ridge count
right	26.17	5.97	10.21	0.00
left	25.57	5.41	10.17	0.00
cd ridge count
right	35.63	5.46	13.41	0.00
left	31.93	7.92	7.38	0.00

Interpretation

The value of ATD, ADT, and DAT angle was normally distributed as seen in Q-Q plot test of normality. A one sample t-test was applied to test whether mean ATD, mean ADT, and mean DAT angles of the present study differ from a hypothesized value. No statistically significant difference was observed (P value < .005) in the mean of any of the angles in the present study from a hypothesized value as shown in [Table 4].

Table 4.

ADT, ATD, ADT angle

Parameter	Mean	SD	t	P
TFRC	58.28	12.44	−16.30	<0.005
AFRC	61.10	11.95	−32.41	<0.005
ab ridge count
right	33.9	6.78	1.75	0.09
left	38.3	6.89	4.76	<0.005
bc ridge count
right	26.17	5.97	10.21	<0.005
left	25.57	5.41	10.17	<0.005
cd ridge count
right	35.63	5.46	13.41	<0.005
left	31.93	7.92	7.38	<0.005
ATD angle
right	40.53	6.64	−0.99	0.32
left	40.96	6.18	−0.383	0.70
ADT angle
right	78.33	5.47	−0.69	0.49
left	80.7	5.16	1.05	0.30
DAT angle
right	29.9	6.21	1.05	0.29
left	57.5	5.56	−0.43	0.66

Discussion

Qualitative parameters

1. Fingerprint: In the present study whorl pattern (48.54%) in males and loop (51.12%) in females was found to be more common in diabetic post-covid mucormycosis patients as shown in [Figure 1]. This finding was found similar to Praveen Ojha et al. (2014)[11] and Rakate et al. (2013)[12] who observed a similar trend among diabetic patients. Hence there is no difference in fingerprint predominance pattern between the diabetic post-covid mucormycosis patients and diabetic patients.

2. C-line pattern, axial triradii (AXT), and axial triradii deviation (AXT-d):

   C-line pattern was found to be radial in 42% of diabetic patients in the study by Praveen Ojha et al.[11] but in our study, the predominant pattern in diabetic post-covid mucormycosis patients was absent C-line 36.6% followed by ulnar (26.6%), radial (21.6%), and proximal (13.3%). The association was not found to be significant between diabetic post-covid mucormycosis patients and diabetic patients.

   The commonest AXT pattern was found to be proximal variety consistent with the findings of diabetic patients in the study by Praveen Ojha et al.[11] but the finding was not significant.

   AXT-d was found to be ulnar deviated in 76.7% of diabetic post-covid mucormycosis patients compared to radial deviation being the most common in the diabetic patients in the study by Praveen Ojha et al.[11]

Figure 1.

Exhibiting distribution of the fingerprint pattern among gender

Quantitative parameters

1. Total finger ridge count (TFRC) and Average finger ridge count (AFRC)

   In the present study mean TFRC and mean AFRC were 58.28 ± 12.44 and 61.10 ± 11.95. On running the statistical analysis P value (<0.005) was found to be highly significant thus showing the importance of TFRC and AFRC in diabetic post-covid mucormycosis patients compared to hypothesized values of diabetic patients.

2. ab ridge count, bc ridge count, and cd ridge count.

   Mean ab ridge count (left) 38.3 ± 6.89, mean bc ridge count (right and left) 26.17 ± 5.97 and 25.57 ± 5.41, respectively, and mean cd ridge count (right and left) was 35.63 ± 5.46 and 31.93 ± 7.92, respectively, P value (<0.005) was found to be highly significant thus showing the importance of the three ridge counts in diabetic post-covid mucormycosis patients.

3. ATD angle, ADT angle, and DAT angle

   ADT angle is known to be a reliable indicator for the diagnosis of diabetes mellitus in the previous researches.[13,14] In my study mean ATD angle, mean ADT angle, and mean DAT angle were 40.74°, 79.01°, and 43.3°, respectively. The mean of all the angles was falling in the range of previous studies done on diabetic patients, hence, it was not significant statistically with respect to diabetic post-covid mucormycosis patients, this shows that angles are not a very reliable parameter for its diagnosis.

Conclusion

The present study aimed to find out if there is any dermatoglyphic parameter in diabetic post-covid patients which will help as a predictor for mucormycosis susceptibility among these patients and help in its early diagnosis. The findings are summed up as under

• AXT-d was more on the ulnar side and absent C-line which was most common was found in 36.6% of diabetic post-covid mucormycosis patients

• TFRC, AFRC, ab ridge count (left), bc ridge count (right and left), and cd ridge count (right and left) were found statistically significant. Indicating them to be a reliable parameter for the diagnosis of diabetic post-covid mucormycosis

• According to literature ATD angle known to be the most reliable parameter for diagnosis of diabetes mellitus in dermatoglyphics is found to be nonsignificant with respect to post-covid mucormycosis.

This study will offer diabetic patients in the covid era, prediction guidance so that they can be timely informed about the likelihood of developing mucormycosis and take the appropriate precautions to prevent it.

In developing nations like India, where the primary health care must be delivered with very few resources in primary level health care facilities, the non-invasive method will be of immense help.

Limitation of the study

This study was done with a limited number of patients in a single tertiary care hospital.

Relevance of the study to the practice of primary care physicians

• This study is conducted using dermatoglyphic as a research parameter.

• Dermatoglyphic is a non-invasive test that can be done in OPD or inpatient, primary, secondary, or tertiary health care facilities.

• Dermatoglyphic can be done with minimal workforce training in a resource-limited setup.

• The study gives information about predicting disease severity and mortality which can be used to create awareness among the vulnerable group, that is, the diabetic post-covid mucormycosis patients.

Henceforth, dermatoglyphic, and the parameters derived through it, can aid in diabetic post-covid mucormycosis patient triaging at the primary assessment.

Non-authors contribution

The authors are sincerely thankful to the faculties of the Department of ENT, RIMS, Ranchi, especially Dr. Noman Alam for his support in conducting the data collection smoothly. The authors are also extremely grateful to the nursing staff for their cooperation during the difficult times of the pandemic.

Declaration of patient consent

The authors certify that they have obtained all appropriate patient consent forms. In the form, the patient(s) has/have given his/her/their consent for his/her/their images and other clinical information to be reported in the journal. The patients understand that their names and initials will not be published and due efforts will be made to conceal their identity, but anonymity cannot be guaranteed.

Financial support and sponsorship

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

Conflicts of interest

There are no conflicts of interest.