Evaluation of Dermatoglyphic Features of Type 2 Diabetic Patients as Compared to Non-Diabetics Attending Hospitals in Southern Ethiopia

Tadesse, Amanuel F.; Gebremickael, Abinet; Mengesha, Melkamu Merid; Wondmagegn, Habtamu; Melaku, Tesfaye; Ayele, Tsegazeab; Meskele, Simeon; Esubalew, Habtamu; Balta, Asaminew Birhanu

doi:10.2147/dmso.s356728

Cited by 3 publications

(3 citation statements)

References 11 publications

(22 reference statements)

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“…In the current study, the most predominant fingerprint pattern were loops (Ulnar + Radial loops) for both diabetic and control groups at 58%. This conforms to findings of other authors who noted that loops were the most frequent patterns (Dhumal et al, 2021;Okeke et al, 2018;Sudharson et al, 2020;Tadesse et al, 2022). The general international distribution of fingerprint patterns as recorded in the literature (Mensvoort, 2013) also notes that loops are the most predominant.…”

Section: Discussionsupporting

confidence: 91%

Finger print patterns distribution among diabetics and non-diabetics in western Uganda population

Marera

2023

Anat. J. Afr.

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Background: Dactyloscopy is a branch of dermatoglyphics (the study of epidermal ridges) which involves assessment and classification of fingerprint patterns for identification. All fingerprint patterns are laid down permanently from the third month of the intra-uterine life and they remain unchanged throughout the life. This is also the time when all organs in the body are finalizing their development. Therefore, a positive association of the dermatoglyphic features with different diseases like diabetes, mongolism, schizophrenia and leprosy have been well documented in the literature. The aim of the present study was to evaluate the dermatoglyphic patterns and the specific variations which may be used as a valuable diagnostic tool for early detection of diabetes mellitus. Methods: This was a prospective cross-sectional study, a total of 150 diabetic subjects and 150 non- diabetics (control) were selected from the KIUTH Western Uganda and their fingerprints were taken by the Indian ink method. The print patterns including whorls, arches, ulnar and radial loops were analysed and the variations were cross-tabulated between sex, the side of the hand and pattern distribution indexes. Data was analysed using SPSS version 26 and Dankmeijer's index and Furuhata's index were used to assess variability of the fingerprint patterns. Chi square tests was used to test for significance in variations at a confidence interval of 95%. Results and conclusion: Ulnar loops were the most predominant patterns among diabetic subjects at 35.2% followed closely by whorls at 35.1%. The most common pattern were whorls found in both hands of females at 21% (315/1500), whilst the most common pattern for male group were whorls at 17.5% (262). However, some fingers such as the ring finger completely lacked an arch pattern in both groups. The increase in arches was strongly supported by a significant increase in Dankmeijer’s index. The presence of high number of ulnar loops can therefore maybe used as an early indicator of type two diabetes.

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Section: Discussionsupporting

confidence: 91%

Finger print patterns distribution among diabetics and non-diabetics in western Uganda population

Marera

2023

Anat. J. Afr.

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“…The a-b ridge count was significantly higher in males than in female diabetics, but in our study, we did not observe any statistically significant difference in a-b ridge count between male and female diabetics. The difference in features was seen among two different regional area populations as Bala et al, 18 performed the study in the hilly region of Sikkim and our study population is Eastern region of India.…”

Section: Discussionmentioning

confidence: 80%

“…They did not report the statistical significance of these changes. Tadesse et al, 18 observed more loop patterns in diabetic males than in females. In our study, the most common pattern was the ulnar loop followed by the whorl pattern.…”

Section: Discussionmentioning

confidence: 93%

Sexual dimorphism of dermatoglyphic features in Type 2 diabetes mellitus patients of West Bengal: A cross-sectional study

Sarkar,

Shahin Salma Khatun,

Pallab Kumar Saha

et al. 2024

Asian J Med Sci

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Background: Dermatoglyphics is the study of epidermal ridge patterns on the fingers, palms, and soles. Correlation of dermatoglyphic patterns with many chromosomal abnormalities and genetic predisposing diseases such as diabetes mellitus, hypertension, schizophrenia, and bronchial asthma is evidenced by many researchers. Literature on sexual dimorphism of dermatoglyphic patterns revealed it as an important characteristic feature. Aims and Objectives: The aim of the study is to study the variance of ridge patterns among male and female patients of Type 2 diabetes mellitus patients of West Bengal and determine the sex-specific digital and palmar ridge patterns in Type 2 Diabetes mellitus. Materials and Methods: A cross-sectional study has been done on 100 male and 100 female Type 2 diabetes mellitus patients. Digital and palmar prints were taken by the traditional ink method. Digital ridge pattern, pattern intensity index, total finger ridge count (TFRC), absolute finger ridge count (AFRC), and a-b ridge count were studied. The data on these patterns was recorded and statistically analyzed by Chi-square test and Student’s t-test. Results: The frequency of ulnar loop is higher in female diabetics in comparison to male diabetics. Statistically significant increase in mean TFRC and mean AFRC is seen in male diabetics. Conclusion: Our study exhibits that dermatoglyphic pattern significantly differs in male and female diabetics. The knowledge and reference range of dermatoglyphic parameters among male and female diabetics are essential in the use of this study as a screening tool or diagnostic tool in Type 2 diabetes mellitus.

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Intelligent Framework for Early Prediction of Type – II Diabetes by Accelerating Palm Print Images using Graph Data Science

Rai,

Pakkala

et al. 2023

2023 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics (DISCOVER)

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Evaluation of Dermatoglyphic Features of Type 2 Diabetic Patients as Compared to Non-Diabetics Attending Hospitals in Southern Ethiopia

Cited by 3 publications

References 11 publications

Finger print patterns distribution among diabetics and non-diabetics in western Uganda population

Finger print patterns distribution among diabetics and non-diabetics in western Uganda population

Sexual dimorphism of dermatoglyphic features in Type 2 diabetes mellitus patients of West Bengal: A cross-sectional study

Intelligent Framework for Early Prediction of Type – II Diabetes by Accelerating Palm Print Images using Graph Data Science

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