Pattern In Diabetic Patients Research Articles

Coronary Artery Patterns in Diabetic Patients Undergoing Diagnostic Coronary Angiography-Data from a Major Cardiac Center in Yemen

Coronary Artery Patterns in Diabetic Patients Undergoing Diagnostic Coronary Angiography-Data from a Major Cardiac Center in Yemen

Neovascularization restructuring patterns in diabetic patients with coronary in stent restenosis an in-vivo optical coherence tomography study

Abstract Background Patients with diabetes mellitus (DM) have an increased risk of in stent restenosis (ISR). Neovascularization (NV) is considered as a unique phathophysiological factor of ISR in diabetic patients. However, the structures of in vivo human coronary NV and their relationship with ISR, especially in diabetic patients remain unclear. In this study, we aimed to investigate the NV structure differentiation between patients with and without DM after coronary stent implantation using optical coherence tomography (OCT). Methods We included 136 patients with ISR (70 patients in DM group and 66 patients in non-DM group) who underwent optical coherence tomography during coronary angiography follow-up. NVs were manually segmented and three-dimensional (3D) rendering of OCT images was performed. NVs >1 mm were classified into longitudinal running and coral tree types according to their 3D structures. Results The popularity of the coral tree pattern NV in the DM group was 2.14-fold higher than in the non-DM group(p=0.012). 47.14% of patients in the DM group and 51.51% of patients in the non-DM group presented longitudinal NV (p = 0.610). The number of coral tree NV was relatively higher in DM patients than in the non-DM patients (p=0.019). However, the number of longitudinal NV showed no difference between the two group (p=0.872). The normalized NV volume of the DM group was significantly larger than the non-DM group (p=0.008). Normalized NV volume and DM were risk factors for coral tree NV formation in ISR lesions after adjustment for other factors. Conclusions NV with particular restructuring patterns, including longitudinal running and coral tree patterns, could be found in ISR lesions. NV with a coral tree pattern, which is leakier and more immature, is more frequently found in patients with DM. Accurate and feasible imaging modalities for NV might offer promising opportunities to evaluate NV and prevent progression of ISR in diabetic patients.Longitudinal running NV by OCT in neointA coral tree pattern NV in the non-calci

An effective rule- and network-based approach for identification of gender- and age-dependent comorbidity patterns in diabetic patients

An effective rule- and network-based approach for identification of gender- and age-dependent comorbidity patterns in diabetic patients

Microbial Profile and Antibiotic Susceptibility Pattern in Diabetic Patients with Mild, Moderate, and Severe Foot Infections in Tehran.

It is estimated that 10-25% of diabetic patients will encounter diabetic foot ulcers (DFU) during their lifetime. This study evaluated the microbiology of DFUs and determined the antibiotic resistance pattern of bacterial isolates based on the severity of wounds and infections in different grades of ulcer. The specimens were collected from115 diabetic foot infections (DFI) deep tissue by needle aspiration and biopsy. The aerobic and anaerobic cultures and antimicrobial susceptibility testing were carried out. The presence of resistance genes including metallo-beta-lactamases (MBL), extended-spectrum β-lactamase (ESBL), ermA, ermC, and mecA was also determined. A total of 222 microorganisms were isolated. The prevalence of poly-microbial infections was 69.6%. Bacterial isolates comprised 64.2% Gram-positive bacteria (GPB), 33.5% Gram-negative bacteria (GNB), and five isolates of anaerobic bacteria were also detected. The most prevalent GPB and GNB were Staphylococcus spp. (52.2%) and Escherichia coli (33.3%), respectively. The prevalence of poly-microbial infections and GNB was positively associated with increased grades of Wagner and IDSA classifications. Among Staphylococcus aureus isolates, resistance to clindamycin (73.5%), ciprofloxacin (70.6%), and erythromycin (70.6%) were noticeable. GNB was also highly resistant to cephalosporins and ciprofloxacin. ESBL genes were detected in approximately 40% of isolates of Enterobacteriaceae. The prevalence of ermA, ermC, and mecA genes in S. aureus isolates were 8.8%, 32.3%, and 14.7%, respectively. In conclusion, our data suggest that GPBs are the most common isolates from DFIs. Furthermore, with the development of wounds and infection, the prevalence of GNB in DFIs are increased.

The role of microRNAs in the pathophysiology, diagnosis, and treatment of diabetic cardiomyopathy.

Diabetic cardiomyopathy (DCM) is an end-point macrovascular complication associated with increased morbidity and mortality in 12% of diabetic patients. MicroRNAs (miRNAs) are small noncoding RNAs that can act as cardioprotective or cardiotoxic agents in DCM. We used PubMed as a search engine to collect and analyse data in published articles on the role of miRNAs on the pathophysiology, diagnosis and treatment of DCM. MiRNAs play an essential role in the pathophysiology, diagnosis and treatment of DCM due to their distinct gene expression patterns in diabetic patients compared to healthy individuals. Advances in gene therapy have led to the discovery of potential circulating miRNAs, which can be used as biomarkers for DCM diagnosis and prognosis. Furthermore, targeted miRNA therapies in preclinical and clinical studies, such as using miRNA mimics and anti-miRNAs, have yielded promising results. Application of miRNA mimics and anti-miRNAs via different nanodrug delivery systems alleviate hypertrophy, fibrosis, oxidative stress and apoptosis of cardiomyocytes. MiRNAs serve as attractive potential targets for DCM diagnosis, prognosis and treatment due to their distinctive expression profile in DCM development.

Finger and palmar dermatoglyphics in diabetic subjects: a study in a Nigeria teaching hospital

<p><strong>Background</strong>: The aim of this study is to evaluate digito-palmer print among diabetic patients visiting Irrua specialist teaching hospital (ISTH), Irrua Edo State, Nigeria.</p><p><strong>Methods</strong>: Using standard procedures of the ink method, the finger prints of both hands were obtained and palm photographed were taken from clinically diagnosed diabetic patients. The data were analyzed using SPSS (version 21) and results presented in tables.</p><p><strong>Results</strong>: The mean age of the patients was 59.64±9.73 years with 64% females. In the right hand the arch finger print was prevalent on the thumb and loop on the little, middle and ring fingers. In the left hand, the arch print was prevalent on the thumb, index and middle fingers. There was no significance between gender on the distribution of the various finger print patterns except in the right middle finger where females were significantly more likely (p<0.05) to present the loop finger print. The 310-palm print was prevalent in the right and left hands of the diabetic patients with 60% chances of symmetric. Female subjects were more likely to present the 310-palm print compare with male in both hands. The 311 point of origin, intercept and cross (PIC) was absent in the right palm of the male and absent on the left palm of the female.</p><p><strong>Conclusions</strong>: It appears that there exists a variation in the dermatoglyphic patterns in diabetic patients. However, there is a need for larger population-based studies to standardize the parameters and translate the findings into clinical and public health practice.</p>

Coronary Artery Disease Patterns in Diabetic Patients

Coronary Artery Disease Patterns in Diabetic Patients

Pulmonary Spirometry in Type 2 Diabetics in Baghdad Teaching Hospital

Background: Diabetes mellitus is a serious progressive condition associated with multisystemic involvement with a number of chronic complications due to macrovascular and microvascular damage. Pulmonary involvement is not studied extensively and is not explained by factors that influence lung function. Objective: The aim of this article is to study the effects of type 2 diabetes on lung function and delineate the association between lung function impairment and duration of the disease. Materials and Methods: This cross-sectional study was conducted in Baghdad Teaching Hospital. Ninety-one (91) type 2 diabetics with 56 control subjects were included in this study between March 2020 and June 2021. Both groups are matched by age, sex, height, and weight and are met with exclusion criteria. Spirometry was done on an electronic spirometer (videography U.K. 1982) for both groups with the following parameters: forced vital capacity (FVC), force expiratory volume in 1 s (FEV1), FEV1/FVC, and peak expiratory flow rate (PEFR). Statistical methods compared the results. Results: Type 2 diabetic patients show a significant reduction in FVC, FEV1, and PEFR relative to their matched controls (P < 0.05). However, there was no significant change in the FEV1/FVC ratio between the groups, meaning a restrictive pattern in diabetic patients. Conclusion: This study showed that type 2 diabetics had impaired lung function as evidenced by reduced FVC, FEV1, and PEFR as part of chronic complications of diabetes and showed a progressive decline in parameter with increased duration of the disease.

Diabetes Mellitus and Dyslipidemia- A Detailed Analysis

Background: Diabetic atherosclerosis is a heterogeneous condition, and that dyslipidemia is only one aspect of the pathophysiology. However, dyslipidemia is the most readily measured and, at the present time, the most readily treated aspect of the problem. The occurrence of dyslipidemia can be reduced by good glycemic control. However poor awareness and other socio-economic factors is a major concern and pose a major hindrance in controlling blood sugar levels.
 Aims and Objective: This study was conducted to study the dyslipidemia pattern in diabetic patients and its association with other factors.
 Materials and Methods: The study included 500 subjects and was divided into two groups: Group 1(Diabetic) included 276 patients and Group 2 (Non-diabetic) included 224 patients. The study patients were screened using a pretested structured questionnaire. Fasting plasma glucose and serum lipid profile (cholesterol, TG, HDL) were estimated in automated analyzer (Erba Manheim EM 200).
 Results: In the current study, all characteristics of diabetes were correlated with each parameter and it was found that disproportionate body mass index, high waist girth was correlated with incidence of dyslipidemia. The education levels and financial background of the subjects were also studied and it was found to correlate well with diabetic dyslipidemia.
 Conclusion: Early diagnosis and treatment of dyslipidemia in diabetic patients can reduce the morbidity and mortality due to the disease.

Circadian Pattern of Acute Myocardial Infarction and Atrial Fibrillation in a Mediterranean Country: A study in Diabetic Patients.

Background and objectives: The circadian pattern seems to play a crucial role in cardiovascular events and arrhythmias. Diabetes mellitus is a complex metabolic disorder associated with autonomic nervous system alterations and increased risk of microvascular and macrovascular disease. We sought to determine whether acute myocardial infarction (AMI) and atrial fibrillation (AF) follow a circadian pattern in diabetic patients in a Mediterranean country. Materials and Methods: This retrospective study included 178 diabetic patients (mean age: 67.7) with AMI or AF who were admitted to the coronary care unit. The circadian pattern of AMI and AF was identified in the 24-h period (divided in 3-h and 1-h intervals). Patients were also divided in 3 groups according to age; 40–65 years, 66–79 years and patients older than 80 years. A chi-square goodness-of-fit test was used for the statistical analysis. Results: AMI seems to occur more often in the midnight hours (21:00–23:59) (p < 0.001). Regarding age distribution, patients between 40 and 65 years were more likely to experience an AMI compared to other age groups (p < 0.001). Autonomic alterations, working habits, and social reasons might contribute to this phenomenon. AF in diabetic patients occurs more frequently at noon (12:00–14:59) (p = 0.019). Conclusions: Diabetic patients with AMI and AF seem to follow a specific circadian pattern in a Mediterranean country, with AMI occurring most often at midnight hours and AF mostly at noon. Autonomic dysfunction, glycemic fluctuations, intense anti-diabetic treatment before lunch, and patterns of insulin secretion and resistance may explain this pattern. More studies are needed to elucidate the circadian pattern of AMI and AF in diabetic patients to contribute to the development of new therapeutic approaches in this setting.

Altered spontaneous brain activity patterns in diabetic patients with vitreous hemorrhage using amplitude of low‑frequency fluctuation: A resting‑state fMRI study.

The aim of the present study was to assess the local character of spontaneous brain activity in type-2 diabetic patients with vitreous hemorrhage (VH) and its relationship with clinical features via the amplitude of low-frequency fluctuations (ALFF) method. A total of 31 subjects (15 females and 16 males) with type-2 diabetic VH and 31 normal controls (NCs) with similar characteristics (sex, age and educational level) were recruited in the present study. All subjects underwent resting-state functional magnetic resonance imaging scans. The local character of spontaneous brain activity was assessed using the ALFF method. The difference between the type-2 diabetic patients with VH and NCs was determined using receiver operating characteristic curves. Pearson's correlation analysis was applied to evaluate the relationship between the mean ALFF values of specific brain areas and related clinical manifestations in type-2 diabetic patients with VH. The ALFF values of type-2 diabetic patients with VH were significantly increased in the right and left cerebellum posterior lobes, left cerebellum posterior lobe/left lingual gyrus and bilateral superior frontal gyrus/left postcentral gyrus, compared with those obtained for NCs (P<0.05). By contrast, these values were significantly decreased in the left and right middle frontal gyri, right medial frontal gyrus/left anterior cingulate, right inferior frontal gyrus, right superior frontal gyrus, right middle frontal gyrus, right superior frontal gyrus/middle frontal gyrus and left middle frontal gyrus of the former group compared with the NCs (P<0.05). Nevertheless, there was no significant association between the mean ALFF values and clinical characteristics in different brain areas. Unusual spontaneous activity occurred in multiple brain areas, which may suggest the neuropathological mechanisms of visual impairment in type-2 diabetic patients with VH.

Deep Learning Classification for Diabetic Foot Thermograms.

According to the World Health Organization (WHO), Diabetes Mellitus (DM) is one of the most prevalent diseases in the world. It is also associated with a high mortality index. Diabetic foot is one of its main complications, and it comprises the development of plantar ulcers that could result in an amputation. Several works report that thermography is useful to detect changes in the plantar temperature, which could give rise to a higher risk of ulceration. However, the plantar temperature distribution does not follow a particular pattern in diabetic patients, thereby making it difficult to measure the changes. Thus, there is an interest in improving the success of the analysis and classification methods that help to detect abnormal changes in the plantar temperature. All this leads to the use of computer-aided systems, such as those involved in artificial intelligence (AI), which operate with highly complex data structures. This paper compares machine learning-based techniques with Deep Learning (DL) structures. We tested common structures in the mode of transfer learning, including AlexNet and GoogleNet. Moreover, we designed a new DL-structure, which is trained from scratch and is able to reach higher values in terms of accuracy and other quality measures. The main goal of this work is to analyze the use of AI and DL for the classification of diabetic foot thermograms, highlighting their advantages and limitations. To the best of our knowledge, this is the first proposal of DL networks applied to the classification of diabetic foot thermograms. The experiments are conducted over thermograms of DM and control groups. After that, a multi-level classification is performed based on a previously reported thermal change index. The high accuracy obtained shows the usefulness of AI and DL as auxiliary tools to aid during the medical diagnosis.

A study on evaluation of prescribing pattern in diabetic patients at tertiary care Hospital

Diabetes could be a chronic, metabolic illness characterised by elevated levels of blood sugar, that leads over time to serious harm to the guts, blood vessels, eyes, kidneys, and nerves. The foremost common is type two polygenic disease, typically in adults, that happens once the body becomes immune to hypoglycemic agent or does not build enough hypoglycemic agent. Within the past 3 decades the prevalence of type two polygenic disease has up dramatically in countries of all financial gain levels. The main aim of the study provides overview prevalence, drug utilization by using WHO-INRUD (International Network of Rational Use of Drugs) drug core indicators in diabetic patients at tertiary care hospital. The drug utilization studies are focused to study prescription habits of medical practitioners. These studies aims to analyse the type of drugs prescribed, their dosing schedule, and the adequacy of the prescription for a specific diagnosis. The obtained data during the ward rounds were thoroughly analysed to evaluate rationality in drug using. In our study a total of 100 prescriptions were analysed and the most prescribed therapy was Insulin therapy (63%). When coming to oral hypoglycaemic drugs Sulphonylureas (7%) and Biguanides (7%) were more frequently prescribed which indicates their significant role in pharmacotherapy of diabetes, most of the prescriptions were prescribed in combinations in which dual therapy (87%) was most prescribed followed by triple therapy (13%). All the prescriptions were analysed for their compliance to WHO drug core indicators. The results implies that there is an increased need for prescribing generically as it is cost effective and has less potential for errors. Therefore it is advisable for all prescribers to prescribe generically.

Prediction and Diagnosis of Diabetes Mellitus Using a Water Wave Optimization Algorithm

Data mining is an appropriate way to discover information and hidden patterns in large amounts of data, where the hidden patterns cannot be easily discovered in normal ways. One of the most interesting applications of data mining is the discovery of diseases and disease patterns through investigating patients' records. Early diagnosis of diabetes can reduce the effects of this devastating disease. A common way to diagnose this disease is performing a blood test, which, despite its high precision, has some disadvantages such as: pain, cost, patient stress, lack of access to a laboratory, and so on. Diabetic patients’ information has hidden patterns, which can help you investigate the risk of diabetes in individuals, without performing any blood tests. Use of neural networks, as powerful data mining tools, is an appropriate method to discover hidden patterns in diabetic patients’ information. In this paper, in order to discover the hidden patterns and diagnose diabetes, a water wave optimization(WWO) algorithm; as a precise metaheuristic algorithm, was used along with a neural network to increase the precision of diabetes prediction. The results of our implementation in the MATLAB programming environment, using the dataset related to diabetes, indicated that the proposed method diagnosed diabetes at a precision of 94.73%,sensitivity of 94.20%, specificity of 93.34%, and accuracy of 95.46%, and was more sensitive than methods such as: support vector machines, artificial neural networks, and decision trees.

Diabetes mellitus and dyslipidemia: A detailed analysis

Introduction: Diabetic atherosclerosis is a heterogeneous condition, and that dyslipidemia is only one aspect of the pathophysiology. However, dyslipidemia is the most readily measured and, at the present time, the most readily treated aspect of the problem. The occurrence of dyslipidemia can be reduced by good glycemic control. However poor awareness and other socio-economic factors is a major concern and pose a major hindrance in controlling blood sugar levels. Objective: This study was conducted to study the dyslipidemia pattern in diabetic patients and its association with other factors. Methods: The study included 500 subjects and was divided into two groups: Group 1(Diabetic) included 276 patients and Group 2 (Non-diabetic) included 224 patients. The study patients were screened using a pretested structured questionnaire. Fasting plasma glucose and serum lipid profile (cholesterol, TG, HDL) were estimated in automated analyzer (Erba Manheim EM 200). Results: In the current study, all characteristics of diabetes were correlated with each parameter and it was found that disproportionate body mass index, high waist girth was correlated with incidence of dyslipidemia. The education levels and financial background of the subjects were also studied and it was found to correlate well with diabetic dyslipidemia. Conclusion: Early diagnosis and treatment of dyslipidemia in diabetic patients can reduce the morbidity and mortality due to the disease.

Clinical Outcome Pattern in Diabetic Patients with Complicated Urinary Tract Infections Treated with Ceftriaxone-Sulbactam-EDTA. A Retrospective Study

Clinical Outcome Pattern in Diabetic Patients with Complicated Urinary Tract Infections Treated with Ceftriaxone-Sulbactam-EDTA. A Retrospective Study

Principal component analysis of dynamic fluorescence images for diagnosis of diabetic vasculopathy.

Indocyanine green (ICG) fluorescence imaging has been clinically used for noninvasive visualizations of vascular structures. We have previously developed a diagnostic system based on dynamic ICG fluorescence imaging for sensitive detection of vascular disorders. However, because high-dimensional raw data were used, the analysis of the ICG dynamics proved difficult. We used principal component analysis (PCA) in this study to extract important elements without significant loss of information. We examined ICG spatiotemporal profiles and identified critical features related to vascular disorders. PCA time courses of the first three components showed a distinct pattern in diabetic patients. Among the major components, the second principal component (PC2) represented arterial-like features. The explained variance of PC2 in diabetic patients was significantly lower than in normal controls. To visualize the spatial pattern of PCs, pixels were mapped with red, green, and blue channels. The PC2 score showed an inverse pattern between normal controls and diabetic patients. We propose that PC2 can be used as a representative bioimaging marker for the screening of vascular diseases. It may also be useful in simple extractions of arterial-like features.

Heterogeneous choroidal thickness pattern in diabetic patients without diabetic retinopathy

PurposeThe authors intend to present an analysis and comparison of the choroidal thickness in more distant superior regions. Choroidal thickness is increased in a heterogeneous pattern superiorly to the fovea in diabetic patients without diabetic retinopathy.MethodsObservational case‐control study of 60 eyes of 60 patients with diabetes mellitus type 2 without diabetic retinopathy. A control group of 31 eyes of 31 patients without diabetes with similar demographic features was also created. All the patients were recruited from the same outpatient clinic. Enhanced depth imaging spectral‐domain optical coherence tomography (EDI SD‐OCT SPECTRALIS®) was performed and high‐resolution macular scans were obtained. Choroidal thickness was evaluated 2000 μm superiorly to the fovea by manual layer segmentation. Previous studies have validated the validity of using a manual layer segmentation procedure in OCT. Statistical analysis was done with SPSS Statistics. A p value &lt;0.05 was considered statistically significant.ResultsDiabetic patients were in average 67.0 ± 9.6 years old and 56.7% were male. Average choroidal thickness 2000 μm superiorly to the fovea was 287.77 ± 74.32 μm in diabetic patients and 249.81 ± 53.96 μm in non‐diabetic patients. There was a significant increase in choroidal thickness in diabetic patients when compared to non‐diabetic patients (T‐student, p = 0.014).ConclusionsChoroidal thickness can be accurately measured using high‐definition macular OCT scans. This study documented structural differences in the choroid associated with diabetes mellitus type 2 that are not only present in the central foveal area as reported in previous studies. Diabetes Mellitus is associated with multiple microvascular dysfunctions that are probably coupled with choroidal vascular modifications that induce changes in thickness.

Glycemic Pattern in Diabetic Patients on Hemodialysis: Continuous Glucose Monitoring (CGM) Analysis

Background/Aims: Recent evidences suggest that hemodialysis (HD) induces glycemic variations in diabetic patients. Continuous glucose monitoring (CGM) devices measure interstitial glucose in a ‘Holter-like' manner thereby improving the glycemic control assessment method. Methods: A CGM device (Medtronic iPRO) was used on 12 diabetic patients with chronic HD for 6 days to assess intra- and extra-dialytic interstitial glucose. Results: In all enrolled patients, HD was associated with a decrease of interstitial glucose values. Intradialytic glucose nadir was 79 mg/dl and it was reached at the third hour after the beginning of the session. At the end of HD, interstitial glucose increased in all patients and a glycemic peak (187 mg/dl) occurred after an average time of 2.5 h. No episodes of nocturnal hypoglycemia occurred. Conclusion: HD is associated with significant intradialytic reduction of glycemia and postdialytic hyperglycemia. CGM devices result in better monitoring of glycemic trends in diabetic patients on chronic HD and could improve insulin management.

English

The present study is an attempt to understand the spectrum of pleuropulmonary infections in Diabetes mellitus patients. Majority of patients with pleuropulmonary infections in this study have Type 2 DM and there is slight preponderance of males over females. In our study, majority number of patients (accounting for 38%) were diagnosed with diabetes mellitus at the time of diagnosis of pleuropulmonary infection. The peak incidence of pleuropulmonary infections in this study were in the age group of third decade to fifth decade. Thus it would be prudent to screen all patients in this age group presenting with respiratory infection, for diabetes mellitus. Tuberculosis was the most common pleuropulmonary infection in diabetic patients in this study accounting for 59% of the cases followed by bacterial pneumonia and lung abscess. Majority of pleuropulmonary infections of non tuberculous etiology were due to gram negative organisms like Pseudomonas, Klebsiella, H.influenzae (42%) and gram positive organisms like Staphylococcus and Streptococcus (27%). The application of this knowledge is very important in tailoring early appropriate antibiotic therapy for diabetic patients where culture facilities are not available, as even a short delay in initiating treatment may lead to rapid progression of infection leading to increased mortality and morbidity. B/L extensive lesion was the most common radiological pattern in diabetic patients with PTB while consolidation and lung abscess were the commonest patterns in diabetic patients with non tuberculous pleuropulmonary infections. Pulmonary Tuberculosis tends to occur with increased severity in diabetics as evidenced by the occurrence of B/L extensive lesion in around 40% of cases in our study. Further to support this, bacillary loads were high among diabetics with poor glycemic control (as assessed by increased grading of sputum positivity). Risk stratification of bacterial pneumonia in diabetes using CURB 65 scoring system shows that around 57% of patients were categorized under group 2 and group 3 suggesting that bacterial infections tend tobe more aggressive in diabetics especially those with uncontrolled hyperglycemia. Association of pulmonary infections with pleural involvement occurs in about 25% of diabetics demanding protracted course of