Our findings of HRV suggest that in type 2 diabetics with poor glycaemic and good pressure control, hypertension as a co-existing factor does not make significant difference in cardiac dysautonomia emphasizing residual risk despite antihypertensive treatment and need for early HRV screening, strict glycaemic control and other interventions.

Background:Type 2 diabetes mellitus (T2DM) is a proven threat of cardiac dysautonomia with paucity of studies from India. Poor disease control makes it further worse with co-existence of hypertension in majority. Heart rate variability (HRV) is a validated noninvasive tool to assess cardiac autonomic status.Aim:We studied HRV parameters of type 2 diabetics looking for effects of disease control and other co-existing risk factors.Materials and Methods:Ninety-eight hypertensive and forty normotensive under–treatment, Gujarati type 2 diabetics were evaluated for disease control and risk stratification. Five minutes resting, HRV was measured by Variowin HR, software-based instrument, using standard protocols to record time domain, frequency domain, and Poincare plot HRV parameters. They were compared between subgroups for the difference with P < 0.05 defining statistical significance.Results:All HRV parameters were reduced in type 2 diabetics, having mean age 56 years, mean duration 6 years with poor glycemic but comparatively better pressure control. HRV parameters were significantly not different in good compared to poor glycemics or in subjects with optimum pressure control than those without it. Results did not differ significantly, by the presence of individual cardiovascular risk factor in diabetics except resting heart rate.Conclusion:Our findings of HRV suggest that type 2 diabetics with poor glycemic control do not have a significant difference of cardiac dysautonomia by pressure control, glycemic control, and absence of risk cardiovascular factor. It suggests diabetes as a major cause for cardiac dysautonomia, residual risk despite treatment and need for HRV screening, strict glycemic control, and further studies.

Objective About 41 million people aged ≥18 years reported lifetime use of cocaine, and 5.4 million people reported having used cocaine in 2019. We aim to identify trends of cocaine use, manifestations, concomitant drug use, and financial burden on health care among hospitalized patients. Methods We utilized National Inpatient Sample from years 2006-2018. Patients with age ≥18 years, admitted to the hospital with a diagnosis of cocaine abuse, dependence, poisoning, or unspecified cocaine use were included in the study. We used ICD-9 Clinical Modification (CM) and ICD-10-CM codes to retrieve patient samples and comorbid conditions. The primary outcome was the trend in cocaine use among hospitalized patients from the year 2006 to 2018. Cochran-Mantel-Haenszel test was used to assess the significance of trends. Results In the year 2006, the prevalence of cocaine abuse among hospitalized patients was 10,751 per million with an initial decline to 7,451 per million in 2012 and a subsequent increase to 11,891 per million hospitalized patients in 2018 with p =0.01. The majority of patients admitted were older than 50 years (43.27%), and a greater percentage of patients were males. All ethnicities showed a rising trend in the use of cocaine except for Native Americans. Cardiovascular effects, neuropsychiatric and infectious manifestations in hospitalized patients with cocaine abuse showed a consistent increase from year 2006 to 2018 with p <0.001. Conclusions There is a recent uptrend in cocaine use among hospital admissions in the US from 2006 to 2018 with an increased rate of systemic manifestations. This highlights the impact of cocaine use on the health system and the dire need to address this growing problem.

Background and objective In developing countries, the dermatological manifestation of the human immunodeficiency virus (HIV) has a high prevalence. Apart from the systemic infection that ensues HIV, skin manifestations form a major part of the disease burden. They can present with atypical forms, and necessary tools for diagnosis may not be available in rural and remote parts of the country. Hence, they can stay misdiagnosed or undiagnosed, contributing to the morbidity of the patients. We attempted to enumerate the dermatologic opportunistic infections (OIs) in Rajkot city, Gujarat, India, in order to disseminate knowledge regarding the same. Material and methods It is a retrospective observational study. A total of 253 patients under treatment for HIV/acquired immunodeficiency syndrome (AIDS) at the ART Center (anti-retroviral therapy center) from 2011 to 2019 were included. The data recorded in the registry during the above-mentioned period were utilized in the study. The diagnoses of OIs were made clinically by multiple health care providers experienced in the field. Result Two hundred twenty-seven (227) of 253 (89.72%) of the patients had some form of dermatologic OI during the course of their treatment. Overall, fungal infections (33.03%) were most common, followed by bacterial infections (28.18%) and viral (14.55%) infections. Among the non-infectious causes, cheilitis/angular stomatitis topped the list. Among the STDs, herpes was the most common skin manifestation seen with a 10.57% prevalence. The CD4+ cell count for fungal infection ranged from 353-467 and was seen in stage 2 of the disease course. Bacterial infections were seen mainly during the early and middle stages of the disease while viral infections were most prevalent in stage 2 of the disease. Conclusion Skin manifestations can be useful clinical predictors of the disease stage, especially in resource-limited settings and in developing countries. They can present with unusual and atypical forms. Hence, knowledge about the prevalence of these OIs in a particular geographical area can be very useful for physicians in treating them and decreasing the disease burden.

BackgroundLiver transplantation is the life-saving standard of care for those with end-stage liver disease. Unfortunately, many patients on the liver transplant list die waiting. Several studies have demonstrated significant differences based on disparities in race, gender, and multiple socioeconomic factors. We sought to evaluate recent disparities among patients receiving liver transplants using the latest available data from the National Inpatient Sample (NIS), the largest publicly available inpatient care database in the United States. MethodsWe performed an analysis of discharge data from the NIS between 2016 and 2019. We identified adult patients with chronic liver disease who underwent a liver transplant using the International Classification of Diseases, 10th revision (ICD-10) codes. Multivariate logistic regression was used to adjust for differences in race, gender, socioeconomic status, and comorbidities among those who received a liver transplant. ResultsA total of 24,595 liver transplants were performed over the study period. Female gender was independently associated with decreased transplant rates (adjusted odds ratio (AOR) 0.83, 95% confidence interval (CI), 0.78-0.89, P < 0.001). Compared to White patients, Black patients had decreased transplant rates (AOR 0.86, 95% CI, 0.75-0.99, P = 0.034), as did Native Americans (AOR 0.64; 95% CI, 0.42-0.97, P = 0.035). Hispanics and Asian Americans had increased rates of liver transplantation (AOR 1.16, 95% CI 1.02-1.32, P = 0.022, and 1.36, 95% CI 1.11-1.67, P = 0.003; respectively). The increase in income quartile was associated with an incremental increase in transplant rates. Additionally, patients with private insurance had much higher transplant rates compared to those with Medicare (AOR 2.50, 95% CI 2.31-2.70, P < 0.001) while patients without insurance had the lowest rates of transplantation (AOR 0.18, 95% CI 0.12-0.28, P < 0.001). ConclusionsOur analysis demonstrates that race, gender, and other social determinants of health have significant impacts on the likelihood of receiving a liver transplant. Our study, on a national level, confirms previously described disparities in receiving liver transplantation. Patient-level studies are needed to better understand how these variables translate into differing liver transplantation rates.