Prevalence of sarcopenia and its determinants in people with type 2 diabetes: Experience from a tertiary care hospital in north India.

OBJECTIVES: Changes in skeletal muscle mass and quality are associated with type 2 Diabetes (T2D) and its complications. We evaluated the prevalence of sarcopenia in patients with T2D and its association with various anthropometric and metabolic parameters. METHODS: A total of 229 patients with T2D, ≥20-60 years, were screened for sarcopenia using handgrip strength (HGS) by dynamometer, physical performance test (by Short Physical and chair stand test), and height-adjusted appendicular skeletal muscle index (ASMI) by Dual Energy X-ray Absorptiometry (DXA) applying Asian Working Group on Sarcopenia (AWGS). Multiple logistic regressions were performed to identify the factors associated with sarcopenia. RESULTS: The mean age was 46.2 ± 7.4 years with 55% being women. The prevalence of low HGS, poor physical performance, low ASMI, possible sarcopenia, sarcopenia, and severe sarcopenia was 16.2%, 39.3%, 33%, 43%, 18.8%, and 6.1%, respectively. Age >45 years and use of >2 oral hypoglycaemic agents (OHA's) were risk factors for low HGS (OR:3.51, 95%CI = 1.5-8.3) and low ASMI (OR:2.40, 95%CI = 1.05, 5.49, p-0.04), respectively. Female sex (OR:3.3 1.8-6.1 p < 0.01), age >45 years (OR:2.12, 95% CI = 1.2-3.8 p-0.012) and liver fibrosis (OR: 2.12, 95% CI = 1.01-4.46 p-0.048) were independently associated with poor performance. No association was found with HbA1c, dyslipidaemia, albuminuria, hypertension, or duration of diabetes and sarcopenia. CONCLUSION: Sarcopenia is becoming increasingly recognized as a significant complication in younger individuals with T2D, and poor physical performance plays a vital role in its development. The prevalence of sarcopenia rises with advancing age, underscoring the importance of early intervention to address this condition.

A study on the morbid histopathological changes in COVID-19 patients with or without comorbidities using minimally invasive tissue sampling.

COVID-19 causes morbid pathological changes in different organs including lungs, kidneys, liver, and so on, especially in those who succumb. Though clinical outcomes in those with comorbidities are known to be different from those without-not much is known about the differences at the histopathological level. To compare the morbid histopathological changes in COVID-19 patients between those who were immunocompromised (Gr 1), had a malignancy (Gr 2), or had cardiometabolic conditions (hypertension, diabetes, or coronary artery disease) (Gr 3), postmortem tissue sampling (minimally invasive tissue sampling [MITS]) was done from the lungs, kidney, heart, and liver using a biopsy gun within 2 hours of death. Routine (hematoxylin and eosin) and special staining (acid fast bacilli, silver methanamine, periodic acid schiff) was done besides immunohistochemistry. A total of 100 patients underwent MITS and data of 92 patients were included (immunocompromised: 27, malignancy: 18, cardiometabolic conditions: 71). In lung histopathology, capillary congestion was more in those with malignancy, while others like diffuse alveolar damage, microthrombi, pneumocyte hyperplasia, and so on, were equally distributed. In liver histopathology, architectural distortion was significantly different in immunocompromised; while steatosis, portal inflammation, Kupffer cell hypertrophy, and confluent necrosis were equally distributed. There was a trend towards higher acute tubular injury in those with cardiometabolic conditions as compared to the other groups. No significant histopathological difference in the heart was discerned. Certain histopathological features were markedly different in different groups (Gr 1, 2, and 3) of COVID-19 patients with fatal outcomes.

Clinico-pathological features in fatal COVID-19 infection: a preliminary experience of a tertiary care center in North India using postmortem minimally invasive tissue sampling.

OBJECTIVES: To study the histopathology of patients dying of COVID-19 using post-mortem minimally invasive sampling techniques. METHODS: This was a single-center observational study conducted at JPNATC, AIIMS. Thirty-seven patients who died of COVID-19 were enrolled. Post-mortem percutaneous biopsies were taken from lung, heart, liver, kidney and stained with hematoxylin and eosin. Immunohistochemistry was performed using CD61 and CD163. SARS-CoV-2 virus was detected using IHC with primary antibodies. RESULTS: The mean age was 48.7 years and 59.5% were males. Lung histopathology showed diffuse alveolar damage in 78% patients. Associated bronchopneumonia was seen in 37.5% and scattered microthrombi in 21% patients. Immunopositivity for SARS-CoV-2 was observed in Type II pneumocytes. Acute tubular injury with epithelial vacuolization was seen in 46% of renal biopsies. Seventy-one percent of liver biopsies showed Kupffer cell hyperplasia and 27.5% showed submassive hepatic necrosis. CONCLUSIONS: Predominant finding was diffuse alveolar damage with demonstration of SARS-CoV-2 protein in the acute phase. Microvascular thrombi were rarely identified in any organ. Substantial hepatocyte necrosis, Kupffer cell hypertrophy, microvesicular, and macrovesicular steatosis unrelated to microvascular thrombi suggested that liver might be a primary target of COVID-19.

Consensus Statement on Electronic Health Predictive Analytics: A Guiding Framework to Address Challenges.

CONTEXT: The recent explosion in available electronic health record (EHR) data is motivating a rapid expansion of electronic health care predictive analytic (e-HPA) applications, defined as the use of electronic algorithms that forecast clinical events in real time with the intent to improve patient outcomes and reduce costs. There is an urgent need for a systematic framework to guide the development and application of e-HPA to ensure that the field develops in a scientifically sound, ethical, and efficient manner. OBJECTIVES: Building upon earlier frameworks of model development and utilization, we identify the emerging opportunities and challenges of e-HPA, propose a framework that enables us to realize these opportunities, address these challenges, and motivate e-HPA stakeholders to both adopt and continuously refine the framework as the applications of e-HPA emerge. METHODS: To achieve these objectives, 17 experts with diverse expertise including methodology, ethics, legal, regulation, and health care delivery systems were assembled to identify emerging opportunities and challenges of e-HPA and to propose a framework to guide the development and application of e-HPA. FINDINGS: The framework proposed by the panel includes three key domains where e-HPA differs qualitatively from earlier generations of models and algorithms (Data Barriers, Transparency, and ETHICS) and areas where current frameworks are insufficient to address the emerging opportunities and challenges of e-HPA (Regulation and Certification; and Education and Training). The following list of recommendations summarizes the key points of the framework: Data Barriers: Establish mechanisms within the scientific community to support data sharing for predictive model development and testing.Transparency: Set standards around e-HPA validation based on principles of scientific transparency and reproducibility. ETHICS: Develop both individual-centered and society-centered risk-benefit approaches to evaluate e-HPA.Regulation and Certification: Construct a self-regulation and certification framework within e-HPA.Education and Training: Make significant changes to medical, nursing, and paraprofessional curricula by including training for understanding, evaluating, and utilizing predictive models.