Study on Characteristics and Prognosis of Diabetes and Non Diabetes Patients With COVID 19 Among Southern Indian Population
Study on Characteristics and Prognosis of Diabetes and Non Diabetes Patients With COVID 19 Among Southern Indian Population
There were 83,85,440 confirmed cases of COVID-19 worldwide with a mortality rate of 5.4% according to the situation report of the World Health Organisation on June 19, 2020. In India there were 3,95,048 confirmed cases of COVID-19 with a mortality rate of 3.3%. In Tamil Nadu there were 54,449 confirmed cases of COVID-19 with a mortality rate of 1.2% according to the report of Ministry of Health and Family Welfare, Government of India on June 19, 2020.
COVID-19 infection is a double challenge for people with diabetes. India has a large number of persons with diabetes (more than 77 million). Recent studies have reported rising prevalence both in the urban and rural populations. The incidence of type 2 diabetes (T2D) also shows an increasing trend in the last few decades. Mortality seems to be threefold higher in people with diabetes when COVD-19 coexists when compared with mortality due to COVID-19 without comorbidities.
Yang et al noted that among 52 intensive care patients who had COVID 19 infection, 22% had diabetes among the non-survivors. In a study of 173 patients with severe disease, 16.2% had diabetes, and in another study of 140 hospitalized patients, 12% had diabetes. Li et al compared intensive care and non-intensive care patients who had COVID-19. They showed a twofold increase in the incidence of diabetes in intensive care patients.
In addition to diabetes; the other common co-morbidities present in COVID 19 patients were hypertension (20%), cardiovascular disease (16%), and lung disease (6%). In this context, patients with diabetes have been listed as people with higher severity for COVID-19 by several health authorities. However, precise data regarding patients with and without diabetes having COVID-19 infection are still lacking. Moreover, the relationship between diabetes and the severity of COVID-19 remains unknown. In this study, we intend to identify the disease severity and mortality in people with and without diabetes admitted for COVID-19 in southern India.
The following data from a person tested positive for COVID 19 and hospitalized will be collected. Patient's anthropometry (height in cms, weight in kgs and body mass index in kg/m2), blood pressure, symptoms of COVID-19 (fever, fatigue, cough, cephalalgia, dyspnoea, rhinitis, pharyngeal symptoms, ageusia, anosmia, digestive disorders), history of smoking, hypertension, dyslipidemia, microvascular (retinopathy, nephropathy and neuropathy), macrovascular (coronary artery disease, cerebrovascular disease and peripheral vascular disease) complications and other co morbid conditions will be recorded. Fasting blood glucose, HbA1c and any other relevant investigations if available and treatment for COVID-19 and other co morbid conditions will be recorded.
Details of patients developing new symptoms, shifted to ICU, intubated or died during the course of treatment will be recorded. Appearance of any complication during the stay at hospital will be recorded. The changes in the treatment pattern during the course of the disease will also be noted.
The registry will be fully anonymised and statistician will have no access to patients' personal identifiers. All "investigators" will have to register before entering data in the registry. Data about clinical observations for the individual patient will be entered by clinicians or by authorised research personnel of the care team in the web registry.
Patients' name, date of birth, date of death, residential postal code, hospital number will be fully anonymised at source. In no circumstances, patients' identifiable data be available to anyone outside their own care teams or authorised local administration/research personnel. Patient data will not at any stage will be in identifiable form by the registry managers. The data to be collected from the patients are mentioned in the visit chart.
Inclusion Criteria:
Exclusion Criteria:
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