Background: The prevalence of diabetes mellitus has increased signicantly over the past two decades. Recent estimates project around 285 million people with diabetes around the world presently, and this number is set to increase to 438 million by the year 2030. It became essential to train people with type II diabetes to improve their quality of life in order to manage type II diabetes effectively. Sample: 30 type II diabetes were randomly selected from the Diabetes care centres in Chennai for the assessment of quality of life. Methodolgy: The present study aimed to examine the effect of training programme given to people with type II diabetes on quality of life. The quality of life was assessed using questionnaire “The Quality of Life Scale (QOLS)” by John Flanagan (1970). Paired t- test were used to assess the effectiveness of training programme on quality of life of people with Type II diabetes. Result and Conclusion: The result shows that there was a signicant increase in quality of life of people with type II diabetes due to quality of life enhancement training programme. It was concluded that quality of life training plays a vital role in modifying and improving lifestyle of people with type II diabetes in order to improve adherence to the diabetes treatment regimen and to promote pro-diabetic coping behaviors

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Background:For populations with chronic disease, measurement of QOLprovides a meaningful way to determine the impact of health care when cure is not possible. Revicki and colleagues (2000) dene QOL as "a broad range of human experiences related to one's overall well-being. It implies value based on subjective functioning in comparison with personal expectations and is dened by subjective experiences, states and perceptions. The World Health Organization (2010) denes mental health as a state of positive mental condition in which one realizes his/her capabilities, manages the life stresses, put effort effectively and efciently, and is competent enough to put some contribution to his/her society. According to mental health model (Veit & Ware, 1983), there are two components of mental health, rst is psychological well-being and the other is psychological distress. Therefore, studying the relationship between quality of life and mental health of People with type II diabetes will reveal that to what extend a good quality of life have a relationship in maintaining better mental health in order to cope up with diabetes complications. Objective:The present study was undertaken to know the relationship between quality of life and mental health of people with Type II diabetes. Sample: 30 Type II diabetes were selected from the Diabetes Management Clinic in Rural areas for the assessment of quality of life and mental health. Methodology:The quality of life was assessed using “The Quality of Life Scale (QOLS)” by John Flanagan (1970) and Mental health was assessed using “Mental health inventory (MHI)-18 items by Veit and ware (1983). Finding and Conclusion: The study revealed that there is a signicant relationship between quality of life and mental health of people with Type II diabetes

Funding Acknowledgements Type of funding sources: None. Introduction Decompensation of heart failure leading (HF) to hospitalisation is the single most important drain on healthcare resources when managing patients with left ventricular systolic dysfunction. Cardiac resynchronisation therapy with/without defibrillators (CRT-P/D) decreases hospitalisation due to HF and improves survival while implantable cardiac defibrillators (ICD"s) have a favourable effect on the former. Proprietary software algorithms embedded in these complex devices give an early warning to clinicians when decompensation of HF is imminent allowing preventative action to be undertaken. HeartLogic (HL) is one such new algorithm in Boston Scientific CRT-D/ICD devices using multiple sensors to track 5 physiological parameters, combining them into one composite Index, with an Alert being triggered if the Index is >16. The COVID-19 pandemic, due to multiple reasons, resulted in a significant decrease in availability of routine HF services in the United Kingdom, especially during the initial lockdown period from 23rd March to 1st July 2020. Aim To assess the impact of the COVID-19 pandemic, using HL, in patients with HF and complex devices.  Materials and Methods Retrospective analysis of patients in a tertiary care cardiac centre in whom the HL software had been activated in March/April 2019 (n = 49) and comparison of those with (Group A n = 21) and without (Group B n = 28) an Alert (HLA) during the COVID-19 pandemic.  Results (Table): Whole cohort n = 49. Age:  72 ± 12 years, Median: 75, Range: 36-95. 36/49 (73.5%) males. Type of device implanted: Resonate X4 CRT-D: 28/49 (57.1%); Momentum CRT-D: 8/49 (16.3%); Resonate ICD: 13/49 (26.5%). Ischaemic aetiology of HF: 35/49 (71.4%), Total duration of HL monitoring: 632 ± 7 days (median: 632; range: 626-672).  There was no difference in the age, gender, and type of device implanted between Group A and Group B. Over nearly ∼1 year of monitoring in each of the groups, Group A had more unstable HF with 10/21 (47.6%) having their first HLA during the pandemic. Multiple HLA"s, longer period in HLA and those with ischaemic aetiology of HF were higher in Group A. 17/40 (42.5%) HLA"s in Group A were within the first lockdown period (March - July). 24/28 (85.7%) patients in Group B had no HLA"s either before or during the pandemic. There was no difference in the HLA score between Groups A and B. Conclusion In this limited group of patients with a medium term follow-up, using the HeartLogic software, patients with ischaemic aetiology of HF and those with more HLA"s prior to the pandemic did worse than those who no HLA"s. First HLA"s, multiple alerts and longer duration of alerts in this group of patients suggests a lack of access to adequate HF services during the pandemic. It has implications with regard to how HF services are configured in future whenever resources are constrained. Abstract Figure.