Deaths In India Research Articles

Design of a fire-resistant attachment for quadcopter competent of unmanned firefighting

Fire disasters have become common in the 21st century due to several reasons and extensive industrialization and urbanization have added to this plight. According to the Times of India (daily) dated 22nd of December 2019, there were 27,027 fire-related deaths in India in the year 2017 and, every fifth fire-related death in the world took place in India during that year. These numbers have increased considerably in the preceding years and is a matter of concern. Firefighters face high-risk while dealing with fire in human settlements especially because of the difficulty in finding out the major spot of fire, accessing the areas affected and also due to the presence of trapped-individuals. Human presence in buildings with fire slows down firefighting considerably. The use of an Unmanned Aerial Vehicle (UAV) equipped with a thermal-camera can help identify the location of the fire and trapped individuals, and this could also be highly helpful in the case of fire in thickly populated colonies or high-rise buildings. To lower the direct involvement of firefighters with fire, through this paper, a specially designed attachment, coated with fireproof material that can hold and deploy fire-extinguisher balls, and which can be attached to existing UAVs is proposed. The attachment is made of Aluminum alloy 5052H-32 and it can hold four fire-extinguisher balls at a time which contain ABC dry powder each of 400 g and can extinguish 20,000 sq. cm. of fire in one use. The attachment can be operated using a remote control, thus avoiding direct contact of firefighters with fire and can be used to fight A, B and C class fire. The design of attachment proposed in this paper can be attached to any quadcopter with minimal modifications.

A deep neural architecture for SOTA pneumonia detection from chest X-rays

Pneumonia among children is a leading cause of death in India, and it gains a lot of researchers' attention to develop early detection tools. Due to a lack of the number of radiologists, especially in rural India, the traditional method of diagnosing pneumonia does not address the real-time issues related to early stages. This paper presents a deep learning model, NASNet (Neural Architecture Search Network), pre-trained on ImageNet to predict pneumonia very early stage through chest x-rays of patients. With 2.6 million trainable parameters, the proposed model can run even on a mobile phone with good precision, recall, and an F1 score to detect pneumonia. This approach thus proves to be significantly better than the current state-of-the-art models. It can also help trained radiologists to get a second opinion/ validation of pneumonia diagnosis.

Infant Death Clustering in the Quarter of a Century in India: A Decomposition Analysis.

The study aims to examine the clustering of infant deaths in India and the relative contribution of infant death clustering after accounting for the socio-economic and biodemographic factors that explain the decline in infant deaths. The study utilized 10 years of birth history data from three rounds of the National Family Health Survey (NFHS). The random effects dynamic probit model was used to decompose the decline in infant deaths into the contributions by the socio-economic and demographic factors, including the lagged independent variable, the previous infant death measuring the clustering of infant deaths in families. The study found that there has been a decline in the clustering of infant deaths among families during the past two and half decades. The simulation result shows that if the clustering of infant deaths in families in India was completely removed, there would be a decline of nearly 30 percent in the infant mortality rate (IMR). A decomposition analysis based on the dynamic probit model shows that for NFHS-1 and NFHS-3, in the total change of the probability of infant deaths, the rate of change for a given population composition contributed around 45 percent, and about 44 percent was explained by a compositional shift. Between NFHS-3 and NFHS-4, the rate of change for a given population composition contributed 86%, and the population composition for a given rate contributed 10% to the total change in the probability of infant deaths. Within this rate, the contribution of a previous infant was 0.8% and the mother's age was 10%; nearly 31% was contributed by the region of residence, 69% by the mother's education, and around 20% was contributed by the wealth index and around 8.7% by the sex of the child. The mother's unobserved factors contributed more than 50 percent to the variability of infant deaths in all the survey rounds and was also statistically significant (p < 0.01). Bivariate analysis suggests that women with two or more infant losses were much less likely to have full immunization (10%) than women with no infant loss (62%), although institutional delivery was high among both groups of women.

Nanomaterials for Oral Cancer Diagnosis and Therapeutics- Latest Trends

Oral Cancer is one of the leading causes of deaths in India. Despite growing innovations and trends in the field of oral cancer diagnosis and management, the prevalence rate of the deadly disease keeps escalating. Oral cancer is a debilitating disease, and numerous research activities are being pursued worldwide to combat this deleterious process. Nanotechnology is very diverse field that has revolutionized the industry and is setting new trends in the management of oral cancer. Hence, we have presented an elaborated review on types of available nanoparticles and their use in the field of oral cancer diagnosis

The causes of preterm neonatal deaths in India and Pakistan (PURPOSe): a prospective cohort study

SummaryBackgroundPreterm birth remains the major cause of neonatal death worldwide. South Asia contributes disproportionately to deaths among preterm births worldwide, yet few population-based studies have assessed the underlying causes of deaths. Novel evaluations, including histological and bacteriological assessments of placental and fetal tissues, facilitate more precise determination of the underlying causes of preterm deaths. We sought to assess underlying and contributing causes of preterm neonatal deaths in India and Pakistan.MethodsThe project to understand and research preterm pregnancy outcomes and stillbirths in South Asia (PURPOSe) was a prospective cohort study done in three hospitals in Davangere, India, and two hospitals in Karachi, Pakistan. All pregnant females older than 14 years were screened at the time of presentation for delivery, and those with an expected or known preterm birth, defined as less than 37 weeks of gestation, were enrolled. Liveborn neonates with a weight of 1000 g or more who died by 28 days after birth were included in analyses. Placentas were collected and histologically evaluated. In addition, among all neonatal deaths, with consent, minimally invasive tissue sampling was performed for histological analyses. PCR testing was performed to assess microbial pathogens in the placental, blood, and fetal tissues collected. An independent panel reviewed available data, including clinical description of the case and all clinical maternal, fetal, and placental findings, and results of PCR bacteriological investigation and minimally invasive tissue sampling histology, from all eligible preterm neonates to determine the primary and contributing maternal, placental, and neonatal causes of death.FindingsBetween July 1, 2018, and March 26, 2020, of the 3470 preterm neonates enrolled, 804 (23%) died by 28 days after birth, and, of those, 615 were eligible and had their cases reviewed by the panel. Primary maternal causes of neonatal death were hypertensive disease (204 [33%] of 615 cases), followed by maternal complication of pregnancy (76 [12%]) and preterm labour (76 [11%]), whereas the primary placental causes were maternal and fetal vascular malperfusion (172 [28%] of 615) and chorioamnionitis, funisitis, or both (149 [26%]). The primary neonatal cause of death was intrauterine hypoxia (212 [34%] of 615) followed by congenital infections (126 [20%]), neonatal infections (122 [20%]), and respiratory distress syndrome (126 [20%]).InterpretationIn south Asia, intrauterine hypoxia and congenital infections were the major causes of neonatal death among preterm babies. Maternal hypertensive disorders and placental disorders, especially maternal and fetal vascular malperfusion and placental abruption, substantially contributed to these deaths.FundingBill & Melinda Gates Foundation.

Conceptual Study of Hridroga with its Clinical Management- An Ayurvedic Approach

Hridroga (heart diseases) is one of the major causes of death in India. Hridroga means Cardiac Disorders in Ayurveda. Heart is described as Marma (vital organ) in Ayurveda. Number of people suffering from the heart diseases are quite increased in last few years. According to the global burden of disease, the 24.8 % of all deaths are occurred due to CADs [1] and it affects elders as well as young population, so it is needed to review the concept of Hridroga and its management according to Ayurvedic perspectives with its present updates so, one can prevent these conditions or manage them with more precise approach. Previously number of works has been done on Hridroga in relation to its pathology, treatment aspect, dietary regimen useful for pathological conditions affecting heart. Detail description of causes, symptoms, treatment part of Hridroga is available in the Ayurvedic texts. Ayurveda explains in detail regarding how Ayurveda is afflicted with vitiated Vata, Pitta and Kapha with its symptoms and clinical management. To prevent these conditions and also treat them with more precise approach the review of these concepts is helpful. This article includes the etiological factors, Dosha specific symptoms, types and clinical management of Hridroga (heart disorders) as explained in Ayurvedic texts.

Using household rosters from survey data to estimate all-cause excess death rates during the COVID pandemic in India

Official statistics on deaths from COVID undercount deaths due to lack of testing. In developed countries, death registries are used to estimate excess deaths due to COVID during the pandemic. However, few developing countries had complete death registries even before the pandemic and the pandemic further stressed administrative capacities. As a substitute, we estimate all-cause excess deaths in India using the member rosters of a large, representative household panel survey. We estimate roughly 4.2 million excess deaths during the pandemic through February 2022. We cannot demonstrate causality between COVID and deaths, but the timing and age structure of deaths is consistent with the COVID pandemic and excess deaths are positively correlated with reported infections. Finally, we find that excess deaths were higher among higher-income persons and were negatively associated with mobility. The methods in this paper can be used in countries with a household panel to measure health-related demographic indicators.

How does Nursing Students Knowledge and Attitude correlate in relation to Rabies? An institutional based Cross-Sectional study in Assam

Introduction: Rabies is a vaccine-preventable viral disease. Every year, Rabies causes 18 000-20 000 deaths in India and dogs are responsible for 99 % of all human deaths.Objectives: 1) To assess the knowledge and attitude about rabies among the nursing students.2) To assess whether there is any difference of knowledge and attitude about Rabies among different academic year of the nursing students.3) To assess whether there is any relation between scores of knowledge and attitude.Material &amp; Methods: A cross sectional study was conducted among 142 students of B.Sc. Nursing College, Dibrugarh, Assam in January 2022 using Google form containing pre designed structured closed ended questionnaire by convenience sampling. Knowledge and attitude was assessed by a scoring system. Results were expressed in proportion, percentage, mean, standard deviation. ANOVA and Spearman”s correlation was applied. Results: Mean knowledge &amp; attitude score was 15.7±3.6 and 23.6±2.6.Majority (82.4%) of the students had good knowledge about rabies.Almost all (97.9 %) students had positive attitude towards rabies. There was no significant difference between knowledge score and attitude score among different academic year of the students. Knowledge was positively correlated with attitude of the students.Conclusion: The study revealed good knowledge and positive attitude regarding rabies among the students.

Association of Congenital Anomalies in Newborns with Maternal and Fetal Factors in North Gujarat Region, India: A Cross-Sectional Analytical Study

Background: Approximately 8 to 15% of perinatal deaths and 13 to 16% of neonatal deaths in India are a result of congenital anomalies. The objective of the research was to study incidence of clinically detectable congenital malformations in newborns delivered at secondary and tertiary hospitals and their association with maternal and fetal factors. Material and methods: This study include all new-borns delivered at secondary and tertiary care hospitals in the Mehsana districts of Gujarat, India from January 1st, 2021 to December 31st, 2021. A total of 6900 consecutive births were examined for visible structural anomalies to determine the overall incidence and distribution of congenital malformations and their association with feto-maternal factors. Results: Total numbers of malformed babies were 90 with incidence of 1.30%. Incidence of malformed babies was 1.54% among mother in the age group of 21-35 years, 3.57% among mother with consanguineous marriage, and 6.67.% among mothers with severe anemia. The incidence was 0.97% in babies &lt;1500 birth weight, 0.97% among live births and 12.5% among preterm babies. Conclusion: Congenital anomalies in newborns are significantly associated with maternal factors like maternal age, consanguinity, previous child with malformation, history of previous abortion and severe anemia and fetal factors such as stillbirth, premature babies, and low birth weight.

Risk factors for perinatal mortality in India: a systematic review of observational studies

Perinatal mortality (PM) is a major public health problem in India and multiple maternal and foetal risk factors have been attributed to high perinatal mortality. This review aimed to systematically summarize the epidemiological literature on maternal and fetal risk factors for PM including those for still birth, intrauterine deaths; early neonatal mortality; early neonatal deaths in India. This systematic review was compliant with preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. We searched for peer-reviewed articles from three electronic bibliographic databases: MEDLINE, Embase, Google Scholar published between 1 January 2000 and 31 March 2019 that reported the risk factors of perinatal mortality in India. Observational studies (cross sectional, case-control and COHORT Studies). Eighteen articles were included in this review. The major risk factors identified for perinatal mortality in India were maternal age, parity, higher birth order and maternal anemia. Complications during pregnancy like ante partum hemorrhage, preeclampsia, obstructed labor, preterm labor and fetal factors like gestational age and low birth weight were documented as risk factors for perinatal deaths. Strengthening national health programs and targeted interventions for both antenatal and institutional care is required to bring down perinatal deaths in India.

Meta-analysis of nationwide SARS-CoV-2 infection fatality rates in India.

There has been much discussion and debate around underreporting of deaths in India in media articles and in the scientific literature. In this brief report, we aim to meta-analyze the available/inferred estimates of infection fatality rates for SARS-CoV-2 in India based on the existent literature. These estimates account for uncaptured deaths and infections. We consider empirical excess death estimates based on all-cause mortality data as well as disease transmission-based estimates that rely on assumptions regarding infection transmission and ascertainment rates in India. Through an initial systematic review (Zimmermann et al., 2021) that followed PRISMA guidelines and comprised a search of databases PubMed, Embase, Global Index Medicus, as well as BioRxiv, MedRxiv, and SSRN for preprints (accessed through iSearch) on July 3, 2021, we further extended the search verification through May 26, 2022. The screening process yielded 15 studies qualitatively analyzed, of which 9 studies with 11 quantitative estimates were included in the meta-analysis. Using a random effects meta-analysis framework, we obtain a pooled estimate of nationwide infection fatality rate (defined as the ratio of estimated deaths over estimated infections) and a corresponding confidence interval. Death underreporting from excess deaths studies varies by a factor of 6.1-13.0 with nationwide cumulative excess deaths ranging from 2.6-6.3 million, whereas the underreporting from disease transmission-based studies varies by a factor of 3.5-7.3 with SARS-CoV-2 related nationwide estimated total deaths ranging from 1.4-3.4 million, through June 2021 with some estimates extending to 31 December 2021. Underreporting of infections was found previously (Zimmermann et al., 2021) to be 24.9 (relying on the latest 4th nationwide serosurvey from 14 June-6 July 2021 prior to launch of the vaccination program). Conservatively, by considering the lower values of these available estimates, we infer that approximately 95% of infections and 71% of deaths were not accounted for in the reported figures in India. Nationwide pooled infection fatality rate estimate for India is 0.51% (95% confidence interval [CI]: 0.45%- 0.58%). We often tend to compare countries across the world in terms of total reported cases and deaths. Although the US has the highest number of reported cumulative deaths globally, after accounting for underreporting, India appears to have the highest number of cumulative total deaths (reported + unreported). However, the large number of estimated infections in India leads to a lower infection fatality rate estimate than the US, which in part is due to the younger population in India. We emphasize that the age-structure of different countries must be taken into consideration while making such comparisons. More granular data are needed to examine heterogeneities across various demographic groups to identify at-risk and underserved populations with high COVID mortality; the hope is that such disaggregated mortality data will soon be made available for India.

A review on biomarkers of hypertension

Hypertension is the most prevalent chronic medical condition seen in primary care. It is a silent disease because of its asymptomatic nature and is usually diagnosed at advanced stage. It effects various organs like heart, kidney, etc. It is responsible for 10.8% deaths in India. Over the years many biomarkers are identified to understand the pathophysiology of hypertension. Biomarkers have unique role in prognosis as the level rises before the onset of overt hypertension. Clinically it is beneficial as it helps in identifying the high risk patients for better treatment and prognosis. In this review we have highlighted the importance of various biomarkers of hypertension in early diagnosis, before the onset of overt hypertension, which is associated with long-term end-organ diseases.

Etiopathological and diagnostic study of Margavaranajanya Hridroga w.s.r. to Coronary Artery Disease - An Observational Study

The incidence of cardiac diseases is increasing at an alarming rate in our society due to sedentary lifestyle as an impact of western culture. In India, many studies have reported increasing coronary artery disease incidence over 60 years. One in 4 deaths in India are due to coronary artery disease. So thorough understanding of pathogenesis of this disease is very important. Ayurveda literature elaborates multiple maladies related to heart under Hridroga. Margavarana is a unique pathology explained in our classics. Various dietary, behavioural, psychological factors contribute to morbid accumulation of Kapha and Medas leading to Shonita Abhishyandana. Further morbid state of Shonita Abhishyandana by Upalepa of Dhamani culminates in development of Dhamani Prathicchaya. Eventually due to Siraaja Granthi Dhamani Prathichhaya ends up in Margavarna and is the leading pathology of Hridroga. In the realm of conventional medicine, it is said that sedentary life style is the major cause of morbid accumulation of fat in the body leading to metabolic syndrome. It is characterised by dyslipidemia which in turn leading to atherosclerosis. Atherosclerosis predisposes the thromboembolism and complete obliteration of blood circulation within the vessel. Hence, in the present study an endeavour is made to corelate the concept of Coronary artery disease and its ill effects with the classical reference regarding the concept of Margavarana pathology occurring in the Hridaya causing Margavaranajanya Hridroga and also its diagnosis through the modern tools.

The burden of transport injury and risk factors in India from 1990 to 2019: evidence from the global burden of disease study

BackgroundIndia is one of the fastest-growing developing economies associated with many socio-demographic challenges that include a high density of population, growing urbanization, and poor road infrastructure. These challenges might lead to the cause of injury, especially transport related. Therefore, we aim to analyze the burden of Transport Injury (TI) and associated risk factors in India using the required data from 1990 to 2019.MethodsThis study has used the latest Global Burden of Disease Study (GBD) 2019 data set and estimated TI-related incidence rate, mortality (death) rate, and Disability-Adjusted Life Years (DALYs) lost for India over the period from 1990 to 2019. The latest round of GBD survey-2019 provides information about 369 diseases and injuries and 87 risk factors across age groups and gender.ResultsAround 25% of the death rate of all ages was caused due to TI in 2019, significantly higher than in 1990 (20%). However, between 1990 and 2019, the DALYs rate per 100,000 people due to TI decreased slightly by 1.6% for all ages and both gender while more reduction has been observed in under 5- and 5–14-years age groups. On the contrary, the incidence rate and DALYs rate had increased substantially in the age group above 50 years which could be a serious issue for the safety of aging people. By analyzing the sub-cause of TI, we found that motorcyclist road injuries and pedestrian road injuries have been major causes of deaths in India during the last three decades. Further, we have found four risk factors associated with environmental change, occupational hazard, behavioral risk, and metabolic risk that cause TI injuries.ConclusionsTI-related disease burden has not been reduced over the years in India despite improvements in road infrastructure and digital technology. Improvement in transport policies; awareness about traffic rules and laws among citizens, and improvement in governance in the road & transport sector could change the behavioral risk factors of TI and reduce population unwanted death and suffering.

Perceptions and experiences of people living with non-communicable diseases during covid pandemic-a cross sectional study

Background: COVID pandemic has been more challenging to people living with non-communicable diseases, (NCD) regarding availability of medicines, physician consultation etc. In the absence of effective public interventions, socioeconomically vulnerable groups are likely to develop complications. Diseases like cardiovascular diseases, chronic respiratory disease, cancers and diabetes, contribute to about 82% of all NCD deaths in India. Present study was conducted with aim to identify the challenges faced and perceptions in the management of NCDs during COVID pandemic.Methods: A cross-sectional study was conducted between March to June 2022 by the department of community medicine, SVS medical college, Mahabubnagar. A pre-tested questionnaire was used on was used to collect data, which included demographic details of individuals and the information regarding their experiences and perceptions in the management of NCDs during the pandemic. The calculations were performed with SPSS program, version 23.Results: In the present study it was found that about 37.5% had decrease in the physical activity, 43.8% changed their dietary habits, 45.2% population has gained weight and 41.4% had increase in stress, anxiety and sleeping disorder during the pandemic.Conclusions: In the present study it was found that majority had change in the lifestyle behaviors, Challenges faced included non-availability of bed in the hospital and non-availability of medication. Half of the participants received guidance from the healthcare professionals.

A study on suicidal tendency and their socio demographic profile among the patients attending the psychiatric outpatient department, tertiary care hospital, Nellore, SPSR Nellore district, Andhra Pradesh

Background: Suicide is one of the ten major causes of death in India. Intentional self-harm is also associated with long term risk for repeated attempts as well as death by suicide. Individuals differ in the degree to which risk and protective factors affect their propensity for engaging in suicidal behaviours. The present study seeks to explore about suicidal intent among the self-harm attempters.Methods: This was a hospital based cross-sectional study and includes both male and female patients attending the psychiatric outpatient department of government general hospital, Nellore. After obtaining the informed consent, the necessary data was obtained by a semi-structured interview schedule.Results: Descriptive analysis of the cases showed that those aged less than 30 years (49.3%), unmarried (52.0%), female subjects (52.0%), urban residents (51.3%) and those belonging to nuclear families (60.6%) were commonly involved. Organo-phosphorus poisoning was the commonly used method (30%). The psychological problems were the most common reason (40.0%) for attempting suicide. Mode of attempt, type of stress, existing physical illness and past psychiatric illness influenced the suicidal attempts.Conclusions: Gender specific differences were noted with regard to mode of attempt, type of stressors, physical illness, and past psychiatric illness. Young age groups are vulnerable for suicide. Identifying risk factors helps to design interventions to prevent further attempts.

A study on suicidal tendency and co-morbidities among the patients attending the psychiatric outpatient department, tertiary care hospital, Nellore, SPSR Nellore district, Andhra Pradesh

Background: Suicide is one of the ten major causes of death in India. Intentional self-harm is also associated with long term risk for repeated attempts as well as death by suicide. Individuals differ in the degree to which risk and protective factors affect their propensity for engaging in suicidal behaviors. The present study seeks to explore about suicidal intent among the self-harm attempters.Methods: This was a hospital based cross-sectional study and includes both male and female patients attending the psychiatric outpatient department. After obtaining the informed consent and socio-demographic information, they were evaluated with semi-structured proforma.Results: Descriptive analysis of the cases shows that 56 (46.6%) of age group between 31-40 years are commonly affected. Among the study subjects 79 (65.8%) attempters had no psychiatric illness for attempt and 41 (34.2%) subjects with past psychiatric illness, OP poisoning being the common method in 40 (33.3%) of attempters. In this study 80 (66.6%) of people did not have co-morbid conditions, drug dependency (alcohol dependence) was 20 (16.6%) and others are 20 (16.6%).Conclusions: The suicidal attempts are more in females than males and it is also common in nuclear families, rural areas and individuals with past psychological problems. In this study suicidal attempts were more common among the people not suffering any other co morbid condition.

Pneumonia Detection in X-Ray Chest Images Based on CNN and Data Augmentation

Abstract: Pneumonia is a life-threatening infectious disease affecting one or both lungs in humanscommonly caused by bacteria called Streptococcus pneumonia. One in three deaths in India is caused due to pneumonia as reported by World Health Organization (WHO). Chest X- Rays which are used to diagnose pneumonia need expert radiotherapists for evaluation. Thus, developing an automatic system for detecting pneumonia would be beneficial for treating the disease without any delay particularly in remote areas. Due to the success of deep learning algorithms in analyzing medical images, Convolutional Neural Networks(CNNs) have gained much attention for disease classification. In addition, features learnedby pre-trained CNN models on large-scale datasets are much useful in image classificationtasks. In this work, appraise the functionality of pretrained CNN models utilized as feature- extractors followed by different classifiers for the classification of abnormal and normal chest X-Rays. We analytically determine the optimal CNN model for the purpose.Statistical results obtained demonstrates that pretrained CNN models employed along withsupervised classifier algorithms can be very beneficial in analyzing chest X-ray images, specifically to detect Pneumonia.

Clinical Decision Making using Machine Learning

Abstract: Deaths due to cardiovascular diseases are increasing at an alarming rate. This led to nearly 2.1 million deaths in India in 2015. Heart disease is one of the deadliest causes of death worldwide and has a major impact on the lives of rural people. According to a recent study, cardiovascular disease mortality among rural Indians has surpassed urban Indians. Such numbers are alarming, especially when 68% of India's population lives in rural areas that have poor access to quality healthcare. This paper aims to provide a solution to this problem by introducing a new model*clinical*decision*support system*, abbreviated as CDSS, which*includes machine learning algorithms for the diagnosis of cardiovascular diseases. CDSS is intelligent enough to diagnose a patient's*disease* and help the doctor prescribe the*correct medication, reducing the cost and effort required to prescribe unnecessary treatment. *In this work, we applied correlation-based feature selection (CFS) and a multilayer perceptron classifier on a large heart disease dataset. The dataset used in this study is the "Cleveland Clinic Foundation Heart Disease Dataset" available at the UCI Machine Learning Repository. Our proposed model produced greater accuracy compared to other existing models used in this study. This system can be integrated into a public health care setting to help rural people get a correct, timely and cost-effective diagnosis.

Evaluation of correlation of oxygen desaturation with bode index in stable COPD patients

Chronic Obstructive Pulmonary Disease (COPD) is the world's third leading cause of death, accounting for 3.23 million deaths in 20191. It is the second major cause of death in India and affects an estimated 53 million people 1. BODE INDEX is multivariable grading system that estimates severity of respiratory and systemic components of COPD patients and was designed to predict quality of life in COPD patients. The four variables BMI (B), FEV1% predicted (O), Dyspnoea (D) as measured by MMRC, Exercise capacity (E) as measured by the six-minute–walk test. In stable COPD patients desaturation upon exertion is a major factor which can be used as a predictor of QOL (quality of life) , future exacerbations, severity of the disease etc. The current study is focussed upon estimation of COPD prevalence by clinical severity stages as measured by BODE index and the correlation between exercise induced desaturation and various quartiles of BODE INDEX in stable COPD patients.