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Introduction: COVID-19 is a widespread disease having more impact on elderly as compared to younger age group. [2] Although many parameters have emerged as predictors of prognosis of COVID-19, a simple clinical score at baseline can be used for early risk stratification. NEWS2 (National Early Warning Score) is one such scoring system which was originally developed to improve detection of deterioration in acutely ill patients.[8] Therefore, the present study has been conducted to assess the effectiveness of NEWS2 in predicting critical outcomes and mortality in geriatric patients with COVID-19. Material(s) and Method(s): A cross sectional Observational study was done on 200 Geriatric patients hospitalised with confirmed COVID-19 between December 2020 to November 2022. Baseline NEWS2 score was calculated. The sensitivity, specificity, Positive Predictive Value and Negative Predictive Value were established for NEWS2 score of 5 or above. Result(s): In critical group, all 109 (100%) patients' deterioration was predicted, and in non-critical group, in 14 (15.4%) patients non deterioration was predicted while 77 (84.6%) patients' deterioration was predicted. Statistically significant association has been observed between the critical, non-critical groups and NEWS2 scale (P=0.001). Deterioration was predicted by NEWS2 scale in all the critical patients. Conclusion(s): NEWS2 score of 5 or more on admission predicts poor prognosis in geriatric patients with COVID-19 with good sensitivity and it can easily be applied for risk stratification at baseline. We recommend further studies in the Indian setting to validate this simple score and use it further in Geriatric patients with COVID-19.Copyright © 2023, Dr Yashwant Research Labs Pvt Ltd. All rights reserved.
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Medical care is vital to having a decent existence. Be that as it may, it is undeniably challenging to get an appointment with a specialist for each medical issue and due to the current global pandemic in the form of Coronavirus, the healthcare industry is under immense pressure to meet the ends of patients' needs. Doctors and nurses are working relentlessly to treat and help the patients in the best possible way and still, they face problems in terms of time management, technical resources, healthcare infrastructure, support staff as well as healthcare personnel. To resolve this problem, we have made a chatbot utilizing Artificial Intelligence (AI) that can analyze the illness and give fundamental insights regarding the infection by looking at the data of a patient who was previously counselled at a health specialist This will also assist in lessening the medical services costs. The chatbot is a product application intended to recreate discussions with human clients through intuitive and customized content. It is in many cases portrayed as the most moving and promising articulations of communication among people and machines utilizing Artificial Intelligence and Natural Language Processing (NLP). The chatbot stores the information in the data set to recognize the sentence and pursue an inquiry choice and answer the corresponding inquiry. Through this paper, we aim to create a fully functional chatbot that will help the patients/users to know about the disease by simply entering the symptoms they possess. Additionally, they can also get information about certain medicine by simply typing the name of the medicine. Another additional feature is the ability of the bot to answer general questions regarding healthcare and wellbeing. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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Amidst Covid-19, identity fraud in exams is becoming more and more advanced. Therefore, identifying these fake candidates accurately has become a difficult problem in exam administration. The novelty of this work is the introduction of optimized Inception ResNetV2 for an ideal online testing system where the system can detect the faces of test-takers and generate a report of the automated monitoring of the candidate. The point of the work is to design a biometric module that is to be implemented as the candidate authentication and identity verification proctoring method for the exams. For research, the suggested method concentrates on a single image. The system integrates various technologies, such as facial imaging, human-computer interaction, data transmission, and communication. Using video proctoring, the system can continuously monitor the examinee's behaviour by live streaming. This is done by using, MediaPipe Face Mesh, MediaPipe Face Detection, Pretrained Inception-ResNet-v2 Convolutional Neural Network, Django Framework, and OpenCV. The proposed work involves two modules: Online Examination Management and Face Recognition Proctor. This research attempts to build automated face recognition and identity features in order to detect fraud. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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The COVID19 pandemic has disturbed the daily lives of people, including those in the education sector. It has tested the readiness of Higher Education Institutes (HEIs) and put in question the adaptability of students and faculty in using online teaching-learning modalities. This paper describes the development of an online engineering education in the department of Electronics and Telecommunication Engineering of Rajarambapu Institute of Technology, Islampur. The authors sampled 211 engineering students and 16 faculty members from the department of Electronics and Telecommunication Engineering using online survey forms. The author highlighted the requirements of online teaching-learning, the implementation methodology, online platforms, sample ICT tools and active learning tools used for the delivery of contents and conducting examinations. From the feedback of students and faculties members, it was found out that availability of resources, institute support, skill development and engagement have significant contribution to the adaptability of faculties and students to online teaching-learning. The pandemic situation has enhanced the adaptability of online teaching-learning during the COVID19 pandemic and also students and faculties are ready if any other similar man-made or natural disruptions occur. © 2022, Rajarambapu Institute Of Technology. All rights reserved.
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The devastating COVID 19 Pandemic, which set an outbreak by the end of 2019, has led the whole world into an alarming situation. So, considering the need of the time, we decided to put some light on the important aspects of the pandemic. Here we have discussed the different coronaviruses which can affect humans and also how this new coronavirus is different than the previously identified coronaviruses. In general, SARS CoV-2 is elaborated along with origin, virology, and transmission. The disease (COVID 19) is studied and briefed for its prognosis and symptoms and as to how the detection of the infection is done. As we know that we have not found any full proof solution for this outbreak but can fight it to save mankind, the need for new drug development and the current scenario on available options is discussed along with how the world is combatting the situation to stop its spread. Also, the common myths among the public about the disease are busted here. The paper is concluded with the current statistics of the outbreak. The purpose of this paper is to provide the general public with some know-how of the pandemic.Copyright © 2021 Bentham Science Publishers.
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Medical care is vital to having a decent existence. Be that as it may, it is undeniably challenging to get an appointment with a specialist for each medical issue and due to the current global pandemic in the form of Coronavirus, the healthcare industry is under immense pressure to meet the ends of patients' needs. Doctors and nurses are working relentlessly to treat and help the patients in the best possible way and still, they face problems in terms of time management, technical resources, healthcare infrastructure, support staff as well as healthcare personnel. To resolve this problem, we have made a chatbot utilizing Artificial Intelligence (AI) that can analyze the illness and give fundamental insights regarding the infection by looking at the data of a patient who was previously counselled at a health specialist This will also assist in lessening the medical services costs. The chatbot is a product application intended to recreate discussions with human clients through intuitive and customized content. It is in many cases portrayed as the most moving and promising articulations of communication among people and machines utilizing Artificial Intelligence and Natural Language Processing (NLP). The chatbot stores the information in the data set to recognize the sentence and pursue an inquiry choice and answer the corresponding inquiry. Through this paper, we aim to create a fully functional chatbot that will help the patients/users to know about the disease by simply entering the symptoms they possess. Additionally, they can also get information about certain medicine by simply typing the name of the medicine. Another additional feature is the ability of the bot to answer general questions regarding healthcare and wellbeing. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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Organizations regardless of their size are rapidly transforming, adopting and embracing digitalization amid the COVID pandemic. The pandemic forced organizations to ratio- nalize offline operations and swift towards online operations. Many organizations have digitized their services and have witnessed increasing Multistage cyber-attacks. Further, a lot of organizations have enabled remote access to the enterprise resources and services. As a result, organizations are striving to defend against Multistage cyber-attacks. These multistage attacks often spread across many stages, which is best described by MITRE Adversarial Tactics, Techniques, and Common Knowl- edge (ATT&CK) Framework. There are many research efforts for static detection of malicious binaries but very few or limited research targeting run-time detection of malicious processes in the system. Detection of these malicious processes are key for identifying new variants of multistage attacks or malware in the real world. This paper proposes a system for detecting multistage attacks in real-time or run-time by leveraging Machine learning and MITRE ATT&CK Framework. Machine learning facilitates detecting the malicious process in the system, and the MITRE ATT&CK framework offers insight into adversary techniques. Combination of these two is very effective in detecting multistage attacks and identifying individual stages. The proposed system shows promising results when tested on real-time/latest malware. Test result shows that our system can achieve 95.83% of accuracy. This paper discusses the challenges in detection of runtime malware, dataset generation © 2022 IEEE.
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Objective: There is a scarcity of data on the factors that influence home blood pressure (BP) and heart rate (HR) variability. This study was undertaken to determine the factors that influence home BP and HR fluctuation post COVID infection in the urban Indian population. Designs and Methods: We conducted a cross-sectional study among 1000 patients between the ages of 30 and 80 who were previously infected with COVID- 19 infection, but not hospitalized. These patients were guided and trained to measure BP at home. BP and HR readings were taken at home twice a day, in the morning and evening, for seven days (28 measurements). The SD of morning minus evening, and first minus second readings was used to calculate BP and HR variability. Results: Old age, cardiovascular illness, diabetes, and high home blood pressure were all found to be independent predictors of an increased morning than evening home blood pressure variability. Old age, and high home blood pressure were all independent determinants of greater day-to-day home blood pressure variability, while old age, female sex, cardiovascular disease, and high home blood pressure were all independent determinants of greater first versus second home blood pressure variability. Young age, and high home HR, on the other hand, were all independent drivers of increased morning vs evening variability. Young age, female sex, and a high home HR were also independent predictors of first versus second home HR variability. Conclusion: Considering home BP and HR fluctuation have prognostic value, it is critical for clinicians to understand the underlying reasons for these variables. Doctors should focus on alcohol, diabetes, and cardiovascular disease prevention counseling for their high-risk patients. (Table Presented).
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Introduction: Physiotherapy and medical management have shown to be beneficial in managing COVID-19 patients. Prone positioning was maximally used in managing these patients, which helped improve ventilation. Crocodile breathing emphasizes diaphragmatic recruitment, decreases accessory muscle use, and triggers the body's relaxation response. The study aims to see the immediate effect of crocodile breathing versus prone positioning in COVID-19. Methods: Thirty participants who passed the eligibility criteria were randomly assigned into two groups. Group A was asked to perform standard of care treatment followed by prone positioning, and after a washout period of a day, they were made to perform standard of care treatment followed by crocodile breathing. Group B performed crocodile breathing on Day 1 and prone positioning on the next day. Outcome measures pulse rate, respiratory rate, rate of perceived exertion, oxygen saturation, single-breath count (SBC), and chest expansion. The patient's feedback was recorded immediately within 1 min pre and post-treatment on both days. Results: Significant improvement was seen in physiological parameters (P < 0.0001), chest expansion (P < 0.0001), and SBC (P < 0.0001) in both groups. However, crocodile breathing was seen to be more effective than prone positioning on SBC (P < 0.0001), rate of perceived exertion (P = 0.000), and chest expansion (P < 0.0001). Twenty-six out of 30 (86%) participants reported crocodile breathing was a more comfortable and better position to relieve dyspnea. Conclusion: Crocodile breathing effectively manages COVID-19 and can be safely incorporated into physiotherapy management for patients with COVID-19.
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Aims: To determine the severity of deficiency and the presenting features Introduction: Vitamin D insufficiency affects almost 50% of the population worldwide. An estimated 1 billion people worldwide, across all ethnicities and age groups, have a vitamin D deficiency (VDD). This pandemic of hypovitaminosis D can mainly be attributed to lifestyle and environmental factors that reduce exposure to sunlight, which is required for ultraviolet-B (UVB)-induced vitamin D production in the skin. The high prevalence of vitamin D insufficiency is a particularly important public health issue because hypovitaminosis D is an independent risk factor for total mortality in the general population. Many health care providers have increased their recommendations for vitamin D supplementation to at least 1000 IU. Methodology: this study was done over a span of 10 months from September 2021 to July 2022 This was a retrospective descriptive study in which data were recorded for all patients aged from 6 months to 12 years of age with features suggestive of vitamin D deficiency seen in Dr DY Patil Medical College and Hospital, Pune for a period of 10 months The Health Research and ethics committee of Dr DY Patil Medical College and Hospital, Pune approved the study and waived the requirement for the informed consent. A total of 69 patients were included in this study. Result(s): 69 patients were included in the study out of which 39 were males { 56.52%} and 30 were females { 43.48%}. the main presenting feature was bowing of legs { 31.9%} followed by difficulty in walking in 15.9% Out of 69 children 53 had severe deficiency, 13 had mild to moderate deficiency and 3 had optimum levels of vitamin D. 28 children belonged to the age group of 1-5 years followed by 18 children in age group of 5-10 years and 11 children in age group less than 1 year and 10-15 years Out of the entire study group 56 children had bony deformities and 13 had neurodevelopmental presentation Conclusion(s): the above results emphasise the fact that due to covid most of the children were restricted to stay indoors for several months leading to vitamin D deficiency in them. it also emphasis the fact that regular screening of children should be done with respect to vitamin D levels and also other micronutrients and children should be encouraged to have some amount of sun exposure to get natural supplementation of vitamin D and also be supplemented at desired intervals so that they adequate amount of vitamin D levels. Copyright © 2023 Ubiquity Press. All rights reserved.
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Introduction: The coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to spread worldwide. Antigen point-of-care tests are needed to help speed up the testing of SARS-CoV-2. In this study, we evaluated the performance of a rapid SARS-CoV-2 antigen detection assay to the SARS-CoV-2 real-time reverse transcription-polymerase chain reaction (RT-PCR) test. Materials and Methods: COVID-19 infection suspected patients and contact individuals provided 185 respiratory samples (mostly nasopharyngeal and throat swabs) during the study from April to June 2021. The rapid SARS-CoV-2 antigen detection test was compared to the real-time RT-PCR test for SARS-CoV-2 detection in respiratory specimens. Results: By real-time RT-PCR testing, 80 (43.2%) of 185 respiratory samples were positive for SARS-CoV-2 RNA, while 105 (56.8%) were negative. The sensitivity and specificity of the fast SARS-CoV-2 antigen detection test were 63.1% and 90.1%, respectively. Conclusion: The sensitivity and specificity of the fast assay for SARS-CoV-2 antigen detection were comparable to those of the real-time RT-PCR assay. As a result, the rapid and easy SARS-CoV-2 antigen detection test could be used as a screening assay. © 2022 Journal of Datta Meghe Institute of Medical Sciences University ;Published by Wolters Kluwer-Medknow.
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The COVID-19 pandemic has disrupted our lives in ways we would not have imagined. Many lives have been drastically affected because of negligence on our part and because we didn’t know how to stop the virus from spreading. It’s an illness that needs combatting against. The only way we can fight this disease is if we are aware of our surroundings and have the relevant information about this virus to protect ourselves from it. This project aims to provide people with a website that is a one-stop solution for all the important details about this disease. It aims to educate people with relevant data displayed in the form of graphs. This project also includes a machine-learning model that tells you the probability of contracting the virus. Our goal is to make sure this information is accessible and comprehensible to any user which could potentially save someone’s life
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Malnutrition is a particularly serious problem, which indicates a poor outcome in terms of morbidity, quality of life, length of stay in the hospital and mortality1. This study was conducted to assess the relationship between malnutrition and hospitalized duration in patients with COVID-192. [Formula presented] An epidemiological study was conducted where in total 250 COVID hospitalised patients from 3 hospitals in MultiSpeciality hospitals in urban setting were included in the study from December 2020 to April 2021 with mean age 59 ± 8.8 yrs. Nutritional assessment on admission was done using the “Global leadership Initiative on Malnutrition (GLIM)” assessment tool. In accordance with the GLIM criteria, patients were divided into 2 groups- well-nourished and under nourished. On comparing the two groups, under nourished patients had a longer hospitalization time (16.36±5.81 days versus 31.04±6.91 days, P = 0.001). Kaplan-Meier analysis showed patients with malnutrition were more likely to be hospitalized longer compared to those with normal nutrition. Elderly patients in malnutrition group were higher than in well-nourished group, and similar pattern was seen with higher proportion of diabetics (22.8% versus 56%, p= 0.002), the proportion of low lymphocytes was higher (14.0% versus 34.4%, p=0.047), the neutrophil/lymphocyte ratio (NLR) was higher (1.88[1.15, 2.29] versus 2.39[1.81, 4.20], p=0.001). The current findings revealed that malnutrition played a role in predicting the likelihood of prolonged hospitalisation in COVID-19 infection patients, who should be given special attention and precautions throughout clinical treatments. Malnutrition assessment in inpatients with nutritional risk thus is important and nutritional support treatment should be started as soon as possible. References 1. Li T, Zhang Y, Gong C, et al. Prevalence of malnutrition and analysis of related factors in elderly patients with COVID-19 in Wuhan, China. Eur J Clin Nutr. 2020, 74(6): 871–875. 2. Coats KG, Morgan SL, Bartolucci AA, Weinsier RL. Hospital-associated malnutrition: a reevaluation 12 years later. J Am Diet Assoc. 1993, 93(1): 27–33.
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Malnutrition, both severe and acute in covid 19 patients are particularly serious problems, may depress the immune system further indicating a poor outcome in terms of morbidity, quality of life and mortality1. Thus, dietary intake may play a major role in determining nutritional status of patients with pneumonia due to COVID 19. Aim was to screen and evaluate the intake of macro-nutrients in subjects who could tolerate oral intake with mild to moderate pneumonia due to Covid 19 assessed for nutritional status, fat free mass index (FFMI) and basic lung function. A cross sectional study was carried out on 71 patients admitted to an ICU in an urban multispecialty hospital from August 2020 to January 2021. Nutritional status, lung function, body composition was assessed using Patient generated Subjective global assessment (PGSGA), Spirometry and Fat Free Mass Index (FFMI) respectively. Dietary intakes were assessed using Food record charts (FRCs). The results show that higher proportion of subjects were unable to meet the RDI for energy (56%), protein (90%) and fat (66%);carbohydrate intake was above RDI (41%) despite of providing oral nutritional supplements in an attempt to meet the required dietary allowance and nutritional needs in these subjects. 24 (73%) subjects out of 33 under stage B & C reported lack of appetite with early satiety. Mean age of the patients was 62± 8.8 yrs. and mean BMI on admission was 21.1± 4.2 kg/m2. [Formula presented] In conclusion subjects included in this study with better nutritional status and nutrient intakes had better lung function. Hence, early identification of malnutrition by screening, assessment with timely nutrition intervention in COVID 19 subjects by fueling of deficits in nutrient intake may preserve lean body mass, improve nutritional status, avoid deterioration of lung function due to malnutrition thus leading to a probable positive prognosis of the disease. References 1. Damayanthi HDWT, Prabani KIP. Nutritional determinants and COVID-19 outcomes of older patients with COVID-19: A systematic review. Arch Gerontol Geriatr. 2021 Jul-Aug;95:104411.
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Non-IT businesses also contribute equally like IT businesses in increasing the Indian economy. But due to COVID-19, they failed to contribute effectively. As a result, they faced many economic disruptions in running businesses and caused massive dislocation among non-IT businesses. Cloud computing plays a vital role in running IT businesses, and it is an effective way to deliver IT solutions. The main objective of this paper is to identify the problems of non-IT businesses during COVID-19 and suggest optimized cloud solutions. This paper demonstrates how to determine potential problems by analyzing the survey responses and then drawing a problem solution matrix for each business type. Using survey-based data analysis as a domain, this work relates to collecting real-time data from Non-IT business firms, which helps us identify their problems. The experimental result of this approach shows an improvement factor in the economy and influence of cloud technology. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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According to the World Health Organization data, the global epidemic of COVID-19 has profoundly affected the world and has now infected more than eight million people worldwide. The COVID-19 epidemic forced governments worldwide to close their doors to prevent the spread of the virus. Reports indicate that wearing a facemask and maintaining public distance while at work reduces the risk of infection. CCTV cameras are installed in educational and industrial spaces, residential areas, and crowded places. However, it is difficult to physically monitor buildings to find people without masks and people who do not keep public distance, and it is challenging to monitor video footage of large buildings and find people without a facemask and social distance correction. A mixed model that uses in-depth reading and machine learning to face masks and correct public distances will help managers look after people roaming the grounds without hiding their faces and distance from the public. The supervised machine-learning algorithm will train the model with the data available online. The facemask data acquisition set contains masked and non-masked images. OpenCV will be used for real-time face recognition and social distance adjustment from live streaming videos from web-enabled videos. The Convolution Neural Network will be used to extract features from the database. After the feature removal process, the newly installed photo/video will be classified as face masked or face masked. The proposed methodology has shown that person detection, social distance, and F.I. scores approximate 91.2%, and the average F1 score is 90.79%. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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The COVID-19 virus was first reported in December 2019 in China. Since then, it has created havoc on global level by causing health and financial crisis. The novel corona virus is continuously evolving into new variants of virus and still spreading in every part of the world. The virus is spread mostly by the droplets transferring from the infected person to an uninfected person. The only direct method of preventing such transfer of droplets can be done by washing of hands, avoiding contact with nostrils, eyes and mouth. Only complete vaccination of citizens can help in containment of virus till then use of face mask and social distancing has been made mandatory by authorities. This project proposes a contactless face mask detection model based on machine learning and image processing technology. It will follow the protocols of social distancing. This project will be helpful in accurately identifying whether a person is wearing a mask properly or not. This model can be easily installed in the entrance of ATMs, malls, educational institutions, offices and in the entrance of public offices. Being a contact less model it will effectively reduce the need of having a manual way of detection and will reduce the spreading of disease to further people. It is highly effective and cheap model as all the tools required for this project are free of cost and easily available online. Proposed model can be easily used on low end computers like Raspberry Pi. The model will encourage people to continuously wear mask in correct manner. © 2022 IEEE.
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Background and AimsProximal shoulder surgery in patients with compromised pulmonary function stipulates anaesthesiologists to look for an alternative to interscalene block. Such aforementioned challenge pioneered the initiation of use of superior trunk block to utilise distinct advantage of phrenic nerve sparing, allowing the patients to execute normal respiratory functions perioperatively. Superior trunk of brachial plexus visualised accurately through ultrasound, steers effortless performance and achieving acceptable block characteristics.MethodsHere we present a case series of 8 patients aged between 40 years to 80 years with significant restrictive, obstructive pulmonary disease and post-covid patients posted for proximal humerus surgeries. The block was performed under ultrasound guidance, 23G Quincke spinal needle, 1:1 local anaesthetic mixture of 2% Lignocaine+Adrenaline and 0.5% Bupivacaine with total volume injected being 15 ml. The outcomes measured were loss of shoulder abduction, numbness of shoulder and pain relief, numbness of arm and sonographic assessment of diaphragm movement, oxygen saturation perioperatively and closed-circuit measurement of tidal volume generatedResults7 patients with superior trunk block achieved complete surgical anaesthesia of proximal shoulder. There was solitary use of Dexmedetomidine for patient with severe anxiety. 2 patients required oxygen supplementation throughout the intraoperative period extending to post-operative period as well. Sonographic assessment intraoperatively and post-operatively disclosed adequate diaphragmatic excursion in all patients. Post-operative pain scores revealed satisfactory pain relief.ConclusionsEffective surgical anaesthesia and analgesia can be delivered considerably with Superior trunk block for surgeries of proximal humerus in patients with compromised pulmonary function by sparing phrenic nerve and it is an appropriate substitute for interscalene block
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limited to employee productivity then on we graduated to shifting our focus to correlating performance with employee satisfaction. Higher the levels of employee satisfaction, greater the performance. Of late with the changes in nature of businesses we have started realizing and talking about the most critical and neglected aspect known as "employee engagement". Engagement is often said as a capture of an employee's head and heart. Today the world is different than it used to be nearly a year ago. The global pandemic has caused an atmosphere of uncertainties and confusion creating communication gaps and lead to complete disruption in our lives. In such a scenario, keeping employees engaged and passionate about work is a challenge ahead of organizations worldwide. This paper attempts to focus on studying the impact the global pandemic has on various employee engagement practices and strategies of the firms. The primary purpose of this research is to understand how such periods of crisis impacts the employee engagement practices and to be more specific which areas of employee engagement has changed drastically during this crisis. Employee engagement in such trying times assumes a paramount importance. Though a lot of organizations have encountered a plethora of challenges due to Covid-19 crisis in adjusting their management styles and working practices it is a question unanswered as to how the lessons learned about the employee engagement will be brought to practice in their working model. It will surely bring scope for positive improvements and shift in area of focus in employee engagement practices in the organizations in years to come.
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The joint family system provides a support system especially for children, young parents, and parents-to-be and is a major factor in their survival, health, education, development, and protection. It has the major potential to provide stability and support when there are problems. The joint family system even in India is on the decline, and nuclear families are on the rise both in urban and rural areas. This has left the pregnant woman with little or no family support to fall back on, which can be a cause of stress and thus affect the outcome of pregnancy. Moreover, during the COVID, the medical support was also limited, which has added to the distress. Stress in the mother can result in hypertensive disorders of pregnancy with resultant low-birth-weight babies, preterm delivery, adverse neurodevelopmental outcomes for the child, and developmental delays in babies, and all these need to be avoided. iMumz pregnancy, the baby care and parenting digital program, has sought to address these issues by partnering closely with pregnant women, offering a wide range of assistance and activities for maternal well-being in the comfort of their own homes. This study captures the responses and pregnancy outcomes of the women who have used the iMumz pregnancy digital program during pregnancy. Materials and methods: This longitudinal study (panel study) was conducted on 512 primigravidas. The study group included 255 pregnant women who opted for a digital holistic health program: “Baby Care Program” (BCP), while the control group consisted of 257 pregnant women who received no such interventions. The BCP included mindfulness meditation, 3 hours of yoga and breathing practices every week, 2 hours of harmonizing music every week, 1 hour of baby bonding activities every week, and 1 hour of personalized diet and pregnancy education each week. The data were collected at 15 and 35 weeks of pregnancy and then from 1 month until 6 months of postdelivery. Results: The study showed a statistically significant improvement in sleep patterns and stress levels. It also showed a statistically significant decrease in the incidence of preterm delivery and low birth weight and a better maternal–fetal bonding or attachment (MFA) in the BCP study group compared to the control group. After initiation of BCP activities in the App, 88% of the patients reported a significant reduction in stress. The BCP study group also reported a higher sense of mastery in coping with postpartum blues. Eighty percent of the control group reported postpartum blues as compared to 19% of the BCP users. Moreover, 81.4% of the BCP study group reported more sense of control in managing their pregnancies, despite the stressful COVID environment. Conclusion: The BCP activities, such as meditation, yoga and breathing exercise, harmonizing music, baby bonding activities and personalized diet, and pregnancy education, have helped pregnant women to reduce their stress levels with improvement in sleep quality, increased a sense of control over diet and nutrition, and educated about MFA. The use of BCP has also positively correlated with better early childhood development and milestones. © Jaypee Brothers Medical Publishers.