ABSTRACT
Background: The current United Nations sustainable development goal 3 sets to reduce maternal mortality to less than 70 per 100 000 live births by 2030. To monitor whether India is on track to attaining sustainable development goals, it is essential to routinely assess trends of health indicators. Objective(s): This study was conducted to assess trends of maternal mortality and cause-specific maternal death in tertiary care hospitals in Southern India. Method(s): This is a retrospective study of hospital records and death summaries of all maternal deaths between January 1, 2009, and December 31, 2018, at the tertiary care hospital in Southern India. The demographic, clinical, and delivery details of all the maternal deaths were collected. Causes of maternal deaths were classified as direct, indirect, and nonspecific. To observe trends of maternal death, the maternal mortality ratio was calculated for each year, and Pearson's chi-square test was used. Result(s): Maternal mortality ratio was 555/100000 and had a decreasing trend from its highest in 2010 of 1230/100000 to its lowest of 229/100000 in 2017 (t = 7.71 p = 0.02). The majority of women who died were aged 21-35 years, resided in rural, were primigravidae, and had operative delivery. Most of the maternal deaths had been referred to our facility (90.8%) from other healthcare units. Obstetric hemorrhage (27.8%) and puerperal sepsis (37.7%) among direct causes;H1N1 pneumonia (34.8%) among indirect causes were the major causes of maternal death. The number of maternal deaths due to sepsis increased from the beginning until the end of the study from 10% to 50% (t = 5.9, p = 0.01). On the contrary, there was a decline in maternal deaths due to obstetric hemorrhage from 50% to 25% (t = 4.2, p = 0.03). Conclusion(s): Although the maternal mortality ratio has reduced over the years, sepsis was an important cause of maternal deaths.Copyright © 2023 Bentham Science Publishers.
ABSTRACT
The appearance of a novel coronavirus (COVID-19) has presented an immense challenge for the healthcare community around the world. Many patients with COVID-19 have primary cardiovascular (CV) sickness or create intense heart injury throughout the infection. These patients are at exceptionally great danger from COVID-19 because of their fragility and powerlessness for a myocardial involvement. Good comprehension of the exchange between COVID-19 and CV illness is required for these patients' ideal administration. As a growing range of applications for patient management and system incorporation in real time is available, artificial intelligence (AI) can play a decisive role in the emergency department (ED), in fields such as intelligent monitoring, the estimation of clinical results, and resource planning. The proposed system aims to develop an adaptation of a smart medical evaluation method to decide if people with an underlying cardiovascular health disorder would contract COVID-19 based on the limited range of pre-selected variables deemed scientifically necessary and easily calculated when designing clinical judgment regulations. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
The impact of COVID-19 on urban travel behavior has been unprecedented. It has significantly influenced the travel mode choices of different urban commuters in various countries across the globe. Given that the public transport providers need to tradeoff between minimizing the spread of COVID-19 and providing an affordable travel choice in this environment, we develop a strategic queueing model to analyze the effect of different pricing strategies on the commuter behavior. In particular, we consider a Markovian queue in front of a public transport ticket counter wherein strategic commuters arrive at the service facility and make joining or balking decisions based on their derived utilities. In contrast to conventional wisdom, we suggest that the public transport provider needs to decrease the price to filter out the wealthy commuters who possess feasible alternative travel options from using public transport and promote the commuters with no alternatives in using public transport. © 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.
ABSTRACT
As a disease process sepsis represents an interplay between pathogen and host immune response. This interaction results in characteristic physical exam findings that can differ based on pathology. Early recognition and proper understanding of the underlying disease pathology is imperative to effective treatment and prevention of long-term complications. This chapter reviews disease presentation, pathophysiology, and current standard of care treatment for patients with sepsis, including those with COVID-19 pneumonia. Utilizing the most up-to-date guideline recommendations, this overview covers both medical and surgical causes of sepsis along with their treatments, while providing a molecular and cellular understanding for the disease process. © 2023 Elsevier Inc. All rights reserved.
ABSTRACT
This was a retrospective cohort study of patients who delivered singleton, small-for-gestational-Age (SGA) neonates between April and June 2019, before the coronavirus disease 2019 (COVID-19) pandemic (pre-COVID-19), and between April and July 2020, during the pandemic (COVID-19 epoch). The primary outcome was the rate of undetected antenatal fetal growth restriction (FGR) in the two periods. A total of 268 patients met inclusion criteria. Patients who delivered small-for-gestational-Age neonates during the COVID-19 epoch were significantly more likely to have undetected FGR compared with those who delivered pre-COVID-19 (70.1% vs 58.1%, P=.04). Patients who delivered SGA neonates during the COVID-19 epoch had more telehealth visits but fewer in-person prenatal visits, recorded fundal height measurements, and growth ultrasonograms. As telemedicine continues to be incorporated into prenatal care, these data may lend further support toward self-Assessment of fundal height or routine third-Trimester growth ultrasonograms to identify fetal growth abnormalities. Copyright © 2023 Lippincott Williams and Wilkins. All rights reserved.
ABSTRACT
This study aims to evaluate, through a questionnaire, general public awareness preference regarding mouth wash and their perceptions of the importance of self-care to control the disease. Methods: General public completed a 20-item questionnaire that aimed to assess the following: their profile, knowledge, and awareness of the mouthwash, preferences on mouthwashes in terms of their constituent ingredients, short- and long-term side effects, and their attitude towards the use of mouthwashes as plaque control agents. Data tabulation and the frequency distribution using tables and graphics were done. Results: The data showed that 134 participants answered the google form, out of which 56% of participants did not use mouthwash, and 64% gave reasons why it was unnecessary to do so. While another 14.7% were unaware that mouthwash is an adjunct in aiding oral hygiene, and 15% of participants said they did not have enough time to use it. The remaining justifications included difficulty in mouth washing and finding it costly. Conclusion: We conclude with this questionnaire-based survey during the pandemic COVID-19 regarding the public perception and preference of mouth wash, the general public becomes motivated to promote self-care when the dentist promotes proper instruction. The present study throws light on the fact that widespread usages of herbal products now need to be advocated and prescribed. Hence more evidence pertaining to the usage of herbal product needs to done with a greater number of clinical and randomized control trials on a larger scale to continue their development and usage at grassroots level. Copyright©2022 by authors, all rights reserved.
ABSTRACT
The Advent of Artificial Intelligence (AI) has led to the use of auditory data for detecting various diseases, including COVID-19. SARS-CoV-2 infection has claimed more than 6 million lives till date and hence, needs a robust screening technique to control the disease spread. In the present study we developed and validated the Swaasa AI platform for screening and prioritizing COVID-19 patients based on the signature cough sound and the symptoms presented by the subjects. The cough data records collected from 234 COVID-19 suspects were subjected to validate the convolutional neural network (CNN) architecture and tabular features-based algorithm. The likelihood of the disease was predicted by combining the final output obtained from both the models. In the clinical validation phase, Swaasa was found to be 75.54% accurate in detecting the likely presence of COVID-19 with 95.45% sensitivity and 73.46% specificity. The pilot testing of Swaasa was carried out on 183 presumptive COVID subjects, out of which 82 subjects were found to be positive for the disease by Swaasa. Among them, 58 subjects were truly COVID-19 positive, which corresponds to a Positive Predictive Value of 70.73%. The currently available rapid screening methods are very costly and require technical expertise, therefore a cost effective, remote monitoring tool would be very beneficial for preliminary screening of the potential COVID-19 subject.
Subject(s)
COVID-19ABSTRACT
The outbreak of Covid-19 has exacerbated the mental health of Healthcare Workers (HCWs), caused by an increase in their stress levels owing to an exponential rise in their workloads. Previous works have revealed visible changes in Heart Rate Variability (HRV), in response to increased/decreased stress levels. This study focused on analyzing HRV as a parameter to observe the impact of higher stress levels, on clinicians, due to the pandemic. Their responses to a Perceived Stress Score (PSS) questionnaire were used as a reference to determine their escalated stress levels. The responses showed that 40% of clinicians revealed increased levels of high chronic stress while the remaining were affected by moderate chronic stress. We computed HRV for each clinician from HR data obtained using a chest-based wearable device during sleep and ward sessions. Through detailed analysis of HRV, we observed clinicians with high chronic stress showed lower HRV when compared to clinicians with moderate chronic stress during both sleep and ward sessions. Later we did a close investigation of their HRV on Day 1 and Day 2 in Covid-IP (Inpatient) and compared the HRV features. Finally, we compared the HRV features of clinicians between Covid-IP Covid-OP (Outpatient) ward sessions. The above study validated that HRV is a reliable parameter for an objective assessment of stress levels. © 2022 IEEE.
ABSTRACT
The COVID-19 coronavirus pandemic is causing health crises around the world. According to the World Health Organization (WHO), wearing a face mask is an effective means of protection in public places. In most public gatherings such as shopping centers, theaters, parks, it is increasingly necessary to make sure that people in the crowd are wearing masks. Developing an artificial intelligence solution that determines regardless of whether an individual is wearing a cover and letting it in will be great help for the society. In this case, a simple face mask detection system is built using deep learning techniques such as machine learning and persuasive neural network. The model is built with machine learning and OpenCV libraries often used for real-time applications. This model can also be used to develop complete software that scans each person before going to a public meeting © 2022 IEEE.
ABSTRACT
Global guidelines driven by the United Nations/World Health Organization, such as the Declaration of Alma Ata, Millennium Development Goals and the Sustainable Development Goals have been guiding the Member State countries in formulating their implementation plans in health. India, as a signatory of these guidelines, utilizes them as well. As healthcare professionals, awareness of pharmacists about these guidelines and their mindful incorporation in consciously building the ‘health and well-being’ of our population, is crucial. COVID-19 presents an opportunity to realign our roles and responsibilities which moves beyond the traditional biomedical model where ‘access to medicines, devices and services’ drives the priorities. Rebuilding our approach and outcomes around the concept of ‘Health and well-being’ requires expansion of our traditional thinking and our roles. This article highlights the importance of Sustainable Development Goals and International Pharmaceutical Federation (FIP) Development Goals 2020. A clear understanding of these goals and addressing the underlying causes of our burden of diseases will provide future opportunities to elevate public health outcomes. During a pandemic when health and development of our nation needs more engaged health care professionals, this situation is an opportune time for committing ourselves to the well-being of our public. © 2020, Indian Pharmaceutical Association. All rights reserved.
ABSTRACT
Background: The COVID-19 pandemic prompted rapid changes in cancer care delivery. We sought to examine oncology provider perspectives on clinical decisions and care delivery during the pandemic and to compare provider views early versus late in the pandemic. Methods: We invited oncology providers, including attendings, trainees and advanced practice providers, to complete a cross-sectional online survey using a variety of outreach methods including social media (Twitter), email contacts, word of mouth and provider list-serves. We surveyed providers at two time points during the pandemic when the number of COVID-19 cases was rising in the United States, early (March 2020) and late (January 2021). The survey responses were analyzed using descriptive statistics and Chisquared tests to evaluate differences in early versus late provider responses. Results: A total of 132 providers completed the survey and most were white (n = 73/132, 55%) and younger than 49 years (n = 88/132, 67%). Respondents were attendings in medical, surgical or radiation oncology (n = 61/132, 46%), advanced practice providers (n = 48/132, 36%) and oncology fellows (n = 16/132, 12%) who predominantly practiced in an academic medical center (n = 120/132, 91%). The majority of providers agreed patients with cancer are at higher risk than other patients to be affected by COVID-19 (n = 121/132, 92%). However, there was a significant difference in the proportion of early versus late providers who thought delays in cancer care were needed. Early in the pandemic, providers were more likely to recommend delays in curative surgery or radiation for early-stage cancer (p < 0.001), delays in adjuvant chemotherapy after curative surgery (p = 0.002), or delays in surveillance imaging for metastatic cancer (p < 0.001). The majority of providers early in the pandemic responded that “reducing risk of a complication from a COVID-19 infection to patients with cancer” was the primary reason for recommending delays in care (n = 52/76, 68%). Late in the pandemic, however, providers were more likely to agree that “any practice change would have a negative impact on patient outcomes” (p = 0.003). At both time points, the majority of providers agreed with the need for other care delivery changes, including screening patients for infectious symptoms (n = 128/132, 98%) and the use of telemedicine (n = 114/132, 86%) during the pandemic. Conclusions: We found significant differences in provider perspectives of delays in cancer care early versus late in the pandemic which reflects the swiftly evolving oncology practice during the COVID-19 pandemic. Future studies are needed to determine the impact of changes in treatment and care delivery on outcomes for patients with cancer.
ABSTRACT
Introduction: Pulmonary fibrosis after pneumonia due to SARS-CoV-2 (COVID-19) is poorly understood. In patients who required transplantation, explant gene expression profiles are similar to those in patients with pulmonary fibrosis. Currently, two antifibrotic agents have been shown to reduce the rate of progression in other etiologies of lung fibrosis. Here, we describe our experience with antifibrotic therapy in COVID-19 patients. Case#1 A 45 year old male with metabolic syndrome presented with 4 days of worsening dyspnea. He failed initial therapy with high flow nasal cannula (HFNC) and noninvasive ventilation requiring intubation on hospital day 10. He received treatment with remdesivir, steroids and inhaled nitric oxide (iNO). He remained intubated for 21 days, complicated by pneumomediastinum. Total hospitalization was 75 days. Chest imaging throughout hospitalization had cystic changes and bronchiectasis. Pirfenidone was initiated at the time of discharge. On 6-month clinic follow up, he remained on oxygen. He denied any significant side effects to pirfenidone and had no lab abnormalities. Case#2 A 61 year old male with no past medical history (PMH) presented with week-long constitutional symptoms. HFNC for severe hypoxia was started but ultimately intubation was required. He was treated with remdesivir, steroids, iNO, an interleukin-6 inhibitor and convalescent plasma. Weaning from ventilatory support after tracheostomy tube placement was complicated by pneumomediastinum. He was discharged on nocturnal ventilation to long term acute care. He was started on pirfenidone during hospitalization and continued without incident. On subsequent clinic follow up, tracheostomy was decannulated and he could tolerate low flow nasal cannula. Case#3 A 64 year old male with no PMH was admitted with 10 days of worsening respiratory symptoms. The patient required HFNC. He received remdesivir, steroids, broad spectrum antibiotics and convalescent plasma. He was discharged after 13 days on supplemental oxygen. On one month follow up, chest imaging showed reticular and ground glass opacities and traction bronchiectasis. Nintedanib was initiated. One month later he was off supplemental oxygen. Follow up CT imaging showed resolution of ground glass and reticular opacities after 6 months. The patient denied any medication intolerance but abnormal liver function lead to dose reduction of nintedanib. Conclusion: COVID-19 pneumonia can lead to significant pulmonary fibrosis. Further analysis is needed to determine the long term incidence of persistent fibrosis and any risk factors predicting its development. Additionally, in those patients with established pulmonary fibrosis, the role of antifibrotic therapy should prospectively be investigated.
ABSTRACT
The education sector is always facing challenges related to various teaching and learning aspects. With continuous advancements in education technology, students, as well as staff, constantly face issues related to upgrading their knowledge to the next level. During the situation of COVID-19 pandemic, many educational organizations were forced to adopt these technologies very rapidly in order to keep themselves on track and not to lose their students involvement. This research paper has shown the effect of mobile technology and its role in the e-learning process during the online mode of study. A survey was conducted having 206 participants. The questionnaire was having 27 attributes. The research has used association rule mining technique such as CN2 Rule Induction. Principal Component Analysis was used to reduce the components and the gradient approach was used to optimize the results. The study shows a high impact on learning with the usage of mobile phones and better internet infrastructure providing learning anywhere at any time. © 2021 IEEE.
ABSTRACT
Supply chains in general and last-mile logistics in particular, have been disrupted due to COVID-19. Though several innovative last-mile logistics solutions have been proposed in the past, they possess certain limitations, especially during COVID-19 motivating the need for an alternative last-mile logistics solution. We present a review of literature related to last-mile logistics and supply chain disruptions to identify the limitations of existing last-mile delivery practices during COVID-19. Using a stylized analytical model, we then propose that "mobile warehouse" can be an effective solution to last-mile logistics issues faced during COVID-19 and beyond under certain conditions. A mobile warehouse is a truck dedicated to a particular geographical location and carries the inventory of various products based on the estimated demand requirements for these products in that geographical location. We provide the condition under which the B2C e-commerce providers find it profitable to adopt a truck as a mobile warehouse to sell high demand items quickly.