Comparison of Obstetric Outcomes in First and Second COVID-19 Waves: Analysis from a COVID-19-dedicated Tertiary Care Hospital

Introduction: The physiological changes in the respiratory and cardiovascular systems in the immunosuppressed state of pregnancy may exacerbate clinical features and deteriorate outcomes due to COVID-19 infection. We aimed to compare the maternal and neonatal adverse effects in the first and second COVID-19 waves. Methodology: This study was a prospective cohort study conducted in a tertiary care COVID-19-dedicated hospital. In total, 104 (group A) and 96 (group B) COVID-19-positive pregnant women admitted during the first and second waves, respectively, were included in the study. Data on baseline variables, associated comorbidities, clinical presentations, management strategies, and neonatal and maternal outcomes were collected and compared using parametric and nonparametric tests and analyzed. Result(s): Around 2.08% in group A and 6.72% in group B of COVID-19-infected pregnant women, respectively, had moderate-to-severe disease and required intensive care unit stay. Almost 1.04% in group A and 3.84% in group B had maternal mortality, 13.4% and 19.8% babies of groups A and B required admission in neonatal intensive care units, and 8.6% and 7.3% of newborns in groups A and B had COVID-19-positive reports by reverse transcriptase polymerase chain reaction (RT-PCR) at birth, respectively. Of them, 2.1% newborns in group B had RT-PCR positive on day 7 of life and beyond, whereas none had positive RT-PCR reports on 7 days and beyond in group A. Conclusion(s): Dreadful maternal outcomes like requirement of ICU and mechanical ventilator and persistence of neonatal infections were higher during the second wave.Copyright © The Author(s). 2023.

Epidemiological and Demographic Profile of COVID-19 Suspects in a Tertiary Care Hospital at Jaipur, Rajasthan

Background: The coronavirus disease (COVID-19) was a pandemic which spread to various countries and originated in Wuhan, China. For appropriate response, planning, and allocation of resources demographic data play an important role in understanding the impact of COVID-19 across the country. Aim(s): To estimate epidemiological and demographic parameters like age, sex, area, sample type etc. of samples reported in COVID-19 diagnostic laboratory of RUHS College of Medical Sciences, Jaipur, Rajasthan. Material(s) and Method(s): The study was conducted retrospectively in a tertiary care hospital at Jaipur. Data like age, gender, urban or rural, IPD/ICU or OPD etc. were collected between January 1, 2021 to June 30, 2021. The collected data were expressed in number, counts and percentage. The data of six months were analysed using Microsoft Excel. Result(s): From January to June 2021, April and May 2021 showed highest positivity 13084 (27.42%) and 10968 (23.06%) respectively. February 2021 and June 2021 showed least positivity 156 (2.39%) and 163 (0.8%) respectively. Total COVID-19 positive cases during 6 months were 25134 and deaths were 357 with highest deaths were during May 2021 (n=270). Males (64.28% to 72.20%) were affected most. In April and May 2021 positivity in urban area was 6053 (46.26%) and 5712 (52.07%) respectively, while in rural area 7031 (53.74%) and 5256 (47.93%) respectively. The positivity in OPD patient during April and May was 93.58% (12245) and 95.26 % (10449) respectively. Nineteen to forty years was most affected age group. Conclusion(s): During second wave both urban and rural population was affected. Males and working age group were affected more. Among COVID-19 suspects' positivity rate was low in IPD patients as compared to OPD patients. Critical factors for an effective public health response are surveillance and contact tracing.Copyright © 2023, Dr Yashwant Research Labs Pvt Ltd. All rights reserved.

Antibody response to ChAdOx1 nCoV-19 (Covishield®) vaccine in people on maintenance hemodialysis.

INTRODUCTION: People on renal replacement therapy (RRT) have a high risk of COVID-19 infection and subsequent death. COVID-19 vaccination is strongly recommended for those on RRT. Data are limited on the immune response of the ChAdOx1 nCoV-19/AZD1222 (Covishield®) vaccine in patients on RRT. METHODS: A prospective cohort of adult (age > 18 years), on RRT in the form of hemodialysis were included and received two intramuscular doses of Covishield®. A blood specimen of 5.0 mL was collected at two time points, within a few days before administering the first dose of the vaccine and at 4-16 weeks after the second dose. According to their prior COVID-19 infection status, the participants were grouped as (i) prior symptomatic COVID-19 infection, (ii) prior asymptomatic COVID-19 infection, and (iii) no prior COVID-19 infection. RESULTS: A large proportion (81%) of participants had anti-spike antibodies (ASAb) before vaccination, and a reasonable proportion (30%) also had neutralizing antibodies (NAb). The titer of ASAb was relatively low (207 U/mL) before vaccination. The ASAb titer (9405 [1635-25,000] U/mL) and percentage of NAb (96.4% [59.6-98.1%]) were markedly increased following the administration of two doses of the vaccine. The participants' prior COVID-19 exposure status did not influence the rise in ASAb titer and NAb percentage. Further, administering two doses of the Covishield vaccine helps them achieve a high ASAb titer. CONCLUSION: Two doses of ChAdOx1 nCoV-19/AZD1222 (Covishield®) vaccine, given 12 weeks apart, achieve a high titer of ASAb and a high percentage of NAb in people on hemodialysis.

Large Ovarian Dermoid, a Cause for Fetal Growth Restriction and Oligohydramnios: Rare Instance in Literature

Ovarian dermoids mostly remain asymptomatic during pregnancy. Large dermoids may present with torsion, hemorrhage, or rupture. However, a dermoid cyst causing fetal growth restriction (FGR) and oligohydramnios is a very rare entity. The authors report a case of a large ovarian dermoid (15 x 12 cm) hampering intrauterine fetal growth. Due to the coronavirus disease-2019 (COVID-19) lockdown, the patient was unable to get ultrasound examinations in early gestation, and thereby, surgical intervention was not possible during the second trimester. As a result, this growing teratoma finally led to FGR by either exerting a pressure effect upon the uterus or by dwindling its blood supply. Copyright © The Author(s). 2022.

A case control investigation of COVID-19 associated mucormycosis in India.

BACKGROUND: Increased occurrence of mucormycosis during the second wave of COVID-19 pandemic in early 2021 in India prompted us to undertake a multi-site case-control investigation. The objectives were to examine the monthly trend of COVID-19 Associated Mucormycosis (CAM) cases among in-patients and to identify factors associated with development of CAM. METHODS: Eleven study sites were involved across India; archived records since 1st January 2021 till 30th September 2021 were used for trend analysis. The cases and controls were enrolled during 15th June 2021 to 30th September 2021. Data were collected using a semi-structured questionnaire. Among 1211 enrolled participants, 336 were CAM cases and 875 were COVID-19 positive non-mucormycosis controls. RESULTS: CAM-case admissions reached their peak in May 2021 like a satellite epidemic after a month of in-patient admission peak recorded due to COVID-19. The odds of developing CAM increased with the history of working in a dusty environment (adjusted odds ratio; aOR 3.24, 95% CI 1.34, 7.82), diabetes mellitus (aOR: 31.83, 95% CI 13.96, 72.63), longer duration of hospital stay (aOR: 1.06, 95% CI 1.02, 1.11) and use of methylprednisolone (aOR: 2.71, 95% CI 1.37, 5.37) following adjustment for age, gender, occupation, education, type of houses used for living, requirement of ventilatory support and route of steroid administration. Higher proportion of CAM cases required supplemental oxygen compared to the controls; use of non-rebreather mask (NRBM) was associated as a protective factor against mucormycosis compared to face masks (aOR: 0.18, 95% CI 0.08, 0.41). Genomic sequencing of archived respiratory samples revealed similar occurrences of Delta and Delta derivates of SARS-CoV-2 infection in both cases and controls. CONCLUSIONS: Appropriate management of hyperglycemia, judicious use of steroids and use of NRBM during oxygen supplementation among COVID-19 patients have the potential to reduce the risk of occurrence of mucormycosis. Avoiding exposure to dusty environment would add to such prevention efforts.

Antibody Response to ChAdOx1 nCoV-19 (AZD1222) Vaccine in Kidney Transplant Recipients.

Kidney transplant recipients (KTRs) are at a much higher risk of complications and death following COVID-19 and are poor vaccine responders. The data are limited on the immune response to Covishield® in KTRs. We prospectively recruited a cohort of 67 KTRs aged >18 between April 2021 and December 2021. Each participant was given two intramuscular doses of Covishield®, each of 0.5 mL, at an interval of 12 weeks. A blood specimen of 5.0 mL was collected from each participant at two points within a few days before administering the first dose of the vaccine and at any time between 4-12 weeks after administering the second dose. The sera were tested for anti-RBD antibody (ARAb) titre and neutralising antibody (NAb). An ACE2 competition assay was used as a proxy for virus neutralization. According to the prior COVID-19 infection, participants were grouped as (i) group A: prior symptomatic COVID-19 infection, (ii) group B: prior asymptomatic COVID-19 infection as evidenced by detectable ARAb in the prevaccination specimen, (iii) Group C: no prior infection with COVID-19, (iv) group D: Unclassified, i.e., participants had no symptoms suggestive of COVID-19, but their prevaccination specimen was not available for ARAb testing before vaccination. Fifty of sixty-seven participants (74.6%) provided paired specimens (group A 14, group B 27, and group C 9) and 17 participants (25.4%) provided only postvaccination specimens (group D). In the overall cohort (n = 67), 91% and 77.6% of participants developed ARAb and NAb, respectively. Their ARAb titre and NAb proportion were 2927 (520-7124) U/mL and 87.9 (24.4-93.2) %, respectively. Their median ARAb titre increased 65.6 folds, from 38.2 U/mL to 3137 U/mL. Similarly, the proportion of participants with NAb increased from 56% to 86%, and the NAb proportion raised 2.7 folds, from 23% to 91%. A comparison of vaccine response between the study groups showed that all those with or without prior COVID-19 infection showed a significant rise in ARAb titre (p < 0.05) and NAb proportion (p < 0.05) after the two doses of vaccine administration. The median value of folds rise in anti-RBD and NAb between groups A and B were comparable. Hence, ARAb is present in more than 3/4th of KTRs before the ChAdOx1 vaccine in India. The titer of ARAb and the proportion of NAb significantly increased after the two doses of the ChAdOx1 vaccine in KTRs.

A case control investigation of COVID-19 associated Mucormycosis in India (preprint)

Background: Increased occurrence of mucormycosis in India during the second wave of the COVID-19 pandemic in early 2021 in India subsequently prompted us to undertake a multi-site case-control investigation. The objectives were to examine the monthly trend of Covid-19 Associated Mucormycosis (CAM) cases among in-patients and to identify factors associated with it.Methods: Eleven study sites were involved across India and archived records since 1st January till 30th September, 2021 were used for trend analysis. The cases and controls were enrolled during 15th June 2021 to 30th September 2021. Data were collected using a semi-structured questionnaire. Among 1211 enrolled participants, 336 were CAM cases and 875 were COVID-19 positive non-mucormycosis controls. Results: Admitted CAM-case number reached highest point in May 2021 after a month of peak admission for COVID-19. Odds of developing CAM increased with the history of working in a dusty environment (adjusted odds ratio; aOR 3.24, 95%CI: 1.34, 7.82), diabetes mellitus (aOR: 31.83, 95%CI: 13.96, 72.63), longer duration of hospital stay (aOR: 1.06, 95%CI: 1.02, 1.11) and use of methyl prednisolone (aOR: 2.71, 95%CI: 1.37, 5.37) following adjustment for age, gender, occupation, education, type of houses used for living, requirement of ventilatory support and route of steroid administration. Higher proportion of CAM cases required supplemental oxygen compared to the controls; use of non-rebreather mask (NRBM) was associated as a protective factor against mucormycosis compared to face masks (aOR: 0.18, 95%CI: 0.08, 0.41). Genomic sequencing of archived respiratory samples showed similar presence of Delta and Delta derivates in both cases and controls.Conclusions: Appropriate management of hyperglycemia, judicious use of steroids and use of NRBM during oxygen supplementation among COVID-19 patients bear the potential to reduce the risk of occurrence of mucormycosis. Avoiding exposure to dusty environment would add to prevention efforts.  

A machine learning-based approach to determine infection status in recipients of BBV152 (Covaxin) whole-virion inactivated SARS-CoV-2 vaccine for serological surveys.

Data science has been an invaluable part of the COVID-19 pandemic response with multiple applications, ranging from tracking viral evolution to understanding the vaccine effectiveness. Asymptomatic breakthrough infections have been a major problem in assessing vaccine effectiveness in populations globally. Serological discrimination of vaccine response from infection has so far been limited to Spike protein vaccines since whole virion vaccines generate antibodies against all the viral proteins. Here, we show how a statistical and machine learning (ML) based approach can be used to discriminate between SARS-CoV-2 infection and immune response to an inactivated whole virion vaccine (BBV152, Covaxin). For this, we assessed serial data on antibodies against Spike and Nucleocapsid antigens, along with age, sex, number of doses taken, and days since last dose, for 1823 Covaxin recipients. An ensemble ML model, incorporating a consensus clustering approach alongside the support vector machine model, was built on 1063 samples where reliable qualifying data existed, and then applied to the entire dataset. Of 1448 self-reported negative subjects, our ensemble ML model classified 724 to be infected. For method validation, we determined the relative ability of a random subset of samples to neutralize Delta versus wild-type strain using a surrogate neutralization assay. We worked on the premise that antibodies generated by a whole virion vaccine would neutralize wild type more efficiently than delta strain. In 100 of 156 samples, where ML prediction differed from self-reported uninfected status, neutralization against Delta strain was more effective, indicating infection. We found 71.8% subjects predicted to be infected during the surge, which is concordant with the percentage of sequences classified as Delta (75.6%-80.2%) over the same period. Our approach will help in real-world vaccine effectiveness assessments where whole virion vaccines are commonly used.

A machine learning-based approach to determine infection status in recipients of BBV152 whole virion inactivated SARS-CoV-2 vaccine for serological surveys (preprint)

Data science has been an invaluable part of the COVID-19 pandemic response with multiple applications, ranging from tracking viral evolution to understanding the effectiveness of interventions. Asymptomatic breakthrough infections have been a major problem during the ongoing surge of Delta variant globally. Serological discrimination of vaccine response from infection has so far been limited to Spike protein vaccines used in the higher-income regions. Here, we show for the first time how statistical and machine learning (ML) approaches can discriminate SARS-CoV-2 infection from immune response to an inactivated whole virion vaccine (BBV152, Covaxin, India), thereby permitting real-world vaccine effectiveness assessments from cohort-based serosurveys in Asia and Africa where such vaccines are commonly used. Briefly, we accessed serial data on Anti-S and Anti-NC antibody concentration values, along with age, sex, number of doses, and number of days since the last vaccine dose for 1823 Covaxin recipients. An ensemble ML model, incorporating a consensus clustering approach alongside the support vector machine (SVM) model, was built on 1063 samples where reliable qualifying data existed, and then applied to the entire dataset. Of 1448 self-reported negative subjects, 724 were classified as infected. Since the vaccine contains wild-type virus and the antibodies induced will neutralize wild type much better than Delta variant, we determined the relative ability of a random subset of such samples to neutralize Delta versus wild type strain. In 100 of 156 samples, where ML prediction differed from self-reported uninfected status, Delta variant, was neutralized more effectively than the wild type, which cannot happen without infection. The fraction rose to 71.8% (28 of 39) in subjects predicted to be infected during the surge, which is concordant with the percentage of sequences classified as Delta (75.6%-80.2%) over the same period.

Leveraging machine learning and self-administered tests to predict COVID-19:An olfactory and gustatory dysfunction assessment through crowd-sourced data in India (preprint)

It has been established that smell and taste loss are frequent symptoms during COVID-19 onset. Most evidence stems from medical exams or self-reports. The latter is particularly confounded by the common confusion of smell and taste. Here, we tested whether practical smelling and tasting with household items can be used to assess smell and taste loss. We conducted an online survey and asked participants to use common household items to perform a smell and taste test. We also acquired generic information on demographics, health issues including COVID-19 diagnosis, and current symptoms. We developed several machine learning models to predict COVID-19 diagnosis. We found that the random forest classifier consistently performed better than other models like support vector machines or logistic regression. The smell and taste perception of self-administered household items were statistically different for COVID-19 positive and negative participants. The most frequently selected items that also discriminated between COVID-19 positive and negative participants were clove, coriander seeds, and coffee for smell and salt, lemon juice, and chillies for taste. Our study shows that the results of smelling and tasting household items can be used to predict COVID-19 illness and highlight the potential of a simple home-test to help identify the infection and prevent the spread.

Aftermath of fortnightly universal testing for severe acute respiratory corona virus-2 infection in maintenance hemodialysis patients.

INTRODUCTION: Asymptomatic maintenance hemodialysis patients with acute respiratory corona virus-2 (SARS-COV-2) are missed with pre-dialysis screening without testing. The possible ideal strategy of testing each patient before each shift with reverse transcription polymerase chain reaction (RT-PCR) is not feasible. We aimed to study the effectiveness of fortnightly screening with RT-PCR for SARS-CoV-2 in curbing transmission. METHODS: Between July 1, 2020 and September 30, 2020, all 273 patients receiving hemodialysis were subjected to fortnightly testing for SARS-Cov-2 in the unit to detect asymptomatic patients. The cost and effectiveness of universal testing in preventing transmission were analyzed using susceptible-infectious-removed (SIR) modeling assuming R0 of 2.2. RESULTS: Of 273 MHD patients, 55 (20.1%) found infected with SARS-CoV-2 over 3 months. Six (10.9%) were symptomatic, and 49 (89.1%) asymptomatic at the time of testing. Six (10.9%) asymptomatic patients develop symptoms later, and 43 (78.2%) remained asymptomatic. A total of seven (6.1%) HCWs also tested positive for the virus. Fortnightly universal testing is cost-effective, and SIR modeling proved effective in preventing person-to-person transmission. CONCLUSIONS: Repeated universal testing in maintenance hemodialysis patients detected 89% of asymptomatic SARS-CoV-2 patients over 3 months and appeared to be an effective strategy to prevent person-to-person transmission in the dialysis unit.

The differential impact of pediatric COVID-19 between high-income countries and low- and middle-income countries: A systematic review of fatality and ICU admission in children worldwide.

BACKGROUND: The overall global impact of COVID-19 in children and regional variability in pediatric outcomes are presently unknown. METHODS: To evaluate the magnitude of global COVID-19 death and intensive care unit (ICU) admission in children aged 0-19 years, a systematic review was conducted for articles and national reports as of December 7, 2020. This systematic review is registered with PROSPERO (registration number: CRD42020179696). RESULTS: We reviewed 16,027 articles as well as 225 national reports from 216 countries. Among the 3,788 global pediatric COVID-19 deaths, 3,394 (91.5%) deaths were reported from low- and middle-income countries (LMIC), while 83.5% of pediatric population from all included countries were from LMIC. The pediatric deaths/1,000,000 children and case fatality rate (CFR) were significantly higher in LMIC than in high-income countries (HIC) (2.77 in LMIC vs 1.32 in HIC; p < 0.001 and 0.24% in LMIC vs 0.01% in HIC; p < 0.001, respectively). The ICU admission/1,000,000 children was 18.80 and 1.48 in HIC and LMIC, respectively (p < 0.001). The highest deaths/1,000,000 children and CFR were in infants < 1 year old (10.03 and 0.58% in the world, 5.39 and 0.07% in HIC and 10.98 and 1.30% in LMIC, respectively). CONCLUSIONS: The study highlights that there may be a larger impact of pediatric COVID-19 fatality in LMICs compared to HICs.

Insights from a Pan India Sero-Epidemiological survey (Phenome-India Cohort) for SARS-CoV2 (preprint)

BackgroundIndia has been amongst the most affected nations during the SARS-CoV2 pandemic, with sparse data on country-wide spread of asymptomatic infections and antibody persistence. This longitudinal cohort study was aimed to evaluate SARS-CoV2 sero-positivity rate as a marker of infection and evaluate temporal persistence of antibodies with neutralization capability and to infer possible risk factors for infection. MethodsCouncil of Scientific and Industrial Research, India (CSIR) with its more than 40 laboratories and centers in urban and semi-urban settings spread across the country piloted the pan country surveillance. 10427 adult individuals working in CSIR laboratories and their family members based on voluntary participation were assessed for antibody presence and stability was analyzed over 6 months utilizing qualitative Elecsys SARS CoV2 specific antibody kit and GENScript cPass SARS-CoV2 Neutralization Antibody Detection Kit. Along with demographic information, possible risk factors were evaluated through self to be filled online forms with data acquired on blood group type, occupation type, addiction and habits including smoking and alcohol, diet preferences, medical history and transport type utilized. Symptom history and information on possible contact and compliance with COVID 19 universal precautions was also obtained. Findings1058 individuals (10{middle dot}14%) had antibodies against SARS-CoV2. A follow-up on 346 sero-positive individuals after three months revealed stable to higher antibody levels against SARS-CoV2 but declining plasma activity for neutralizing SARS-CoV2 receptor binding domain and ACE2 interaction. A repeat sampling of 35 individuals, at six months, revealed declining antibody levels while the neutralizing activity remained stable compared to three months. Majority of sero-positive individuals (75%) did not recall even one of nine symptoms since March 2020. Fever was the most common symptom with one-fourth reporting loss of taste or smell. Significantly associated risks for sero-positivity (Odds Ratio, 95% CI, p value) were observed with usage of public transport (1{middle dot}79, 1{middle dot}43 - 2{middle dot}24, 2{middle dot}81561E-06), occupational responsibilities such as security, housekeeping personnel etc. (2{middle dot}23, 1{middle dot}92 - 2{middle dot}59, 6{middle dot}43969E-26), non-smokers (1{middle dot}52, 1{middle dot}16 - 1{middle dot}99, 0{middle dot}02) and non-vegetarianism (1{middle dot}67, 1{middle dot}41 - 1{middle dot}99, 3{middle dot}03821E-08). An iterative regression analysis was confirmatory and led to only modest changes to estimates. Predilections for sero-positivity was noted with specific ABO blood groups -O was associated with a lower risk. InterpretationIn a first-of-its-kind study from India, we report the sero-positivity in a country-wide cohort and identify variable susceptible associations for contacting infection. Serology and Neutralizing Antibody response provides much-sought-for general insights on the immune response to the virus among Indians and will be an important resource for designing vaccination strategies. FundingCouncil of Scientific and Industrial Research, India (CSIR)

Development and Validation of an Attitude Scale towards Online Teaching and Learning for Higher Education Teachers.

The aim of this study is to develop an attitude scale towards online teaching and learning for higher education teachers. It included 687 participants (77 Professors, 67 Associate Professors and 543 Assistant Professors) from various colleges and Universities of India. This tool development was a part of research conducted to examine the preparedness of Indian higher education teachers during the period of lockdown due to Covid-19 pandemic. After reviewing related literature, initially 37 items related with the attitude of teachers towards online education were framed. Later on, 11 items were modified and four were deleted as per the opinions of the experts. The draft scale consisting of 33 items was administered on teachers and data was collected with the help of Google forms. Item analysis was carried out using t-value and r-value. Reliability of scale was determined by using Cronbach Alpha value (0.88) and split-halt correlation (0.82). After item analysis, the scale items were reduced to 30 and four factors were established as a result of factor analysis (Principal Component Analysis). Psychometric scale analyses have shown that this scale is valid, reliable and thus can be used in the evaluation of teachers 'attitudes towards online teaching and learning.