Circulatory cytokine levels as a predictor of disease severity in COVID-19: a study from Western India

Background: Inflammatory response in COVID-19 responsible for acute respiratory distress syndrome (ARDS) and multiorgan failure and play a major role in morbidity and mortality of patients. The present study was undertaken to assess serum level of cytokines and its association with other inflammatory markers and disease severity in COVID-19 and hence their prognostic significance.

Analysis of predictors and outcomes of COVID-19 patients requiring ICU admission from COVID 19 (preprint)

BackgroundSevere Corona virus disease (COVID-19) is associated with high mortality. Although single centre intensive care units (ICU) have reported clinical characteristics and outcomes, no large scale multicentric study from India has been published. The present retrospective, multi-centre study was aimed to describe the predictors and outcomes of COVID-19 patients requiring ICU admission from COVID-19 Registry of Indian council of Medical Research (ICMR), India.MethodsProspectively collected data from multiple participating institutions was entered in the electronic National Clinical Registry of COVID 19. We enrolled patients aged>18 years with COVID-19 pneumonia requiring ICU admission between March 2020 and August 2021. Exclusion criteria were negative RT PCR, death within 24 hours of ICU admission, or patients with incomplete data in the registry Their demographic characteristics, laboratory variables, ICU severity indices, treatment strategies and outcomes were analysed.ResultsA total of 5865 patients, with mean age 56±15 years, with 3840/5865 (65.4%) men, were enrolled in the ICMR registry.. Overall mortality was 2535/5865 (43.5%). Non-survivors were older than survivors (58.2±15.4 years vs 53.6 ±14.7 years; P=0.001). Non-survivors had multiple comorbidities (n=1951, 52.9%) with hypertension (47.2%) and diabetes (45.6%) being the most common, higher creatinine (1.6 ± P=0.001, high D-dimer (1.56 vs 1.37, P=0.001), higher CT severity index (16.8±5.2 vs 13.5 ±5.47 ) compared to  survivors. Non survivors had longer hospital and ICU stay (P=0.001). On multivariate regression analysis, high NLR (HR 1.017, 95% CI 1.005- 1.029, P=0.001), high CRP (HR 1.008, 95% CI 1.006- 1.010, P=0.001), high D dimer ((HR 1.089, 95% CI 1.065- 1.113, P=0.001) were associated with mechanical ventilation while younger age, (HR 0.974, CI 0.965-0.983, p=0.001), high D dimer (HR-1.014, CI 1.001-1.027, P=0.035) and use of prophylactic LMWH (HR 0.647, CI 0.527-0.794, p=0.001) were independently associated with mortality. ConclusionIn this large retrospective study of 5865 critically ill COVID 19 patients admitted to ICU, overall mortality was 2535/5865 (43.5%). Age, high D dimer, CT Severity score and use of prophylactic LMWH were independently associated with mortality. 

A preventive study on hydroxychloroquine prophylaxis against COVID-19 in health care workers at a tertiary care center in north India

Background: The menace of COVID-19 has put a huge burden on health care system predisposing health care workers engaged in management to COVID-19 infections. The nonavailability of effective drug against COVID-19 warrants extra cover as prophylactic therapy for health care workers, especially against transmission from asymptomatic patients. Hydroxychloroquine (HCQ) for prophylaxis of COVID-19 had been advocated by some researchers. Hence, in this project, evaluation of HCQ as preventive strategy for healthcare workers against COVID-19 infection was studied. Materials and Methods: HCQ was prescribed as a prophylactic therapy as per the advisory of National Task Force of Indian Council of Medical Research, India. The data regarding consumption profile, COVID-19 infection and adverse drug reaction profile of HCQ in healthcare workers was collected.

Clinical profile of Covid-19 infected patients admitted in a tertiary care hospital in north India

Background: The novel coronavirus (Covid-19) continues to wreck havoc across China, European countries, USA and now seems to gain a strong foothold in India. The aim of this report is to describe the clinical profiles of these Covid-19 infected patients admitted in Sawai Mansingh Hospital(S.M.S), Jaipur ranging from their age, sex, travel history, clinical symptoms, laboratory evaluation, radiological characteristics, treatment provided along with common side effects and the final outcome. The described cases are one of the earliest cases of Covid-19 in the Indian subcontinent.

Clinico epidemiological profile of Omicron variant of SARS CoV2 in Rajasthan (preprint)

Background: Omicron a new variant of SARS COV2 was first detected in November 2021. This was believed to be highly transmissible and evade immunity as a result urgent need was felt to screen all positive, identify Omicron cases and isolate them to prevent spread of infection and study their clinico-epidemiological profile. Methodology: All positive cases detected in state of Rajasthan during November to January beginning were selected for next generation sequencing. Processing was done as per protocol on Ion Torrent S5 system for 1210 samples and bioinformatics analysis was done. Results: Among the 1210 samples tested 762(62.9%) were Delta/Delta like and other lineages, 291(24%) were Omicron and 157(12.9%) were invalid or repeat samples. Within a month the proportion of Delta and other variants was reversed, from zero omicron became 81% and delta and other variants 19%, initially all omicron cases were international travellers and their contacts but soon community transmission was seen. Majority of omicron patients were asymptomatic (56.7%) or had mild disease (33%), 9.2% had moderate symptoms and 2(0.7%) had severe disease requiring hospitalization, of which one (0.3%) died and rest (99.7%) recovered. History of vaccination was seen in 81.1%, of previous infection in 43.2%. Among the Omicron cases BA.1 (62.8%) was the predominant lineage followed by BA.2(23.7%) and B.1.529 (13.4%), however rising trends were seen initially for BA.1 and later for BA.2 also. Conclusion: In very short time Omicron has spread in community and has taken over the pre-existing Delta/Delta like and other lineages, it evades immunity, but the good part is most of the cases were asymptomatic or had mild disease and mortality rate was very low. Key words; SARSCoV2, NGS, Omicron

High throughput detection and genetic epidemiology of SARS-CoV-2 using COVIDSeq next-generation sequencing

The rapid emergence of coronavirus disease 2019 (COVID-19) as a global pandemic affecting millions of individuals globally has necessitated sensitive and high-throughput approaches for the diagnosis, surveillance, and determining the genetic epidemiology of SARS-CoV-2. In the present study, we used the COVIDSeq protocol, which involves multiplex-PCR, barcoding, and sequencing of samples for high-throughput detection and deciphering the genetic epidemiology of SARS-CoV-2. We used the approach on 752 clinical samples in duplicates, amounting to a total of 1536 samples which could be sequenced on a single S4 sequencing flow cell on NovaSeq 6000. Our analysis suggests a high concordance between technical duplicates and a high concordance of detection of SARS-CoV-2 between the COVIDSeq as well as RT-PCR approaches. An in-depth analysis revealed a total of six samples in which COVIDSeq detected SARS-CoV-2 in high confidence which were negative in RT-PCR. Additionally, the assay could detect SARS-CoV-2 in 21 samples and 16 samples which were classified inconclusive and pan-sarbeco positive respectively suggesting that COVIDSeq could be used as a confirmatory test. The sequencing approach also enabled insights into the evolution and genetic epidemiology of the SARS-CoV-2 samples. The samples were classified into a total of 3 clades. This study reports two lineages B.1.112 and B.1.99 for the first time in India. This study also revealed 1,143 unique single nucleotide variants and added a total of 73 novel variants identified for the first time. To the best of our knowledge, this is the first report of the COVIDSeq approach for detection and genetic epidemiology of SARS-CoV-2. Our analysis suggests that COVIDSeq could be a potential high sensitivity assay for the detection of SARS-CoV-2, with an additional advantage of enabling the genetic epidemiology of SARS-CoV-2.

The epidemiological and trending pattern of ncovid-19 in the state of Rajasthan, India

Purpose: The present study was undertaken to investigate the behavioral distribution pattern and progression of coronavirus disease 2019 (COVID-19) across age and gender in the state of Rajasthan, India, inherently distinctive and native to localized part of the globe giving requisite information and paraphernalia to designate advisory board of the state to design and frame customized policy for demands of the state as per the trending pattern relative to age and sex distribution, profile of new infected cases, recovery rate, and case fatality rate.

Hydroxychloroquine in Rheumatological Disorders: The Potential Buffer Against COVID-19 (preprint)

Background: Hydroxychloroquine (HCQ) is a well prescribed drug in rheumatological disorders. The repurposed drug HCQ was also used for SARS-CoV-2 as prophylactic and therapeutic strategy in Indian context. The present study aimed to describe that either rheumatological disorder had threatening effect on COVID-19 or advantageous particularly with the use of HCQ.Methods: The present retrospective, observational study included 4100 COVID-19 patients of SMS Medical college and Hospitals, Jaipur, India. The patient’s data (after anonymizing and de-linking) concerning underlying chronic medical illness especially focused on rheumatological disorders was extracted from their medical records. The data from rheumatological patients concerning medical history, clinical manifestation, severity of COVID-19, extension of disease, treatment history and outcome were collected and analyzed.Results: Out of large study cohort of 4100 patients of COVID-19, rheumatological disorders found only in seven patients (0.17%) including rheumatoid arthritis (RA) in four patients, systemic lupus erythematous (SLE) in two patients and Wegener granulomatosis in one patient. All rheumatologic patients of study group had symptomatic presentations with one patient had critical, another one had severe, two had moderate and three patients had mild illness. Only one patient was on hydroxychloroquine (HCQ) treatment (200 mg daily) who presented with mild illness of COVID-19. One patient of SLE with lupus nephritis on glucocorticoids and immunosuppressive agents but not on HCQ, developed critical illness and later on succumbed to life.Conclusion: The present study showed that patients with rheumatological disorders might not be at increased risk of acquiring COVID-19 or a more severe disease. Moreover, HCQ has some protective role against COVID-19 in patients of rheumatological disorders and it also play an important role in reducing the disease severity.Funding Statement: The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not for profit sectors.Declaration of Interests: All authors report no potential conflicts. All authors have submitted the ICMJE Form for Disclosure of Potential.Ethics Approval Statement: This study approved by ethical and research committee of SMS medical college and Hospital, Jaipur, India.

Convalescent plasma in the management of moderate COVID-19 in India: An open-label parallel-arm phase II multicentre randomized controlled trial (PLACID Trial) (preprint)

ObjectivesConvalescent plasma (CP) as a passive source of neutralizing antibodies and immunomodulators is a century-old therapeutic option used for the management of viral diseases. We investigated its effectiveness for the treatment of COVID-19. DesignOpen-label, parallel-arm, phase II, multicentre, randomized controlled trial. SettingThirty-nine public and private hospitals across India. ParticipantsHospitalized, moderately ill confirmed COVID-19 patients (PaO2/FiO2: 200-300 or respiratory rate > 24/min and SpO2 [≤] 93% on room air). InterventionParticipants were randomized to either control (best standard of care (BSC)) or intervention (CP + BSC) arm. Two doses of 200 mL CP was transfused 24 hours apart in the intervention arm. Main Outcome MeasureComposite of progression to severe disease (PaO2/FiO2< 100) or all-cause mortality at 28 days post-enrolment. ResultsBetween 22nd April to 14th July 2020, 464 participants were enrolled; 235 and 229 in intervention and control arm, respectively. Composite primary outcome was achieved in 44 (18.7%) participants in the intervention arm and 41 (17.9%) in the control arm [aOR: 1.09; 95% CI: 0.67, 1.77]. Mortality was documented in 34 (13.6%) and 31 (14.6%) participants in intervention and control arm, respectively [aOR) 1.06 95% CI: -0.61 to 1.83]. InterpretationCP was not associated with reduction in mortality or progression to severe COVID-19. This trial has high generalizability and approximates real-life setting of CP therapy in settings with limited laboratory capacity. A priori measurement of neutralizing antibody titres in donors and participants may further clarify the role of CP in management of COVID-19. Trial registrationThe trial was registered with Clinical Trial Registry of India (CTRI); CTRI/2020/04/024775.

High throughput detection and genetic epidemiology of SARS-CoV-2 using COVIDSeq next generation sequencing (preprint)

The rapid emergence of coronavirus disease 2019 (COVID-19) as a global pandemic affecting millions of individuals globally has necessitated sensitive and high-throughput approaches for the diagnosis, surveillance and for determining the genetic epidemiology of SARS-CoV-2. In the present study, we used the COVIDSeq protocol, which involves multiplex-PCR, barcoding and sequencing of samples for high-throughput detection and deciphering the genetic epidemiology of SARS-CoV-2. We used the approach on 752 clinical samples in duplicates, amounting to a total of 1536 samples which could be sequenced on a single S4 sequencing flow cell on NovaSeq 6000. Our analysis suggests a high concordance between technical duplicates and a high concordance of detection of SARS-CoV-2 between the COVIDSeq as well as RT-PCR approaches. An in-depth analysis revealed a total of six samples in which COVIDSeq detected SARS-CoV-2 in high confidence which were negative in RT-PCR. Additionally, the assay could detect SARS-CoV-2 in 21 samples and 16 samples which were classified inconclusive and pan-sarbeco positive respectively suggesting that COVIDSeq could be used as a confirmatory test. The sequencing approach also enabled insights into the evolution and genetic epidemiology of the SARS-CoV-2 samples. The samples were classified into a total of 3 clades. This study reports two lineages B.1.112 and B.1.99 for the first time in India. This study also revealed 1,143 unique single nucleotide variants and added a total of 73 novel variants identified for the first time. To the best of our knowledge, this is the first report of the COVIDSeq approach for detection and genetic epidemiology of SARS-CoV-2. Our analysis suggests that COVIDSeq could be a potential high sensitivity assay for detection of SARS-CoV-2, with an additional advantage of enabling genetic epidemiology of SARS-CoV-2.

Patient flow dynamics in hospital systems during times of COVID-19: Cox proportional hazard regression analysis. (preprint)

Objectives: The present study is aimed at estimating patient flow dynamical parameters and requirement of hospital beds. Secondly, the effects of age and gender on parameters were evaluated. Patients and Methods: In this retrospective cohort study, 987 COVID-19 patients were enrolled from SMS Medical College, Jaipur (Rajasthan, India). The survival analysis was carried out from 29 Feb to 19 May 2020 for two hazards – ‘Hazard 1’ was hospital discharge and ‘Hazard 2’ was hospital death. The starting point for survival analysis of the two hazards was considered to be hospital admission . The survival curves were estimated and additional effects of age and gender were evaluated using Cox proportional hazard regression analysis. Results: The Kaplan Meier estimates of lengths of hospital stay  (Median =10 days, IQR =10 days) and median survival rate ( more than 60 days due to large amount of censored data) were obtained. The Cox Model for ‘Hazard 1’ showed no significant effect of age and gender on duration of hospital stay. Similarly, the Cox Model 2 showed no significant difference of gender on survival rate. The case fatality rate 8.1 % , recovery rate 78.8% , mortality rate 0.10 per 100 person--days and hospital admission rate 0.35 per 105 person-days were estimated.Conclusion : The study estimates hospital bed requirement based on patient flow dynamic parameters. Furthermore, study concludes that average length of  hospital stay were similar for patients of both genders and all age groups.

Evolving trajectories of COVID-19 curves in India: Prediction using autoregressive integrated moving average modeling. (preprint)

The forecasting of Coronavirus Disease-19 (COVID-19) dynamics is a centerpiece in evidence based disease management. Numerous approaches that use mathematical modeling have been used to predict the outcome of the pandemic, including data driven models, empirical and hybrid models. This study was aimed at prediction COVID-19 evolution in India using a model based on  autoregressive integrated moving average (ARIMA). Retrieving real time data from the Johns Hopkins dashboard from 11 Mar 2020 to 25 Jun 2020 (N = 107 time points) to fit the model. The ARIMA (1,3,2) and ARIMA (3,3,1) model fit best for cumulative cases and deaths respectively with minimum Akaike Informaton Criteria. The prediction of cumulative cases and deaths for next 10 days from 26 Jun 2020 to 05 Jul 2020 showed a trend toward continuous increment. The predicted root mean square error (PredRMSE) and base root mean square error (BaseRMSE) of ARIMA(1,3,2) model was 21137 and 166330 respectively. Similarly, PredRMSE and BaseRMSE of ARIMA(3,3,1) model was 668.7 and 5431 respectively. We propose that data on COVID-19 be collected continuously, and that forecasting continue in real time. The COVID-19 forecast assist government in resource optimization and evidence based decision making for a subsequent state of affairs.

Evidence based decision making and COVID-19: what a posteriori probability distributions speak. (preprint)

Background: In the absence of a vaccine for coronavirus disease-19, the management of the current pandemic revolves around public health measures such as social distancing, lockdown, and contact tracing. A number of epidemiological models are used in decision making and for generating research intelligence. The models require information regarding the structures of social contact between different ages and genders. The present study fosters evidence-based decision making by estimating various a posteriori probability distributions from data of COVID-19 patients. Patients and Methods: In this retrospective observational study, 987 real-time RT-PCR SARS CoV-2 positive patients from SMS Medical College, Jaipur, India were enrolled after approval of the institutional ethics committee. The data regarding age, gender, and outcome were collected from case sheets. The univariate and bivariate distributions of COVID-19 cases with respect to age, gender, and outcome were estimated. The age distribution of COVID-19 cases was compared with the age distribution of general population using goodness of fit c2 test. The independence of attributes in bivariate distributions was evaluated using the chi square test for independence.Results: The age group ‘25-29’ has shown highest probability of COVID-19 cases (P[25-29] = 0.14, 95% CI: 0.12- 0.16). The men (P[Male] = 0.62, 95%CI: 0.59-0.65) were dominant sufferers. The most common outcome was recovery (P[Recovered] = 0.79, 95%CI: 0.76-0.81) followed by admitted cases (P[Active]= 0.13, 95%CI: 0.11-0.15) and death (P[Death] = 0.08, 95%CI: 0.06-0.10). The age distribution of COVID-19 cases differs significantly from the age distribution of the general population (c2 = 399.04, p < 0.001). The bivariate distribution of COVID-19 across age and outcome was not independent (c2 =106.21, df = 32, p < 0.001).Conclusion: The age, gender, and outcome distributions helps in evaluating disease dynamics and the social structure of the community. The knowledge of patterns of disease frequency helps in optimum allocation of limited resources and manpower. The study provides information for various epidemiological models, to decide the duration of lockdown. 

Relationship Between ABO Blood group Phenotypes and nCOVID-19 Susceptibility – A Retrospective Observational Study (preprint)

Background: Since the outbreak of coronavirus disease-19 research has been continued to explore multiple facets of the disease. The objective of the present study is to evaluate the relationship between blood group phenotypes and COVID-19 susceptibility.Methods: In this hospital based, retrospective observational study 132 COVID-19 patients were enrolled from SMS Medical Hospital in Jaipur, India after receiving approval from the institutional ethics committee. The ABO, Rh and Kell blood group phenotypes along with demographic data of the patients were recorded. The observed proportions of ‘A’ , ‘B’, ‘AB’, ‘O’, ‘Rh’, and ‘Kell’ blood groups in COVID-19 patients were compared against the expected proportions (the null hypothesis) of the general population using Pearson’s chi-squared test and partition analysis.Results: There were significant differences between observed and expected frequency for the ABO and Kell blood phenotypes. Further partition analysis of ABO phenotypes showed that the group ‘A’ phenotypes were more susceptible to COVID-19. The Kell negatives were also more susceptible. The blood groups ‘AB’, ‘B’, ‘O’, and ‘Rh’ showed no significant difference for susceptibility to COVID-19.Conclusion: The study shows a relationship between ABO, Rh, and Kell blood groups and COVID-19 susceptibility. The application of these relationships in clinics should be explored in future studies.