Effect of COVID-19 vaccine on long-COVID: A 2-year follow-up observational study from hospitals in north India (preprint)

IntroductionLong-COVID syndrome encompasses a constellation of fluctuating, overlapping systemic symptoms after COVID. We know that vaccination reduces the risk of hospitalization and death but not of re-infections. How these vaccines impact long-COVID is under debate. The current study was designed to analyze the patterns of long-COVID amongst vaccinated and unvaccinated hospitalized patients during the three waves in India. MethodsThe computerized medical records of the patients admitted to a group of hospitals in the National Capital Region of Delhi with a nasopharyngeal swab positive RT-PCR for SARS-CoV-2, during the three distinct COVID-19 waves, were accessed. Because of large numbers, every 3rd case from the data sheet for the wave-1 and wave-2 but all cases admitted during wave-3 were included because of small numbers (total 6676). The selected patients were telephonically contacted in April 2022 for symptoms and their duration of long-COVID and their vaccination status. Of these, 6056 (90.7%) responded. These were divided into fully vaccinated who received both doses of COVID vaccine at least 14 days before admission (913) and unvaccinated at the time of admission (4616). Others and deaths were excluded. "Symptom-weeks" was calculated as the sum of weeks of symptoms in case of two or more symptoms. The statistical significance was tested, and odds ratio (unadjusted and adjusted) were calculated by logistic regression. ResultsNearly 90% of COVID-19 patients reported at least one symptom irrespective of their vaccination status. Almost three-fourths of these had symptoms lasting up to a month but nearly 15% reported a duration a least 4 weeks including 11% even exceeding one year. During wave-3, significantly more vaccinated patients reported short term post-acute sequelae of COVID-19 than did the unvaccinated group. The cases with diabetes and hypertension had higher odds of reporting at least one symptom when the effect of vaccination, age, sex, severity, and length of stay was adjusted. The fully vaccinated cases had reduced length of stay in the hospital and had a milder disease. Most common symptoms reported by both the groups were fatigue (17.0%), insomnia (15.1%) and myalgia (15%). There were significant differences in the duration and the type of long-COVID symptoms across the three waves, and the presence of comorbidities between the vaccinated and the unvaccinated groups but overall no difference could be detected. No significant difference was seen between the cases receiving covishield and covaxin. ConclusionsNearly 15% reported symptoms of duration exceeding 4 weeks including 11% exceeding one year. There were significant differences in the specific symptoms with some more common in the vaccinated and some others more common in the unvaccinated but overall the vaccination or the type of vaccine did not significantly alter either the incidence or the duration of long COVID.

Relative Importance of Various Inflammatory Markers and Their Critical Thresholds for COVID-19 Mortality (preprint)

BackgroundVarious inflammatory markers are commonly assessed in many patients to help in the management of COVID-19 patients. It is not clear, though, how much risk of mortality their different levels of elevations entail, and which marker signifies more risk than others and how much. This study was undertaken to describe their levels and to answer these questions regarding eight inflammatory markers, namely, CRP, D-dimer, ferritin, IL-6, LDH, CPK, troponin-I. MethodsThe data were retrieved from the electronic records of 19852 CoViD-19 patients admitted to a chain of hospitals in north India from March 2020 to July 2021. Levels for most markers were available for more than 10,000 patients. In view of widely different ranges of values of different markers, we divided their values into quintiles (Qs) and studied the pattern of mortality and for running the logistic regression. In addition, logarithm transformation was also tried. The statistical distribution of the values was compared by Mann-Whitney test. Relative importance was judged by the mortality rates, area under the ROC curves (AUROCs), and the odds ratios. ResultsAlthough the mortality increased with decreasing ALC and increasing level of all the other markers, more than 70% survived even with levels in the extreme quintile. The adjusted odds ratio was the highest (7.62) for the Q5 levels of IL-6, closely followed by D-dimer (OR = 6.04). The AUROC was the highest (0.817) for LDH and the least (0.612) for CPK. However, the optimal cut-off for any marker could correctly classify not more than 80% deaths and the multivariable logistic regression could correctly classify patients with mortality in less than 24% cases. ConclusionAlthough elevated levels of all the markers and low values of ALC were significant risk factor but no firm evidence was available for any of the eight markers to be a major indicator of the mortality in COVID-19 unless they reach to a critical threshold. Among those studied, D-Dimer (>192 ng/mL) followed by IL-6 (>4.5 pg/mL) had stronger association with mortality even with moderate and higher end of the normal levels and LDH (>433 U/L) and troponin-I (>0.002ng/mL) with only steeply increased levels. Ferritin had modest association, and CPK, CRP and ALC were a relatively poor risk of mortality.

Secondary infections modify the overall course of hospitalized COVID-19 patients: A retrospective study from a network of hospitals across North India (preprint)

IntroductionSARS-CoV-2 infection increases the risk of secondary bacterial and fungal infections and contributes to adverse outcomes. The present study was undertaken to get better insights into the extent of secondary bacterial and fungal infections in Indian hospitalized patients and to assess how these alter the course of COVID-19 so that the control measures can be suggested. MethodsThis is a retrospective, multicentre study where data of all RT-PCR positive COVID-19 patients was accessed from Electronic Health Records (EHR) of a network of 10 hospitals across 5 North Indian states, admitted during the period from March 2020 to July 2021.The data included demographic profile of patients, clinical characteristics, laboratory parameters, treatment modalities, and outcome in those with secondary infections (SIs) and those without SIs. Spectrum of SIS was also studied in detail. ResultsOf 19852 RT-PCR positive SARS-CO2 patients admitted during the study period, 1940 (9.8%) patients developed SIs. Patients with SIs were 8 years older on average (median age 62.6 years versus 54.3 years; P<0.001) than those without SIs. The risk of SIs was significantly (p < 0.001) associated with age, severity of disease at admission, diabetes, ICU admission, and ventilator use. The most common site of infection was urinary tract infection (UTI) (41.7%), followed by blood stream infection (BSI) (30.8%), sputum/BAL/ET fluid (24.8%), and the least was pus/wound discharge (2.6%). As many as 13.4% had infections with more than organism and 34.1% patients had positive cultures from more than one site. Gram negative bacilli (GNB) were the commonest organisms (63.2%), followed by Gram positive cocci (GPC) (19.6%) and fungus (17.3%). Most of the patients with SIs were on multiple antimicrobials - the most commonly used were the BL-BLI for GNBs (76.9%) followed by carbapenems (57.7%), cephalosporins (53.9%) and antibiotics carbapenem resistant entreobacteriace (47.1%). The usage of emperical antibiotics for GPCs was in 58.9% and of antifungals in 56.9% of cases, and substantially more than the results obtained by culture. The average stay in hospital for patients with SIs was twice than those without SIs (median 13 days versus 7 days). The overall mortality in the group with SIs (40.3%) was more than 8 times of that in those without SIs (4.6%). Only 1.2% of SI patients with mild COVID-19 at presentation died, while 17.5% of those with moderate disease and 58.5% of those with severe COVID-19 died (P< 0.001). The mortality was highest in those with BSI (49.8%), closely followed by those with HAP (47.9%), and then UTI and SSTI (29.4% each). The mortality rate where only one microorganism was identified was 37.8% and rose to 56.3% in those with more than one microorganism. The mortality in cases with only one site of infection was 28.8%, which steeply rose to 62.5% in cases with multiple sites of infection. The mortality in diabetic patients with SIs was 45.2% while in non-diabetics it was 34.3% (p < 0.001). ConclusionsSecondary bacterial and fungal infections can complicate the course of almost 10% of COVID-19 hospitalised patients. These patients tend to not only have a much longer stay in hospital, but also a higher requirement for oxygen and ICU care. The mortality in this group rises steeply by as much as 8 times. The group most vulnerable to this complication are those with more severe COVID-19 illness, elderly, and diabetic patients. Varying results in different studies suggest that a region or country specific guideline be developed for appropriate use of antibiotics and antifungals to prevent their overuse in such cases. Judicious empiric use of combination antimicrobials in this set of vulnerable COVID-19 patients can save lives.

Profile of Mucormycosis Cases from a Network of Hospitals in North India Amidst COVID-19 Pandemic (preprint)

Incidence of mucormycosis suddenly surged in India after the second wave of COVID-19. This is a crippling disease and needs to be studied in detail to understand the disease, its course, and the outcomes. Between 1st March and 15th July 2021, our network of hospitals in North India received a total of 155 cases of COVID-associated mucormycosis cases as all of them reported affliction by COVID-19 earlier or concurrent. Their records were retrieved from the Electronic Health Records system of the hospitals and their demographics, clinical features, treatments, and outcomes were studied. More than 80% (125 cases) had proven disease and the remaining 30 were categorized as possible mucormycosis as per the EORTC criteria. More than two-thirds (69.0%) of the cases were males and the mean age was 53 years for either sex. Nearly two-thirds (64.5%) had symptoms of nose and jaws and 42.6% had eye involvement. Some had multiple symptoms. As many as 78.7% had diabetes and 91.6% gave history of use of steroids during COVID-19 treatment. The primary surgery was functional endoscopic sinus surgery (FESS) (83.9%). Overall mortality was 16.8%, which is one-and-a-half times the mortality in hospitalized COVID-19 patients in the corresponding population. Occurrence of mucormycosis was associated with diabetes and use of steroids, but mortality was not associated with either of them. Cases undergoing surgery and on antifungal had steeply lower mortality (11.9% vs. 50.0%, P < 0.001) than those who were exclusively on antifungal drugs. Treatment by different drugs did not make much of a difference in mortality.

Long Term Health Consequences of COVID-19 in Hospitalized Patients from North India: A follow up study of upto 12 months (preprint)

Purpose: Long COVID syndrome is now a real and pressing public health concern. We cannot reliably predict who will recover quickly or suffer with mild debilitating long COVID 19 symptoms or battle life threatening complications. In order to address some of these questions, we studied the presence of symptoms and various correlates in COVID 19 patients who were discharged from hospital, 3 months and up to 12 months after acute COVID 19 illness. Methods: This is an observational follow up study of RT PCR confirmed COVID 19 patients admitted at 3 hospitals in north India between April August 2020. Patients were interviewed telephonically using a questionnaire regarding the post COVID symptoms. The first tele calling was done in the month of September 2020, which corresponded to 4 to 16 weeks after disease onset. All those who reported presence of long COVID symptoms, were followed up with a second call, in the month of March 2021, corresponding to around 9 to 12 months after the onset of disease. Results: Of 990 patients who responded to the first call, 615 (62.2%) had mild illness, 227 (22.9%) had moderate and 148 (15.0%) had severe COVID 19 illness at the time of admission. Nearly 40% (399) of these 990 patients reported at least one symptom at that time. Of these 399 long COVID patients, 311 (almost 78%) responded to the second follow up. Nearly 8% reported ongoing symptomatic COVID, lasting 1 to 3 months and 32% patients having post COVID phase with symptoms lasting 3 to 12 months. Nearly 11% patients continued to have at least one symptom even at the time of the second interview (9 to 12 months after the disease onset). Overall, we observed Long COVID in almost 40% of our study group. Incidence of the symptoms in both the follow ups remained almost same across age groups, gender, severity of illness at admission and presence of comorbidity, with no significant association with any of them. Most common symptoms experienced in long COVID phase in our cohort were fatigue, myalgia, neuro psychiatric symptoms like depression, anxiety, brain fog and sleep disorder, and breathlessness. Fatigue was found to be significantly more often reported in the elderly population and in those patients who had a severe COVID 19 illness at the time of admission. Persistence of breathlessness was also reported significantly more often in those who had severe disease at the onset. The overall median duration of long COVID symptoms was 16.9 weeks with inter quartile range of 12.4 to 35.6 weeks. The duration of symptom resolution was not associated with age, gender or comorbidity but was significantly associated with severity of illness at the time of admission (P=0.006). Conclusions: Long COVID is now being recognized as a new disease entity, which includes a constellation of symptoms. Long COVID was in almost 40% of our study group with no correlation to age, gender, comorbidities or to the disease severity. The duration of symptom resolution was significantly associated with severity of illness at the time of admission (P = 0.006). In our study, all patients reported minor symptoms such as fatigue, myalgia, neuro psychiatric symptoms like depression, anxiety, brain fog and sleep disorder and persistence of breathlessness. Severe organ damage was not reported by our subjects. This might be the longest post COVID follow up study on a sample of nearly 1000 cases from India.

Differentials in the characteristics of COVID-19 cases in Wave-1 and Wave-2 admitted to a network of hospitals in North India (preprint)

Second wave of COVID 19 pandemic in India came with unexpected quick speed and intensity, creating an acute shortage of beds, ventilators, and oxygen at the peak of occurrence. This may have been partly caused by emergence of new variant delta. Clinical experience with the cases admitted to hospitals suggested that it is not merely a steep rise in cases but also possibly the case profile is different. This study was taken up to investigate the differentials in the characteristics of the cases admitted in the second wave versus those admitted in the first wave. Records of a total of 14398 cases admitted in the first wave (2020) to our network of hospitals in north India and 5454 cases admitted in the second wave (2021) were retrieved, making it the largest study of this kind in India. Their demographic profile, clinical features, management, and outcome was studied. Age sex distribution of the cases in the second wave was not much different from those admitted in the first wave but the patients with comorbidities and those with greater severity had larger share. Level of inflammatory markers was more adverse. More patients needed oxygen and invasive ventilation. ICU admission rate remained nearly the same. On the positive side, readmissions were lower, and the duration of hospitalization was slightly less. Usage of drugs like remdesivir and IVIG was higher while that of favipiravir and tocilizumab was lower. Steroid and anticoagulant use remained high and almost same during the two waves. More patients had secondary bacterial and fungal infections in Wave 2. Mortality increased by almost 40% in Wave 2, particularly in the younger patients of age less than 45 years. Higher mortality was observed in those admitted in wards, ICU, with or without ventilator support and those who received convalescent plasma. No significant demographic differences in the cases in these two waves, indicates the role of other factors such as delta variant and late admissions in higher severity and more deaths. Comorbidity and higher secondary bacterial and fungal infections may have contributed to increased mortality.

Effectiveness of Convalescent Plasma Therapy in Indian Patients with COVID-19 (preprint)

Background: Convalescent plasma (CP) is being used as a treatment option in hospitalized patients with COVID-19. Till date, there is conflicting evidence on efficacy of CP in reducing COVID-19 related mortality.Objective: to evaluate the effect of CP on 28-day mortality reduction in patients with COVID-19.Methods: We did a multi-center, retrospective case control observational study from 1st May 2020 to 31st August 2020. A total of 1079 adult patients with moderate and severe COVID-19 requiring oxygen, were reviewed. Of these, 694 patients were admitted to ICU. Out of these, 333 were given CP along with best supportive care and remaining 361 received best supportive care only.Results: In the overall group of 1079 patients, mortality in plasma vs no plasma group was statistically not significant (22.4% vs 18.5%; p = 0.125). However, in patients with COVID-19 admitted to ICU, mortality was significantly lower in plasma group (25.5% vs 33.2%; p = 0.026). This benefit of reduced mortality was most seen in age group 60 to 74 years (26.7% vs 43.0%; p = 0.004), driven mostly by females of this age group (23.1% vs 53.5%; p = 0.013). Significant difference in mortality was observed in patients with one comorbidity (22.3% vs 36.5%; p = 0.004). Moreover, patients on ventilator had significantly lower mortality in the plasma arm (37.2% vs 49.3%; p = 0.009); particularly so for patients on invasive mechanical ventilation (63.9% vs 82.9%; p = 0.014).Conclusion: The use of CP reduced mortality in COVID-19 elderly patients admitted in ICU, above 60 years of age, particularly females, those with comorbidities and especially those who required some form of ventilation.Funding Statement: None to declare.Declaration of Interests: None to declare. Ethics Approval Statement: The manuscript has ethical clearance and approval from the ethics committee of the institute . A copy of the approval letter is attached. (Reference number isRS/MSSH/GMRCHS/IEC/IM/20-16).

Clinical Profile of First 1000 COVID-19 Cases Admitted at Tertiary Care Hospitals and the Correlates of their Mortality: An Indian Experience (preprint)

ObjectiveTo describe the clinical profile and factors leading to increased mortality in coronavirus disease (COVID-19) patients admitted to a group of hospitals in India. DesignA records-based study of the first 1000 patients with a positive result on real-time reverse transcriptase-polymerase-chain-reaction assay for SARS-CoV-2 admitted to our facilities. Various factors such as demographics, presenting symptoms, co-morbidities, ICU admission, oxygen requirement and ventilator therapy were studied. ResultsOf the 1000 patients, 24 patients were excluded due to lack of sufficient data. Of the remaining 976 in the early phase of the epidemic, males were admitted twice as much as females (67.1% and 32.9%, respectively). Mortality in this initial phase was 10.6% and slightly higher for males and steeply higher for older patients. More than 8% reported no symptoms and the most common presenting symptoms were fever (78.3%), productive cough (37.2%), and dyspnea (30.64%). More than one-half (53.6%) had no co-morbidity. The major co-morbidities were hypertension (23.7%), diabetes without (15.4%), and with complications (9.6%). The co-morbidities were associated with higher ICU admissions, greater use of ventilators as well as higher mortality. A total of 29.9% were admitted to the ICU, with a mortality rate of 32.2%. Mortality was steeply higher in those requiring ventilator support (55.4%) versus those who never required ventilation (1.4%). The total duration of hospital stay was just a day longer in patients admitted to the ICU than those who remained in wards. ConclusionMale patients above the age of 60 and with co-morbidities faced the highest rates of mortality. They should be admitted to the hospital in early stage of the disease and given aggressive treatment to help reduce the morbidity and mortality associated with COVID-19.

Preliminary Estimates of Years of Life Lost (YLL) Due to COVID-19 in India (preprint)

More than 7 million cases of COVID have been detected in India by the middle of October 2020 and more than 100 thousand deaths have occurred. In this communication, we present an estimate the years of life lost (YLL) due to COVID-19 so far and the projection for the full year so that the health damage by this new disease can be compared with some other ailments. The YLL by one premature death is the expectation of life at that age. To calculate YLL, age-wise distribution of COVID cases and deaths was obtained from the official sources of the government of India. Similar calculations were done for the general population from all causes for comparison. A total of more than 2 million years of life have already lost due to COVID-19 and the pattern indicates that we may end up with nearly 4 million YLL due to this disease in India. This is nearly 20 years lost per COVID death, 303 years lost per 1000 cases of COVID, and about 3 years lost per 1000 population in the full year. The age-group 50-59 years has been particularly affected. Other important findings are summarized as key messages. The years of life lost so far and anticipated in full year are enormous but may still be lower compared with some other causes such as road injuries.

Relation of Doubling Time and Reproduction Number with Testing Rate for Corona Infections in India (preprint)

There is a general feeling that increased testing has a salutary effect on the course of the current coronavirus epidemic. We quantify the relationship of testing rate with the doubling time and reproduction number in India, estimate the effect, and use these relationships to make projections for the near future.

CoViD-19 Epidemic in India and Projections: Is Relief in Sight? (preprint)

Background: Projection of cases and deaths in an epidemic such as CoViD-19 is hazardous and the early projections were way-off the actual pattern. However, we now have actual data for more than 50 consecutive days in India that can be effectively used for projection. Methods: We closely track the trend and use the same pattern for projection. We call this Empirical Model. We also fit a Theoretical Model based on a Gamma function on the pattern of some of the previous epidemics. Results: The Empirical Model predicts the peak around the fourth week of May and the near end of the epidemic by the end of June 2020. The maximum number of active cases is likely to be nearly 75,000 during the second week of June. This would mean a peak demand of nearly 15,000 beds and nearly 4000 ventilators. The case-fatality based on those who have reached an outcome was nearly 10% in the first week of May and is likely to remain at this level for some time. Theoretical Model projected a peak of nearly 2500 new cases per day in the second week of May that seems to have been already breached. This model predicts the near end of the epidemic by the middle of July 2020.