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.

Impact of lockdown on self-care management among patients with type 2 Diabetes Mellitus residing in Lucknow city, India – A cross-sectional study

Objective To assess the effect of nationwide lockdown and its associated repercussion on the self-care management of Type 2 Diabetes Mellitus (T2D). Methods Response from 1406 diabetic patients was collected against a 16 item questionnaire. Data was collected on diabetic self-management practices, behavioral aspects, psychological implications, drug availability and awareness towards the pandemic. Emphasis was on choices made by patients in the absence of guidance from physicians and impact of stress and blood sugar levels on other variables. The data was analyzed using Chi-square tests at P < 0.05. Results About 27% were under stress, 14.7% and 30.8% reported a change in dietary and sleep pattern. About 83% could not consult a doctor and as a result 13% stopped taking medications. Patients with stress slept less, observed a change in dietary patterns and had uncontrolled blood sugar levels (P = 0.0001). On the contrary those without stress spent time with family and were occupied with a hobby (P = 0.0001). Those with controlled blood sugar levels exercised more and had normal sleep patterns. Fluctuation with doses was observed among those with uncontrolled blood sugar levels in the absence of physicians consultation (P = 0.001). Conclusion Even though majority of study participants were not able to consult their physicians yet nearly 2/3rd were practicing Self-Monitoring of Blood Glucose (SMBG), more than half were exercising regularly, more than 2/3rds continued taking their medications and majority were following appropriate diet pattern. Stress management is a key factor during these times due to its association with other variables.

Preparedness and Mitigation by projecting the risk against COVID-19 transmission using Machine Learning Techniques (preprint)

The outbreak of COVID-19 is first identified in China, which later spread to various parts of the globe and was pronounced pandemic by the World Health Organization (WHO). The disease of transmissible person-to-person pneumonia caused by the extreme acute respiratory coronavirus 2 syndrome (SARS-COV-2, also known as COVID-19), has sparked a global warning. Thermal screening, quarantining, and later lockdown were methods employed by various nations to contain the spread of the virus. Though exercising various possible plans to contain the spread help in mitigating the effect of COVID-19, projecting the rise and preparing to face the crisis would help in minimizing the effect. In the scenario, this study attempts to use Machine Learning tools to forecast the possible rise in number of cases by considering the data of daily new cases. To capture the uncertainty, three different techniques: (i) Decision Tree algorithm, (ii) Support Vector Machine algorithm, and (iii) Gaussian process regression are used to project the data and capture the possible deviation. Based on the projection of new cases, recovered cases, deceased cases, medical facilities, population density, number of test conducted, and facilities of services, are considered to define the criticality index (CI). CI is used to classify all the districts of country in the regions of high risk, low risk and moderate risk. An online dashpot is created which updates the data on daily bases for next four weeks. The prospective suggestions of this study would aid in planning the strategies to apply the lockdown/ any other plan for any country, which can take other parameters to define the CI.

Analysis of SteraMist ionized hydrogen peroxide technology as a method for sterilizing N95 respirators and other personal protective equipment (preprint)

ObjectiveThe COVID-19 pandemic has led to widespread shortages of personal protective equipment (PPE) for healthcare workers, including filtering facepiece respirators (FFRs) such as N95 masks. These masks are normally intended for single use, but their sterilization and subsequent reuse could substantially mitigate a world-wide shortage. DesignQuality assurance. SettingA sealed environment chamber installed in the animal facility of an academic medical center. InterventionsOne to five sterilization cycles using ionized hydrogen peroxide (iHP), generated by SteraMist(R) equipment (TOMI; Frederick, MD). Main outcome measuresPersonal protective equipment, including five N95 mask models from three manufacturers, were evaluated for efficacy of sterilization following iHP treatment (measured with bacterial spores in standard biological indicator assemblies). Additionally, N95 masks were assessed for their ability to efficiently filter particles down to 0.3{micro}m and for their ability to form an airtight seal using a quantitative fit test. Filtration efficiency was measured using ambient particulate matter at a university lab and an aerosolized NaCl challenge at a National Institute for Occupational Safety and Health (NIOSH) pre-certification laboratory. ResultsThe data demonstrate that N95 masks sterilized using SteraMist iHP technology retain function up to five cycles, the maximum number tested to date. Some but not all PPE could also be sterilized using an iHP environmental chamber, but pre-treatment with a handheld iHP generator was required for semi-enclosed surfaces such as respirator hoses. ConclusionsA typical iHP environment chamber with a volume of ~80 m3 can treat ~7000 masks per day, as well as other items of PPE, making this an effective approach for a busy medical center.

Disposable N95 Masks Pass Qualitative Fit-Test But Have Decreased Filtration Efficiency after Cobalt-60 Gamma Irradiation (preprint)

The current COVID-19 pandemic has led to a dramatic shortage of masks and other personal protective equipment (PPE) in hospitals around the globe [1]. One component of PPE that is in particular demand are disposable N95 face masks. To alleviate this, many methods of N95 mask sterilization have been studied and proposed with the hope of being able to safely reuse masks [2]. Two major considerations must be made when re-sterilizing masks: (1) the sterilization method effectively kills pathogens, penetrating into the fibers of the mask, and (2) the method does not degrade the operational integrity of the N95 filters. We studied Cobalt-60 (60Co) gamma irradiation as a method of effective sterilization without inducing mask degradation. Significant literature exists supporting the use of gamma radiation as a sterilization method, with viral inactivation of SARS-CoV reported at doses of at most 10 kGy [3], with other studies supporting 5 kGy for many types of viruses [4]. However, concerns have been raised about the radiation damaging the fiber material within the mask, specifically by causing cross-linking of polymers, leading to cracking and degradation during fitting and/or deployment [5, 6]. A set of 3M 8210 and 9105 masks were irradiated using MITs 60Co irradiator. Three masks of each type received 0 kiloGray (kGy), 10 kGy and 50 kGy of approximately 1.3 MeV gamma radiation from the circular cobalt sources, at a dose rate of 2.2kGy per hour. Following this sterilization procedure, the irradiated masks passed a OSHA Gerson Qualitative Fit Test QLFT 50 (saccharin apparatus) [7] when donned correctly, performed at the Brigham and Womens Hospital, in a blinded study repeated in triplicate. However, the masks filtration of 0.3 {micro}m particles was significantly degraded, even at 10 kGy. These results suggest against gamma, and possibly all ionizing radiation, as a method of disposable N95 sterilization. Even more importantly, they argue against using the qualitative fit test alone to assess mask integrity.

Apps Gone Rogue: Maintaining Personal Privacy in an Epidemic (preprint)

Containment, the key strategy in quickly halting an epidemic, requires rapid identification and quarantine of the infected individuals, determination of whom they have had close contact with in the previous days and weeks, and decontamination of locations the infected individual has visited. Achieving containment demands accurate and timely collection of the infected individual's location and contact history. Traditionally, this process is labor intensive, susceptible to memory errors, and fraught with privacy concerns. With the recent almost ubiquitous availability of smart phones, many people carry a tool which can be utilized to quickly identify an infected individual's contacts during an epidemic, such as the current 2019 novel Coronavirus crisis. Unfortunately, the very same first-generation contact tracing tools have been used to expand mass surveillance, limit individual freedoms and expose the most private details about individuals. We seek to outline the different technological approaches to mobile-phone based contact-tracing to date and elaborate on the opportunities and the risks that these technologies pose to individuals and societies. We describe advanced security enhancing approaches that can mitigate these risks and describe trade-offs one must make when developing and deploying any mass contact-tracing technology. With this paper, our aim is to continue to grow the conversation regarding contact-tracing for epidemic and pandemic containment and discuss opportunities to advance this space. We invite feedback and discussion.