Severity and mortality prediction models to triage Indian COVID-19 patients.

As the second wave in India mitigates, COVID-19 has now infected about 29 million patients countrywide, leading to more than 350 thousand people dead. As the infections surged, the strain on the medical infrastructure in the country became apparent. While the country vaccinates its population, opening up the economy may lead to an increase in infection rates. In this scenario, it is essential to effectively utilize the limited hospital resources by an informed patient triaging system based on clinical parameters. Here, we present two interpretable machine learning models predicting the clinical outcomes, severity, and mortality, of the patients based on routine non-invasive surveillance of blood parameters from one of the largest cohorts of Indian patients at the day of admission. Patient severity and mortality prediction models achieved 86.3% and 88.06% accuracy, respectively, with an AUC-ROC of 0.91 and 0.92. We have integrated both the models in a user-friendly web app calculator, https://triage-COVID-19.herokuapp.com/, to showcase the potential deployment of such efforts at scale.

Recruitment, Readiness, and Retention of Providers at a Field Hospital during the Pandemic.

In response to the coronavirus disease 2019 (COVID-19) pandemic, the State of Maryland established a 250-bed emergency response field hospital at the Baltimore Convention Center to support the existing healthcare infrastructure. To operationalize this hospital with 65 full-time equivalent (FTE) clinicians in less than four weeks, more than 300 applications were reviewed, 186 candidates were interviewed, and 159 clinicians were credentialed and onboarded. The key steps to achieve this undertaking involved employing multidisciplinary teams with experienced personnel, mass outreach, streamlined candidate tracking, pre-interview screening, utilizing all available expertise, expedited credentialing, and focused onboarding. To ensure staff preparedness, the leadership developed innovative team models, applied principles of effective team building, and provided 'just in time' training on COVID-19 and non-COVID-19 related topics to the staff. The leadership focused on staff safety and well-being, offered appropriate financial remuneration and provided leadership opportunities that allowed retention of staff.

Characteristics & outcomes of cancer patients with COVID-19: A multicentre retrospective study from India.

Background & objectives: High mortality has been observed in the cancer population affected with COVID-19 during this pandemic. We undertook this study to determine the characteristics and outcomes of cancer patients with COVID-19 and assessed the factors predicting outcome. Methods: Patients of all age groups with a proven history of malignancy and a recent diagnosis of SARS-CoV-2 infection based on nasal/nasopharyngeal reverse transcriptase (RT)-PCR tests were included. Demographic, clinical and laboratory variables were compared between survivors and non-survivors groups, with respect to observed mortality. Results: Between May 11 and August 10, 2020, 134 patients were included from the three centres and observed mortality was 17.1 per cent. The median age was 53 yr (interquartile range 39-61 yr) and thirty four patients (25%) were asymptomatic. Solid tumours accounted for 69.1 per cent and breast cancer was the most common tumour type (20%). One hundred and five patients (70.5%) had received chemotherapy within the past four weeks and 25 patients (19.3%) had neutropenia at presentation. On multivariate analysis, age [odds ratio (OR) 7.99 (95% confidence interval [CI] 1.18-54.00); P=0.033], haemoglobin [OR 6.28 (95% CI 1.07-37.04); P=0.042] neutrophil-lymphocyte ratio [OR 12.02 (95% CI 2.08-69.51); P=0.005] and baseline serum albumin [OR 18.52 (95% CI 2.80-122.27); P=0.002], were associated with higher mortality. Recent chemotherapy, haematological tumours type and baseline neutropenia did not affect the outcome. Interpretation & conclusions: Higher mortality in moderate and severe infections was associated with baseline organ dysfunction and elderly age. Significant proportion of patients were asymptomatic and might remain undetected.

High Sensitivity and NPV for BinaxNOW Rapid Antigen Test in Children at a Mass Testing Site during Prevalent Delta Variant Period.

SARS-CoV-2 continues to develop new, increasingly infectious variants including delta and omicron. We evaluated the efficacy of the Abbott BinaxNOW Rapid Antigen Test against Reverse Transcription PCR (RT-PCR) in 1,054 pediatric participants presenting to a high-volume Coronavirus Disease 2019 (COVID-19) testing site while the delta variant was predominant. Both tests utilized anterior nares swabs. Participants were grouped by COVID-19 exposure and symptom status. 5.2% of samples tested positive by RT-PCR for SARS-CoV-2. For all participants, sensitivity of the BinaxNOW was 92.7% (95% CI 82.4%-98.0%), and specificity was 98.0% (95% CI 97.0%-98.8%). For symptomatic participants, positive predictive value (PPV) was 72.7% (95% CI 54.5%-86.7%) and negative predictive value (NPV) was 99.2% (95% CI 98.2%-100%). Among asymptomatic participants, PPV was 71.4% (95% CI 53.7%-85.4%) and NPV was 99.7% (95% CI 99.0%-100%). Our reported sensitivity and NPV are higher than other pediatric studies, potentially because of higher viral load from the delta variant, but specificity and PPV are lower. IMPORTANCE The BinaxNOW rapid antigen COVID-19 test had a sensitivity of nearly 92% in both symptomatic and asymptomatic children when performed at a high-throughput setting during the more transmissible delta variant dominant period. The test may play an invaluable role in asymptomatic screening and keeping children safe in school.

Molecular signature of postmortem lung tissue from COVID-19 patients suggests distinct trajectories driving mortality.

To elucidate the molecular mechanisms that manifest lung abnormalities during severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections, we performed whole-transcriptome sequencing of lung autopsies from 31 patients with severe COVID-19 and ten uninfected controls. Using metatranscriptomics, we identified the existence of two distinct molecular signatures of lethal COVID-19. The dominant 'classical' signature (n=23) showed upregulation of the unfolded protein response, steroid biosynthesis and complement activation, supported by massive metabolic reprogramming leading to characteristic lung damage. The rarer signature (n=8) that potentially represents 'cytokine release syndrome' (CRS) showed upregulation of cytokines such as IL1 and CCL19, but absence of complement activation. We found that a majority of patients cleared SARS-CoV-2 infection, but they suffered from acute dysbiosis with characteristic enrichment of opportunistic pathogens such as Staphylococcus cohnii in 'classical' patients and Pasteurella multocida in CRS patients. Our results suggest two distinct models of lung pathology in severe COVID-19 patients, which can be identified through complement activation, presence of specific cytokines and characteristic microbiome. These findings can be used to design personalized therapy using in silico identified drug molecules or in mitigating specific secondary infections.

Healthcare Worker Mental Health After the Initial Peak of the COVID-19 Pandemic: a US Medical Center Cross-Sectional Survey.

BACKGROUND: There is a paucity of data on the mental health impact of the Coronavirus disease 2019 (COVID-19) pandemic on United States (US) healthcare workers (HCWs) after the first surge in the spring of 2020. OBJECTIVE: To determine the impact of the pandemic on HCWs, and the relationship between HCW mental health and demographics, occupational factors, and COVID-19 concerns. DESIGN: Cross-sectional survey in an urban medical center (September-November 2020) in Baltimore, MD, in the United States. PARTICIPANTS: A total of 605 HCWs (physicians, nurse practitioners, nurses, physician assistants, patient care technicians, respiratory therapists, social workers, mental health therapists, and case managers). MAIN MEASURES: Measures of mental health (Patient Health Questionnaire-2, Generalized Anxiety Disorder-7, PROMIS Sleep Disturbance 4a, Impact of Event Scale-Revised, Maslach Burnout Inventory-2 item, Connor-Davidson Resilience Scale-2 item), demographics, occupational factors, and COVID-19 related concerns. KEY RESULTS: Fifty-two percent of 1198 HCWs responded to the survey and 14.2% reported depression, 43.1% mild or higher anxiety, 31.6% sleep disturbance, 22.3% posttraumatic stress symptoms, 21.6% depersonalization, 46.0% emotional exhaustion, and 23.1% lower resilience. Relative to HCWs providing in-person care to COVID-19 infected patients none of their working days, those doing so all or most days were more likely to experience worse depression (adjusted odds ratio, 3.9; 95% CI, 1.3-11.7), anxiety (aOR, 3.0; 95% CI, 1.4-6.3), possible PTSD symptoms (aOR, 2.6; 95% CI, 1.1-5.8), and higher burnout (aOR, 2.6; 95% CI, 1.1-6.0). Worse mental health in several domains was associated with higher health fear (aORs ranged from 2.2 to 5.0), job stressors (aORs ranged from 1.9 to 4.0), perceived social stigma/avoidance (aORs ranged from 1.8 to 2.9), and workplace safety concerns (aORs ranged from 1.8 to 2.8). CONCLUSIONS: US HCWs experienced significant mental health symptoms eight months into the pandemic. More time spent providing in-person care to COVID-19-infected patients and greater COVID-19-related concerns were consistently associated with worse mental health.

Genetic Risk Prediction of COVID-19 Susceptibility and Severity in the Indian Population.

Host genetic variants can determine their susceptibility to COVID-19 infection and severity as noted in a recent Genome-wide Association Study (GWAS). Given the prominent genetic differences in Indian sub-populations as well as differential prevalence of COVID-19, here, we compute genetic risk scores in diverse Indian sub-populations that may predict differences in the severity of COVID-19 outcomes. We utilized the top 100 most significantly associated single-nucleotide polymorphisms (SNPs) from a GWAS by Pairo-Castineira et al. determining the genetic susceptibility to severe COVID-19 infection, to compute population-wise polygenic risk scores (PRS) for populations represented in the Indian Genome Variation Consortium (IGVC) database. Using a generalized linear model accounting for confounding variables, we found that median PRS was significantly associated (p < 2 x 10-16) with COVID-19 mortality in each district corresponding to the population studied and had the largest effect on mortality (regression coefficient = 10.25). As a control we repeated our analysis on randomly selected 100 non-associated SNPs several times and did not find significant association. Therefore, we conclude that genetic susceptibility may play a major role in determining the differences in COVID-19 outcomes and mortality across the Indian sub-continent. We suggest that combining PRS with other observed risk-factors in a Bayesian framework may provide a better prediction model for ascertaining high COVID-19 risk groups and to design more effective public health resource allocation and vaccine distribution schemes.

Detrimental effect of diabetes and hypertension on the severity and mortality of COVID-19 infection: A multi-center case-control study from India.

AIMS: This study aims to find a quantitative association between the presence of co-existing diabetes mellitus (DM) and/or hypertension (HTN) with COVID-19 infection severity and mortality. METHODS: A total of 813 patients with a positive COVID-19 were included. A case-control design was used to dissect the association between DM and HTN with COVID-19 severity and mortality. RESULTS: According to MOHFW guidelines, 535 (65.7%) patients had mild, 160 (19.7%) patients had moderate, and 118 (14.5%) patients had severe disease outcomes including mortality in 52 patients. Age, Neutrophil%, and Diabetes status were significantly associated with severe COVID-19 infection. After adjusting for age, patients with diabetes were 2.46 times more likely to have severe disease (Chi-squared = 18.89, p-value<0.0001) and 2.11 times more likely to have a fatal outcome (Chi-squared = 6.04, p-value = 0.014). However, we did not find evidence for Hypertension modifying the COVID-19 outcomes in Diabetic patients. CONCLUSION: COVID-19 severity and mortality both were significantly associated with the status of DM and its risk may not be modified by the presence of HTN.

Rationale and design of the Prone Position and Respiratory Outcomes in Non-intubated COVID-19 PatiEnts: The "PRONE" Study.

While benefits of prone position in mechanically-ventilated patients have been well-described, a randomized-control trial to determine the effects of prone positioning in awake, spontaneously-breathing patients with an acute pneumonia has not been previously conducted. Prone Position and Respiratory Outcomes in Non-Intubated COVID-19 PatiEnts: the "PRONE" Study (PRONE) was conducted in non-intubated hospitalized patients with coronavirus disease 2019 (COVID-19) pneumonia as defined by respiratory rate ≥ 20/min or an oxyhemoglobin saturation (SpO2) ≤ 93% without supplemental oxygen [1]. The PRONE trial was designed to investigate the effects of prone positioning on need for escalation in respiratory support, as defined by need for transition to a higher acuity level of care, increased fraction of inspired oxygen (FiO2), or the initiation of invasive mechanical ventilation. Secondary objectives were to assess the duration of effect of prone positioning on respiratory parameters such as respiratory rate and SpO2, as well as other outcomes such as time to discharge or transition in level of care.