scholarly journals Silent SARS-CoV-2 Infections, Waning Immunity, Serology Testing, and COVID-19 Vaccination: A Perspective

2021 ◽  
Vol 12 ◽  
Author(s):  
Madhusudhanan Narasimhan ◽  
Lenin Mahimainathan ◽  
Jungsik Noh ◽  
Alagarraju Muthukumar
Keyword(s):  
Immune Status ◽  
Learning Algorithm ◽  
Clinical Manifestations ◽  
Severe Illness ◽  
Control And Prevention ◽  
General Mass ◽  
Waning Immunity ◽  
Data Driven Modeling ◽  
Serology Testing ◽  
New Machine

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus causes a spectrum of clinical manifestations, ranging from asymptomatic to mild, moderate, or severe illness with multi-organ failure and death. Using a new machine learning algorithm developed by us, we have reported a significantly higher number of predicted COVID-19 cases than the documented counts across the world. The sole reliance on confirmed symptomatic cases overlooking the symptomless COVID-19 infections and the dynamics of waning immunity may not provide ‘true’ spectrum of infection proportion, a key element for an effective planning and implementation of protection and prevention strategies. We and others have previously shown that strategic orthogonal testing and leveraging systematic data-driven modeling approach to account for asymptomatics and waning cases may situationally have a compelling role in informing efficient vaccination strategies beyond prevalence reporting. However, currently Centers for Disease Control and Prevention (CDC) does not recommend serological testing either before or after vaccination to assess immune status. Given the 27% occurrence of breakthrough infections in fully vaccinated (FV) group with many being asymptomatics and still a larger fraction of the general mass remaining unvaccinated, the relaxed mask mandate and distancing by CDC can drive resurgence. Thus, we believe it is a key time to focus on asymptomatics (no symptoms) and oligosymptomatics (so mild that the symptoms remain unrecognized) as they can be silent reservoirs to propagate the infection. This perspective thus highlights the need for proactive efforts to reevaluate the current variables/strategies in accounting for symptomless and waning fractions.

Personalized stratification of back to work risk amidst COVID-19: A machine learning approach (Preprint)

2020 ◽  
Author(s):  
Carson Lam ◽  
Jacob Calvert ◽  
Gina Barnes ◽  
Emily Pellegrini ◽  
Anna Lynn-Palevsky ◽  
...  
Keyword(s):  
Machine Learning ◽  
High Risk ◽  
Learning Algorithm ◽  
Severe Disease ◽  
High Specificity ◽  
Population Level ◽  
The United States ◽  
Health Condition ◽  
Available P ◽  
Severe Illness

BACKGROUND In the wake of COVID-19, the United States has developed a three stage plan to outline the parameters to determine when states may reopen businesses and ease travel restrictions. The guidelines also identify subpopulations of Americans that should continue to stay at home due to being at high risk for severe disease should they contract COVID-19. These guidelines were based on population level demographics, rather than individual-level risk factors. As such, they may misidentify individuals at high risk for severe illness and who should therefore not return to work until vaccination or widespread serological testing is available. OBJECTIVE This study evaluated a machine learning algorithm for the prediction of serious illness due to COVID-19 using inpatient data collected from electronic health records. METHODS The algorithm was trained to identify patients for whom a diagnosis of COVID-19 was likely to result in hospitalization, and compared against four U.S policy-based criteria: age over 65, having a serious underlying health condition, age over 65 or having a serious underlying health condition, and age over 65 and having a serious underlying health condition. RESULTS This algorithm identified 80% of patients at risk for hospitalization due to COVID-19, versus at most 62% that are identified by government guidelines. The algorithm also achieved a high specificity of 95%, outperforming government guidelines. CONCLUSIONS This algorithm may help to enable a broad reopening of the American economy while ensuring that patients at high risk for serious disease remain home until vaccination and testing become available.

Prognostic implication of hypocalcaemia in COVID-19: a systematic review

2021 ◽  
Vol 22 (2) ◽  
pp. 124-132
Author(s):  
T.A. Azeez ◽  
S. Lakoh ◽  
O.T. Bamidele ◽  
E. Ekhaiyeme ◽  
S.A. Nwosu
Keyword(s):  
Systematic Review ◽  
Prognostic Factors ◽  
Prognostic Factor ◽  
Clinical Manifestations ◽  
Severe Illness ◽  
Prognostic Implication ◽  
Poor Prognostic Factor ◽  
Medical Databases ◽  
Reactive Protein ◽  
Prognostic Implications

Coronavirus disease-2019 (COVID-19) has been declared as a pandemic affecting several millions of people worldwide. It has varied clinical manifestations ranging from asymptomatic to critical illness. It has led to the mortality of several affected individuals. However, the prognosis seems to vary from one person to the other and efforts are being made to identify the prognostic factors. Hypocalcaemia has been identified as a poor prognostic factor with a high frequency among individuals affected with COVID-19. This review aims to estimate the prevalence of hypocalcaemia among COVID-19 patients and identify the poor prognostic factors associated with the presence of hypocalcaemia in COVID-19 patients. Electronic medical databases were searched for publications on the prognostic implications of hypocalcaemia in COVID-19 infection, and relevant articles were selected for systematic review following PRISMA algorithm. The prevalence of hypocalcaemia among patients with COVID-19 was 40.0-74.4%. There was a significant association between the rate of hospital admission, intensive care unit (ICU) admission as well as septic shock and hypocalcaemia in patients with COVID-19. Hypocalcaemia is also associated with a higher mortality rate in these patients. COVID-19 patients with hypocalcaemia tend to have elevated C-reactive protein, interleukin6, alanine transaminase, procalcitonin, serum creatinine and low albumin.   Hypocalcaemia is common in COVID-19 patients and is a poor prognostic factor in these patients. Presence of hypocalcaemia is  associated with a severe illness and even death. Keywords: COVID-19; hypocalcaemia; prognosis; systematic review

scholarly journals Evidence of a wide gap between COVID-19 in humans and animal models: a systematic review

Critical Care ◽  
2020 ◽  
Vol 24 (1) ◽  
Author(s):  
Salleh N. Ehaideb ◽  
Mashan L. Abdullah ◽  
Bisher Abuyassin ◽  
Abderrezak Bouchama
Keyword(s):  
Animal Models ◽  
Nonhuman Primates ◽  
Clinical Manifestations ◽  
Full Recovery ◽  
Severe Illness ◽  
Original Research ◽  
Lung Pathology ◽  
Inclusion Criteria ◽  
Hypoxemic Respiratory Failure ◽  
Wide Gap

Abstract Background Animal models of COVID-19 have been rapidly reported after the start of the pandemic. We aimed to assess whether the newly created models reproduce the full spectrum of human COVID-19. Methods We searched the MEDLINE, as well as BioRxiv and MedRxiv preprint servers for original research published in English from January 1 to May 20, 2020. We used the search terms (COVID-19) OR (SARS-CoV-2) AND (animal models), (hamsters), (nonhuman primates), (macaques), (rodent), (mice), (rats), (ferrets), (rabbits), (cats), and (dogs). Inclusion criteria were the establishment of animal models of COVID-19 as an endpoint. Other inclusion criteria were assessment of prophylaxis, therapies, or vaccines, using animal models of COVID-19. Result Thirteen peer-reviewed studies and 14 preprints met the inclusion criteria. The animals used were nonhuman primates (n = 13), mice (n = 7), ferrets (n = 4), hamsters (n = 4), and cats (n = 1). All animals supported high viral replication in the upper and lower respiratory tract associated with mild clinical manifestations, lung pathology, and full recovery. Older animals displayed relatively more severe illness than the younger ones. No animal models developed hypoxemic respiratory failure, multiple organ dysfunction, culminating in death. All species elicited a specific IgG antibodies response to the spike proteins, which were protective against a second exposure. Transient systemic inflammation was observed occasionally in nonhuman primates, hamsters, and mice. Notably, none of the animals unveiled a cytokine storm or coagulopathy. Conclusions Most of the animal models of COVID-19 recapitulated mild pattern of human COVID-19 with full recovery phenotype. No severe illness associated with mortality was observed, suggesting a wide gap between COVID-19 in humans and animal models.

Immune response of guinea-pigs to chemically abbreviated prepatent Metastrongylus apri infection

Parasitology ◽  
1976 ◽  
Vol 72 (1) ◽  
pp. 13-18 ◽  
Author(s):  
V. Kumar ◽  
J. Mortelmans
Keyword(s):  
Guinea Pigs ◽  
Gamma Globulin ◽  
Immune Status ◽  
Clinical Manifestations ◽  
Control Group ◽  
Infection Dose ◽  
Infective Larvae ◽  
Worm Recovery ◽  
The Status ◽  
Experimental Group

The effect of chemical abbreviation of the primary infection dose (PID) of 160 infective larvae of Metastrongylus apri on the immune status of the guinea-pig host was studied. The criteria used for assessing the status of immunity consisted of clinical manifestations following administration of a challenge infection dose (CID) of 800 infective larvae of M. apri, the rate of worm recovery 15 days post-CID and the rate of mortality following administration of CID.Among the guinea-pigs of the main experimental group, where 15-day-old PID was abbreviated by two parenteral doses of levamisole*, a strong immunity to CID given 35 days post-PID was built-up. Against this, all the guinea-pigs of a control group, which did not receive PID, died between 16 and 22 days post-CID.The increase in serum gamma-globulin level of the guinea-pigs, where the PID was abbreviated chemically, suggested that the rise of this globulin fraction in the serum could be in some way related to the resistant state of guinea-pigs.

scholarly journals Leprosy with Atypical Skin Lesions Masquerading as Relapsing Polychondritis

2016 ◽  
Vol 2016 ◽  
pp. 1-3 ◽  
Author(s):  
Punit Pruthi ◽  
Hariharan Munganda ◽  
Amit Bangia ◽  
Uma Rani ◽  
Rajesh Budhiraja ◽  
...  
Keyword(s):  
Immune Status ◽  
Clinical Manifestations ◽  
Relapsing Polychondritis ◽  
Skin Lesions ◽  
Neurological Involvement ◽  
Inappropriate Therapy ◽  
External Ear ◽  
Unique Case ◽  
The Individual ◽  
Common Manifestation

Leprosy can present with a variety of clinical manifestations depending on the immune status of the individual. After dermatological and neurological involvement, rheumatic features specially various forms of arthritis are the third most common manifestation of the disease. We describe a unique case of a 22-year-old patient presenting with external ear involvement mimicking relapsing polychondritis along with inflammatory joint symptoms and skin lesions. Ear involvement in relapsing polychondritis characteristically is painful and spares the noncartilaginous ear lobules, in contrast to painless ear involvement in leprosy affecting the lobules as well. Histopathology confirmed the diagnosis, although the ear and skin lesions were not classical of leprosy. Such a presentation of leprosy closely mimicking relapsing polychondritis has not been described previously. Tissue diagnosis should always be attempted whenever possible in patients presenting with autoimmune features, so that inappropriate therapy with immunosuppressants is avoided.

scholarly journals Neutralizing antibody responses over time in demographically and clinically diverse individuals recovered from SARS-CoV-2 infection in the United States and Peru: A cohort study

PLoS Medicine ◽  
2021 ◽  
Vol 18 (12) ◽  
pp. e1003868
Author(s):  
Shelly Karuna ◽  
Shuying Sue Li ◽  
Shannon Grant ◽  
Stephen R. Walsh ◽  
Ian Frank ◽  
...  
Keyword(s):  
United States ◽  
Disease Severity ◽  
Disease Onset ◽  
Clinical Manifestations ◽  
The United States ◽  
Immune Defense ◽  
Severe Illness ◽  
Pseudotyped Virus ◽  
Wide Range ◽  
Over Time

Background People infected with Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) experience a wide range of clinical manifestations, from asymptomatic and mild illness to severe illness and death, influenced by age and a variety of comorbidities. Neutralizing antibodies (nAbs) are thought to be a primary immune defense against the virus. Large, diverse, well-characterized cohorts of convalescent individuals provide standardized values to benchmark nAb responses to past SARS-CoV-2 infection and define potentially protective levels of immunity. Methods and findings This analysis comprises an observational cohort of 329 HIV–seronegative adults in the United States (n = 167) and Peru (n = 162) convalescing from SARS-CoV-2 infection from May through October 2020. The mean age was 48 years (range 18 to 86), 54% of the cohort overall was Hispanic, and 34% identified as White. nAb titers were measured in serum by SARS-CoV-2.D614G Spike-pseudotyped virus infection of 293T/ACE2 cells. Multiple linear regression was applied to define associations between nAb titers and demographic variables, disease severity and time from infection or disease onset, and comorbidities within and across US and Peruvian cohorts over time. nAb titers peaked 28 to 42 days post-diagnosis and were higher in participants with a history of severe Coronavirus Disease 2019 (COVID-19) illness (p < 0.001). Diabetes, age >55 years, male sex assigned at birth, and, in some cases, body mass index were also independently associated with higher nAb titers, whereas hypertension was independently associated with lower nAb titers. nAb titers did not differ by race, underlying pulmonary disease or smoking. Two months post-enrollment, nAb ID50 (ID80) titers declined 3.5 (2.8)-fold overall. Study limitations in this observational, convalescent cohort include survivorship bias and missing early viral loads and acute immune responses to correlate with the convalescent responses we observed. Conclusions In summary, in our cohort, nAb titers after SARS-CoV-2 infection peaked approximately 1 month post-diagnosis and varied by age, sex assigned at birth, disease severity, and underlying comorbidities. Our data show great heterogeneity in nAb responses among people with recent COVID-19, highlighting the challenges of interpreting natural history studies and gauging responses to vaccines and therapeutics among people with recent infection. Our observations illuminate potential correlations of demographic and clinical characteristics with nAb responses, a key element for protection from COVID-19, thus informing development and implementation of preventative and therapeutic strategies globally. Trial registration ClinicalTrials.gov NCT04403880.

scholarly journals ConceptWAS: a high-throughput method for early identification of COVID-19 presenting symptoms

2020 ◽  
Author(s):  
Juan Zhao ◽  
Monika E Grabowska ◽  
Vern Eric Kerchberger ◽  
Joshua C. Smith ◽  
H. Nur Eken ◽  
...  
Keyword(s):  
Language Processing ◽  
High Throughput ◽  
Medical Center ◽  
Clinical Manifestations ◽  
Public Health Response ◽  
Clinical Notes ◽  
Sense Of Smell ◽  
Presenting Symptoms ◽  
Control And Prevention ◽  
The Difference

AbstractObjectiveIdentifying symptoms highly specific to COVID-19 would improve the clinical and public health response to infectious outbreaks. Here, we describe a high-throughput approach – Concept-Wide Association Study (ConceptWAS) that systematically scans a disease’s clinical manifestations from clinical notes. We used this method to identify symptoms specific to COVID-19 early in the course of the pandemic.MethodsUsing the Vanderbilt University Medical Center (VUMC) EHR, we parsed clinical notes through a natural language processing pipeline to extract clinical concepts. We examined the difference in concepts derived from the notes of COVID-19-positive and COVID-19-negative patients on the PCR testing date. We performed ConceptWAS using the cumulative data every two weeks for early identifying specific COVID-19 symptoms.ResultsWe processed 87,753 notes 19,692 patients (1,483 COVID-19-positive) subjected to COVID-19 PCR testing between March 8, 2020, and May 27, 2020. We found 68 clinical concepts significantly associated with COVID-19. We identified symptoms associated with increasing risk of COVID-19, including “absent sense of smell” (odds ratio [OR] = 4.97, 95% confidence interval [CI] = 3.21–7.50), “fever” (OR = 1.43, 95% CI = 1.28–1.59), “with cough fever” (OR = 2.29, 95% CI = 1.75–2.96), and “ageusia” (OR = 5.18, 95% CI = 3.02–8.58). Using ConceptWAS, we were able to detect loss sense of smell or taste three weeks prior to their inclusion as symptoms of the disease by the Centers for Disease Control and Prevention (CDC).ConclusionConceptWAS is a high-throughput approach for exploring specific symptoms of a disease like COVID-19, with a promise for enabling EHR-powered early disease manifestations identification.

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