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1.
Frontiers in neurology ; 13, 2022.
Article in English | EuropePMC | ID: covidwho-2045862

ABSTRACT

Objective An alarming proportion (>30%) of patients affected by SARS-CoV-2 (COVID-19) continue to experience neurological symptoms, including headache, dizziness, smell and/or taste abnormalities, and impaired consciousness (brain fog), after recovery from the acute infection. These symptoms are self-reported and vary from patient to patient, making it difficult to accurately diagnose and initiate a proper treatment course. Objective measures to identify and quantify neural deficits underlying the symptom profiles are lacking. This study tested the hypothesis that oculomotor, vestibular, reaction time, and cognitive (OVRT-C) testing using eye-tracking can objectively identify and measure functional neural deficits post COVID-19 infection. Methods Subjects diagnosed with COVID-19 (n = 77) were tested post-infection with a battery of 20 OVRT-C tests delivered on a portable eye-tracking device (Neurolign Dx100). Data from 14 tests were compared to previously collected normative data from subjects with similar demographics. Post-COVID subjects were also administered the Neurobehavioral Symptom Inventory (NSI) for symptom evaluation. Results A significant percentage of post COVID-19 patients (up to 86%) scored outside the norms in 12 out of 14 tests, with smooth pursuit and optokinetic responses being most severely affected. A multivariate model constructed using stepwise logistic regression identified 6 metrics as significant indicators of post-COVID patients. The area under the receiver operating characteristic curve (AUC) was 0.89, the estimated specificity was 98% (with cutoff value of 0.5) and the sensitivity was 88%. There were moderate but significant correlations between NSI domain key variables and OVRT-C tests. Conclusions This study demonstrates the feasibility of OVRT-C testing to provide objective measures of neural deficits in people recovering from COVID-19 infection. Such testing may serve as an efficient tool for identifying hidden neurological deficits post COVID-19, screening patients at risk of developing long COVID, and may help guide rehabilitation and treatment strategies.

2.
Commun Med (Lond) ; 1: 33, 2021.
Article in English | MEDLINE | ID: covidwho-1860415

ABSTRACT

Background: It is estimated that up to 80% of infections caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are asymptomatic and asymptomatic patients can still effectively transmit the virus and cause disease. While much of the effort has been placed on decoding single nucleotide variation in SARS-CoV-2 genomes, considerably less is known about their transcript variation and any correlation with clinical severity in human hosts, as defined here by the presence or absence of symptoms. Methods: To assess viral genomic signatures of disease severity, we conducted a systematic characterization of SARS-CoV-2 transcripts and genetic variants in 81 clinical specimens collected from symptomatic and asymptomatic individuals using multi-scale transcriptomic analyses including amplicon-seq, short-read metatranscriptome and long-read Iso-seq. Results: Here we show a highly coordinated and consistent pattern of sgRNA expression from individuals with robust SARS-CoV-2 symptomatic infection and their expression is significantly repressed in the asymptomatic infections. We also observe widespread inter- and intra-patient variants in viral RNAs, known as quasispecies frequently found in many RNA viruses. We identify unique sets of deletions preferentially found primarily in symptomatic individuals, with many likely to confer changes in SARS-CoV-2 virulence and host responses. Moreover, these frequently occurring structural variants in SARS-CoV-2 genomes serve as a mechanism to further induce SARS-CoV-2 proteome complexity. Conclusions: Our results indicate that differential sgRNA expression and structural mutational burden are highly correlated with the clinical severity of SARS-CoV-2 infection. Longitudinally monitoring sgRNA expression and structural diversity could further guide treatment responses, testing strategies, and vaccine development.

3.
Commun Biol ; 5(1): 439, 2022 05 11.
Article in English | MEDLINE | ID: covidwho-1839575

ABSTRACT

SARS-CoV-2 variants shaped the second year of the COVID-19 pandemic and the discourse around effective control measures. Evaluating the threat posed by a new variant is essential for adapting response efforts when community transmission is detected. In this study, we compare the dynamics of two variants, Alpha and Iota, by integrating genomic surveillance data to estimate the effective reproduction number (Rt) of the variants. We use Connecticut, United States, in which Alpha and Iota co-circulated in 2021. We find that the Rt of these variants were up to 50% larger than that of other variants. We then use phylogeography to show that while both variants were introduced into Connecticut at comparable frequencies, clades that resulted from introductions of Alpha were larger than those resulting from Iota introductions. By monitoring the dynamics of individual variants throughout our study period, we demonstrate the importance of routine surveillance in the response to COVID-19.


Subject(s)
COVID-19 , SARS-CoV-2 , COVID-19/epidemiology , Genomics , Humans , Pandemics , SARS-CoV-2/genetics , United States/epidemiology
4.
Cell Rep Med ; 3(4): 100583, 2022 04 19.
Article in English | MEDLINE | ID: covidwho-1735052

ABSTRACT

The SARS-CoV-2 Delta variant rose to dominance in mid-2021, likely propelled by an estimated 40%-80% increased transmissibility over Alpha. To investigate if this ostensible difference in transmissibility is uniform across populations, we partner with public health programs from all six states in New England in the United States. We compare logistic growth rates during each variant's respective emergence period, finding that Delta emerged 1.37-2.63 times faster than Alpha (range across states). We compute variant-specific effective reproductive numbers, estimating that Delta is 63%-167% more transmissible than Alpha (range across states). Finally, we estimate that Delta infections generate on average 6.2 (95% CI 3.1-10.9) times more viral RNA copies per milliliter than Alpha infections during their respective emergence. Overall, our evidence suggests that Delta's enhanced transmissibility can be attributed to its innate ability to increase infectiousness, but its epidemiological dynamics may vary depending on underlying population attributes and sequencing data availability.


Subject(s)
COVID-19 , SARS-CoV-2 , COVID-19/epidemiology , Humans , New England/epidemiology , Public Health , SARS-CoV-2/genetics
5.
Intern Emerg Med ; 17(3): 675-684, 2022 04.
Article in English | MEDLINE | ID: covidwho-1460480

ABSTRACT

In this study of patients admitted with COVID-19, we examined differences between the two waves in patient characteristics and outcomes. Data were collected from the first COVID-19 admission to the end of study (01/03/2020-31/03/2021). Data were adjusted for age and sex and presented as odds ratios (OR) with 95% confidence intervals (CI). Among 12,471 admissions, 1452 (11.6%) patients were diagnosed with COVID-19. On admission, the mean (± SD) age of patients with other causes was 68.3 years (± 19.8) and those with COVID-19 in wave 1 was 69.4 years (± 18.0) and wave 2 was 66.2 years (± 18.4). Corresponding ages at discharge were 67.5 years (± 19.7), 63.9 years (± 18.0) and 62.4 years (± 18.0). The highest proportion of total admissions was among the oldest group (≥ 80 years) in wave 1 (35.0%). When compared with patients admitted with other causes, those admitted with COVID-19 in wave 1 and in wave 2 were more frequent in the 40-59 year band: 20.8, 24.6 and 30.0%; consisted of more male patients: 47.5, 57.6 and 58.8%; and a high LACE (Length of stay, Acuity of admission, Comorbidity and Emergency department visits) index (score ≥ 10): 39.4, 61.3 and 50.3%. Compared to wave-2 patients, those admitted in wave 1 had greater risk of death in hospital: OR = 1.58 (1.18-2.12) and within 30 days of discharge: OR = 2.91 (1.40-6.04). Survivors of COVID-19 in wave 1 stayed longer in hospital (median = 6.5 days; interquartile range = 2.9-12.0) as compared to survivors from wave 2 (4.5 days; interquartile range = 1.9-8.7). Patient characteristics differed significantly between the two waves of COVID-19 pandemic. There was an improvement in outcomes in wave 2, including shorter length of stay in hospital and reduction of mortality.


Subject(s)
COVID-19 , Adult , Aged , Aged, 80 and over , COVID-19/epidemiology , Hospital Mortality , Hospitalization , Humans , Length of Stay , Male , Middle Aged , Pandemics , Retrospective Studies
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