Attributes and predictors of long COVID Sudre, Carole H; Murray, Benjamin; Varsavsky, Thomas ...
Nature medicine,
04/2021, Letnik:
27, Številka:
4
Journal Article
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Reports of long-lasting coronavirus disease 2019 (COVID-19) symptoms, the so-called 'long COVID', are rising but little is known about prevalence, risk factors or whether it is possible to predict a ...protracted course early in the disease. We analyzed data from 4,182 incident cases of COVID-19 in which individuals self-reported their symptoms prospectively in the COVID Symptom Study app
. A total of 558 (13.3%) participants reported symptoms lasting ≥28 days, 189 (4.5%) for ≥8 weeks and 95 (2.3%) for ≥12 weeks. Long COVID was characterized by symptoms of fatigue, headache, dyspnea and anosmia and was more likely with increasing age and body mass index and female sex. Experiencing more than five symptoms during the first week of illness was associated with long COVID (odds ratio = 3.53 (2.76-4.50)). A simple model to distinguish between short COVID and long COVID at 7 days (total sample size, n = 2,149) showed an area under the curve of the receiver operating characteristic curve of 76%, with replication in an independent sample of 2,472 individuals who were positive for severe acute respiratory syndrome coronavirus 2. This model could be used to identify individuals at risk of long COVID for trials of prevention or treatment and to plan education and rehabilitation services.
The Pfizer-BioNTech (BNT162b2) and the Oxford-AstraZeneca (ChAdOx1 nCoV-19) COVID-19 vaccines have shown excellent safety and efficacy in phase 3 trials. We aimed to investigate the safety and ...effectiveness of these vaccines in a UK community setting.
In this prospective observational study, we examined the proportion and probability of self-reported systemic and local side-effects within 8 days of vaccination in individuals using the COVID Symptom Study app who received one or two doses of the BNT162b2 vaccine or one dose of the ChAdOx1 nCoV-19 vaccine. We also compared infection rates in a subset of vaccinated individuals subsequently tested for SARS-CoV-2 with PCR or lateral flow tests with infection rates in unvaccinated controls. All analyses were adjusted by age (≤55 years vs >55 years), sex, health-care worker status (binary variable), obesity (BMI <30 kg/m2vs ≥30 kg/m2), and comorbidities (binary variable, with or without comorbidities).
Between Dec 8, and March 10, 2021, 627 383 individuals reported being vaccinated with 655 590 doses: 282 103 received one dose of BNT162b2, of whom 28 207 received a second dose, and 345 280 received one dose of ChAdOx1 nCoV-19. Systemic side-effects were reported by 13·5% (38 155 of 282 103) of individuals after the first dose of BNT162b2, by 22·0% (6216 of 28 207) after the second dose of BNT162b2, and by 33·7% (116 473 of 345 280) after the first dose of ChAdOx1 nCoV-19. Local side-effects were reported by 71·9% (150 023 of 208 767) of individuals after the first dose of BNT162b2, by 68·5% (9025 of 13 179) after the second dose of BNT162b2, and by 58·7% (104 282 of 177 655) after the first dose of ChAdOx1 nCoV-19. Systemic side-effects were more common (1·6 times after the first dose of ChAdOx1 nCoV-19 and 2·9 times after the first dose of BNT162b2) among individuals with previous SARS-CoV-2 infection than among those without known past infection. Local effects were similarly higher in individuals previously infected than in those without known past infection (1·4 times after the first dose of ChAdOx1 nCoV-19 and 1·2 times after the first dose of BNT162b2). 3106 of 103 622 vaccinated individuals and 50 340 of 464 356 unvaccinated controls tested positive for SARS-CoV-2 infection. Significant reductions in infection risk were seen starting at 12 days after the first dose, reaching 60% (95% CI 49–68) for ChAdOx1 nCoV-19 and 69% (66–72) for BNT162b2 at 21–44 days and 72% (63–79) for BNT162b2 after 45–59 days.
Systemic and local side-effects after BNT162b2 and ChAdOx1 nCoV-19 vaccination occur at frequencies lower than reported in phase 3 trials. Both vaccines decrease the risk of SARS-CoV-2 infection after 12 days.
ZOE Global, National Institute for Health Research, Chronic Disease Research Foundation, National Institutes of Health, UK Medical Research Council, Wellcome Trust, UK Research and Innovation, American Gastroenterological Association.
•Seventy-eight metabolites covering a large polarity range were investigated.•Unified chromatography allows the comprehensive UHPSFC/MS analysis of biomolecules.•The effect of columns, additives and ...ion source were studied.•Higher identification confidence was achieved by MSE for human plasma.•5823 metabolites were identified in human plasma using MSDIAL.
The applicability of ultrahigh-performance supercritical fluid chromatography coupled with mass spectrometry (UHPSFC/MS) for the qualitative analysis of metabolites with a wide polarity range (log P: −3.89–18.95) was evaluated using a representative set of 78 standards belonging to nucleosides, biogenic amines, carbohydrates, amino acids, and lipids. The effects of the gradient shape and the percentage of water (1, 2, and 5%) were investigated on the Viridis BEH column. The screening of eight stationary phases was performed for columns with different interaction sites, such as hydrogen bonding, hydrophobic, π-π, or anionic exchange type interactions. The highest number of compounds (67) of the set studied was detected on the Torus Diol column, which provided a resolution parameter of 39. The DEA column had the second best performance with 58 detected standards and the resolution parameter of 54. The overall performance of other parameters, such as selectivity, peak height, peak area, retention time stability, asymmetry factor, and mass accuracy, led to the selection of the Diol column for the final method. The comparison of additives showed that ammonium acetate gave a superior sensitivity over ammonium formate. Moreover, the influence of the ion source on the ionization efficiency was studied by employing atmospheric pressure chemical ionization (APCI) and electrospray ionization (ESI). The results proved the complementarity of both ionization techniques, but also the superior ionization capacity of the ESI source in the negative ion mode, for which 53% of the analytes were detected compared to only 7% for the APCI source. Finally, optimized analytical conditions were applied to the analysis of a pooled human plasma sample. 44 compounds from the preselected set were detected in human plasma using ESI-UHPSFC/MS in MSE mode considering both ionization modes.
COVID-19 vaccines show excellent efficacy in clinical trials and effectiveness in real-world data, but some people still become infected with SARS-CoV-2 after vaccination. This study aimed to ...identify risk factors for post-vaccination SARS-CoV-2 infection and describe the characteristics of post-vaccination illness.
This prospective, community-based, nested, case-control study used self-reported data (eg, on demographics, geographical location, health risk factors, and COVID-19 test results, symptoms, and vaccinations) from UK-based, adult (≥18 years) users of the COVID Symptom Study mobile phone app. For the risk factor analysis, cases had received a first or second dose of a COVID-19 vaccine between Dec 8, 2020, and July 4, 2021; had either a positive COVID-19 test at least 14 days after their first vaccination (but before their second; cases 1) or a positive test at least 7 days after their second vaccination (cases 2); and had no positive test before vaccination. Two control groups were selected (who also had not tested positive for SARS-CoV-2 before vaccination): users reporting a negative test at least 14 days after their first vaccination but before their second (controls 1) and users reporting a negative test at least 7 days after their second vaccination (controls 2). Controls 1 and controls 2 were matched (1:1) with cases 1 and cases 2, respectively, by the date of the post-vaccination test, health-care worker status, and sex. In the disease profile analysis, we sub-selected participants from cases 1 and cases 2 who had used the app for at least 14 consecutive days after testing positive for SARS-CoV-2 (cases 3 and cases 4, respectively). Controls 3 and controls 4 were unvaccinated participants reporting a positive SARS-CoV-2 test who had used the app for at least 14 consecutive days after the test, and were matched (1:1) with cases 3 and 4, respectively, by the date of the positive test, health-care worker status, sex, body-mass index (BMI), and age. We used univariate logistic regression models (adjusted for age, BMI, and sex) to analyse the associations between risk factors and post-vaccination infection, and the associations of individual symptoms, overall disease duration, and disease severity with vaccination status.
Between Dec 8, 2020, and July 4, 2021, 1 240 009 COVID Symptom Study app users reported a first vaccine dose, of whom 6030 (0·5%) subsequently tested positive for SARS-CoV-2 (cases 1), and 971 504 reported a second dose, of whom 2370 (0·2%) subsequently tested positive for SARS-CoV-2 (cases 2). In the risk factor analysis, frailty was associated with post-vaccination infection in older adults (≥60 years) after their first vaccine dose (odds ratio OR 1·93, 95% CI 1·50–2·48; p<0·0001), and individuals living in highly deprived areas had increased odds of post-vaccination infection following their first vaccine dose (OR 1·11, 95% CI 1·01–1·23; p=0·039). Individuals without obesity (BMI <30 kg/m2) had lower odds of infection following their first vaccine dose (OR 0·84, 95% CI 0·75–0·94; p=0·0030). For the disease profile analysis, 3825 users from cases 1 were included in cases 3 and 906 users from cases 2 were included in cases 4. Vaccination (compared with no vaccination) was associated with reduced odds of hospitalisation or having more than five symptoms in the first week of illness following the first or second dose, and long-duration (≥28 days) symptoms following the second dose. Almost all symptoms were reported less frequently in infected vaccinated individuals than in infected unvaccinated individuals, and vaccinated participants were more likely to be completely asymptomatic, especially if they were 60 years or older.
To minimise SARS-CoV-2 infection, at-risk populations must be targeted in efforts to boost vaccine effectiveness and infection control measures. Our findings might support caution around relaxing physical distancing and other personal protective measures in the post-vaccination era, particularly around frail older adults and individuals living in more deprived areas, even if these individuals are vaccinated, and might have implications for strategies such as booster vaccinations.
ZOE, the UK Government Department of Health and Social Care, the Wellcome Trust, the UK Engineering and Physical Sciences Research Council, UK Research and Innovation London Medical Imaging and Artificial Intelligence Centre for Value Based Healthcare, the UK National Institute for Health Research, the UK Medical Research Council, the British Heart Foundation, and the Alzheimer's Society.
The General Linear Model (GLM) used in task-fMRI relates activated brain areas to extrinsic task conditions. The translation of resulting neural activation into a hemodynamic response is commonly ...approximated with a linear convolution model using a hemodynamic response function (HRF). There are two major limitations in GLM analysis. Firstly, the GLM assumes that neural activation is either on or off and matches the exact stimulus duration in the corresponding task timings. Secondly, brain networks observed in resting-state fMRI experiments present also during task experiments, but the GLM approach models these task-unrelated brain activity as noise. A novel kernel matrix factorization approach, called hemodynamic matrix factorization (HMF), is therefore proposed that addresses both limitations by assuming that task-related and task-unrelated brain activity can be modeled with the same convolution model as in GLM analysis. By contrast to the GLM, the proposed HMF is a blind source separation (BSS) technique, which decomposes fMRI data into modes. Each mode comprises of a neural activation time course and a spatial mapping. Two versions of HMF are proposed in which the neural activation time course of each mode is convolved with either the canonical HRF or predetermined subject-specific HRFs.
Firstly, HMF with the canonical HRF is applied to two open-source cohorts. These cohorts comprise of several task experiments including motor, incidental memory, spatial coherence discrimination, verbal discrimination task and a very short localization task, engaging multiple parts of the eloquent cortex. HMF modes were obtained whose neural activation time course followed original task timings and whose corresponding spatial map matched cortical areas known to be involved in the respective task processing.
Secondly, the alignment of these neural activation time courses to task timings were further improved by replacing the canonical HRF with subject-specific HRFs during HMF mode computation.
In addition to task-related modes, HMF also produced seemingly task-unrelated modes whose spatial maps matched known resting-state networks.
The validity of a fMRI task experiment relies on the assumption that the exposure to a stimulus for a given time causes an imminent increase in neural activation of equal duration. The proposed HMF is an attempt to falsify this assumption and allows to identify subject task participation that does not comply with the experiment instructions.
In children, SARS-CoV-2 infection is usually asymptomatic or causes a mild illness of short duration. Persistent illness has been reported; however, its prevalence and characteristics are unclear. We ...aimed to determine illness duration and characteristics in symptomatic UK school-aged children tested for SARS-CoV-2 using data from the COVID Symptom Study, one of the largest UK citizen participatory epidemiological studies to date.
In this prospective cohort study, data from UK school-aged children (age 5–17 years) were reported by an adult proxy. Participants were voluntary, and used a mobile application (app) launched jointly by Zoe Limited and King's College London. Illness duration and symptom prevalence, duration, and burden were analysed for children testing positive for SARS-CoV-2 for whom illness duration could be determined, and were assessed overall and for younger (age 5–11 years) and older (age 12–17 years) groups. Children with longer than 1 week between symptomatic reports on the app were excluded from analysis. Data from symptomatic children testing negative for SARS-CoV-2, matched 1:1 for age, gender, and week of testing, were also assessed.
258 790 children aged 5–17 years were reported by an adult proxy between March 24, 2020, and Feb 22, 2021, of whom 75 529 had valid test results for SARS-CoV-2. 1734 children (588 younger and 1146 older children) had a positive SARS-CoV-2 test result and calculable illness duration within the study timeframe (illness onset between Sept 1, 2020, and Jan 24, 2021). The most common symptoms were headache (1079 62·2% of 1734 children), and fatigue (954 55·0% of 1734 children). Median illness duration was 6 days (IQR 3–11) versus 3 days (2–7) in children testing negative, and was positively associated with age (Spearman's rank-order rs 0·19, p<0·0001). Median illness duration was longer for older children (7 days, IQR 3–12) than younger children (5 days, 2–9). 77 (4·4%) of 1734 children had illness duration of at least 28 days, more commonly in older than younger children (59 5·1% of 1146 older children vs 18 3·1% of 588 younger children; p=0·046). The commonest symptoms experienced by these children during the first 4 weeks of illness were fatigue (65 84·4% of 77), headache (60 77·9% of 77), and anosmia (60 77·9% of 77); however, after day 28 the symptom burden was low (median 2 symptoms, IQR 1–4) compared with the first week of illness (median 6 symptoms, 4–8). Only 25 (1·8%) of 1379 children experienced symptoms for at least 56 days. Few children (15 children, 0·9%) in the negatively tested cohort had symptoms for at least 28 days; however, these children experienced greater symptom burden throughout their illness (9 symptoms, IQR 7·7–11·0 vs 8, 6–9) and after day 28 (5 symptoms, IQR 1·5–6·5 vs 2, 1–4) than did children who tested positive for SARS-CoV-2.
Although COVID-19 in children is usually of short duration with low symptom burden, some children with COVID-19 experience prolonged illness duration. Reassuringly, symptom burden in these children did not increase with time, and most recovered by day 56. Some children who tested negative for SARS-CoV-2 also had persistent and burdensome illness. A holistic approach for all children with persistent illness during the pandemic is appropriate.
Zoe Limited, UK Government Department of Health and Social Care, Wellcome Trust, UK Engineering and Physical Sciences Research Council, UK Research and Innovation London Medical Imaging and Artificial Intelligence Centre for Value Based Healthcare, UK National Institute for Health Research, UK Medical Research Council, British Heart Foundation, and Alzheimer's Society.
•Development of an efficient clean-up strategy for short peptides in plasma.•Comparison of 4 different clean-up protocols (advantages and disadvantages).•Untargeted peptidomic approach for short ...peptide identification in plasma.•Identification of 91 short peptides, the largest number never identified before.•Development of a rapid and simple method for clinical applications.
Short peptides, namely di- tri- and tetra peptides, have been proven to play an important diagnostic role in several diseases. Therefore, the development of an analytical approach for their detection and identification is nowadays an important research goal. This paper describes an analytical procedure able to overcome the issues of short peptide isolation, clean-up and identification in plasma samples. Four different protocols were compared and tested to maximize both recovery and total number of identifications of short circulating plasma endogenous peptides. The purified peptides, coming from the four different tested protocols, were separated by zwitterionic hydrophilic liquid chromatography coupled to high-resolution mass spectrometry with the purpose of accomplishing an untargeted investigation based on suspect screening for short peptides in plasma. In particular, the use of Phree™ Phospholipid removal cartridge in combination with a purification step by solid phase extraction on a graphitized carbon black sorbent allowed the identification of the largest number of amino acid sequences (91 short peptides). The clean-up procedure allowed to tackle the issue of the low abundance of such peptides and their suppression during mass-spectrometric analysis. The results indicated that sample preparation is therefore fundamental for short peptide analysis in plasma samples.
The chemical composition of
Cannabis sativa
L. has been extensively investigated for several years; nevertheless, a detailed lipidome characterization is completely lacking in the literature. To ...achieve this goal, an extraction and enrichment procedure was developed for the characterization of phospholipids and sulfolipids. Firstly, a study on the solid-liquid extraction was performed, to maximize the recovery of the considered lipids; the best procedure consisted of a simple extraction with a mixture of methanol and chloroform (1:1,
v
/
v
). The hemp extracts were analyzed by ultra-high-performance liquid chromatography coupled to high-resolution mass spectrometry and lipids were tentatively identified by Lipostar. To improve the number of identifications, an enrichment method, based on graphitized carbon black solid phase extraction, was evaluated to fractionate phospholipids and sulfolipids into separate eluates. Recovery and matrix effects of the procedure were determined on a mixture of standard lipids, containing representative compounds for each considered lipid class. The optimized method allowed the tentative identification of 189 lipids, including 51 phospholipids and 80 sulfolipids, in the first and second fractions, respectively. The detection of only 6 sulfolipids in the first fraction and 9 phospholipids in the second fraction proved the efficacy of the fractionation method, which also allowed the number of lipid identifications to be increased compared to the same procedure without enrichment, which scored 100 lipids. Finally, a semi-quantitative analysis permitted the hemp polar lipidome to be characterized. The results of this study allow knowledge of the hemp chemical composition to be improved with a detailed description of its phospho- and sulfolipid profiles.
Graphical abstract
Computer-aided diagnosis (CAD) of prostate cancer on multiparametric magnetic resonance imaging (mpMRI), using artificial intelligence (AI), may reduce missed cancers and unnecessary biopsies, ...increase inter-observer agreement between radiologists, and alleviate pressures caused by rising case incidence and a shortage of specialist radiologists to read prostate mpMRI. However, well-designed evaluation studies are required to prove efficacy above current clinical practice. A systematic search of the MEDLINE, EMBASE, and arXiv electronic databases was conducted for studies that compared CAD for prostate cancer detection or classification on MRI against radiologist interpretation and a histopathological reference standard, in treatment-naïve men with a clinical suspicion of prostate cancer. Twenty-seven studies were included in the final analysis. Due to substantial heterogeneities in the included studies, a narrative synthesis is presented. Several studies reported superior diagnostic accuracy for CAD over radiologist interpretation on small, internal patient datasets, though this was not observed in the few studies that performed evaluation using external patient data. Our review found insufficient evidence to suggest the clinical deployment of artificial intelligence algorithms at present. Further work is needed to develop and enforce methodological standards, promote access to large diverse datasets, and conduct prospective evaluations before clinical adoption can be considered.
Asparagus waste represents products of great interest since many compounds with high biological value are located in the lower portion of the spears. The extraction of bioactive compounds from ...asparagus by-products is therefore crucial for the purpose of adding value to these by-products. In this paper, bioactive peptides from asparagus waste were extracted, digested, purified and identified. In particular, Alcalase
was chosen as the enzyme to use to obtain protein hydrolysate due to its low cost and, consequently, the possibility of implementing the method on a large scale. In order to simplify the peptide extract to reach better identification, the hydrolysate was fractionated by reversed-phase chromatography in 10 fractions. Two tests were carried out for antioxidant activity (ABTS-DPPH) and one for antihypertensive activity (ACE). Fractions with a higher bioactivity score were identified by peptidomics technologies and screened for bioactivity with the use of bioinformatics. For ACE-inhibitor activity, two peptides were synthetized, PDWFLLL and ASQSIWLPGWL, which provided an EC
value of 1.76 µmol L
and 4.02 µmol L
, respectively. For the antioxidant activity, by DPPH assay, MLLFPM exhibited the lowest EC50 value at 4.14 µmol L
, followed by FIARNFLLGW and FAPVPFDF with EC50 values of 6.76 µmol L
and 10.01 µmol L
, respectively. A validation of the five identified peptides was also carried out. The obtained results showed that peptides obtained from asparagus by-products are of interest for their biological activity and are suitable for being used as functional ingredients.
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