ABSTRACT
Considering sex as a biological variable in modern digital health solutions, we investigated sex-specific differences in the trajectory of four physiological parameters across a COVID-19 infection. A wearable medical device measured breathing rate, heart rate, heart rate variability, and wrist skin temperature in 1163 participants (mean age = 44.1 years, standard deviation [SD]=5.6; 667 [57%] females). Participants reported daily symptoms and confounders in a complementary app. A machine learning algorithm retrospectively ingested daily biophysical parameters to detect COVID-19 infections. COVID-19 serology samples were collected from all participants at baseline and follow-up. We analysed potential sex-specific differences in physiology and antibody titres using multilevel modelling and t-tests. Over 1.5 million hours of physiological data were recorded. During the symptomatic period of infection, men demonstrated larger increases in skin temperature, breathing rate and heart rate as well as larger decreases in heart rate variability than women. The COVID-19 infection detection algorithm performed similarly well for men and women. Our study belongs to the first research to provide evidence for differential physiological responses to COVID-19 between females and males, highlighting the potential of wearable technology to inform future precision medicine approaches. This work has received support from the Princely House of the Principality of Liechtenstein, the government of the Principality of Liechtenstein, the Hanela Foundation in Switzerland, and the Innovative Medicines Initiative (IMI) 2 Joint Undertaking under grant agreement No 101005177. This Joint Undertaking receives support from the European Union's Horizon 2020 research and innovation programme and EFPIA.
Subject(s)
COVID-19 , Learning Disabilities , Severe Acute Respiratory SyndromeABSTRACT
BackgroundDespite its high prevalence, the determinants of smelling impairment in COVID-19 remain opaque. Olfactory bulb volumetry has been previously established as a promising surrogate marker of smelling function in multiple otorhinolaryngological diseases. In this work, we aimed to elucidate the correspondence between olfactory bulb volume and the clinical trajectory of COVID-19-related smelling impairment. Therefore, we conducted a large-scale magnetic resonance imaging (MRI)-based investigation of individuals recovered from mainly mild to moderate COVID-19. MethodsData of 233 COVID-19 convalescents from the Hamburg City Health Study COVID Program were analyzed. Upon recruitment, patients underwent cranial MR imaging and assessment of neuropsychological testing. Automated olfactory bulb volumetry was performed on T2-weighted MR imaging data. Olfactory function was assessed longitudinally after recruitment and at follow-up via a structured questionnaire. Follow-up assessment included quantitative olfactometric testing with Sniffin Sticks. Group comparisons of olfactory bulb volume and olfactometric scores were performed between individuals with and without smelling impairment. The associations of olfactory bulb volume and neuropsychological as well as olfactometric scores were assessed via multiple linear regression. ResultsLongitudinal assessment demonstrated a declining prevalence of olfactory dysfunction from 67.6% at acute infection, 21.0% at baseline examination (on average 8.31 {+/-} 2.77 months post infection) and 17.5% at follow-up (21.8 {+/-} 3.61 months post infection). Participants with post-acute olfactory dysfunction had a significantly lower olfactory bulb volume [mm3] at scan-time than normally smelling individuals (mean {+/-} SD, baseline: 40.76 {+/-} 13.08 vs. 46.74 {+/-} 13.66, f=4.07, p=0.046; follow-up: 40.45 {+/-} 12.59 vs. 46.55 {+/-} 13.76, f=4.50, p=0.036). Olfactory bulb volume successfully predicted olfactometric scores at follow-up (rsp = 0.154, p = 0.025). Performance in neuropsychological testing was not significantly associated with the olfactory bulb volume. ConclusionsOur work demonstrates the association of smelling dysfunction and olfactory bulb integrity in a sample of individuals recovered from mainly mild to moderate COVID-19. Olfactory bulb volume was demonstrably lower in individuals with sustained smelling impairment and predicted smelling function longitudinally. Collectively, our results highlight olfactory bulb volume as a surrogate marker that may inform diagnosis and guide rehabilitation strategies in COVID-19.
Subject(s)
Acute Disease , Otorhinolaryngologic Diseases , Olfaction Disorders , COVID-19 , SeizuresABSTRACT
Importance: As SARS-CoV-2 infections have been shown to affect the central nervous system, it is crucial to investigate associated alterations of brain structure and neuropsychological sequelae to help address future health care needs. Objective: To determine whether a mild to moderate SARS-CoV-2 infection is associated with alteration of brain structure detected by magnetic resonance imaging (MRI) and neuropsychological deficits. Design, Setting and Participants: Following a case-control design, 223 non-vaccinated individuals with a positive polymerase chain reaction test (PCR) for SARS-CoV-2 obtained between 1 March and 31 December 2020 received MRI and neuropsychological assessments within the framework of the Hamburg City Health Study (median 9.7 months after testing). Two hundred twenty-three healthy controls, examined prior to the SARS-CoV-2 pandemic, were drawn from the main study and matched for age, sex, education and cardiovascular risk factors. Exposure: Infection with SARS-CoV-2 confirmed by a positive PCR. Main Outcomes and Measures: Primary study outcomes were advanced diffusion MRI measures of white matter microstructure, cortical thickness, white matter hyperintensity load and neuropsychological test scores. Results: The present analysis included 223 individuals recovered from mainly mild to moderate SARS-CoV-2 infections (100 female/123 male, age [years], mean +- SD, 55.54 +- 7.07) and 223 matched healthy controls (93 female/130 male, 55.74 +- 6.60). Among all 11 MR imaging markers tested, significant differences between groups were found in global measures of mean diffusivity and extracellular free-water which were both elevated in the white matter of post-SARS-CoV-2 individuals comparing to matched controls (free-water: 0.148 +- 0.018 vs. 0.142 +- 0.017, P
Subject(s)
COVID-19 , Neurologic Manifestations , Severe Acute Respiratory SyndromeABSTRACT
Background: The coronavirus disease 2019 (COVID-19) pandemic demands reliable prognostic models for estimating the risk of long COVID. We developed and validated a prediction model to estimate the probability of known common long COVID symptoms at least 60 days after acute COVID-19. Methods: The prognostic model was built based on data from a multicentre prospective Swiss cohort study. Included were adult patients diagnosed with COVID-19 between February and December 2020 and treated as outpatients, at ward or intensive/intermediate care unit. Perceived long-term health impairments, including reduced exercise tolerance/reduced resilience, shortness of breath and/or tiredness (REST), were assessed after a follow-up time between 60 and 425 days. Predictors were selected out of twelve candidate predictors based on three reliable methods, namely the augmented backward elimination (ABE) method, the adaptive best-subset selection (ABESS) method and model-based recursive partitioning (MBRP) approach. Model performance was assessed with the scaled Brier score, concordance c statistic and calibration plot. The final prognostic model was determined based on best model performance. Results: In total 2799 patients were included in the analysis, of which 1588 patients were in the derivation cohort and 1211 patients in the validation cohort. The REST prevalence was similar between the cohorts with 21.6% (n = 343) in the derivation cohort and 22.1% (n = 268) in the validation data. The same predictors were selected with the ABE and ABESS variable selection method. The final prognostic model was based on the ABE and ABESS selected predictors. The corresponding model discrimination in the validation cohort was 0.78 (95% CI: 0.75 to 0.81), calibration slope was 0.92 (95% CI: 0.78 to 1.06) and calibration intercept was -0.06 (95% CI: -0.22 to 0.09). A patient’s probability of developing REST symptoms \hat{y} = exp(S) / (1 + exp(S)) can be calculated with S = −4.947 + 0.349 × number of acute COVID-19 symptoms + 0.339 × severity of acute COVID-19 ward + 1.737 × severity of acute COVID-19 intensive or intermediate care + 0.128 × feeling of stress at home + 0.013 × age at presentation + 0.352 × female sex + 0.346 × presence of at least one cardiovascular risk factor − 0.097 × responsible for childcare/family member + 0.022 × body mass index, with feeling of stress at home ranges from 1 (no stress) to 10 (maximum stress) and responsibility for childcare/family member ranges from 1 (no responsibility/not applicable) to 6 (full responsibility). Conclusion: The proposed model is reliable to identify COVID-19 infected patients at risk for REST symptoms. Before implementing the prognostic model in daily clinical practice, the conduct of an impact study is recommended.
Subject(s)
COVID-19ABSTRACT
Background Women are overrepresented amongst individuals suffering from post-acute sequelae of SARS-CoV-2 infection (PASC). Biological (sex) as well as sociocultural (gender) differences between women and men might account for this imbalance, yet their impact on PASC is unknown. Methods and Findings By using Bayesian models comprising >200 co-variates, we assessed the impact of social context in addition to biological data on PASC in a multi-centre prospective cohort study of 2927 (46% women) individuals in Switzerland. Women more often reported at least one persistent symptom than men (43.5% vs 32.0% of men, p<0.001) six (IQR 5–9) months after SARS-CoV-2 infection. Adjusted models showed that women with personality traits stereotypically attributed to women were most often affected by PASC (OR 2.50[1.25-4.98], p<0.001), in particular when they were living alone (OR 1.84[1.25-2.74]), had an increased stress level (OR 1.06[1.03-1.09]), had undergone higher education (OR 1.30[1.08-1.54]), preferred pre-pandemic physical greeting over verbal greeting (OR 1.71[1.44-2.03]), and had experienced an increased number of symptoms during index infection (OR 1.27[1.22-1.33]). Conclusion Besides gender- and sex-sensitive biological parameters, sociocultural variables play an important role in producing sex differences in PASC. Our results indicate that predictor variables of PASC can be easily identified without extensive diagnostic testing and are targets of interventions aiming at stress coping and social support.
Subject(s)
COVID-19ABSTRACT
With the COVID-19 pandemic causing a global health crisis, accurate diagnosis is critical. Diagnosing acute disease relies on RT-PCR tests measuring the presence of SARS-CoV-2 in the sampled material but in patients with suspected COVID-19 with a negative RT-PCR result, measuring anti-viral antibodies can help clinicians identify infected individuals. Antibody testing can also determine if someone was previously infected and help to measure the prevalence of the virus in a community. A new study characterizes an assay measuring total antibodies – combined IgA, IgM, and IgG isotypes – against SARS-CoV-2. The assay, ECLIA, specifically measures antibodies against the S1 subunit of the viral spike, which carries the virus’s receptor binding domain. Researchers in Liechtenstein evaluated ECLIA in a population with 125 cases of confirmed SARS-CoV-2 infection and 1159 individuals without evidence of COVID-19. The results showed a test sensitivity of 97.6%, while the specificity was 99.8%. Antibody levels were highest in hospitalized patients and lower in symptomatic patients outside the hospital and those with asymptomatic infection. Following COVID-19, smokers developed lower antibody titers than non-smokers, whereas patients without fever had lower antibody titers than patients with fever. Following COVID-19, smokers developed lower antibody titers than non-smokers, whereas patients without fever had lower antibody titers than patients with fever suggesting that the assay may be able to test the association between clinical characteristics and antibody levels and help identify individuals with potential cross-reactivity to SARS-CoV-2.
Subject(s)
Acute Disease , Fever , COVID-19ABSTRACT
ObjectivesTo predict ultimate treatment intensity of COVID-19 patients using pulmonary and cardiovascular metrics fully automatically extracted from initial chest CTs.Methods All patients tested positive for SARS-CoV-2 by RT-PCR at our emergency department between March 25 and April 14, 2020 were identified (n=391). For those patients, all initial chest CTs were analyzed (n=85). Multiple pulmonary and cardiovascular metrics were extracted using deep convolutional neural networks. Three clinical treatment intensity groups were defined according to the most intensive treatment of a patient, determined six weeks later: Group 1 (outpatient), group 2 (general ward), and group 3 (intensive care unit; ICU). Univariate analyses were performed to analyze differences between groups. Subsequently, multiple metrics were combined in two binary logistic regression analyses and resulting prediction probabilities used to classify whether a patient needed hospitalization or ICU care. For analysis of discriminatory power, ROC curves were plotted and areas-under-the-curves (AUCs) calculated.ResultsThe mean interval between presentation at the emergency department and the chest CT was 1.4 days. Among others, mean percentage of lung volume affected by opacities (PO) and mean total pericardial volume (TPV) increased statistically significantly with higher treatment intensity [from group 1 to 3, standard deviation in brackets: PO: 0.8%(1.5)–11.6%(13.1)–31.6%(20.1); TPV: 733.4ml(231.7)–866.2ml(211.2)–925.7ml(125.5); both: p<0.001]. AUCs were 0.85 (ICU vs. no ICU) and 0.94 (hospitalization vs. no hospitalization).Conclusions Metrics fully automatically extracted from initial chest CTs increase with treatment intensity of COVID-19 patients. This information can be exploited to prospectively manage allocation of healthcare resources.
Subject(s)
COVID-19ABSTRACT
In a rapid response published online by the British Medical Journal, Sommerstein and Gräni1 pushed forward the hypothesis that angiotensin-converting enzyme (ACE) inhibitors (ACE-Is) could act as a potential risk factor for fatal Corona virus disease 2019 (COVID-19) by up-regulating ACE2. This notion was quickly picked up by the lay press and sparked concerns among physicians and patients regarding the intake of inhibitors of the renin–angiotensin–aldosterone system (RAAS) by severe acute respiratory syndrome coronavirus 2 (SARS-CoV2) infected individuals.1 In this article, we try to shed light on what is known and unknown regarding the RAAS and SARS-CoV2 interaction. We find translational evidence for diverse roles of the RAAS, which allows to formulate also the opposite hypothesis, i.e. that inhibition of the RAAS might be protective in COVID-19.[Truncated]