SARS-CoV-2 infection in children and adolescents: a Brazilian experience.

OBJECTIVE: To describe clinical and epidemiological aspects of children and adolescents infected with the SARS-CoV-2 in the Municipality of Taubaté, SP, from March to November 2020. METHODS: Cross-sectional study with secondary data obtained from the Epidemiological Surveillance System about confirmed cases in city residents and from medical records of patients who were treated in hospitals in Taubaté, aged between 0 and 19 years. Chi-square and Student's t tests were used for comparisons. RESULTS: 677 cases in the studied age range were reported during the study period, corresponding to 10.1% of cases reported in the municipality. The rapid antibody test was the most used to confirm infection, followed by RT-PCR and serology. Symptoms were described in 57.7% of the cases, mainly fever and cough. Diarrhea was associated with age below 4 years, while fever, cough, headache, odynophagia, ageusia, anosmia, myalgia, and dyspnea were associated with an age ranging from 10 to 19 years. In the study period, there were no deaths from COVID-19 of residents of the municipality in the age group from 0 to 19 years. CONCLUSIONS: The study was able to identify the proportion of involvement of COVID-19 in children and adolescents in the city, and the disease had a mild evolution. The main symptoms were fever and cough, but mainly diarrhea in younger children, and headache, odynophagia, anosmia, ageusia, and myalgia in adolescents.

Diagnostic value of symptoms for pediatric SARS-CoV-2 infection in a primary care setting.

PURPOSE: To evaluate the diagnostic value of symptoms used by daycares and schools to screen children and adolescents for SARS-CoV-2 infection, we analyzed data from a primary care setting. METHODS: This cohort study included all patients ≤17 years old who were evaluated at Providence Community Health Centers (PCHC; Providence, U.S.), for COVID-19 symptoms and/or exposure, and received SARS-CoV-2 polymerase chain reaction (PCR) testing between March-June 2020. Participants were identified from PCHC electronic medical records. For three age groups- 0-4, 5-11, and 12-17 years-we estimated the sensitivity, specificity, and area under the receiver operating curve (AUC) of individual symptoms and three symptom combinations: a case definition published by the Rhode Island Department of Health (RIDOH), and two novel combinations generated by different statistical approaches to maximize sensitivity, specificity, and AUC. We evaluated symptom combinations both with and without consideration of COVID-19 exposure. Myalgia, headache, sore throat, abdominal pain, nausea, anosmia, and ageusia were not assessed in 0-4 year-olds due to the lower reliability of these symptoms in this group. RESULTS: Of 555 participants, 217 (39.1%) were SARS-CoV-2-infected. Fever was more common among 0-4 years-olds (p = 0.002); older children more frequently reported fatigue (p = 0.02). In children ≥5 years old, anosmia or ageusia had 94-98% specificity. In all ages, exposure history most accurately predicted infection. With respect to individual symptoms, cough most accurately predicted infection in <5 year-olds (AUC 0.69) and 12-17 year-olds (AUC 0.62), while headache was most accurate in 5-11 year-olds (AUC 0.62). In combination with exposure history, the novel symptom combinations generated statistically to maximize test characteristics had sensitivity >95% but specificity <30%. No symptom or symptom combination had AUC ≥0.70. CONCLUSIONS: Anosmia or ageusia in children ≥5 years old should raise providers' index of suspicion for COVID-19. However, our overall findings underscore the limited diagnostic value of symptoms.

Predictive symptoms for COVID-19 in the community: REACT-1 study of over 1 million people.

BACKGROUND: Rapid detection, isolation, and contact tracing of community COVID-19 cases are essential measures to limit the community spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We aimed to identify a parsimonious set of symptoms that jointly predict COVID-19 and investigated whether predictive symptoms differ between the B.1.1.7 (Alpha) lineage (predominating as of April 2021 in the US, UK, and elsewhere) and wild type. METHODS AND FINDINGS: We obtained throat and nose swabs with valid SARS-CoV-2 PCR test results from 1,147,370 volunteers aged 5 years and above (6,450 positive cases) in the REal-time Assessment of Community Transmission-1 (REACT-1) study. This study involved repeated community-based random surveys of prevalence in England (study rounds 2 to 8, June 2020 to January 2021, response rates 22%-27%). Participants were asked about symptoms occurring in the week prior to testing. Viral genome sequencing was carried out for PCR-positive samples with N-gene cycle threshold value < 34 (N = 1,079) in round 8 (January 2021). In univariate analysis, all 26 surveyed symptoms were associated with PCR positivity compared with non-symptomatic people. Stability selection (1,000 penalized logistic regression models with 50% subsampling) among people reporting at least 1 symptom identified 7 symptoms as jointly and positively predictive of PCR positivity in rounds 2-7 (June to December 2020): loss or change of sense of smell, loss or change of sense of taste, fever, new persistent cough, chills, appetite loss, and muscle aches. The resulting model (rounds 2-7) predicted PCR positivity in round 8 with area under the curve (AUC) of 0.77. The same 7 symptoms were selected as jointly predictive of B.1.1.7 infection in round 8, although when comparing B.1.1.7 with wild type, new persistent cough and sore throat were more predictive of B.1.1.7 infection while loss or change of sense of smell was more predictive of the wild type. The main limitations of our study are (i) potential participation bias despite random sampling of named individuals from the National Health Service register and weighting designed to achieve a representative sample of the population of England and (ii) the necessary reliance on self-reported symptoms, which may be prone to recall bias and may therefore lead to biased estimates of symptom prevalence in England. CONCLUSIONS: Where testing capacity is limited, it is important to use tests in the most efficient way possible. We identified a set of 7 symptoms that, when considered together, maximize detection of COVID-19 in the community, including infection with the B.1.1.7 lineage.

Pain Symptoms in COVID-19.

OBJECTIVE: The clinical manifestations of COVID-19 range from mild symptoms to severe pneumonia and severe organ damage. When evaluated specifically for pain, the data so far have shown that myalgia, headache, and chest pain can be seen in patients at varying rates; myalgia and headache, especially, are among the initial symptoms. DESIGN: This retrospective chart review, followed by a descriptive survey design study, was carried out by examining patients afflicted with COVID-19. After discharge, patients were asked about the severity and the body region of their pain, their use of analgesics, their mood and mental health, and their overall quality of life. RESULTS: A total of 206 patients with a mean age of 56.24 ± 16.99 yrs were included in the study. Pain during COVID-19 was found to be higher compared with the preinfectious and postinfectious states. The most frequent painful areas were reported to be the neck and back before the infection, whereas the head and limbs during the infection. The most frequently used analgesic during infection was paracetamol. There was no relationship between the patients' pain and anxiety and depression; the quality of life was found to be worse in patients with persistent pain. CONCLUSIONS: This study showed that the head and limbs were the most common painful body regions during COVID-19. It was also found that pain can continue in the postinfection period.

Persistent Somatic Symptom Burden and Sleep Disturbance in Patients with COVID-19 During Hospitalization and After Discharge: A Prospective Cohort Study.

BACKGROUND The present study was designed to reveal the trajectory of self-reported somatic symptom burden and sleep quality over time in patients with COVID-19 and to identify prognostic factors for greater somatic symptom burden and sleep disturbance. MATERIAL AND METHODS Seventy-four patients with COVID-19 were prospectively followed for longitudinal assessment of somatic symptom burden and sleep quality. We used the 8-item Somatic Symptom Scale (SSS-8) and the modified Medical Research Council (mMRC) scale for somatic symptom burden and the Pittsburgh Sleep Quality Index for sleep quality investigation. Univariate and multivariate analyses were performed to identify independent factors associated with somatic symptom burden and sleep quality. RESULTS Although the degree of physical discomfort and sleep quality issues tended to decline during self-quarantine, patients still experienced these problems to a certain degree. Univariate and multivariate analyses showed that SSS-8 scores at admission (relative risk [RR] 1.234, 95% CI 1.075-1.417, P=0.003) and mMRC scores at discharge (RR 2.420, 95% CI 1.251-4.682, P=0.009) were 2 independent prognostic indicators of somatic symptom burden. In addition, muscle pain as a chief complaint (RR 4.682, 95% CI 1.247-17.580, P<0.022) and history of use of hypnotic drugs (RR 0.148, 95% CI 0.029-0.749, P<0.019) were 2 independent indicators of patient sleep quality during hospitalization. CONCLUSIONS To the best of our knowledge, the present study was the first dynamic assessment of the somatic symptom burden and sleep quality in patients with COVID-19 during hospitalization and quarantine after discharge. Patients with high somatic symptom burden at admission, especially muscle pain as the chief complaint, are prone to having a higher physical burden and more sleep disturbance at discharge.

Signs and symptoms to determine if a patient presenting in primary care or hospital outpatient settings has COVID-19.

BACKGROUND: The clinical implications of SARS-CoV-2 infection are highly variable. Some people with SARS-CoV-2 infection remain asymptomatic, whilst the infection can cause mild to moderate COVID-19 and COVID-19 pneumonia in others. This can lead to some people requiring intensive care support and, in some cases, to death, especially in older adults. Symptoms such as fever, cough, or loss of smell or taste, and signs such as oxygen saturation are the first and most readily available diagnostic information. Such information could be used to either rule out COVID-19, or select patients for further testing. This is an update of this review, the first version of which published in July 2020. OBJECTIVES: To assess the diagnostic accuracy of signs and symptoms to determine if a person presenting in primary care or to hospital outpatient settings, such as the emergency department or dedicated COVID-19 clinics, has COVID-19. SEARCH METHODS: For this review iteration we undertook electronic searches up to 15 July 2020 in the Cochrane COVID-19 Study Register and the University of Bern living search database. In addition, we checked repositories of COVID-19 publications. We did not apply any language restrictions. SELECTION CRITERIA: Studies were eligible if they included patients with clinically suspected COVID-19, or if they recruited known cases with COVID-19 and controls without COVID-19. Studies were eligible when they recruited patients presenting to primary care or hospital outpatient settings. Studies in hospitalised patients were only included if symptoms and signs were recorded on admission or at presentation. Studies including patients who contracted SARS-CoV-2 infection while admitted to hospital were not eligible. The minimum eligible sample size of studies was 10 participants. All signs and symptoms were eligible for this review, including individual signs and symptoms or combinations. We accepted a range of reference standards. DATA COLLECTION AND ANALYSIS: Pairs of review authors independently selected all studies, at both title and abstract stage and full-text stage. They resolved any disagreements by discussion with a third review author. Two review authors independently extracted data and resolved disagreements by discussion with a third review author. Two review authors independently assessed risk of bias using the Quality Assessment tool for Diagnostic Accuracy Studies (QUADAS-2) checklist. We presented sensitivity and specificity in paired forest plots, in receiver operating characteristic space and in dumbbell plots. We estimated summary parameters using a bivariate random-effects meta-analysis whenever five or more primary studies were available, and whenever heterogeneity across studies was deemed acceptable. MAIN RESULTS: We identified 44 studies including 26,884 participants in total. Prevalence of COVID-19 varied from 3% to 71% with a median of 21%. There were three studies from primary care settings (1824 participants), nine studies from outpatient testing centres (10,717 participants), 12 studies performed in hospital outpatient wards (5061 participants), seven studies in hospitalised patients (1048 participants), 10 studies in the emergency department (3173 participants), and three studies in which the setting was not specified (5061 participants). The studies did not clearly distinguish mild from severe COVID-19, so we present the results for all disease severities together. Fifteen studies had a high risk of bias for selection of participants because inclusion in the studies depended on the applicable testing and referral protocols, which included many of the signs and symptoms under study in this review. This may have especially influenced the sensitivity of those features used in referral protocols, such as fever and cough. Five studies only included participants with pneumonia on imaging, suggesting that this is a highly selected population. In an additional 12 studies, we were unable to assess the risk for selection bias. This makes it very difficult to judge the validity of the diagnostic accuracy of the signs and symptoms from these included studies. The applicability of the results of this review update improved in comparison with the original review. A greater proportion of studies included participants who presented to outpatient settings, which is where the majority of clinical assessments for COVID-19 take place. However, still none of the studies presented any data on children separately, and only one focused specifically on older adults. We found data on 84 signs and symptoms. Results were highly variable across studies. Most had very low sensitivity and high specificity. Only cough (25 studies) and fever (7 studies) had a pooled sensitivity of at least 50% but specificities were moderate to low. Cough had a sensitivity of 67.4% (95% confidence interval (CI) 59.8% to 74.1%) and specificity of 35.0% (95% CI 28.7% to 41.9%). Fever had a sensitivity of 53.8% (95% CI 35.0% to 71.7%) and a specificity of 67.4% (95% CI 53.3% to 78.9%). The pooled positive likelihood ratio of cough was only 1.04 (95% CI 0.97 to 1.11) and that of fever 1.65 (95% CI 1.41 to 1.93). Anosmia alone (11 studies), ageusia alone (6 studies), and anosmia or ageusia (6 studies) had sensitivities below 50% but specificities over 90%. Anosmia had a pooled sensitivity of 28.0% (95% CI 17.7% to 41.3%) and a specificity of 93.4% (95% CI 88.3% to 96.4%). Ageusia had a pooled sensitivity of 24.8% (95% CI 12.4% to 43.5%) and a specificity of 91.4% (95% CI 81.3% to 96.3%). Anosmia or ageusia had a pooled sensitivity of 41.0% (95% CI 27.0% to 56.6%) and a specificity of 90.5% (95% CI 81.2% to 95.4%). The pooled positive likelihood ratios of anosmia alone and anosmia or ageusia were 4.25 (95% CI 3.17 to 5.71) and 4.31 (95% CI 3.00 to 6.18) respectively, which is just below our arbitrary definition of a 'red flag', that is, a positive likelihood ratio of at least 5. The pooled positive likelihood ratio of ageusia alone was only 2.88 (95% CI 2.02 to 4.09). Only two studies assessed combinations of different signs and symptoms, mostly combining fever and cough with other symptoms. These combinations had a specificity above 80%, but at the cost of very low sensitivity (< 30%). AUTHORS' CONCLUSIONS: The majority of individual signs and symptoms included in this review appear to have very poor diagnostic accuracy, although this should be interpreted in the context of selection bias and heterogeneity between studies. Based on currently available data, neither absence nor presence of signs or symptoms are accurate enough to rule in or rule out COVID-19. The presence of anosmia or ageusia may be useful as a red flag for COVID-19. The presence of fever or cough, given their high sensitivities, may also be useful to identify people for further testing. Prospective studies in an unselected population presenting to primary care or hospital outpatient settings, examining combinations of signs and symptoms to evaluate the syndromic presentation of COVID-19, are still urgently needed. Results from such studies could inform subsequent management decisions.

Covid-19 presentation among symptomatic healthcare workers in Ireland.

BACKGROUND: It is recognized that healthcare workers (HCWs) are at high risk of contracting Covid-19. It is incumbent on occupational health staff to recognize potential symptoms of Covid-19 among HCWs. AIMS: The aims of the study were to describe the presenting symptoms of HCWs who developed Covid-19 in Ireland, and to estimate the odds of specific symptoms being associated with a positive Covid-19 polymerase chain reaction (PCR) result. METHODS: A retrospective chart review of all symptomatic HCWs who self-presented for Covid-19 testing in Cork from March to May 2020 was conducted. A sex-matched case-control study was carried out to compare presenting features among those who tested positive compared to those who tested negative. Univariate and multivariable-adjusted conditional logistic regression models were run using Stata 15.0 to identify the symptoms associated with positive Covid-19 swab results. RESULTS: Three hundred and six HCWs were included in the study; 102 cases and 204 controls. Common presenting features among cases were fever/chills (55%), cough (44%) and headache (35%). The symptoms which were significantly associated with a positive Covid-19 swab result were loss of taste/smell (adjusted odds ratio [aOR] 12.15, 95% confidence interval [CI] 1.36-108.79), myalgia (aOR 2.36, 95% 1.27-4.38), fatigue (aOR 2.31, 95% CI 1.12-4.74), headache (aOR 2.11, 95% CI 1.19-3.74) and fever/chills (aOR 1.88, 95% CI 1.12-3.15). CONCLUSIONS: Fever, fatigue, myalgia, loss of taste/smell and headache were associated with increased odds of a Covid-19 diagnosis among symptomatic self-referred HCWs compared with those had negative swab results. Testing criteria for HCWs should reflect the broad range of possible symptoms of Covid-19.

Post-COVID-19 Symptom Burden: What is Long-COVID and How Should We Manage It?

The enduring impact of COVID-19 on patients has been examined in recent studies, leading to the description of Long-COVID. We report the lasting symptom burden of COVID-19 patients from the first wave of the pandemic. All patients with COVID-19 pneumonia discharged from a large teaching hospital trust were offered follow-up. We assessed symptom burden at follow-up using a standardised data collection technique during virtual outpatient clinic appointments. Eighty-six percent of patients reported at least one residual symptom at follow-up. No patients had persistent radiographic abnormalities. The presence of symptoms at follow-up was not associated with the severity of the acute COVID-19 illness. Females were significantly more likely to report residual symptoms including anxiety (p = 0.001), fatigue (p = 0.004), and myalgia (p = 0.022). The presence of long-lasting symptoms is common in COVID-19 patients. We suggest that the phenomenon of Long-COVID may not be directly attributable to the effect of SARS-CoV-2, and believe the biopsychosocial effects of COVID-19 may play a greater role in its aetiology.

Viral arthralgia a new manifestation of COVID-19 infection? A cohort study of COVID-19-associated musculoskeletal symptoms.

OBJECTIVES: Musculoskeletal symptoms are often unrecognised as a prominent feature of COVID-19 infection. This study hypothesised that viral arthralgia is an uncommon but distinct manifestation of COVID-19 infection. In addition, it aimed to characterise the other musculoskeletal presentations of COVID-19 infection and study their prognostic implications. METHODS: Patients hospitalised with COVID-19 infection were divided into two groups: those with and without musculoskeletal symptoms. Those with musculoskeletal symptoms were subdivided according to four patterns of musculoskeletal involvement: myalgia, arthralgia, backache and generalised body ache. Using binary regression logistic analysis, the risk of developing a viral pneumonia in patients with and without musculoskeletal complaints was compared. RESULTS: Of 294 hospitalised patients with COVID-19, 88 (30%) reported musculoskeletal complaints. Among these 88 patients, 37.5% had myalgia, 5.7% arthralgia, 6.8% new-onset backache and 50% generalised body ache. The presence of musculoskeletal complaints was not associated with the risk of developing viral pneumonia (6.8% vs. 9.7%, OR 0.68, 95% CI 0.26-1.76, p = 0.426). COVID-19 arthralgia was often more severe and had variable onset, while generalised body ache and myalgia were milder and coincided with the occurrence of fever or respiratory symptoms. CONCLUSION: Viral arthralgia is a novel clinical manifestation of COVID-19, and untypical of a viral prodrome or a reactive arthropathy. While musculoskeletal symptoms were not associated with developing a pneumonia, to avoid missing a diagnosis of COVID-19, clinicians should be aware of its variable onset, particularly when respiratory symptoms are absent at the time of presentation.

Signs and symptoms to determine if a patient presenting in primary care or hospital outpatient settings has COVID-19 disease.

BACKGROUND: Some people with SARS-CoV-2 infection remain asymptomatic, whilst in others the infection can cause mild to moderate COVID-19 disease and COVID-19 pneumonia, leading some patients to require intensive care support and, in some cases, to death, especially in older adults. Symptoms such as fever or cough, and signs such as oxygen saturation or lung auscultation findings, are the first and most readily available diagnostic information. Such information could be used to either rule out COVID-19 disease, or select patients for further diagnostic testing. OBJECTIVES: To assess the diagnostic accuracy of signs and symptoms to determine if a person presenting in primary care or to hospital outpatient settings, such as the emergency department or dedicated COVID-19 clinics, has COVID-19 disease or COVID-19 pneumonia. SEARCH METHODS: On 27 April 2020, we undertook electronic searches in the Cochrane COVID-19 Study Register and the University of Bern living search database, which is updated daily with published articles from PubMed and Embase and with preprints from medRxiv and bioRxiv. In addition, we checked repositories of COVID-19 publications. We did not apply any language restrictions. SELECTION CRITERIA: Studies were eligible if they included patients with suspected COVID-19 disease, or if they recruited known cases with COVID-19 disease and controls without COVID-19. Studies were eligible when they recruited patients presenting to primary care or hospital outpatient settings. Studies including patients who contracted SARS-CoV-2 infection while admitted to hospital were not eligible. The minimum eligible sample size of studies was 10 participants. All signs and symptoms were eligible for this review, including individual signs and symptoms or combinations. We accepted a range of reference standards including reverse transcription polymerase chain reaction (RT-PCR), clinical expertise, imaging, serology tests and World Health Organization (WHO) or other definitions of COVID-19. DATA COLLECTION AND ANALYSIS: Pairs of review authors independently selected all studies, at both title and abstract stage and full-text stage. They resolved any disagreements by discussion with a third review author. Two review authors independently extracted data and resolved disagreements by discussion with a third review author. Two review authors independently assessed risk of bias using the QUADAS-2 checklist. Analyses were descriptive, presenting sensitivity and specificity in paired forest plots, in ROC (receiver operating characteristic) space and in dumbbell plots. We did not attempt meta-analysis due to the small number of studies, heterogeneity across studies and the high risk of bias. MAIN RESULTS: We identified 16 studies including 7706 participants in total. Prevalence of COVID-19 disease varied from 5% to 38% with a median of 17%. There were no studies from primary care settings, although we did find seven studies in outpatient clinics (2172 participants), and four studies in the emergency department (1401 participants). We found data on 27 signs and symptoms, which fall into four different categories: systemic, respiratory, gastrointestinal and cardiovascular. No studies assessed combinations of different signs and symptoms and results were highly variable across studies. Most had very low sensitivity and high specificity; only six symptoms had a sensitivity of at least 50% in at least one study: cough, sore throat, fever, myalgia or arthralgia, fatigue, and headache. Of these, fever, myalgia or arthralgia, fatigue, and headache could be considered red flags (defined as having a positive likelihood ratio of at least 5) for COVID-19 as their specificity was above 90%, meaning that they substantially increase the likelihood of COVID-19 disease when present. Seven studies carried a high risk of bias for selection of participants because inclusion in the studies depended on the applicable testing and referral protocols, which included many of the signs and symptoms under study in this review. Five studies only included participants with pneumonia on imaging, suggesting that this is a highly selected population. In an additional four studies, we were unable to assess the risk for selection bias. These factors make it very difficult to determine the diagnostic properties of these signs and symptoms from the included studies. We also had concerns about the applicability of these results, since most studies included participants who were already admitted to hospital or presenting to hospital settings. This makes these findings less applicable to people presenting to primary care, who may have less severe illness and a lower prevalence of COVID-19 disease. None of the studies included any data on children, and only one focused specifically on older adults. We hope that future updates of this review will be able to provide more information about the diagnostic properties of signs and symptoms in different settings and age groups. AUTHORS' CONCLUSIONS: The individual signs and symptoms included in this review appear to have very poor diagnostic properties, although this should be interpreted in the context of selection bias and heterogeneity between studies. Based on currently available data, neither absence nor presence of signs or symptoms are accurate enough to rule in or rule out disease. Prospective studies in an unselected population presenting to primary care or hospital outpatient settings, examining combinations of signs and symptoms to evaluate the syndromic presentation of COVID-19 disease, are urgently needed. Results from such studies could inform subsequent management decisions such as self-isolation or selecting patients for further diagnostic testing. We also need data on potentially more specific symptoms such as loss of sense of smell. Studies in older adults are especially important.

COVID-19 and the nervous system.

A pandemic due to novel coronavirus arose in mid-December 2019 in Wuhan, China, and in 3 months' time swept the world. The disease has been referred to as COVID-19, and the causative agent has been labelled SARS-CoV-2 due to its genetic similarities to the virus (SARS-CoV-1) responsible for the severe acute respiratory syndrome (SARS) epidemic nearly 20 years earlier. The spike proteins of both viruses dictate tissue tropism using the angiotensin-converting enzyme type 2 (ACE-2) receptor to bind to cells. The ACE-2 receptor can be found in nervous system tissue and endothelial cells among the tissues of many other organs.Neurological complications have been observed with COVID-19. Myalgia and headache are relatively common, but serious neurological disease appears to be rare. No part of the neuraxis is spared. The neurological disorders occurring with COVID-19 may have many pathophysiological underpinnings. Some appear to be the consequence of direct viral invasion of the nervous system tissue, others arise as a postviral autoimmune process, and still others are the result of metabolic and systemic complications due to the associated critical illness. This review addresses the preliminary observations regarding the neurological disorders reported with COVID-19 to date and describes some of the disorders that are anticipated from prior experience with similar coronaviruses.