Persistent Symptoms in Children Admitted with Covid Similar to Controls 1 Year Later

Background: The aim of this study was to describe the prevalence of persistent symptoms of COVID in hospitalized pediatric population one year after admission compared to a control group. Method(s): Prospective observational study conducted in 2 hospitals. We included patients aged 0-18 years hospitalized for acute COVID-19 more than a year ago and controls, matched by age and sex, hospitalized for causes other than COVID-19, and who had never COVID-19 at recruitment or during the follow-up. Families were contacted and a standardized survey was conducted. Persistent COVID/disease was defined as the presence of symptoms with onset in the first 3 months after COVID-19 and with persistence for more than 2 months. Result(s): 50 cases and 46 controls were analyzed, 58.3% male, 36% <5 years. Families were interviewed a median of 1.89 years (interquartile range;1.25-2.07) after hospitalization. The definition of persistent COVID-19/disease was met in 34% of cases vs. 37% of controls (p=0.767). Symptoms persisted >=11 months in 24% (12/50) of cases vs. 13% (6/46) of controls (p=0.182), with no differences by age group. The most frequent symptoms at 1 year in cases were fatigue (8%), headache (6%), poor appetite (6%), abdominal pain (6%) and variations in heart rate (6%). In controls, persistent symptoms were mostly abdominal pain (6%) and poor appetite (6%). The number of readmissions was 11/50 (22%) and 6/46 (13%) (p=0.267), respectively. On emotional/behavioral items, 16/50 (32%) of cases reported that their emotional state was worse or much worse than before admission, compared to 16/46 (34.7%). No risk factors associated with the development of persistent symptoms were found, except the length of hospital admission (p=0.043). Conclusion(s): In this study, the prevalence of persistent symptoms was not different in patients with and without COVID-19. 1-year persistence was higher in COVID-19 cases but did not reach significance. Persistence correlated with length of hospitalization.

Comorbidities That Increase Risk for Severe Acute Covid-19 in Pediatric Population

Background: Little is understood about which comorbidities are associated with severe outcomes in children hospitalized with acute COVID-19. Some confusion lies especially for cancer or diabetes. Method(s): Data from 2 multicenter prospective cohort studies of hospitalized children (aged 0-18 years) with confirmed SARS-CoV-2 in Spain and Colombia were combined for this analysis. Data were obtained from 116 hospitals. Outcome was classified as (in decreasing order of severity): death, mechanical ventilation (MV), pediatric intensive care unit (PICU) admission, high flow/CPAP, oxygen therapy with nasal prong (NP) and hospitalization without respiratory support. Risk factors for severity, adjusting for age and gender, were identified using multinominal logistic regression and a backwards selection process. Result(s): A total of 1,753 patients were included, 734 (41.8%) in Spain and 1,019 (58.1%) in Colombia. The most frequent comorbidities were asthma (9.0%), chronic neurological disorder (NRL) (7.4%), immunosuppressive medication (7.2%), malignant neoplasms (5.4%) and chronic lung disease (not asthma) (CLD) (4.5%). Comorbidities associated with the different endpoints are summarized in Figure 1. Asthma was associated with a significantly increased risk of death (OR: 4.17;95%CI 1.34-12.97), MV (OR: 7.94 (3.59-17.56)), PICU admission (OR: 3.37 (1.91- 5.96)), high flow/CPAP (OR: 6.65 (2.69-16.46)), and NP (OR: 3.85 (2.57-5.77)) compared to hospitalization without respiratory support. NRL was associated with increased risk of death (OR: 7.34 (3.01-17.90)), MV (OR: 3.07 (1.20-7.82)) and high flow/CPAP (OR: 4.36 (1.68-11.29)). CLD was associated with increased risk of death (OR: 6.22 [2.28-16.94]) and NP (OR: 3.1 (1.74-5.58)) and in addition, chronic cardiac disease was associated with increased risk of MV (OR: 5.21 (1.76-15.41)) and PICU (OR: 2.78 (1.27-6.08)). Risks of death (OR: 4.49 (2.03-9.05)), MV (OR: 2.97 (1.52-5.81)), PICU (OR: 4.27 (2.89-6.33)), and NP (OR: 4.67 (3.64-5.99)) were higher in the Colombia Cohort. Conclusion(s): Asthma, chronic neurological, cardiac and lung disease;and belonging to the Colombia cohort were consistently associated with multiple severe outcomes of COVID-19. Cancer and diabetes association with selected endpoints rather than with most endpoints may be more related to the baseline disease than with the actual COVID-19.

Persistence of Symptoms One Year after Multisystem Inflammatory Syndrome in Children

Background: Long term evolution of Multisystem Inflammatory Syndrome in children (MIS-C) is poorly understood. In this report, we described the frequency of persistent symptoms and sequels after one-year monitoring in a cohort of MIS-C patients. Method(s): This is a prospective observational study in under-18-aged patients diagnosed with MIS-C between October 2020 and April 2021 in a tertiary hospital. Data from initial episode was obtained from the Spanish national database and the medical history. A standardized phone questionnaire was done one year after the acute episode. As patients pared by age and sex were included with i) history of acute COVID-19, from the same national database, and ii) with peritonitis diagnosis in the electronic medical record. Data was collected using REDCap and analysed with R. Ethics committee approval was obtained. Result(s): A total of 48 patients were included in the study, 16 in each group. Average age at hospitalization was 11,2 years old [IQR: 6,6-14,4] and 52% (23/48) were male. MIS-C patients presented high frequently 94% (15/16) cardiological complications during hospitalization, in contrast with 19% (3/16) of acute COVID-19 patients and 25% (4/16) of peritonitis group (p< 0.01). All of them resolved after a year except the ones associated to hypoxic ischemic encephalopathy in a patient with MIS-C that need ECMO assistance. Summary characteristics during acute episode are shown in Table 1. After one-year follow-up, 88% MIS-C patients suffered one or more symptoms, more frequently: headache (44%), fatigue (38%), insomnia (38%) and concentration problems (38%). A total of 56% of COVID-19 patients presented persisted symptoms, mainly fatigue and concentration problems (19%), and 31% in peritonitis group (19% loss of appetite and abdominal pain), (p< 0.001). MIS-C patients visited more frequently the medical professionals due to emotional change, behaviour or interpersonal relationships after the disease [4/16 (25%) in MIS-C vs. 0/16 (0%) in both control groups, p= 0.028]. Conclusion(s): Majority of MIS-C patients have persistent symptoms one year after acute episode, even with the resolution of cardiological complications. Frequency of long term symptoms in MIS-C patients is significantly higher than in COVID-19 hospitalized and than in a control group of surgical peritonitis patients. Summary characteristics during acute episode.

TREATMENTS for MIS-C in CHILDREN-DISCHARGE, FEVER and SECOND-LINE THERAPIES

Background: We aimed to analyse the effects of steroids, intravenous immunoglobulin (IVIG), and their combination on the probability of discharge over time, probability of switching to second-line treatment over time, and persistent fever after 2 days of treatment. Methods: We did a retrospective study to investigate the effect of treatments (IVIG plus steroids, steroids alone or IVIG alone) of children with MIS-C in a nationwide study, from 1 March to 1 June 2021. We used a Markovian multi-state model with the clock-forward approach and unidirectional arrows to build a multi-state model. Three transitions were defined: initiation of treatment to hospital discharge (t1), initiation of treatment to second-line therapy (t2), and second-line therapy to hospital discharge (t3). A treatment was considered as second-line if initiated >2 days after the first therapy. We estimated the time-to-event probability using a Cox model weighted by the propensity score to balance the baseline characteristics. Results: 30/132 (22.7%) patients were initially treated with steroids alone, 29/132 (21.9%) with IVIG alone, and 73/132 (55%) with IVIG plus steroids. The probability of early discharge was higher with IVIG than with IVIG plus steroids (hazard ratio [HR] 1.65, 95% CI 1.11-2.45, p=0.013), but with a higher probability of needing second-line therapy versus IVIG plus steroids (HR 3.05, 95% CI 1.12-8.25, p=0.028). Patients on steroids had a lower probability of persistent fever after 2 days of treatment (odds ratio [OR] 0.55, 95% CI, 0.28-1.05, p=0.081) versus patients on IVIG plus steroids, and those on the combination had with a lower probability versus IVIG alone (OR 0.21, 95% CI, 0.09-0.46, p=0.0001). We also directly compared the IVig-and steroid-alone treatments. The probability of early discharge of the patients on steroids and on IVig were not different (HR 0·58, 95% CI 0·27-1·24, p=0·166). The probability of transition second-line therapy was also similar (HR 0·71, 95% CI 0·29-1·74, p=0·456). IVIG had a 4-fold higher probability of persistent fever after treatment initiation than steroids (OR 4·23 95% CI 1·43-13·5, p=0·011). Conclusion: IVIG seemed to increase the probability of discharge over time but increased the probability of needing second-line treatment over time. Steroids seemed to reduce persistent fever after 2 days of treatment, and combination therapy reduced the need for escalating treatment.

ORAL SALIVA SWAB RT-PCR AS A FIT-FOR-PURPOSE DIAGNOSTIC TEST for COVID-19 in CHILDREN

Background: Testing using nasopharyngeal swabs (NPS) samples is the cornerstone for the control of the COVID-19 pandemic, but the procedure is uncomfortable and generates anxiety, especially in children. We aimed to evaluate the adequacy of oral saliva swab analysis using RT-PCR comparing to NPS by RT-PCR and Antigen Rapid Test (AgRT) on NPS in children. Methods: Cross-sectional multicenter diagnostic study nested in a prospective, observational cohort (EPICO-AEP) carried out between February and March 2021 at 10 hospitals in Spain. Participants were children 0 to 18 years old with symptoms compatible with SARS-CoV-2 infection of ≤5 days of duration attending at emergency departments. Three samples were collected, two NPS (for AgRT and for RT-PCR) and one oral saliva swab for RT-PCR. In patients with discordant results, new NPS was collected for viral culture and original samples were tested for viral RNA subgenomic (sgRNA) study. Results: 1174 children were included in the analysis, aged 3.8 years (IQR, 1.7-9.0), 647/1174 (55.1%) were male and 760/1174 (64.7%) presented fever 1 day before emergency department admission (IQR 1.0-2.0). Overall, 73/1174 (6.2%) patients tested positive in at least one of the techniques. Sensitivity for RT-PCR in oral saliva swab was 72.1% (95%CI, 59.7-81.9) and specificity 99.6% (95%CI, 99.0-99.9);AgRT in NPS was 61.8% (95%CI, 49.1-73.0) and 99.9% (95%CI, 99.4-100). Kappa index for RT-PCR oral saliva swab was 0.80 (95%CI, 0.72-0.88), and for AgRT was 0.74 (95%CI, 0.65-0.84) vs RT-PCR in NPS. A Bayesian model was used to estimate the accuracy assuming that RT-PCR in NPS is not a perfect gold standard. In this model, sensitivity for RT-PCR oral saliva swab was 84.8% (95%Cr 71.5-93.6), and for AgRT, it was 72.5% (95%Cr, 58.8-83.6). Specificity for RT-PCR oral saliva swab was 99.7% (95%Cr, 99.2-99.9), and for AgRT it was 99.9% (95% Cr, 99.6-100). The Cts were higher in oral saliva swabs compared with NPS;being Ct (NPS)=0.5 x (Ct saliva) + 4.5 (p=0.027). Overall, 4 (10.8%) patients with discordant results had a positive culture. In 3 of the 4 patients, the discordance consisted of positive result on oral saliva swab and nasopharyngeal swabs RT-PCR but negative by antigen rapid diagnostic test. No patient had (+) culture, (+)NP, (-)oral swab. Conclusion: RT-PCR on oral saliva swab is an accurate option for SARS-CoV-2 testing in children. A friendlier technique for younger patients, who must be tested very frequently, may help to increase the number of patients tested.

Diagnostic accuracy of sars-cov-2 antigen rapid test compared to real time pcr in ped

Background: The accuracy of rapid antigen tests (RAT) SARS-CoV-2 for in children is unknown. Our aim was to determine the diagnostic accuracy and concordance of the RAT PanBioTM (Abbott) compared to RT-PCR in nasopharyngeal smear (NPS) samples, in symptomatic pediatric population. Methods: This is a descriptive, retrospective, multicentre clinical study nested in a prospective, observational, multicenter cohort study. We included pediatric patients aged 0 to 16 years with symptoms consistent with COVID-19 of ≤5 days of evolution, attended in the Emergency Departments of the seven centers involved. A total of two consecutive NPS were obtained from each patient: one was employed to perform the RAT and the other to perform RT-PCR. Sample size for a non-inferiority study was calculated considering 80% power, for a 5% prevalence and a 90% sensitivity, using RT-PCR as the gold standard reference. A confusion matrix was displayed. Non-inferiority of sensitivity and specificity between diagnostic tests was assessed using the McNemar's test. The agreement between the two methods was calculated using Cohen's kappa index. Results: A total of 1620 patients were tested in 7 hospitals. The overall sensitivity for RAT PanBioTM was 45.4% (95%CI, 34.1-57.2), and specificity was 99.8% (95%CI, 99.4-99.9) (Figure 1). The positive predictive value (PPV) for this 4.8% prevalence was 92.5% (95%CI, 78.6-97.4). The negative predictive value was 97.3 % (95%CI, 96.8-97.8). Positive likelihood ratio (PLR) was high - 233.8 (IC 95%, 73.5-743.3), and negative likelihood ratio (NLR) was low - 0.54 (95%CI, 0.44-0.67). Conclusion: Compared to RT-PCR, the sensitivity of the RAT PanBioTM was low in children with <5 days of symptoms of COVID-19. The specificity and PLR were good, and the NLR and concordance with RT-PCR were only moderate. These results suggest that the test is very good when the result is positive, and that the test has only a limited value when the result is negative. In relation with screening and public health policy, these results should be interpreted considering also rapidness, availability and false positives ratio compared to RT-PCR or other tests.

Clinical syndromes caused by covid-19 and a bayesian model to predict severity

Background: This study aimed to identify the different syndromes presented in hospitalized children with SARS-CoV-2, to analyze if the clinical features and biomarkers confer different risk depending on the syndromes, and to create a predictive model to anticipate the probability of the need for critical care Methods: We conducted a multicenter, prospective study of children aged 0 to 18 years old with SARS-CoV-2 infection in 52 Spanish hospitals. The primary outcome was the need for critical care: defined as the combined outcome of admission into a PICU, and/or need for respiratory support beyond nasal prongs. To understand the probability of needing critical care according to the diagnostic group and for each risk factor, a Bayesian multivariable model was applied. To build a predictive model of critical care, a naïve Bayes algorithm was implemented in a web app. Results: 292 children were hospitalized from March 12th, 2020 to July 1st, 2020;Of them, 214 (73.3%) were considered to have relevant COVID-19 (r-COVID-19). Among patients with r-COVID-19, 24.2% needed critical care. Out of 214 patients, 22.4% were admitted into a pediatric intensive care unit, 41.6% required respiratory support, and 38.8% presented complications (mostly cardiological). Four patients (1.8%) died, all of them had severe comorbidities. We identified 11 primaries diagnoses and grouped them into 4 large syndromes of decreasing severity: MIS-C (17.3%), bronchopulmonary (51.4%), gastrointestinal (11.6%), and mild syndrome with complications (19.6%). In the predictive model, the predictors with higher relative importance were high C-reactive protein, anemia, lymphopenia, platelets <220 000/mm3, type of syndrome, high creatinine, and days of fever. The different risk factors increase the risk differently depending on the patient's syndrome: the more severe the syndrome, the more risk the factor confers. We developed an online risk prediction tool to quantify the risk of critical disease (https://rserver.h12o. es/pediatria/EPICOAPP/, username: user, password:0000) Conclusion: We described the spectrum of r-COVID-19 in hospitalized children, consisting of 4 large syndromes of decreasing severity: MIS-C, bronchopulmonary syndrome, gastrointestinal syndrome, and a mild syndrome with complications. The risk factors increase the risk differently depending on the syndrome. A Bayesian model was implemented in an online app to anticipate the individual risk of critical care.