Risk factors for severe respiratory syncytial virus infection during the first year of life: development and validation of a clinical prediction model.

BACKGROUND: Novel immunisation methods against respiratory syncytial virus (RSV) are emerging, but knowledge of risk factors for severe RSV disease is insufficient for optimal targeting of interventions against them. Our aims were to identify predictors for RSV hospital admission from registry-based data and to develop and validate a clinical prediction model to guide RSV immunoprophylaxis for infants younger than 1 year. METHODS: In this model development and validation study, we studied all infants born in Finland between June 1, 1997, and May 31, 2020, and in Sweden between June 1, 2006, and May 31, 2020, along with the data for their parents and siblings. Infants were excluded if they died or were admitted to hospital for RSV within the first 7 days of life. The outcome was hospital admission due to RSV bronchiolitis during the first year of life. The Finnish study population was divided into a development dataset (born between June 1, 1997, and May 31, 2017) and a temporal hold-out validation dataset (born between June 1, 2017, and May 31, 2020). The development dataset was used for predictor discovery and selection in which we screened 1511 candidate predictors from the infants', parents', and siblings' data, and developed a logistic regression model with the 16 most important predictors. This model was then validated using the Finnish hold-out validation dataset and the Swedish dataset. FINDINGS: In total, there were 1 124 561 infants in the Finnish development dataset, 130 352 infants in the Finnish hold-out validation dataset, and 1 459 472 infants in the Swedish dataset. In addition to known predictors such as severe congenital heart defects (adjusted odds ratio 2·89, 95% CI 2·28-3·65), we confirmed some less established predictors for RSV hospital admission, most notably oesophageal malformations (3·11, 1·86-5·19) and lower complexity congenital heart defects (1·43, 1·25-1·63). The prediction model's C-statistic was 0·766 (95% CI 0·742-0·789) in Finnish data and 0·737 (0·710-0·762) in Swedish validation data. The infants in the highest decile of predicted RSV hospital admission probability had 4·5 times higher observed risk compared with others. Calibration varied according to epidemic intensity. The model's performance was similar to a machine learning (XGboost) model using all 1511 candidate predictors (C-statistic in Finland 0·771, 95% CI 0·754-0·788). The prediction model showed clinical utility in decision curve analysis and in hypothetical number needed to treat calculations for immunisation, and its C-statistic was similar across different strata of parental income. INTERPRETATION: The identified predictors and the prediction model can be used in guiding RSV immunoprophylaxis in infants, or as a basis for further immunoprophylaxis targeting tools. FUNDING: Sigrid Jusélius Foundation, European Research Council, Pediatric Research Foundation, and Academy of Finland.

Risk factors for multisystem inflammatory syndrome in children - A population-based cohort study of over 2 million children.

Background: Although severe acute COVID-19 is rare in children, SARS-CoV-2 infection can trigger the novel post-infectious condition multisystem inflammatory syndrome in children (MIS-C). Increased knowledge on risk factors for MIS-C could improve our understanding of the pathogenesis of the condition and better guide targeted public health interventions. The aim of the study was to assess risk factors for MIS-C with the aim to identify vulnerable children. Methods: A register-based cohort study including all children and adolescents <19 years born in Sweden between March 1, 2001- December 31, 2020 was performed. Data on sociodemographic risk factors and comorbidities (sex, age, parental region of birth, parental education, asthma, autoimmune disease, chromosomal anomalies, chronic heart disease, chronic lung disease, obesity, life-limiting condition) were retrieved from national health and population registers. The outcome was MIS-C diagnosis according to the Swedish Pediatric Rheumatology Quality Register during March 1, 2020 - December 8, 2021.Hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated using Cox regression analysis. Incidence rates per 100 000 person-years were calculated assuming a Poisson distribution. Findings: Among 2 117 443 children included in the study, 253 children developed MIS-C, corresponding to an incidence rate of 6·8 (95% CI: 6·0-7·6) per 100 000 person-years. Male sex (HR 1·65, 95% CI: 1·28-2·14), age 5-11 years (adjusted HR 1·44, 95% CI: 1·06-1·95 using children 0-4 years as reference), foreign-born parents (HR 2·53, 95% CI: 1·93-3·34), asthma (aHR 1·49, 95% CI: 1·00-2·20), obesity (aHR 2·15, 95% CI: 1·09-4·25) and life-limiting conditions (aHR 3·10, 95% CI: 1·80-5·33) were associated with MIS-C. Children 16-18 years had a reduced risk for MIS-C (aHR 0·45, 95% CI: 0·24-0·85). Interpretation: We report increased risks for MIS-C in children with male sex, age 5-11 years, foreign-born parents, asthma, obesity, and life-limiting condition. Knowing these risk populations might facilitate identification of children with MIS-C and potentially guide targeted public health interventions. Nevertheless, the absolute risks for MIS-C were very low. Funding: Financial support was provided from the Swedish Research Council (grant no 2018-02640), the Swedish Heart-Lung Foundation (grant no 20210416), the Asthma and Allergy Association, Ake Wiberg foundation, the Samariten Foundation, the Society of Child Care, and Region Stockholm.

Paediatric asthma and non-allergic comorbidities: A review of current risk and proposed mechanisms.

It is increasingly recognized that children with asthma are at a higher risk of other non-allergic concurrent diseases than the non-asthma population. A plethora of recent research has reported on these comorbidities and progress has been made in understanding the mechanisms for comorbidity. The goal of this review was to assess the most recent evidence (2016-2021) on the extent of common comorbidities (obesity, depression and anxiety, neurodevelopmental disorders, sleep disorders and autoimmune diseases) and the latest mechanistic research, highlighting knowledge gaps requiring further investigation. We found that the majority of recent studies from around the world demonstrate that children with asthma are at an increased risk of having at least one of the studied comorbidities. A range of potential mechanisms were identified including common early life risk factors, common genetic factors, causal relationships, asthma medication and embryologic origins. Studies varied in their selection of population, asthma definition and outcome definitions. Next, steps in future studies should include using objective measures of asthma, such as lung function and immunological data, as well as investigating asthma phenotypes and endotypes. Larger complex genetic analyses are needed, including genome-wide association studies, gene expression-functional as well as pathway analyses or Mendelian randomization techniques; and identification of gene-environment interactions, such as epi-genetic studies or twin analyses, including omics and early life exposure data. Importantly, research should have relevance to clinical and public health translation including clinical practice, asthma management guidelines and intervention studies aimed at reducing comorbidities.

Pneumonia in Infancy and Risk for Asthma: The Role of Familial Confounding and Pneumococcal Vaccination.

BACKGROUND: Studies have reported an increased risk for asthma following lower respiratory tract infections, but few studies have specifically assessed this risk in children diagnosed with pneumonia in infancy. Furthermore, it is not fully understood whether this association is indicative of a causal relationship or if certain children have a predisposition for both diseases. RESEARCH QUESTION: Are children diagnosed with pneumonia in infancy at increased risk for asthma, and what is the role of familial confounding and pneumococcal conjugate vaccine immunization on the association? STUDY DESIGN AND METHODS: This study was a nationwide register-based cohort analysis of > 900,000 Swedish children to assess the association between pneumonia in infancy and prevalent asthma at 4 years. A secondary aim was to assess if the association has changed after the introduction of nationwide pneumococcal conjugate vaccine (PCV) immunization as this has led to a shift in pneumonia etiology. The study controlled for important confounders, including shared environmental and familial confounding, by using sibling analyses. RESULTS: There was a strong association between pneumonia diagnosis in infancy and prevalent asthma at 4 years (adjusted OR, 3.38; 95% CI, 3.26-3.51), as well as in the full sibling analyses (adjusted OR, 2.81; 95% CI, 2.58-3.06). The risk for asthma following pneumonia diagnosis in infancy was slightly higher for those born in the PCV period compared with the pre-PCV period (adjusted OR, 3.80 [95% CI, 3.41-4.24] vs 3.28 [95% CI, 3.15-3.42]) when the proportion of viral pneumonia etiology was also higher (14.5% vs 10.7%, respectively) and the overall asthma prevalence was lower (5.3% vs 6.6%). INTERPRETATION: Children diagnosed with pneumonia in infancy have a highly increased risk for prevalent asthma at 4 years, which might have implications for future asthma preventive measures and needs to be considered when assessing the morbidity that can be attributed to pneumonia.

Asthma and subsequent school performance at age 15-16 years: A Swedish population-based sibling control study.

Asthma may negatively affect children's school performance, such as grades and exam results. Results from previous studies have shown varying results and may have suffered from confounding and other biases. We used a Swedish population-based cohort of 570,595 children with data on asthma (including severity and control) in Grades 7-8 and 9, school performance from Grade 9 (grade point sum, non-eligibility for upper secondary school and national test results) and measured confounders from national registers. We used sibling comparisons to account for unmeasured familial factors. Children with asthma and severe asthma performed slightly better in school than children without asthma when adjusting for measured confounders, but the associations were attenuated in sibling comparisons. In contrast, children with uncontrolled asthma performed slightly worse (e.g. Grade 9: ßadj = -9.9; 95% CI -12.8 to -7.0; Cohen's d = 0.16). This association remained for uncontrolled asthma in Grade 9 in sibling comparisons (Grade 9: ß = -7.7 points; 95% CI -12.6 to -2.6; Cohen's d = 0.12), but not for Grades 7-8. The attenuation of estimates when controlling for familial factors using sibling comparisons suggests that the differences were due to familial factors, rather than being causal. The remaining associations in sibling comparisons between uncontrolled asthma in Grade 9 and school performance are consistent with a causal association.