Early Identification Of Children Research Articles

Predicting Intensive Care Admission in Children with Acute Asthma: A Meta-Analysis of Predictive Models

Background: Acute asthma is a common cause of pediatric emergency department visits and hospitalizations. Early identification of children at high risk of requiring intensive care unit (ICU) admission is crucial for optimal management and resource allocation. This meta-analysis aimed to evaluate the performance of predictive models for ICU admission in children presenting with acute asthma. Methods: A systematic search of PubMed, Embase, and Cochrane Library was conducted for studies published between 2013 and 2024 that developed or validated predictive models for ICU admission in children with acute asthma. Studies reporting sensitivity, specificity, and area under the receiver operating characteristic curve (AUROC) were included. Methodological quality was assessed using the QUADAS-2 tool. Pooled estimates of diagnostic accuracy were calculated using a random-effects model. Results: Six studies (n = 2,850 children) met the inclusion criteria. The predictive models included clinical features (respiratory rate, oxygen saturation, accessory muscle use), lung function measures (peak expiratory flow rate), and blood gas analysis. Pooled sensitivity ranged from 0.71 (95% CI 0.59-0.82) to 0.78 (95% CI 0.72-0.83), specificity from 0.79 (95% CI 0.75-0.83) to 0.86 (95% CI 0.78-0.91), and AUROC from 0.79 (95% CI 0.72-0.86) to 0.88 (95% CI 0.84-0.92). Conclusion: Several predictive models demonstrate moderate to high accuracy in identifying children with acute asthma at risk of ICU admission. However, heterogeneity in model performance highlights the need for further research to validate existing models in diverse populations and develop more robust tools to guide clinical decision-making.

Linguistic, Metalinguistic and Psychiatric Characteristics of Children with Speech Sound Disorder

Abstract: Comparing the linguistic and metalinguistic profiles in common developmental speech and language disorders is important in advancing our understanding of their clinical symptoms, as well as potentially informing the conceptual basis of novel interventions. The purpose of the present review article is summarizing linguistic, metalinguistic and psychiatric characteristics of children with speech sound disorder (SSD). Clinically and theoretically, it is important that we can understand different error pattern uses among children with SSD only and children with co-occurring SSD and language impairment (LI). Identifying differences in error pattern use will help to discovering the underlying causes of the different types of patterns. In comparison with children with SSD, children with co-occurring SSD and LI use certain patterns more frequently that suggest more global linguistic deficits. The early identification of children who are at risk for development of co-occurring SSD and LI as well as later literacy problems needs to distinguish these patterns. Identification of speech error patterns and their underlying cognitive-linguistic processing deficits will contribute to diagnosis of children at risk of co-occurring SSD and LI and reading problems. Mounting studies have reported that children with SSD, with and without language impairment have differences in phonological processing, literacy skills, and speech production patterns. Children with both speech sound and language disorders are likely to have more severe literacy problems than those with isolated speech sound disorders. In addition, this paper focuses on the comorbidity between psychiatric disorders specially attention deficit/hyperactivity disorder (ADHD) symptoms and SSD.

Mental health problems identified in early school age and later mental health problems and disorders

Abstract Background Poor mental health in childhood and adolescence youth is an important public health challenge. We aimed to examine the prospective association between mental health problems among primary school children and later diagnosed mental disorders and mental health problems in youth. Methods A prospective cohort study of children participating in school health nurse examination during first years of primary school (approx. 6 years) in 17 municipalities in the capital region of Copenhagen, Denmark, with follow-up until their 16th birthday. Baseline data included information from national population registers and school health nurse records. Outcome variables: mental disorders diagnosed at hospital from approx. age 6 until 16 years (N = 6,930) and school health nurse records of mental health problems at approx. age 16 (N = 11,250). Results Problematic relations to peers in early primary school was associated with later neurodevelopmental disorders, including intellectual disability, autism-spectrum disorder and disorders of hyperactivity and inattention (AOR=4.14, 95% CI 2.15-7.97), and poor home related well-being in youth (AOR=1.67, 95% CI 1.02-2.74). Poor school well-being in early primary school was associated with poor school well-being ten years later (AOR=1.67, 95% CI 1.19-2.34) as well as problematic relations to peers (AOR=1.83, 95% CI 1.08-3.10). Further poor general well-being in early primary school was associated with problematic relations to peers in youth (AOR=2.21, 95% CI 1.17-4.18). Conclusions School health nurses identify a group of children in the early years of primary school with mental health problems and an increased risk of later mental health problems and disorders, and therefore they play an important role in the early identification of children at risk. Key messages • Children with problematic relations to peers have up to a fourfold increased risk of later mental disorders. • The school health nurses play an important role in the early identification of children at risk of later mental health problems.

Child development lags and learning trajectories in primary school in Uruguay: compensation or divergence? / Rezagos en el desarrollo infantil y trayectorias de aprendizaje en la enseñanza primaria de Uruguay: ¿compensación o divergencia?

We evaluate two rival hypotheses of: (a) divergent trajectories — or cumulative learning gaps — between children with severe and moderate developmental lags and developmentally on-track children; and (b) convergent trajectories — which predict the inverse pattern. We estimate growth curves using panel data from a cohort of students first assessed by the Early Years Evaluation (Uruguay) at the end of kindergarten (age five), assessed up to three times in language and mathematics on an annual basis during years three to five since their transition to first grade. By the third year in school, substantial differences are found in reading and maths skills between children that did and did not show early developmental lags (effects range between .31 and .46 sd). We find a prevalent pattern of divergence in learning gains between years three to five in school (gaps increase by .10 sd per year). Our results suggest that tackling academic gaps will require timely interventions based on early identification of children who are academically at risk. Uruguay has developed early developmental assessment tools and learning monitoring systems, both of which should serve as the basis of an effective early warning system to deal with learning disparities from early ages.

Long-Term Neurodevelopmental Outcome of Children With Mild Traumatic Brain Injury

BackgroundTo investigate the long-term outcome of pediatric mild traumatic brain injury (mTBI) in terms of neurocognitive, behavioral, and school functioning and to identify clinical risk factors for adverse outcomes. MethodsThis study describes the follow-up of a prospective multicenter sample of 89 children with mTBI 3.6 years postinjury and 89 neurologically healthy children matched for sex, age, and socioeconomic status. Neurodevelopmental outcomes were assessed using an intelligence test, behavioral questionnaires, computerized neurocognitive tests, and longitudinal (pre- and postinjury) standardized school performance data. ResultsChildren with mTBI exhibited intelligence in the average range but had more behavioral problems related to inattentiveness (P = 0.004, d = 0.47) and hyperactive impulsivity (P = 0.01, d = 0.40) and showed poorer neurocognitive performance in information processing stability (P = 0.003, d = −0.55) and Visual Working Memory (P = 0.04, d = −0.39) compared with matched peers. Longitudinal school performance data revealed poorer performance in Technical Reading up to two years postinjury (P = 0.005, d = −0.42) when compared with normative data. Clinical risk factors did not reveal predictive value for adverse outcomes in children with mTBI. ConclusionsThis study indicates that children with mTBI are at risk of long-term deficits in neurocognitive and behavioral functioning, with longitudinal evidence suggesting shortfalls in school performance up to two years postinjury. Clinical risk factors do not provide a solid basis for long-term neurodevelopmental prognosis. Findings emphasize the importance of, and challenges for, early identification of children at risk for adverse neurodevelopmental outcome after mTBI.

Utility of anthropometry in defining overweight and obesity in urban South Indian children.

Waist-based indicators of obesity are being used to detect central obesity and are predictive for metabolic syndrome (MS). The aim of the study is to assess the basic anthropometric indices in children, to determine the prevalence of overweight and obesity, and to determine the association between various waist-based measurements and body mass index (BMI). A cross-sectional study was conducted among children aged 10 to 15 years attending government corporation schools in Chennai. Basic anthropometric measurements were taken. BMI, waist circumference/height ratio (WHtR), and waist circumference/hip circumference ratio (WHR) were calculated. The percentiles (Indian reference cutoffs) were determined for waist circumference (WC) and BMI. The prevalence of overweight and obesity was determined and compared to waist-based parameters. Of 820 children, males constituted 47.1%. Stunting was seen in 9.8% and 7.8% were underweight. 8.2% had BMI less than the 3rd percentile. The prevalence of overweight and obese children was 9% and 3.2%, respectively, with female predominance. The majority had WC less than the 5th percentile. The prevalence of children under risk for MS based on WC >70th percentile was 4.5% and based on WHtR >0.5 was 8.2%. A significant association was identified between all waist-based anthropometric measurements to detect children at risk for MS and overweight/obese children as per BMI category. WHtR >0.5 was an indicator of overweight/obese children in logistic regression analysis. Early identification of children at risk of MS would require a combination of BMI to detect general obesity and waist-based anthropometric measurements to identify central obesity.

Obesity and dental caries in childhood: trends in prevalence and socioeconomic inequalities—a multicohort population-wide data linkage study

ObjectivesTo quantify levels of coexisting obesity and caries experience in children in Scotland, and any associated socioeconomic inequalities over the years 2011/2012–2017/2018.DesignA multicohort population-wide data linkage study.SettingLocal authority primary schools...

Anthropometric Influence on Preschool Children's Physical Fitness and Motor Skills: A Systematic Review.

Early childhood is a critical period for physical and motor development with implications for long-term health. This systematic review examined the relationship between anthropometric characteristics and measures of physical fitness and motor skills in preschool-aged children (typically 2-6 years). The search strategy was applied in four databases (PubMed, ProQuest Central, Scopus, and Web of Science) to find articles published before 11 April 2024. The results consistently demonstrated significant associations between anthropometric variables (height, weight, body mass index [BMI], body composition) and physical performance measures. Notably, height and mass were often better predictors of fitness status than BMI alone. Indicators of undernutrition (stunting, wasting) were negatively associated with motor development, emphasizing the importance of adequate nutrition. While some studies reported impaired fitness and motor skills among overweight/obese preschoolers compared to normal-weight peers, others found no differences based on weight status. Relationships between physical activity levels, anthropometrics, and motor outcomes were complex and inconsistent across studies. This review highlights key findings regarding the influence of anthropometric factors on physical capabilities in early childhood. Early identification of children with impaired growth or excessive adiposity may inform tailored interventions to promote optimal motor development and prevent issues like obesity. Creating supportive environments for healthy growth and age-appropriate physical activity opportunities is crucial during this critical developmental window.

Risk factors for intensive care admission in pediatric patients with COVID-19 - results of the German na-tionwide inpatient sample

Abstract Funding Acknowledgements None. Background In December 2019 first patient-cases of pneumonia caused by an unknown virus were detected in Wuhan, China. From this day on, SARS-CoV-2 spread throughout the world with an enormous pace causing the deadliest pandemic of the twenty-first century. First infection cases in Germany were reported at the end of January 2020 in Bavaria and sustained transmission of SARS-CoV-2 resulted also in Germany in a strong spread of COVID-19 in the population. Although children and young people aged ≤18 years represent approximately 2%-5% of the SARS-CoV-2 cases globally, research efforts regarding COVID-19 pandemic have mainly focused on disease course of adults. Thus, early identification of children who must be monitored for life-threatening severe COVID-19 course remains difficult. Understanding of risk factors for ICU admission as one important bottleneck of adequate management regarding escalated treatment of COVID-19 pandemic is of outstanding interest to understand determinants, which are both crucial factors for adequate health care planning, decision making and pandemic management. Purpose We aimed to close this gap with identification of associated factors with pediatric ICU admissions in Germany. Methods We used the German nationwide inpatient sample analysing all hospitalised children ≤18 years with confirmed COVID-19 diagnosis in Germany between January 1st and December 31st, 2020 stratified fur ICU admission (source: RDC of the Federal Statistical Office and the Statistical Offices of the federal states, DRG Statistics 2020, own calculations). Results Overall, 3,360 cases of hospitalised children ≤18 years with COVID-19 infection were diagnosed in Germany 2020 (median age 7.0 [IQR 0.0-15.0] years, 49.8% of female sex); among them 4.3% had to be admitted on ICU. In-hospital death occurred in five patients with and three without ICU admission (3.5% vs. 0.1%, P<0.001) and ICU admission was independently associated with increased case-fatality (OR 21.573 [95%CI 4.191-111.044], P<0.001). Obesity (OR 3.419 [95%CI 1.300-8.993], P=0.013), diabetes mellitus (OR 6.929 [95%CI 3.327-14.432], P<0.001), pneumonia (OR 7.373 [95%CI 4.823-11.271], P<0.001), ARDS (OR 48.058 [95%CI 11.689-197.588], P<0.001) and multi-segmental Inflammatory syndrome caused by COVID-19 (OR 9.573 [95%CI 3.036-30.191], P<0.001), heart failure (OR 64.509 [95%CI 24.462-170.121], P<0.001), myocarditis (OR 4.682 [95%CI 1.278-17.149], P=0.020), acute and/or chronic kidney failure (OR 7.946 [95%CI 3.606-17.508], P<0.001), cancer (OR 5.220 [95%CI 2.599-10.485], P<0.001) and liver diseases (OR 5.501 [95%CI 2.177-13.899], P<0.001) were associated with ICU admission. Conclusions The proportion of hospitalized paediatric COVID-19 patients admitted on ICU in Germany was low with 4.3% accompanied by 3.5% case-fatality rate. Independent factors for ICU admission comprised cardio-vascular risk factors, comorbidities and complications of COVID-19.

Development and validation of an online dynamic nomogram system for pulmonary consolidation in children with Mycoplasma pneumoniae pneumonia.

The occurrence of pulmonary consolidation in children with Mycoplasma pneumoniae pneumonia (MPP) can lead to exacerbation of the disease. Therefore, early identification of children with MPP in combination with pulmonary consolidation is critical. The purpose of this study was to develop a straightforward, easy-to-use online dynamic nomogram for the identification of children with MPP who are at high risk of developing pulmonary consolidation. 491 MPP patients were chosen and divided randomly into a training cohort and an internal validation cohort at a 4:1 ratio. Multi-factor logistic regression was used to identify the risk variables for mixed pulmonary consolidation in children with Mycoplasma pneumoniae (MP). The selected variables were utilized to build the nomograms and validated using the C-index, decision curve analysis, calibration curves, and receiver operating characteristic (ROC) curves. Seven variables were included in the Nomogram model: age, fever duration, lymphocyte count, C-reactive protein (CRP), ferritin, T8 lymphocyte percentage, and T4 lymphocyte percentage. We created a dynamic nomogram that is accessible online ( https://ertong.shinyapps.io/DynNomapp/ ). The C-index was 0.90. The nomogram calibration curves in the training and validation cohorts were highly comparable to the standard curves. The area under the curve (AUC) of the prediction model was, respectively, 0.902 and 0.883 in the training cohort and validation cohort. The decision curve analysis (DCA) curve shows that the model has a significant clinical benefit. We developed a dynamic online nomogram for predicting combined pulmonary consolidation in children with MP based on 7 variables for the first time. The predictive value and clinical benefit of the nomogram model were acceptable.

Exhaled Volatile Organic Compounds for Asthma Control Classification in Children with Moderate to Severe Asthma: Results from the SysPharmPediA Study.

Early identification of children with poorly controlled asthma is imperative for optimizing treatment strategies. The analysis of exhaled volatile organic compounds (VOCs) is an emerging approach to identify prognostic and diagnostic biomarkers in pediatric asthma. To assess the accuracy of gas chromatography-mass spectrometry based exhaled metabolite analysis to differentiate between controlled and uncontrolled pediatric asthma. This study encompassed a discovery (SysPharmPediA) and validation phase (U-BIOPRED, PANDA). Firstly, exhaled VOCs that discriminated asthma control levels were identified. Subsequently, outcomes were validated in two independent cohorts. Patients were classified as controlled or uncontrolled, based on asthma control test scores and number of severe attacks in the past year. Additionally, potential of VOCs in predicting two or more future severe asthma attacks in SysPharmPediA was evaluated. Complete data were available for 196 children (SysPharmPediA=100, U-BIOPRED=49, PANDA=47). In SysPharmPediA, after randomly splitting the population into training (n=51) and test sets (n=49), three compounds (acetophenone, ethylbenzene, and styrene) distinguished between uncontrolled and controlled asthmatics. The area under the receiver operating characteristic curve (AUROCC) for training and test sets were respectively: 0.83 (95% CI: 0.65-1.00) and 0.77 (95% CI: 0.58-0.96). Combinations of these VOCs resulted in AUROCCs of 0.74 ±0.06 (UBIOPRED) and 0.68 ±0.05 (PANDA). Attacks prediction tests, resulted in AUROCCs of 0.71 (95% CI 0.51-0.91) and 0.71 (95% CI 0.52-0.90) for training and test sets. Exhaled metabolites analysis might enable asthma control classification in children. This should stimulate further development of exhaled metabolites-based point-of-care tests in asthma.

An integrated molecular risk score early in life for subsequent childhood asthma risk.

Numerous children present with early wheeze symptoms, yet solely a subgroup develops childhood asthma. Early identification of children at risk is key for clinical monitoring, timely patient-tailored treatment, and preventing chronic, severe sequelae. For early prediction of childhood asthma, we aimed to define an integrated risk score combining established risk factors with genome-wide molecular markers at birth, complemented by subsequent clinical symptoms/diagnoses (wheezing, atopic dermatitis, food allergy). Three longitudinal birth cohorts (PAULINA/PAULCHEN, n = 190 + 93 = 283, PASTURE, n = 1133) were used to predict childhood asthma (age 5-11) including epidemiological characteristics and molecular markers: genotype, DNA methylation and mRNA expression (RNASeq/NanoString). Apparent (ap) and optimism-corrected (oc) performance (AUC/R2) was assessed leveraging evidence from independent studies (Naïve-Bayes approach) combined with high-dimensional logistic regression models (LASSO). Asthma prediction with epidemiological characteristics at birth (maternal asthma, sex, farm environment) yielded an ocAUC = 0.65. Inclusion of molecular markers as predictors resulted in an improvement in apparent prediction performance, however, for optimism-corrected performance only a moderate increase was observed (upto ocAUC = 0.68). The greatest discriminate power was reached by adding the first symptoms/diagnosis (up to ocAUC = 0.76; increase of 0.08, p = .002). Longitudinal analysis of selected mRNA expression in PASTURE (cord blood, 1, 4.5, 6 years) showed that expression at age six had the strongest association with asthma and correlation of genes getting larger over time (r = .59, p < .001, 4.5-6 years). Applying epidemiological predictors alone showed moderate predictive abilities. Molecular markers from birth modestly improved prediction. Allergic symptoms/diagnoses enhanced the power of prediction, which is important for clinical practice and for the design of future studies with molecular markers.

Medication Usage Record-Based Predictive Modeling of Neurodevelopmental Abnormality in Infants under One Year: A Prospective Birth Cohort Study.

Early identification of children with neurodevelopmental abnormality is a major challenge, which is crucial for improving symptoms and preventing further decline in children with neurodevelopmental abnormality. This study focuses on developing a predictive model with maternal sociodemographic, behavioral, and medication-usage information during pregnancy to identify infants with abnormal neurodevelopment before the age of one. In addition, an interpretable machine-learning approach was utilized to assess the importance of the variables in the model. In this study, artificial neural network models were developed for the neurodevelopment of five areas of infants during the first year of life and achieved good predictive efficacy in the areas of fine motor and problem solving, with median AUC = 0.670 (IQR: 0.594, 0.764) and median AUC = 0.643 (IQR: 0.550, 0.731), respectively. The final model for neurodevelopmental abnormalities in any energy region of one-year-old children also achieved good prediction performance. The sensitivity is 0.700 (IQR: 0.597, 0.797), the AUC is 0.821 (IQR: 0.716, 0.833), the accuracy is 0.721 (IQR: 0.696, 0.739), and the specificity is 0.742 (IQR: 0.680, 0.748). In addition, interpretable machine-learning methods suggest that maternal exposure to drugs such as acetaminophen, ferrous succinate, and midazolam during pregnancy affects the development of specific areas of the offspring during the first year of life. This study established predictive models of neurodevelopmental abnormality in infants under one year and underscored the prediction value of medication exposure during pregnancy for the neurodevelopmental outcomes of the offspring.

Recognizing Traumatization in Children Aged 4 to 8: A Pilot Validation Study of the Odense Child Trauma Screening (OCTS) Measure in Lithuania

ABSTRACT Early identification of children at risk of posttraumatic stress symptomatology or other emotional and behavioral problems is highly needed for the prevention of long-term consequences of traumatic events and abuse. However, the assessment of the traumatization of very young children is challenging because they cannot fully verbalize their psychological experiences. The purpose of this pilot study was to test the internal consistency, interrater reliability, and validity of the Odense Child Trauma Screening (OCTS) measure, a structured play test for signs of traumatization in young children. The total sample was comprised of 26 (50%) children from the community and 26 from risk groups in Lithuania. The mean age of the participants was 6.44 (SD = 1.63; range 3–9); 62% were girls. The OCTS interviews were conducted with all children. The Child and Adolescent Trauma Screen (CATS) and the Strengths and Difficulties Questionnaire (SDQ) were used to collect data about the child from the caregivers. Caregivers of the risk sample group reported significantly more potentially traumatic events experienced by the children (M = 2.73) than in the community sample (M = 1.00). The OCTS results indicated acceptable internal consistency and good inter-rater reliability. However, only one of the four OCTS stories scores was significantly higher in the risk group. We found no sex effects on the OCTS scores. This pilot study of the psychometric properties of the OCTS supports the reliability of the OCTS and indicates that the OCTS administration and coding procedures can be consistently applied in various settings.

Development and Validation of a Nomogram for Predicting Obstructive Sleep Apnea Severity in Children.

The clinical presentation of Obstructive Sleep Apnea (OSA) in children is insidious and harmful. Early identification of children with OSA, particularly those at a higher risk for severe symptoms, is essential for making informed clinical decisions and improving long-term outcomes. Therefore, we developed and validated a risk prediction model for severity in Chinese children with OSA to effectively identify children with moderate-to-severe OSA in a clinical setting. From June 2023 to September 2023, we retrospectively analyzed the medical records of 367 Children diagnosed with OSA through portable bedside polysomnography (PSG). Predictor variables were screened using the least absolute shrinkage and selection operator (LASSO) and logistic regression techniques to construct nomogram to predict the severity of OSA. Receiver operating characteristic curve (ROC), calibration curve, decision curve analysis (DCA), and clinical impact curve (CIC) were used to determine the discrimination, calibration, and clinical usefulness of the nomogram. A total of 367 children with a median age of 84 months were included in this study. Neck circumference, ANB, gender, learning problem, and level of obstruction were identified as independent risk factors for moderate-severe OSA. The consistency indices of the nomogram in the training and validation cohorts were 0.841 and 0.75, respectively. The nomogram demonstrated a strong concordance between the predicted probabilities and the observed probabilities for children diagnosed with moderate-severe OSA. With threshold probabilities ranging from 0.1 to 1.0, the predictive model demonstrated strong predictive efficacy and yielded improved net benefit for clinical decision-making. ROC analysis was employed to classify the children into high and low-risk groups, utilizing the Optimal Cutoff value of 0.39. A predictive model using LASSO regression was developed and validated for children with varying levels of OSA. This model identifies children at risk of developing OSA at an early stage.

Prevalence of dental fear among students of Hyderabad Sindh.

Background: Despite the advancements in making dentistry more comfortable, dental phobia remains a significant concern. Research suggests that children's dental anxiety may persist into adolescence, leading to avoidance of dental care and disruptive behavior during treatment. Early identification of children with dental fear is crucial for dental professionals to promptly employ appropriate pediatric management strategies. The study aims to assess the prevalence of dental fear among students in Hyderabad, Pakistan. Methodology: A cross-sectional study was conducted among 11- to 16-year-old male and female students in schools in Hyderabad, Pakistan. The Children's Fear Survey Schedule-Dental Subscale (CFSS-DS) in English was utilized. The study included students in grades 6 to 8 residing in Hyderabad, with no general pathology and not on any medication. Data analysis was performed using SPSS version 25. Results: The study encompassed 295 participants, 45.1% females and 54.9% males. The percentage of participants experiencing dental fear (combining moderate and high fear) was 168 (57%), while 127 (41%) reported no dental fear. Analysis based on low to high levels of fear indicated slightly increased moderate and high fear levels in female participants (47.5% and 52%, respectively) compared to male students (36.5% and 47%, respectively). Conclusion: The study suggests the need for significant attention to preventing dental fear. School-based health policies and parents should focus on psychosocial factors associated with the fear of dental treatment, as many of these factors are preventable. Dental anxiety poses challenges not only for patients but also for dentists, occasionally complicating the successful execution of treatments.

The Systemic Immune-Inflammation Index (SII) and coronary artery lesions in Kawasaki disease.

Coronary artery lesions (CALs) are the most common complications of Kawasaki disease (KD) and play a crucial role in determining the prognosis of the disease. Consequently, the early identification of children with KD who are at risk of developing coronary artery damage is vitally important. We sought to investigate the relationship between the Systemic Immune-Inflammation Index (SII) and CALs in patients with KD and to assess its predictive value. We carried out a retrospective review and analysis of medical records for KD patients treated at the First Affiliated Hospital of Anhui Medical University between January 2017 and January 2023. We utilized single-variable tests, binary logistic regression analysis, ROC curve analysis, restricted cubic spline tests, and curve fitting to evaluate the association between SII and CALs. In our study, 364 patients were included, with 63 (17.3%) presenting with CALs at the time of admission. The binary logistic regression analysis indicated that SII was a significant risk factor for CALs at admission, evident in both unadjusted and models adjusted for confounders. The ROC curve analysis revealed an AUC (Area Under the Curve) value of 0.789 (95%CI 0.723-0.855, P < 0.001) for SII's predictive ability regarding CALs at admission. A consistent positive linear relationship between SII and the risk of CALs at admission was observed in both the raw and adjusted models. Our research findings suggest that SII serves as a risk factor for CALs and can be used as an auxiliary laboratory biomarker for predicting CALs.

Investigating autism knowledge, self-efficacy, and confidence following maternal and child health nurse training for the early identification of autism.

Early identification of children with a high likelihood of autism can lead to referral for diagnostic services and access to early supports, resulting in improved outcomes for children and families. Maternal and Child Health Nurses (MCHNs) in Victoria, Australia, are well-placed to monitor infants and toddlers for signs of autism, given children and caregivers attend free, regular, well-baby consultations from birth through to school age. This study aimed to identify the impact of personal and workplace factors on MCHNs' competencies of autism knowledge, self-efficacy in identifying autistic infants and toddlers, and confidence in speaking to parents/caregivers about autism. Additionally, the study sought to identify which personal and workplace factors might predict increased competency in these areas. After identifying training needs and current competency levels via a training needs analysis (TNA), 1,428 MCHNs received training on the early signs of autism and in the use of the Social Attention and Communication Surveillance-Revised (SACS-R) tool for early autism identification; the training program was known as Monitoring of Social Attention, Interaction, and Communication (MoSAIC). Previous MCHN autism training and knowledge of autism community resources significantly contributed to increased MCHN self-efficacy in identifying autistic infants and toddlers, while knowledge of community resources was the best predictor of confidence in speaking with parents/caregivers about autism. Perceived self-efficacy and confidence in speaking with parents/caregivers about autism significantly increased following the MoSAIC autism training. Targeted autism training for primary health practitioners is an important first step for early autism identification and initiating conversations with parents/caregivers.

Nearly Half of Extreme Preterm Infants Are Iron Deficient at 4-6 Months of Corrected Age Despite Prophylactic Iron Supplementation

Background: Iron deficiency (ID) is the most prevalent micronutrient deficiency globally and has been associated with negative neurodevelopmental and behavioral outcomes in infants and young children. Susceptibility to ID is heightened in preterm infants due to lower iron reserves at birth, rapid growth during the initial weeks of life, immature erythropoiesis, and frequent blood samplings during hospitalization. To mitigate this problem, international bodies recommend prophylactic iron therapy from 2-6 weeks of age until at least 6-12 months in preterm infants. Currently, the literature regarding iron status in extremely preterm infants (EPI, infants born less than 28 weeks gestational age) who receive prophylactic iron supplementation after birth is limited. Considering the potential long-term detrimental effects of ID on the developing brain of these high-risk preterm infants, examining the prevalence and risk factors for ID are crucial to implement prevention strategies. Objective: To investigate the prevalence and risk factors associated with ID in EPI Methods: A retrospective cohort study was conducted using a population-based Provincial Perinatal Follow-Up database on all live EPIs born in Nova Scotia between 2005 and 2018. Infants with congenital malformations, chromosomal anomalies, blood disorders or those who died before outcome assessment were excluded. Prophylactic iron supplementation (2-3 mg/kg/day) starting at 2-4 weeks of chronological age was a standard of care for all included infants. Further, the dosage of iron was adjusted regularly during the hospital stay based on serum ferritin (SF) levels. Discharge instructions recommended continuing iron prophylaxis until 9-12 months corrected age (CA). At 4-6 months CA, all infants underwent blood tests to evaluate hemoglobin, and SF levels. ID was defined as SF levels below 20g/L or 12g/L at 4 and 6 months CA, respectively. A univariate analysis was performed by using a series of single-variable logistic regression models to identify the factors associated with presence of ID. Factors with a p-value &amp;lt; 0.20 in the univariate analysis were entered into a multivariable risk model using a backward selection procedure. Variables with a p-value &amp;lt; 0.05 were retained. Results: Among 146 infants, 67 (45.9%) had ID. Ferritin (16.4 µg/L vs 50.0 µg/L, p &amp;lt; .001) and reticulocyte hemoglobin equivalent (28.4pg vs 31.6pg, p &amp;lt; .001) were significantly lower in the ID group than non-ID group. The prevalence of ID decreased over time, from 59.7% in 2005-2011 to 40.3% in 2012-2018 (p = 0.52). Table 1 compares the antenatal and neonatal characteristics of the ID and non-ID groups. Table 2 compares sociodemographic variables and clinical variables at 4-6 months CA between two groups. Breastfeeding (exclusive or partial) versus formula alone at a 4-6 months CA was identified as an independent factor protective for ID (Odds: 0.2 (0.1 - 0.6), p = 0.003). Iron therapy at follow-up was also protective for ID but did not remain significant in the final model. Of note, iron therapy was stopped in 40 (27.4%) EPI before 4-6 months CA. Supplemental iron intake at 4-6 months CA was significantly lower in the infants receiving exclusive formula feeding (66.1%) compared with those breastfed (99.1%, p = 0.006). Conclusion(s): Despite prophylactic iron supplementation, nearly half of the EPI had ID at 4-6 months CA, and iron therapy was discontinued in roughly a quarter of all EPI before 4-6 months CA. Breastfeeding at 4-6 months follow-up was found to be protective for ID. High prevalence of ID in EPI highlights the need for further research in this area to avert the negative neurodevelopmental consequences of ID on the developing brain of these high-risk infants. Closer monitoring of iron status and early identification of children at high risk for ID is imperative to maximize the benefits of prophylactic iron supplementation in EPI. Further, there is lack of sufficient data for iron requirements in EPI leading to a variability in iron therapy recommendations by different professional organizations. Future prospective studies to investigate specific iron requirements of EPI as well as risk factors for ID in this high-risk vulnerable population are essential to optimize their neurodevelopmental outcomes.

1687. Unprecedented Outbreak of Invasive group A Streptococcus Infections in Children - Colorado, October 2022 to March 2023

Abstract Background Since the fall of 2022, we have observed a sharp rise in pediatric invasive group A Streptococcus (iGAS) hospitalizations in Colorado, similar to trends reported in other countries. Methods From October 2022 – March 2023, iGAS cases were prospectively identified in patients hospitalized at Children’s Hospital Colorado and medical charts were systematically reviewed. iGAS was defined as isolation of GAS from a sterile site (confirmed case) or a non-sterile site with clinically consistent disease (probable). Using laboratory specimen records, we compared the number of patients with sterile site GAS-positive cultures across three time periods: Pre-COVID-19 (Jan 2015 – Mar 2020), COVID-19 pandemic (Apr 2020 – Sep 2022), and Outbreak (Oct 2022 – Mar 2023). Results Among the 81 iGAS cases identified during the outbreak (Table 1), median age was 6 years old; 64% of patients were male and 69% were previously healthy. 33% of patients required pediatric intensive care unit (PICU) admission, and two patients died. iGAS was more commonly associated with upper respiratory infection (URI) symptoms (63%) than isolated sore throat (5%) or trauma/skin findings (15%). The most common clinical manifestations were head and neck infections (37%), musculoskeletal infections (32%) and pneumonia (20%). 11% had toxic shock syndrome and 4% had necrotizing fasciitis. Lab findings associated with PICU admission were bandemia, leukopenia and higher CRP values. Disease severity and treatment varied by clinical manifestation (Table 2). There were more iGAS cases during the outbreak (average 10.0/month) compared to pre-pandemic years (3.8/month over the same period) and during the pandemic (1.2/month over the same period) (Figure 1). Conclusion We report an unprecedented outbreak of iGAS in pediatric patients in Colorado, with case numbers close to triple the pre-pandemic baseline at our hospital. The timing and high proportion of cases with associated URI symptoms suggest a link to the recent surges in respiratory viruses, although iGAS cases have continued to persist past the peak of respiratory season. Invasive GAS can be severe and evolve rapidly; there are important clinical and laboratory features that may help in earlier identification of children who are critically ill. Disclosures Samuel R. Dominguez, MD, PhD, Biofire Diagnostics: Advisor/Consultant|Biofire Diagnostics: Grant/Research Support|Cobio Diagnostics: Board Member|Karius: Advisor/Consultant|Pfizer: Grant/Research Support