Modification of an outcome measure to follow symptoms of children with acute otitis media.

BACKGROUND: To modify a parent-reported acute otitis media severity of symptoms scale (AOM-SOS) to ensure that it accurately reflects parental concerns. METHODS: Using qualitative interviews with parents of children with acute otitis media (AOM) (n = 24), we generated 39 candidate items for inclusion in the new version of the scale. We determined the importance of each item by enrolling 50 other parents of children with AOM. We selected 15 items with high importance and used them to create a new version of the scale. During successive rounds of cognitive interviews, 3 items were dropped. Two additional items were dropped because they were highly correlated. We evaluated the psychometric properties of the new, 10-item version (version 6.0) in 139 children with AOM. RESULTS: AOM-SOS scores correlated with functional status (r = -0.53), parent assessment of child's pain level (r = 0.69), and overall symptom severity (r = 0.41). The internal consistency of the scale, as measured by Cronbach's alpha, was 0.90. Responsiveness (standardized response mean = 1.82) and test-retest reliability (0.77) were excellent and good, respectively. CONCLUSION: Data presented here support the use of the new version of the scale as a longitudinal measure of symptom burden in clinical trials of children with AOM. IMPACT STATEMENT: The AOM-SOS scale, which now incorporates parental views, can be used to track symptom severity in future efficacy trials in young children with acute otitis media. Data is presented on the validity, reliability, and responsiveness of the AOM-SOS scale. Otitis media is the most frequent indication for antibiotic use in young children. The AOM-SOS is one of the few validated disease specific scales available for use in efficacy trials of children with acute otitis media.

Antimicrobial prophylaxis for vesicoureteral reflux: which subgroups of children benefit the most?

BACKGROUND: While the Randomized Intervention for Children with Vesicoureteral Reflux (RIVUR) trial found that long-term antimicrobial prophylaxis reduced the risk of urinary tract infection (UTI) recurrences by 50%, 10 children had to be treated for one to benefit (i.e., observed number needed to treat (NNT) of 10). Accordingly, we re-analyzed RIVUR data to systematically identify subgroups of children with vesicoureteral reflux (VUR) with a smaller NNT. METHODS: Using patient-level data from the RIVUR trial, we applied penalized regression methods including the baseline age, VUR grade, type of index UTI, and bowel-bladder dysfunction (BBD) as covariates to identify subgroups. RESULTS: We identified four relevant subgroups of children that appear to benefit from long-term antimicrobial prophylaxis, all with observed NNTs smaller than or equal to 5: children with grade IV VUR, BBD, and febrile index UTI (1% of the sample), children with BBD and febrile index UTI (7% of the sample), children with BBD (12% of the sample), and children with grade IV VUR (8% of the sample). CONCLUSIONS: Use of long-term antimicrobial prophylaxis appears to be particularly relevant for children with BBD (and any grade of VUR) and those with grade IV VUR (regardless of BBD status). However, because details regarding the treatment of BBD are not available, further studies are needed to fully determine the role of prophylactic antimicrobials in the management of children with VUR who have BBD.

Antibiotics for Acute Sinusitis in Children: A Meta-Analysis.

CONTEXT: Acute sinusitis is one of the leading causes of antibiotic prescriptions in children. No recent systematic reviews have examined the efficacy of antibiotics compared with placebo. OBJECTIVE: We sought to determine if antibiotics are superior to placebo in the treatment of acute sinusitis in children. DATA SOURCES: Medline and Embase were searched from their origin to July 2023. STUDY SELECTION: We considered randomized placebo-controlled studies focusing on the treatment of acute sinusitis. In all studies, symptoms were present for <4 weeks and subjects were <18 years of age. DATA EXTRACTION: Two authors independently extracted the data. We pooled data primarily using fixed-effects models. RESULTS: Analysis of 6 included studies showed that antibiotic treatment reduced the rate of treatment failure by 41% (with a risk ratio of 0.59; 95% confidence interval 0.49-0.72) compared with placebo. There was substantial heterogeneity between the studies (I2 = 69.7%), which decreased substantially when the 1 study with a high risk of bias was removed (I2 = 26.9%). Children treated with antibiotics were 1.6 times more likely to have diarrhea than those who were not treated with antibiotics (risk ratio = 1.62, 95% confidence interval 1.04-2.51). LIMITATIONS: A small number of studies were eligible for inclusion. Included studies differed in their methodology. CONCLUSIONS: In children with clinically diagnosed acute sinusitis, antibiotics significantly reduced the rate of treatment failure compared with placebo. However, given the favorable natural history of sinusitis, our results could also support close observation without immediate antibiotic treatment.

Measuring and Reducing Racial Bias in a Pediatric Urinary Tract Infection Model.

Clinical predictive models that include race as a predictor have the potential to exacerbate disparities in healthcare. Such models can be respecified to exclude race or optimized to reduce racial bias. We investigated the impact of such respecifications in a predictive model - UTICalc - which was designed to reduce catheterizations in young children with suspected urinary tract infections. To reduce racial bias, race was removed from the UTICalc logistic regression model and replaced with two new features. We compared the two versions of UTICalc using fairness and predictive performance metrics to understand the effects on racial bias. In addition, we derived three new models for UTICalc to specifically improve racial fairness. Our results show that, as predicted by previously described impossibility results, fairness cannot be simultaneously improved on all fairness metrics, and model respecification may improve racial fairness but decrease overall predictive performance.

Accuracy of Urinalysis for UTI in Spina Bifida.

OBJECTIVES: Urinary tract infections (UTIs) are common, but overdiagnosed, in children with spina bifida. We sought to evaluate the diagnostic test characteristics of urinalysis (UA) findings for symptomatic UTI in children with spina bifida. METHODS: Retrospective cross-sectional study using data from 2 centers from January 1, 2016, to December 31, 2021. Children with myelomeningocele aged <19 years who had paired UA (and microscopy, when available) and urine culture were included. The primary outcome was symptomatic UTI. We used generalized estimating equations to control for multiple encounters per child and calculated area under the receiver operating characteristics curve, sensitivity, and specificity for positive nitrites, pyuria (≥10 white blood cells/high-powered field), and leukocyte esterase (more than trace) for a symptomatic UTI. RESULTS: We included 974 encounters from 319 unique children, of which 120 (12.3%) met our criteria for UTI. Pyuria had the highest sensitivity while nitrites were the most specific. Comparatively, nitrites were the least sensitive and pyuria was the least specific. When the cohort was limited to children with symptoms of a UTI, pyuria remained the most sensitive parameter, whereas nitrites remained the least sensitive. Nitrites continued to be the most specific, whereas pyuria was the least specific. Among all encounters, the overall area under the receiver operating characteristics curve for all components of the UA was lower in children who use clean intermittent catheterizations compared with all others. CONCLUSIONS: Individual UA findings have moderate sensitivity (leukocyte esterase or pyuria) or specificity (nitrites) but overall poor diagnostic accuracy for symptomatic UTIs in children with spina bifida.

Development and Validation of an Automated Classifier to Diagnose Acute Otitis Media in Children.

Importance: Acute otitis media (AOM) is a frequently diagnosed illness in children, yet the accuracy of diagnosis has been consistently low. Multiple neural networks have been developed to recognize the presence of AOM with limited clinical application. Objective: To develop and internally validate an artificial intelligence decision-support tool to interpret videos of the tympanic membrane and enhance accuracy in the diagnosis of AOM. Design, Setting, and Participants: This diagnostic study analyzed otoscopic videos of the tympanic membrane captured using a smartphone during outpatient clinic visits at 2 sites in Pennsylvania between 2018 and 2023. Eligible participants included children who presented for sick visits or wellness visits. Exposure: Otoscopic examination. Main Outcomes and Measures: Using the otoscopic videos that were annotated by validated otoscopists, a deep residual-recurrent neural network was trained to predict both features of the tympanic membrane and the diagnosis of AOM vs no AOM. The accuracy of this network was compared with a second network trained using a decision tree approach. A noise quality filter was also trained to prompt users that the video segment acquired may not be adequate for diagnostic purposes. Results: Using 1151 videos from 635 children (majority younger than 3 years of age), the deep residual-recurrent neural network had almost identical diagnostic accuracy as the decision tree network. The finalized deep residual-recurrent neural network algorithm classified tympanic membrane videos into AOM vs no AOM categories with a sensitivity of 93.8% (95% CI, 92.6%-95.0%) and specificity of 93.5% (95% CI, 92.8%-94.3%) and the decision tree model had a sensitivity of 93.7% (95% CI, 92.4%-94.9%) and specificity of 93.3% (92.5%-94.1%). Of the tympanic membrane features outputted, bulging of the TM most closely aligned with the predicted diagnosis; bulging was present in 230 of 230 cases (100%) in which the diagnosis was predicted to be AOM in the test set. Conclusions and Relevance: These findings suggest that given its high accuracy, the algorithm and medical-grade application that facilitates image acquisition and quality filtering could reasonably be used in primary care or acute care settings to aid with automated diagnosis of AOM and decisions regarding treatment.

Nasopharyngeal metatranscriptomics reveals host-pathogen signatures of pediatric sinusitis.

Acute sinusitis (AS) is the fifth leading cause of antibiotic prescriptions in children. Distinguishing bacterial AS from common viral upper respiratory infections in children is crucial to prevent unnecessary antibiotic use but is challenging with current diagnostic methods. Despite its speed and cost, untargeted RNA sequencing of clinical samples from children with suspected AS has the potential to overcome several limitations of other methods. However, the utility of sequencing-based approaches in analysis of AS has not been fully explored. Here, we performed RNA-seq of nasopharyngeal samples from 221 children with clinically diagnosed AS to characterize their pathogen and host-response profiles. Results from RNA-seq were compared with those obtained using culture for three common bacterial pathogens and qRT-PCR for 12 respiratory viruses. Metatranscriptomic pathogen detection showed high concordance with culture or qRT-PCR, showing 87%/81% sensitivity (sens) / specificity (spec) for detecting bacteria, and 86%/92% (sens/spec) for viruses, respectively. We also detected an additional 22 pathogens not tested for in the clinical panel, and identified plausible pathogens in 11/19 (58%) of cases where no organism was detected by culture or qRT-PCR. We assembled genomes of 205 viruses across the samples including novel strains of coronaviruses, respiratory syncytial virus (RSV), and enterovirus D68. By analyzing host gene expression, we identified host-response signatures that distinguished bacterial and viral infections and correlated with pathogen abundance. Ultimately, our study demonstrates the potential of untargeted metatranscriptomics for in depth analysis of the etiology of AS, comprehensive host-response profiling, and using these together to work towards optimized patient care.