Clinical Prediction Models for Suspected Pediatric Foreign Body Aspiration

Abstract

IMPORTANCEAlthough various clinical prediction models (CPMs) have been described for diagnosing pediatric foreign body aspiration (FBA), to our knowledge, there is still no consensus regarding indications for bronchoscopy, the criterion standard for identifying airway foreign bodies.OBJECTIVE To evaluate currently available CPMs for diagnosing FBA in children.DATA SOURCES Performed in Ovid MEDLINE, Ovid Embase, PubMed, Web of Science, and CINAHL database with citation searching of retrieved studies.STUDY SELECTION Prediction model derivation and validation studies for diagnosing FBA in children were included. Exclusion criteria included adult studies; studies that included variables that were not available in routine clinical practice and outcomes for FBA were not separate or extractable.DATA EXTRACTION AND SYNTHESIS We followed the Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modeling Studies and the Prediction Model Risk of Bias Assessment Tool framework. Data were pooled using a random-effects model. MAIN OUTCOMES AND MEASURESThe primary outcome was the diagnosis of FBA as confirmed by bronchoscopy. Characteristics of CPMs and individual predictors were evaluated. The final model presentation with available measures of performance was provided by narrative synthesis. A meta-analysis of individual predictor variables and prediction models was performed.RESULTS After screening 4233 articles, 7 studies (0.2%; 1577 patients) were included in the final analysis. There were 6 model derivation studies and 1 validation study. Air trapping (odds ratio [OR], 8.3; 95% CI, 4.4-15.5), unilateral reduced air entry (OR, 4.8; 95% CI, 3.5-6.5), witnessed choking (OR, 3.1; 95% CI, 1.0-9.6), wheezing (OR, 2.5; 95% CI, 1.2-5.2), and suspicious findings suggestive of FBA on radiography (OR, 18.5; 95% CI, 5.0-67.7) were the most commonly used predictor variables. Model performance varied, with discrimination scores (C statistic) ranging from 0.74 to 0.88. The pooled weighted C statistic score of all models was 0.86 (95% CI, 0.80-0.92). All studies were deemed to be at high risk of bias, with overfitting of models and lack of validation as the most pertinent concerns.CONCLUSIONS AND RELEVANCE This systematic review and meta-analysis suggests that existing CPMs for FBA in children are at a high risk of bias and have not been adequately validated. No current models can be recommended to guide clinical decision-making. Future CPM studies that adhere to recognized standards for development and validation are required.

Current Approach to Diagnosis and Treatment of Foreign Body in Otorhinolaryngology

“…To his day, there are no valid clinical prediction models for FB aspiration. The decision relies on the astute clinical care tailored for each patient by an experienced clinician [49].…”

Foreign body aspiration in children: our pediatric tertiary care experience

“…The clinical course and prognosis of FB inhalation depend on the size and location of the FB, as well as the time that the FB remains in the airway 12 . Therefore, prompt diagnosis and early treatment are crucial to prevent potentially fatal sequelae such as pneumonia, atelectasis, bronchiectasis and acute respiratory failure 13 . Plain chest X-ray is the main investigative tool in FB aspiration, but the de nite diagnosis and subsequent treatment, is provided only by rigid bronchoscopy.…”

Prediction Models for Prognosis of Hypoglycemia in Patients with Diabetes: A Systematic Review and Meta-Analysis

“…In recent years, systematic reviews of predictive models and methods of meta-analyses have been reported, which allow quantitative analysis of predictive models (Debray et al, 2017(Debray et al, , 2019Moons et al, 2014;Wolff et al, 2019). Subsequently, some scholars used these methods to conduct a systematic review and meta-analysis of prognostic prediction models for other diseases and obtained some meaningful results; some predictive models that can be widely used in clinical practice have been found (Bellou et al, 2019; J. J. W. Lee et al, 2021;Siriyotha et al, 2021). However, systematic reviews and meta-analyses of prognostic prediction models for hypoglycemia have not been found by authors.…”