Cardiac Implications of Adenotonsillar Hypertrophy and Obstructive Sleep Apnea in Pediatric Patients: A Comprehensive Systematic Review
Bibliographic record
Abstract
This review investigates the relationship between pediatric obstructive sleep apnea, often associated with adenotonsillar hypertrophy, and cardiovascular health, particularly pulmonary hypertension. We conducted a comprehensive literature search using electronic databases, including Medline Pub-Med, Scopus, and the Web of Science. The study analyzed a total of 230 articles and screened 48 articles, with 20 included in the final analysis, involving 2429 children. The PRISMA flowchart visually illustrates the selection process, and the ROBINS-E and -I tools help ensure the reliability and validity of the evidence produced by these studies. These studies explored various aspects, including the severity of obstructive sleep apnea, cardiac anomalies, cardiac stress markers, risk factors for pulmonary hypertension, and the impact of adenoidectomy and tonsillectomy on cardiac function. The research found that adenotonsillar hypertrophy and obstructive sleep apnea are significant risk factors for cardiovascular complications, especially pulmonary hypertension, in children. Adenoidectomy and tonsillectomy may provide effective treatments. Following adenoidectomy in relation to obstructive sleep apnea, there appears to be a reduction in mean pulmonary artery pressure during echocardiographic examination. However, the efficacy of these procedures can vary based on the severity of obstructive sleep apnea and individual cardiac conditions. The study also identified concerns regarding data bias. The authors emphasize the need for well-designed clinical studies, including both healthy patients with adenotonsillar hypertrophy and vulnerable children with genetic disorders, to ensure that clinical decisions are based on solid scientific evidence.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".