Incidence, Characteristics, and Outcomes of Robin Sequence: A Population-Based Analysis in the United States
Bibliographic record
Abstract
INTRODUCTION: While the literature is replete of clinical studies reporting on the Robin sequence (RS), population-based analyses are scarce with significant variability within the literature in terms of reported incidence, demographic parameters, and outcomes. The authors have conducted a 20-year population-based analysis to guide clinical practice. METHODS: A birth cohort was created from the available datasets in the Healthcare Cost and Utilization Project-Kids' Inpatient Database (HCUP-KID; 2000-2019). Robin sequence patients were identified and further stratified by syndromic status. Incidence, demographic parameters, and outcomes including mortality and tracheostomy rates were computed. A subset analysis comparing the isolated and syndromic cohorts was conducted. Data was analyzed through a χ 2 or t test. RESULTS: The incidence of RS was 5.15:10,000 (95% CI: 4.99-5.31) from a birth cohort of 7.5 million. Overall, 63.3% of the cohort was isolated RS and 36.7% had syndromic RS. Robin sequence patients had a significantly higher rate of cardiac (25.9%) and neurological (8.6%) anomalies compared with the general birth cohort and were most commonly managed in urban teaching hospitals ( P <0.0001). The pooled mortality and tracheostomy rates were 6.6% and 3.6%, respectively. Syndromic status was associated with a longer length of hospital stay (27.8 versus 13.6 d), tracheostomy rate (6.2% versus 2.1%), and mortality (14.1% versus 2.2%) compared with isolated RS ( P <0.0001). CONCLUSIONS: The true incidence of RS is likely higher than previously reported estimates. Isolated RS patients have a low associated mortality and tracheostomy rate and are typically managed in urban teaching hospitals. Syndromic status confers a higher mortality rate, tracheostomy rate, and length of stay compared with nonsyndromic counterparts.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".