Cleft lip and/or palate mortality trends in the USA: a retrospective population-based study
Why this work is in the frame
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Bibliographic record
Abstract
Background Cleft lip and/or palate (CL/P) is one of the most common congenital anomalies worldwide. Although CL/P management may require a series of interventions, mortality resulting from CL/P alone is rare. This study aims to examine recent trends of CL/P mortality rates in the USA. Methods A retrospective population-based study was conducted using official US birth and death certificate data from the Centers for Disease Control and Prevention from 2000 to 2019. Annual mortality rates per 1000 births with CL/P were calculated across sex and racial groups. Multivariable logistic regression models estimated the effects of sex and race on the risk of mortality with CL/P, and linear regression models were used to examine temporal changes in mortality rate across sex and race. Results From 2000 to 2019, 1119 deaths occurred in patients with documented CL/P, for an overall incidence of 20.3 deaths per 1000 births with CL/P (95% CI 18.9 to 22.8). Of these, Patau syndrome was the listed cause of death in 167 cases (14.9%). Black individuals (OR 1.93, 95% CI 1.85 to 2.01), Hispanic (1.54, 1.49 to 1.58) and American Indian individuals (1.28, 1.20 to 1.35) were at a greater risk of CL/P mortality compared with white individuals. Additionally, females were also at a greater risk (1.35, 1.21 to 1.49). A significant upward trend in CL/P mortality was observed in Hispanic (r 2 =0.70, p<0.01) and American Indian individuals (r 2 =0.81, p<0.01) from 2000 to 2019. Conclusions Cleft birth and mortality surveillance is essential in healthcare and prevention planning. Future studies are required to understand the differences in CL/P mortality rates across various sociodemographic groups.
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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 | 0.002 | 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 it