Global, Regional, and National Survey on Burden and Quality of Care Index (QCI) of Orofacial Clefts: Global Burden of Disease Systematic Analysis 1990–2019
Bibliographic record
Abstract
Abstract Background Orofacial clefts are the most common craniofacial anomalies that include a variety of conditions affecting the lips and oral cavity. They remain a significant global public health challenge. Despite this, the quality of care for orofacial clefts has not been investigated in global and country level. Objective We aimed to measure the quality of care index (QCI) for orofacial clefts worldwide. Methods We used the 2019 Global Burden of Disease data to create a multifactorial index (QCI) to assess orofacial clefts globally and nationally. By utilizing data on incidence, prevalence, years of life lost, and years lived with disability, we defined four ratios aimed at indirectly reflecting the quality of healthcare. Subsequently, we conducted a principal component analysis to identify the most critical variables that could account for the observed variability. The outcome of this analysis was defined as the QCI for orofacial clefts. Following this, we tracked the QCI trends among males and females worldwide, across various regions and countries, considering factors such as the socio-demographic index and World Bank classifications. Results Globally, the QCI for orofacial clefts exhibited a consistent upward trend from 1990 to 2019 (66.4 to 90.2) overall and for females (82.9 to 94.3) and males (72.8 to 93.6). In the year 2019, the top five countries with the highest QCI scores were as follows: Norway (QCI=99.9), Ireland (99.4), France (99.4), Germany (99.3), the Netherlands (99.3), and Malta (99.3). Conversely, the five countries with the lowest QCI scores on a global scale in 2019 were Somalia (59.1), Niger (67.6), Burkina Faso (72.6), Ethiopia (73.0), and Mali (74.4). Gender difference showed a converging trend from 1990 to 2019 (optimize gender disparity ratio (GDR): 123 vs. 163 countries), and the GDR showed a move toward optimization (between 0.95 and 1.05) in the better and worse parts of the world. Conclusion Despite the positive results regarding the QCI for orofacial clefts worldwide, some countries showed a slight negative trend.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".