Treatment outcomes of digital nasoalveolar moulding in infants with cleft lip and palate: A systematic review with meta‐analysis
Bibliographic record
Abstract
Abstract The aim of this systematic review was to compare the treatment outcomes of digital nasoalveolar moulding (dNAM) technique with conventional nasoalveolar moulding (cNAM) or non‐presurgical intervention protocol in infants with unilateral (UCLP) or bilateral (BCLP) cleft lip and palate. A bibliometric search by MEDLINE (via Ovid), Embase, Cochrane Library, grey literature and manual method was conducted without language restriction until November 2023. Literature screening and data extraction were undertaken in Covidence. The risk of bias was evaluated using the Newcastle‐Ottawa Scale and RoB‐2. Pooled effect sizes were determined through random‐effects statistical model using R‐Software, and the certainty of evidence was assessed using the GRADE approach. Among 775 retrieved articles, nine studies were included for qualitative synthesis (6‐UCLP, 3‐BCLP), with only three eligible UCLP studies for meta‐analysis. In the UCLP group, very low certainty of evidence indicated no difference in alveolar cleft width (SMD, 0.13 mm; 95% CI, −0.31 to 0.57; I 2 , 0%), soft tissue (lip) cleft gap, nasal width, nasal height, and columellar deviation angle changes between dNAM and cNAM. In the BCLP group, qualitative synthesis suggested similar changes in alveolar, lip, and nasal dimensions with dNAM and cNAM. In both cleft groups (UCLP, BCLP), reduced alveolar cleft width was observed in the dNAM group compared to the non‐presurgical intervention protocol, along with fewer clinical visits and reduced chairside time for dNAM compared to cNAM. It can be concluded that the treatment outcomes with dNAM were comparable to cNAM in reducing malformation severity and were advantageous in terms of chairside time and clinical visit frequency. However, the overall quality of evidence is very low and standardization is needed for the virtual workflow regarding the alveolar movements and growth factor algorithms. Registration: PROSPERO‐database (CRD42020186452).
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 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".