Efficacy and safety of the “mother’s kiss” technique: a systematic review of case reports and case series
Bibliographic record
Abstract
BACKGROUND: Foreign bodies lodged in the nasal cavity are a common problem in children, and their removal can be challenging. The published studies relating to the "mother's kiss" all take the form of case reports and case series. We sought to assess the efficacy and safety of this technique. METHODS: We performed a comprehensive search of the Cochrane library, MEDLINE, CINAHL, Embase, AMED Complementary and Allied Medicine and the British Nursing Index for relevant articles. We restricted the results to only those studies involving humans. In addition, we checked the references of relevant studies to identify further possibly relevant studies. We also checked current controlled trials registers and the World Health Organization search portal. Our primary outcome measures were the successful extraction of the foreign object from the nasal cavity and any reported adverse effects. We assessed the included studies for factors that might predict the chance of success of the technique. We assessed the validity of each study using the Newcastle-Ottawa scale. RESULTS: Eight relevant published articles met our inclusion criteria. The overall success rate for all of the case series was 59.9% (91/152). No adverse effects were reported. INTERPRETATION: Evidence from case reports and case series suggests that the mother's kiss technique is a useful and safe first-line option for the removal of foreign bodies from the nasal cavities of children.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.012 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".