Bibliographic record
Abstract
Pain in infancy and childhood is extremely common. Sources of pain include illness, injury, and medical and dental procedures. Over the past two decades, tremendous progress has been made in the assessment, prevention and treatment of pain. It is important for the paediatric health care provider to be aware of the implications and consequences of pain in childhood. A multitude of interventions are available to reduce or alleviate pain in children of all ages, including neonates. These include behavioural and psychological methods, as well as a host of pharmacological preparations, which are safe and effective when used as indicated. Many complementary and alternative treatments appear to be promising in treating and relieving pain, although further research is required. The present article reviews the most common sources of pain in childhood and infancy, as well as current treatment strategies and options. Les douleurs sont extrêmement courantes chez les nourrissons et les enfants. Elles sont causées par les maladies, les blessures et les interventions médicales et dentaires. Depuis vingt ans, on a réalisé de remarquables progrès dans l'évaluation, la prévention et le traitement de la douleur. Le dispensateur de soins pédiatriques doit connaître les répercussions et les conséquences de la douleur pendant l'enfance. Il existe une multitude d'interventions pour réduire ou soulager la douleur chez les enfants de tout âge, y compris les nouveaunés. Il peut s'agir de méthodes comportementales ou psychologiques ou de toute une série de préparations pharmacologiques sécuritaires et efficaces lorsqu'elles sont utilisées conformément aux indications. De nombreuses approches complémentaires et parallèles en santé semblent prometteuses dans le traitement et le soulagement de la douleur, mais il faudra des recherches plus approfondies à ce sujet. Le présent article contient un examen des principales sources de douleur chez l'enfant et le nourrisson, de même que des stratégies et possibilités de traitement actuelles.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.020 | 0.003 |
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".