Clinical Practice Guideline for Best Practice Management of Pediatric Patients by Chiropractors: Results of a Delphi Consensus Process
Bibliographic record
Abstract
Objective: To build upon existing recommendations on best practices for chiropractic management of children by conducting a formal consensus process and best evidence synthesis. Design: Best practice guide based on recommendations from current best available evidence and formal consensus of a panel of experienced practitioners, consumers, and experts for chiropractic management of pediatric patients. Methods: Synthesis of results of a literature search to inform the development of recommendations from a multidisciplinary steering committee, including experts in pediatrics, followed by a formal Delphi panel consensus process. Results: The consensus process was conducted June to August 2022. All 60 panelists completed the process and reached at least 80% consensus on all recommendations after three Delphi rounds. Recommendations for best practices for chiropractic care for children addressed these aspects of the clinical encounter: patient communication, including informed consent; appropriate clinical history, including health habits; appropriate physical examination procedures; red flags/contraindications to chiropractic care and/or spinal manipulation; aspects of chiropractic management of pediatric patients, including infants; modifications of spinal manipulation and other manual procedures for pediatric patients; appropriate referral and comanagement; and appropriate health promotion and disease prevention practices. Conclusion: This set of recommendations represents a general framework for an evidence-informed and reasonable approach to the management of pediatric patients by chiropractors.
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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 | 0.158 | 0.183 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.007 |
| Bibliometrics | 0.012 | 0.012 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.005 | 0.007 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.007 | 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".