Definition and classification for adverse events following spinal and peripheral joint manipulation and mobilization: A scoping review
Bibliographic record
Abstract
INTRODUCTION: Spinal and peripheral joint manipulation and mobilization are interventions used by many healthcare providers to manage musculoskeletal conditions. Although there are many reports of adverse events (or undesirable outcomes) following such interventions, there is no common definition for an adverse event or clarity on any severity classification. This impedes advances of patient safety initiatives and practice. This scoping review mapped the evidence of adverse event definitions and classification systems following spinal and peripheral joint manipulation and mobilization for musculoskeletal conditions in adults. METHODS: An electronic search of the following databases was performed from inception to February 2021: MEDLINE, EMBASE, CINAHL, Scopus, AMED, ICL, PEDro, Cochrane Library, Open Grey and Open Theses and Dissertations. Studies including adults (18 to 65 years old) with a musculoskeletal condition receiving spinal or peripheral joint manipulation or mobilization and providing an adverse event definition and/or classification were included. All study designs of peer-reviewed publications were considered. Data from included studies were charted using a standardized data extraction form and synthesised using narrative analysis. RESULTS: From 8248 identified studies, 98 were included in the final synthesis. A direct definition for an adverse event and/or classification system was provided in 69 studies, while 29 provided an indirect definition and/or classification system. The most common descriptors to define an adverse event were causality, symptom severity, onset and duration. Twenty-three studies that provided a classification system described only the end anchors (e.g., mild/minor and/or serious) of the classification while 26 described multiple categories (e.g., moderate, severe). CONCLUSION: A vast array of terms, definition and classification systems were identified. There is no one common definition or classification for adverse events following spinal and peripheral joint manipulation and mobilization. Findings support the urgent need for consensus on the terms, definition and classification system for adverse events related to these interventions.
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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 | 0.037 | 0.151 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.008 |
| Bibliometrics | 0.031 | 0.024 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".