Assignment of adverse event indexing terms in randomized clinical trials involving spinal manipulative therapy: an audit of records in MEDLINE and EMBASE databases
Bibliographic record
Abstract
BACKGROUND: Reporting of adverse events in randomized clinical trials (RCTs) is encouraged by the authors of The Consolidated Standards of Reporting Trials (CONSORT) statement. With robust methodological design and adequate reporting, RCTs have the potential to provide useful evidence on the incidence of adverse events associated with spinal manipulative therapy (SMT). During a previous investigation, it became apparent that comprehensive search strategies combining text words with indexing terms was not sufficiently sensitive for retrieving records that were known to contain reports on adverse events. The aim of this analysis was to compare the proportion of articles containing data on adverse events associated with SMT that were indexed in MEDLINE and/or EMBASE and the proportion of those that included adverse event-related words in their title or abstract. METHODS: A sample of 140 RCT articles previously identified as containing data on adverse events associated with SMT was used. Articles were checked to determine if: (1) they had been indexed with relevant terms describing adverse events in the MEDLINE and EMBASE databases; and (2) they mentioned adverse events (or any related terms) in the title or abstract. RESULTS: Of the 140 papers, 91% were MEDLINE records, 85% were EMBASE records, 81% were found in both MEDLINE and EMBASE records, and 4% were not in either database. Only 19% mentioned adverse event-related text words in the title or abstract. There was no significant difference between MEDLINE and EMBASE records in the proportion of available papers (p = 0.078). Of the 113 papers that were found in both MEDLINE and EMBASE records, only 3% had adverse event-related indexing terms assigned to them in both databases, while 81% were not assigned an adverse event-related indexing term in either database. CONCLUSIONS: While there was effective indexing of RCTs involving SMT in the MEDLINE and EMBASE databases, there was a failure of allocation of adverse event indexing terms in both databases. We recommend the development of standardized definitions and reporting tools for adverse events associated with SMT. Adequate reporting of adverse events associated with SMT will facilitate accurate indexing of these types of manuscripts in the databases.
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 | 0.942 | 0.965 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.012 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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; both teacher heads agree on what is shown here.
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".