Low-value clinical practices in adult traumatic brain injury: an umbrella review protocol
Bibliographic record
Abstract
INTRODUCTION: Traumatic brain injury (TBI) leads to 50 000 deaths, 85 000 disabilities and costs $60 billion each year in the USA. Despite numerous interventions and treatment options, the outcomes of TBI have improved little over the last three decades. In a previous scoping review and expert consultation survey, we identified 13 potentially low-value clinical practices in acute TBI. The objective of this umbrella review is to synthesise the evidence on potentially low-value clinical practices in the care of acute TBI. METHODS AND ANALYSIS: Using umbrella review methodology, we will search Cochrane Central Register of Controlled Trials, Embase, Epistemonikos, International Prospective Register of Systematic Reviews (PROSPERO) and PubMed to identify systematic reviews evaluating the effect of potential intrahospital low-value practices using tailored population, intervention, comparator, outcome and study design questions based on the results of a previous scoping review. We will present data on the methodological quality of these reviews (Assessing the Methodological Quality of Systematic Reviews-2), reported effect sizes and strength of evidence (Grading of Recommendations, Assessment, Development and Evaluation). ETHICS AND DISSEMINATION: Ethics approval is not required as original data will not be collected. Knowledge users from five healthcare quality organisations and clinical associations are involved in the design and conduct of the study. Results will be disseminated in a peer-reviewed journal, at international scientific meetings and to clinical, healthcare quality and patient-partner associations. This work will support the development of metrics to measure the use of low-value practices, inform policy makers on potential targets for deimplementation and in the long term reduce the use of low-value clinical practices in acute TBI care. PROSPERO REGISTRATION NUMBER: CRD42019132428.
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 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 | 0.088 | 0.083 |
| Meta-epidemiology (narrow) | 0.006 | 0.006 |
| Meta-epidemiology (broad) | 0.015 | 0.013 |
| Bibliometrics | 0.017 | 0.014 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.006 | 0.007 |
| Research integrity | 0.008 | 0.007 |
| Insufficient payload (model declined to judge) | 0.069 | 0.013 |
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".