Study Protocol on Defining Core Outcomes and Data Elements in Chronic Subdural Haematoma
Bibliographic record
Abstract
BACKGROUND: Core Outcome Sets (COSs) are necessary to standardize reporting in research studies. This is urgently required in the field of chronic subdural hematoma (CSDH), one of the most common disease entities managed in neurosurgery and the topic of several recent trials. To complement the development of a COS, a standardized definition and baseline Data Elements (DEs) to be collected in CSDH patients, would further improve study quality and comparability in this heterogeneous population. OBJECTIVE: To, first, define a standardized COS for reporting in all future CSDH studies; and, second, to identify a unified CSDH Definition and set of DEs for reporting in future CSDH studies. METHODS: The overall study design includes a Delphi survey process among 150 respondents from 2 main stakeholder groups: healthcare professionals or researchers (HCPRs) and Patients or carers. HCPR, patients and carers will all be invited to complete the survey on the COS, only the HCPR survey will include questions on definition and DE. EXPECTED OUTCOMES: It is expected that the COS, definition, and DE will be developed through this Delphi survey and that these can be applied in future CSDH studies. This is necessary to help align future research studies on CSDH and to understand the effects of different treatments on patient function and recovery. DISCUSSION: This Delphi survey should result in consensus on a COS and a standardized CSDH Definition and DEs to be used in future CSDH studies.
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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 | 0.148 | 0.189 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.065 | 0.017 |
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".