A systematic review of definitions and reporting of bleeding outcome measures in haemophilia
Bibliographic record
Abstract
INTRODUCTION: Bleeding frequency is an important outcome commonly used in haemophilia studies. There is a variation in practice in how bleeding is measured and defined. AIM: The primary objective of this study was to determine how investigators define and report bleeding outcome measures. METHODS: MEDLINE, EMBASE and the CENTRAL were searched from January 1990 to January 2014. We retrieved all published studies that included patients with haemophilia A or B and reported some measures of bleeding. Two reviewers independently performed title and abstract screening, full-text review and data abstraction of the identified studies. RESULTS: A total of 118 studies fulfilled the inclusion criteria. Study designs were randomized controlled trials (RCT; 14%), cohort (68%), cross-sectional (5%) and others design (11%). The median duration of follow-up (Q1, Q3) was 20 (7.9, 50) months. We found 10 different bleeding outcomes reported [absolute number of bleeding 60 (50.8%) studies, annualized bleeding rate 60 (50.8%) studies, bleed per month 10 (8.5%) studies and others 11 (9.3%) studies]. Of these, 32 (27%) studies reported only mean or median without dispersion and 33 (28%) studies did not report any measures of central tendency (dispersion). CONCLUSIONS: There is substantial variation in definitions and measures of bleeding outcomes in the haemophilia literature. This creates difficulty and limitations in comparing the outcomes between studies and in performing meta-analysis. The haemophilia research community needs to develop a consensus on a clear definition of bleeding and how to address the limitations associated with variations in measures of bleeding between centres and 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 | 0.058 | 0.240 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.014 | 0.010 |
| Bibliometrics | 0.024 | 0.024 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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; 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".