Red Flag Study: An observational cross-sectional survey looking at bleeding in patients with a bleeding disorder who are lost to follow-up
Bibliographic record
Abstract
Abstract Background Regular follow-up visits and routine care is important for people with a mild bleeding disorder in terms of lowering their risk of complications from untreated bleeds and helping them maintain a healthy lifestyle. However, follow-up visits among this population can sometimes be missed for unclear reasons. Aim The present study aimed to question if lost-to-follow-up patients with a bleeding disorder experience unreported but important bleeding events that are not communicated to their haemophilia treatment centre (HTC) and if they could benefit from more frequent clinic visits. Methods A multicentre paper-based cross-sectional survey was sent to people diagnosed with an inherited blood disorder and lost to follow-up for two years or more. Those who met the eligibility criteria received the survey by mail and completed and returned it to their HTC between October 2015 and July 2016. Results Invitation packages were sent to 71 individuals; 14 questionnaires returned, with a survey response rate of 19.7%. Of the 14 returned surveys, only 11 participants were eligible who either responded completely or partially to the survey. Quality of life was reported as almost never or never a problem by all but one participant, who limited activities due to bleeding problems. Spontaneous nosebleeds were sometimes, often or always a problem for three participants; one female participant reported issues associated with heavy menstrual bleeding as often or almost always a problem. Conclusion We concluded that although the mean annual bleeding self-reported events were relatively low, they cannot be underestimated when keeping in mind the limitations and challenges of accessing data among this population. Our study highlighted the importance of educating this group of patients on their bleeding disorder and engaging them in their own care and health status, which may result in improving their health-related quality of life and overall health outcomes.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".