Early follow-up quality of life and mental health of patients with congenital vascular malformations cared for in a multi-disciplinary specialist centre
Bibliographic record
Abstract
ObjectiveThe study aimed to evaluate the early follow-up quality of life (QoL), pain and mental health of patients with congenital vascular malformation (CVM) from a variety of treatment options.MethodsAll patients with CVM who received care and had follow-up between February 1st 2018 and January 31st 2020 were included. The health-related QoL, pain, and mental health were assessed with RAND Health Care 36-Item Short Form Survey (SF-36), visual analogue score for pain (VAS-P) and Hospital Anxiety and Depression Scale (HADS). Paired t-test was used for all analyses. p < .05 were considered significant.ResultsIn total, 110 patients with a mean age of 36.9 years were included in this study. In all patients following care, significant improvement was found in the bodily pain domain of SF-36 and VAS-P (both p = .01). This was largely driven by high-flow vascular malformation patients who responded better to embolo-sclerotherapy, which revealed significant improvement in the bodily pain domain of SF-36 (p = .002) and VAS-P (p = .02). Patients who received supportive treatment only reported significant improvement in mental health (p = .004) and social functioning (p = .03) domains of SF-36. Meanwhile, patients treated with embolo-sclerotherapy reported significant improvement only in VAS-P (p = .02).ConclusionsThis study concluded that the effects of care on early follow-up QoL, pain and mental health of patients with CVM were heterogenous. Future research should therefore, include larger sample size and longer term follow-up to understand the various factors that affect the QoL and mental health of these patients, as well as the holistic approaches to manage them.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".