Understanding hypermobile Ehlers-Danlos syndrome and Hypermobility Spectrum Disorders in the context of childbearing: An international qualitative study
Bibliographic record
Abstract
OBJECTIVE: The Ehlers-Danlos syndromes (EDS) and Hypermobility Spectrum Disorders (HSD) have profound and life-threatening consequences in childbearing as they affect connective tissues throughout the body. Hypermobile EDS (hEDS) and HSD are estimated here for the first time to affect 6 million (4.6%) pregnancies globally per year. The aim of this study was to arrive at a deeper biopsychosocial understanding of childbearing in the context of hEDS/HSD. METHODS: English speaking women aged over 18 years who had previously given birth and had a confirmed medical diagnosis of hEDS/HSD or equivalent diagnosis under a preceding nosology were included in this study (n=40). Narrative interviews were used to collect qualitative data from this international sample of participants. Thematic narrative analysis was used to understand how participants made sense of their experiences. FINDINGS: Participants were aged between 25 and 55. Births (n= 52) between 1981 and 2018 were captured across United Kingdom=29 (73%), United States of America=10 (25%) and Canada=1 (2%). The majority of participants interviewed recounted a worsening of symptoms during pregnancy and postnatal complications. Anaesthesia was often reportedly ineffective, and for many, long latent phases of labour quickly developed into rapidly progressing active labours and births. Maternity staff were observed to be panicked by these unexpected outcomes and were deemed to lack the knowledge and understanding of how to care for women in this context. Poor maternity care resulted in women disengaging from services, trauma, stress, anxiety and an avoidance of future childbearing. KEY CONCLUSIONS AND IMPLICATIONS FOR PRACTICE: Cases of hEDS/HSD should no longer be considered rare in maternity services. Maternity staff must be adequately prepared for this new reality. As a first step, www.hEDSTogether.com has been developed to provide a repository of evidence in relation to this topic, along with a freely downloadable toolkit for use in practice. It is important to listen, acknowledge and respond to women with hEDS/HSD appropriately throughout their childbearing journey. Dismissal can lead to trauma and needless morbidity.
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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 | 0.014 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.012 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.004 |
| 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".