Medical and Surgical Management for Heavy Menstrual Bleeding in Women with Ehlers-Danlos Syndrome
Bibliographic record
Abstract
Background Ehlers-Danlos syndrome (EDS) is a heterogenous group of inherited collagen disorders associated with bleeding diathesis. While easy bruising is a diagnostic criterion in many EDS subtypes, it is not a formal diagnostic criterion in the most common subtype, hypermobile EDS (hEDS). As such, EDS diagnosis may be delayed in patients with bleeding of unknown cause. While heavy menstrual bleeding (HMB) is present in up to 60-76% of patients with EDS, there is scarce data on management. Existing studies have primarily focused on hormonal therapies in pediatric and adolescent populations. Objectives To describe the rates of gynecological bleeding and evaluate medical and surgical management of HMB in women with EDS, compared with age-matched controls with von Willebrand disease (VWD). Methods This retrospective cohort study included women (≥18 years) followed by the Northern Alberta Bleeding Disorders Program with a diagnosis of EDS (2000-2023). The cohort was matched to women with VWD by age (± 2 years). Those with other bleeding disorders were excluded. We examined quality of care measures including time from bleeding symptom to EDS diagnosis and surgical management for HMB prior to EDS diagnosis. We compared rates of gynecological bleeding, focusing on medical and surgical management for HMB in EDS patients compared with matched controls. Results We included 42 women with EDS and 42 women with VWD (type 1 VWD in 17 [71%], type 2 in 6 [25%], unspecified in 1 [4%]); median age was 38 years. Median ISTH-BAT bleeding scores were similar in EDS (9, IQR 9-10) and VWD cohorts (8, IQR 5-10). EDS subtypes included: hEDS in 29 (69%), unspecified in 8 (19%), and vascular EDS in 5 (12%). Almost half (19; 45%) had medical genetics consultation for EDS. Most common comorbidities in the EDS cohort included psychiatric disorders (18; 43%), hypertension (11; 26%), dyslipidemia (6; 14%), diabetes (6; 14%), and venous thromboembolism (5; 12%). Women experienced delayed diagnosis despite a high proportion (48% of EDS and 33% of VWD cohort) with known family history of bleeding disorder prior to hematology consult. EDS patients were diagnosed at an older age than VWD (median 33 vs 26 years, P=0.04), and experienced a median of 4 bleeding events prior to diagnosis (vs 3 in VWD, P=0.13). Twelve (29%) EDS patients experienced severe bleeding requiring Emergency Department (ED) visit and 6 (14%) required surgical hemostasis prior to diagnosis. Thirty-seven (88%) women with EDS experienced HMB, including 21 (50%) with severe HMB requiring ED visit, hospitalization, transfusions, or surgical hemostasis. Thirteen (31%) experienced postpartum hemorrhage, 6 (14%) hemorrhagic ovarian cysts, and 4 (10%) antepartum hemorrhage. Despite the high prevalence of gynecological bleeding, only 13 (31%) received gynecology consultation. There was no significant difference in the rates of gynecological bleeding between EDS and VWD. Most common HMB management included tranexamic acid (TXA, 29/37 with HMB; 78%), desmopressin (DDAVP, 21; 57%), oral contraceptive pills (OCP, 18; 49%) and intrauterine system (IUS, 16; 43%). Seven (19%) women did not receive hormonal therapy for HMB. Surgical management included hysterectomy (11; 30%), endometrial ablation (4; 11%), and dilation and curettage (3; 8%). Most hysterectomies/ablations (78%) were performed prior to EDS diagnosis. Those who received TXA had a significantly lower rate of ID than those who did not at last follow-up (21% vs 62%, P=0.01); DDAVP recipients trended towards lower rate of ID (19% vs 48%, P=0.10). Medical and surgical therapy rates were comparable among the 36 VWD patients with HMB: TXA (28/36; 78%), DDAVP (21; 58%), OCP (17; 46%), hysterectomy (7; 19%), and endometrial ablation (3; 8%), except for a trend towards lower IUS use (7; 19%, P=0.05). Nearly half (43%) underwent hysterectomies/ablations prior to VWD diagnosis. Conclusions Women with EDS and bleeding diathesis experienced delayed diagnosis despite high prevalence of known family history and gynecological bleeding. Gynecology consultation, hormonal therapies and TXA for HMB all have room for improvement. Delayed diagnosis and suboptimal medical therapy may contribute to higher rates of surgical hemostasis for HMB in EDS compared to age-matched VWD patients. Better patient and clinician education, and multidisciplinary care may improve timely recognition and management of gynecological bleeding in EDS.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".