25 Application of the 2017 Hypermobile Ehlers Danlos Syndrome Diagnostic Criteria in a Paediatric Population
Bibliographic record
Abstract
The genetic basis for hypermobile Ehlers Danlos Syndrome (hEDS) remains unknown. As such, it continues to be a clinical diagnosis. In March 2017, the International Consortium on EDS and Related Disorders published a revised set of diagnostic criteria for hEDS to help reduce heterogeneity between patients and enable researchers to ultimately identify the genetic cause. Currently there is a need to evaluate how these new criteria impact the diagnosis of hEDS in clinical settings. In 2017, the first paediatric EDS clinic in Canada opened to care for patients with suspected EDS. Since March of 2017, diagnostic assessment of all patients has included application of the 2017 criteria. (1) To determine diagnostic outcomes of patients referred to the EDS clinic in a 14-month period early in its operation. (2) To critically analyze the 2017 hEDS diagnostic criteria in a paediatric population with suspected EDS. We conducted a retrospective chart review of all patients seen in the EDS clinic between March 1, 2017 and April 30, 2018. Patient records from initial evaluations were used to construct a database containing demographic information, findings pertinent to the 2017 hEDS diagnostic criteria and non-diagnostic manifestations associated with hEDS. Patients were then stratified into subgroups and univariate analyses were conducted. One hundred and sixty-nine new patients were seen in the clinic in a 14-month period early in its operation. Eleven patients diagnosed with other subtypes of EDS and 6 patients with incomplete assessments were excluded from analysis. One hundred and fifty-two patients were analyzed for this study. There were 54 males and 98 females (2-6yo 18.4%, 7-11yo 25.0%, 12-18yo 56.6%). The majority of patients were referred by paediatricians or family physicians. The most frequent Beighton score, used to measure generalized joint hypermobility (GJH) was 4/9 amongst all patients, suggesting most patients did not present with GJH. Subgroups were established based on initial evaluations at the EDS clinic: Seven patients (4.6%) were diagnosed with hEDS, 30 patients (19.7%) demonstrated GJH and fulfilled some of the hEDS diagnostic criteria, 8 patients (5.3%) demonstrated GJH but did not fulfill any hEDS diagnostic criteria and 107 patients (70.4%) did not demonstrate GJH. This research focuses on the challenges of diagnosing hEDS in the paediatric population and highlights the need for future research focused on diagnosis and management of paediatric patients with hEDS as well as those with similar symptoms but not quite meeting criteria.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".