Genome sequencing among children with medical complexity: What constitutes value from parents’ perspective?
Bibliographic record
Abstract
Genome sequencing (GS) has demonstrated high diagnostic yield in pediatric patients with complex, clinically heterogeneous presentations. Emerging evidence shows generally favorable experiences for patients and families receiving GS. As a result, implementation of GS in pediatrics is gaining momentum. To inform implementation, we conducted a qualitative study to explore the personal utility of GS for parents of children with medical complexity (CMC). GS was performed at an academic tertiary-care center for CMC for whom a genetic etiology was suspected. Following the return of GS results, semi-structured interviews were conducted with 14 parents about their child's diagnostic journey. Of the children whose parents were interviewed, six children received a diagnosis, two received a possible diagnosis, and six did not receive a diagnosis. A predominantly deductive thematic analysis approach to the interview data was used by applying Kohler's personal utility framework to understand affective, cognitive, behavioral and social impacts of GS. Both the diagnosed and undiagnosed groups experienced enhanced emotion-focused coping (affective). The diagnosed group experienced favorable utility related to knowledge of condition (cognitive) and communication with relatives (behavioral). A domain beyond Kohler's framework related to the presence or absence of GS impact on medical management was also described by parents. The deployment of GS late in the diagnostic odyssey and the limited knowledge available for the rare genetic disorders diagnosed in this cohort appeared to diminish the perceived utility of GS. As GS capabilities continue to evolve at a rapid pace and become available earlier in the diagnostic journey, it is important to consider the impact and timing of testing on parents of CMC.
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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 | 0.007 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| 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".