P385: Understanding clinician needs and preferences with respect to returned NBS results
Bibliographic record
Abstract
text review, and 25 were included.Data on patient characteristics, GS methods, turn-around time, diagnostic rate, and change in clinical management were extracted.How clinical utility was defined and measured across publications was synthesized thematically.Guided by existing C-GUIDE items and this scoping review, a preliminary 21-item modified C-GUIDE was created.Clinicians were recruited to participate in qualitative interviews about the relevance, comprehensibility, and comprehensiveness of the modified C-GUIDE to gauge content validity and refine the preliminary list.Eligible clinicians included geneticists, neonatologists, and neurologists routinely involved in genetic testing and/or managing results in NICU settings across Canada.Interviews were conducted virtually, audio-taped, and transcribed.Item-by-item and thematic analyses enabled item refinement and further characterization of this construct of clinical utility.Results: Across 25 publications, clinical utility in this setting was most often defined as a change in clinical management following genetic testing (based on retrospective chart review), with only 7 studies utilizing clinician surveys to assess perceived utility.Across the studies, diagnostic rates of 12-60% were reported for GS and changes in management were reported in 22-100%.Seven putative domains of clinical utility for GS in NICU settings were identified, pertaining to: 1) diagnosis, differential diagnosis and work-up; 2) clinical management; 3) prognosis; 4) referrals; 5) disposition planning; 6) family planning; and 7) psychosocial impact.The role of genotype in selecting pharmaceutical, dietary, and targeted therapeutic interventions, and its contribution to discussions on redirection of care were particularly salient.To date, 14 qualitative interviews with 9 medical geneticists, 4 neonatologists, and 1 neurologist based in 4 Canadian provinces have been completed.Qualitative analysis revealed the following themes: 1) perceived clinical utility is improved across all domains with more rapid turn-around times; 2) GS can allow for cessation of a potentially invasive work-up; 3) streamlined management plans guided by prognosis can improve quality of life for neonates; 4) provision of an "answer" can improve parental understanding, strengthen decision-making, and reduce guilt; and 5) genetic information can facilitate essential social connection via identification of other families and support groups.Themes of "disutility" included: 1) potential prolongation of ICU stay while awaiting GS results; and 2) familial psychosocial harm, in general, associated with the pursuit of genetic testing.Conclusion: While the literature highlighted a high frequency of diagnosis and changes in medical management associated with GS in NICU settings, a broader definition of clinical utility is lacking with no standardized methods to capture clinical utility currently in use.Our preliminary, expert-informed, modified C-GUIDE defines clinical utility as a broad construct that contributes to diagnosis and prognosis, reduction in diagnostic work-up, clinical management, informed discussions on goals of care, disposition planning, and family psychosocial functioning.Qualitative interviews will be completed by the end of 2022, and itembased feedback will be synthesized to guide the development of a refined item list through a Delphi consensus process.Following validation, C-GUIDE NICU will be available for use.
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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 | 0.096 | 0.377 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.019 | 0.003 |
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".