Clinical validity of karyotyping for the diagnosis of chromosomal imbalance following array comparative genomic hybridisation
Bibliographic record
Abstract
BACKGROUND: Array comparative genomic hybridisation (aCGH) represents a major advance in the ability to detect chromosomal imbalances (CI). A recent meta-analysis recommended aCGH for replacing karyotyping for patients with unexplained disabilities. However, favouring aCGH over karyotyping must be based on solid evidence due to the major implications of selecting a preferential diagnostic tool. METHODS AND RESULTS: A prospective study of 376 samples was conducted to assess the relevance of karyotyping after a first-tier aCGH in patients with unexplained disabilities. aCGH detected CI in 28.7% of the cases. Out of 376 patients, 288 had undergone parallel karyotyping testing: 69.8% (201/288) showed similar results for both aCGH and karyotyping. For patients with a CI detected by aCGH, 7.9% (7/89) showed similar results for both aCGH and karyotyping. Among 20 patients with abnormal karyotyping, 13 showed dissimilar results compared to aCGH analysis: 4 patients (1.4%) had balanced rearrangements and 9 patients (3.1%) had additional chromosomal anomalies unseen using aCGH. This rate of unseen chromosomal anomalies is far superior to the previously estimated 0.5-0.78% prevalence and affects 10.1% (9/89) of patients with CI detected by aCGH in the tested population. CONCLUSIONS: Since the clinical significance of CI identified by aCGH might be influenced by such discrepancies between the two methods, these may in turn have an impact on clinical diagnosis and patient counselling. It is proposed that each genetic laboratory should evaluate the relevance of karyotyping for all first-tier abnormal aCGH results in order to include the genomic (chromosomal) aspects of the aCGH findings in the diagnosis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".