Synthetic teaching case
Case 2: two independent caution pathways
Synthetic LASIK example showing why CER-AI does not hide discordance inside one average score.
Not real patient dataThis worked example was created to teach the current CER-AI v2.0 rules. It is not a clinical decision.
Source inputs
| Field | Value |
|---|---|
| Procedure | LASIK |
| Age / thinnest | 25 years / 505 µm |
| I-S / SRAX | +0.80 D / 15° |
| Manifest MRSE | -5.00 D |
| Flap / ablation / RSB | 110 / 70 / 325 µm |
| Final BAD-D | 2.00 |
| NICE inputs | K2 46 D; central 505 µm; B.Ele.Th 16 µm; I-S 0.80 D |
Pathway evaluation
| System | Calculation / finding | Result |
|---|---|---|
| ERSS | Topography 1 + pachymetry 1 = 2 | PASS |
| BAD-D | 2.00 suspicious | CAUTION |
| NICE | 2 + 2 + 2 + 1 = 7 | CAUTION |
| PS3 | Complete; no Moderate/High | PASS |
| Tissue safety | Independent checks complete | PASS |
Final CER-AI result
PASS WITH CAUTION
Report summary
The report lists BAD-D and NICE as separate caution drivers. Because exactly two of the four completed scoring systems are CAUTION and no stop is present, the combined result is PASS WITH CAUTION.
Learning points
- NICE points are not added to ERSS points.
- BAD-D component context does not create extra caution counts.
- The surgeon sees which pathways disagree and reviews the underlying maps.