Abstract O.43: Partial and Complete Non-response to Intravenous Immunoglobulin in the Acute Treatment of Kawasaki Disease: A Matched Case-control Study
Bibliographic record
Abstract
Introduction: Patients non-responsive to intravenous immunoglobulin (IVIG) in the acute phase of Kawasaki disease (KD) are usually considered a single patient group; however, response to second-line therapy varies significantly. We sought to characterize the pattern of temperature response to IVIG infusion, and to define whether the profile was associated with response to second-line therapy in non-responders. Methods: Patients non-responsive to IVIG (temperature >37.5°C >24 hours after the end of IVIG) were identified. Each IVIG non-responder was matched to a IVIG-responsive control patient of the same age and gender, and with the same duration of fever prior to IVIG. Hourly temperature profiles were obtained from immediately before the start of the IVIG infusion until complete defervescence. Results: n=202 patients non-responsive to IVIG were matched (total n=404). For all, temperature reduced by 0.17 (0.06)°C per g/hr IVIG (p=0.006). Important variation in the temperature profile was noted for patients who did not defervesce with IVIG. Thus, non-responders were further classified as partial non-responders (31%) (temperature decreased to <37.5°C within 24 hours of the end of IVG infusion, but fever recurred) and complete non-responders (69%) (temperature consistently >37.5°C throughout IVIG treatment). The temperature profile during IVIG infusion was similar between complete and partial responders [(EST: -0.26 (0.11)°C per g/hr IVIG (p=0.02) for complete responders vs. EST: -0.20 (0.09)°C (p=0.02) for IVIG responders (responders vs. partial non-responders, p=0.65)]. In complete non-responders, IVIG was not associated with significant decreases in temperature (EST: -0.11 (0.14)°C, p=0.43). Factors associated with complete (vs. partial) non-response included presence of infectious symptoms, differences in multiple laboratory values and IVIG brand. Defervescence in partial non-responders was achieved with a second IVIG dose for 88% of patients compared to only 47% of complete non-responder (p<0.001). Conclusions: Non-response to initial IVIG can be further characterized by the temperature profile, and complete non-responders may require more aggressive second-line therapy.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".