Heparin-Mediated Hypotension Associated with Cardiac Surgery
Bibliographic record
Abstract
In Response: We thank Drs. Slaughter and Mark for their interest in this topic, their case description, and their subsequent discussion. Clearly, an association between administration of IV heparin for cardiopulmonary bypass and subsequent hemodynamic instability exists (1–4). The factors which are causal, versus confounding, remain unclear. Our study (1), by its case-control nature, was hypothesis-generating, and we found an association among change in serum potassium, heparin administration, and hemodynamic change. Regarding the observed mean increase of 1.94 mmol/L in serum potassium in the treated group in our review, the range was from 1.14 to 3.04 mmol/L. The lack of any observed change in serum potassium in Slaughter and Mark’s patient would have been unusual in our review, although statistical comparisons would not be possible based on one patient. However, it is noted that Slaughter and Mark administered 300 IU/kg of porcine heparin, whereas our patients received 400 IU/kg. The dose-response effect, if any, of heparin on serum electrolyte levels is unknown and may explain part of the difference in these observations. The other mechanisms suggested by Slaughter and Mark, including hypocalcemia (2) and histamine release (3) merit further investigation. Although not reported in our earlier work (1), we observed a nonsignificant increase in serum ionized calcium in the treated group of 0.01 mmol/L (range: −0.32 to +0.62) and a nonsignificant decrease in the nontreated group of 0.02 mmol/L (range: −0.34 to +0.41). Further investigation might also include, in addition to the dose-response relationship (if any), determination of the frequency and intensity of the hemodynamic effect associated with heparin, its complete hemodynamic characterization (i.e., effect on systemic and pulmonary vascular resistances, cardiac output, and filling pressures), the decay curve of this hemodynamic effect, the association with any patient- or procedure-descriptors, and impact of preventive maneuvers. Michael J. Jacka MD, FRCPC, MSc Andrew Clark MD, FRCPC
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".