Neuroprotective Effect of Mild Hypothermia in Patients Undergoing Coronary Artery Surgery With Cardiopulmonary Bypass
Bibliographic record
Abstract
BACKGROUND: Neuropsychological deficits occur in 30% to 80% of patients undergoing heart surgery and are due in part to ischemic cerebral injury during cardiopulmonary bypass. We tested whether mild hypothermia, the most efficacious neuroprotective strategy found in laboratory studies, improved cognitive outcome in patients undergoing coronary artery surgery. METHODS AND RESULTS: Patients 60 years or older scheduled for coronary artery surgery were enrolled. During cardiopulmonary bypass, patients were initially cooled to 32 degrees C then randomly assigned to rewarming to 37 degrees C (control) or 34 degrees C (hypothermic), with no further intraoperative warming. Testing was scheduled preoperatively and 1 week and 3 months postoperatively. Eleven tests were combined into 3 cognitive domains: memory, attention, and psychomotor speed and dexterity. A patient was classified as having a cognitive deficit if a decrease of >/=0.50 SD was realized in 1 or more domains. The incidence of cognitive deficits 1 week after surgery, which was the primary outcome, was 62% () in the control group and 48% () in the hypothermic group (relative risk 0.77, P=0.048). In the hypothermic group, the magnitude of deterioration in attention and in speed and dexterity was reduced by 55.6% (P=0.038) and 41.3% (P=0.042), respectively. At 3 months, the hypothermic group still performed better on one test of speed and dexterity (grooved pegboard). There was no difference in morbidity or mortality. CONCLUSIONS: Our findings support a neuroprotective effect of mild hypothermia in patients undergoing coronary artery surgery and should encourage physicians and perfusionists to pay careful attention to brain temperature during cardiopulmonary bypass.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| 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 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".