[Chinese consensus of cardiopulmonary resuscitation guides prevention, treatment and rescue of cardiac arrest in pregnancy].
Bibliographic record
Abstract
Pregnant women are a group of people in a special period, once sudden cardiac arrest (CA) occurs, it will threaten the life of both mother and child. It has become a great challenge for hospital, doctors and nurses to minimize maternal mortality during pregnancy. All the efforts should ensure the safety of both mother and child throughout the perinatal period. Because difference of the cardiopulmonary resuscitation strategies for common CA patients of the same age, the resuscitation strategies for CA patients during pregnancy need consider the patient's gestational age and fetal condition. Different resuscitation techniques, such as manual left uterine displacement (MLUD), will involve perimortem cesarean delivery (PMCD). At the same time, drugs should be reasonably used for different causes of CA during pregnancy, such as hypoxemia, hypovolemia, hyperkalemia or hypokalemia and other electrolyte disorders and hypothermia in 4Hs, as well as thrombosis, pericardial tamponade, tension pneumothorax and toxicosis in 4Ts. In view of the fact that many causes of CA in pregnancy are preventable, it is more necessary to introduce guidelines for CA in pregnancy in line with our national conditions for clinical guidance. This paper systematically reviewed the pathophysiological characteristics of CA during pregnancy, the high-risk factors of CA during pregnancy, and identified the correct resuscitation methods and prevention and treatment strategies of CA during pregnancy.
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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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.010 | 0.006 |
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".