A characterization of cortisol level and adrenal reservation in human cardiopulmonary arrest: systematic review and meta-analysis
Bibliographic record
Abstract
Abstract Background Cardiopulmonary arrest (CPA) is an urgency, which is associated with high mortality. This systematic review evaluated the relationship between baseline cortisol level and the outcome of resuscitated CPA patients. Methods We searched the following databases: PubMed, Scopus, ISI Web of Science, and Google Scholar. Relevant observational and controlled trials were explored from inception by April 2020. The quality of the articles was assessed using the Newcastle-Ottawa Scale (NOS). Results Finally, five cohort studies (n = 201 participants in total) were eligible for including in the meta-analysis. The results of this meta-analysis showed that although the baseline serum cortisol levels were higher in survivors of cardiac arrest compared with non-survivors, the differences between groups do not reach a significance level (Hedges’ g = 0.371, 95% CI, −0.727, 1.469, P value = 0.508). Between-study heterogeneity was statistically significant (Cochrane Q test: P value < 0.001, I2 = 89.323). Conclusions The result of the present meta-analysis was suggestive of a higher baseline serum cortisol levels in survivors of CPA. Future randomized controlled studies with a large sample size will determine the exact relationship between adrenal reservation and the eventual outcome of patients with CPA. Systematic review registration PROSPERO CRD42018085468
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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 | 0.013 | 0.037 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.029 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".