Perioperative corticosteroid administration: a systematic review and descriptive analysis
Bibliographic record
Abstract
BACKGROUND: Perioperative administration of corticosteroid is common and variable. Guidelines for perioperative corticosteroid administration before non-cardiac non-transplant surgery in patients with current or previous corticosteroid use to reduce the risk of adrenal insufficiency are lacking. Perioperative use of corticosteroid may be associated with serious adverse events, namely hyperglycemia, infection, and poor wound healing. OBJECTIVE: To determine whether perioperative administration of corticosteroids, compared to placebo or no intervention, reduces the incidence of adrenal insufficiency in adult patients undergoing non-cardiac surgery who were or are exposed to corticosteroids. METHODS: We searched MEDLINE via Ovid and PubMed, EMBASE via Ovid, and the Cochrane Central Register of Controlled Trials, all from 1995 to January 2017. SELECTION CRITERIA: We included randomized controlled trials (RCTs), cohort studies, case-studies, and systematic reviews involving adults undergoing non-cardiac non-transplant surgery and reporting the incidence of postoperative adrenal insufficiency. DATA COLLECTION AND ANALYSIS: Two authors independently assessed studies' quality and extracted data. A descriptive and bias assessment analysis was performed. RESULTS: Two RCTs (total of 37 patients), five cohort studies (total of 462 patients), and four systematic reviews were included. Neither RCT showed a significant difference in the outcome. This result was like that of the five cohort studies. The quality of the evidence was low. CONCLUSION: The current use of perioperative corticosteroid supplementation to prevent adrenal insufficiency is not supported by evidence. Given the significant studies' limitations, it is not possible to conclude that perioperative administration of corticosteroids, compared to placebo, reduces the incidence of adrenal insufficiency.
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 | 0.019 | 0.078 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.014 |
| Bibliometrics | 0.023 | 0.026 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".