Effect of prophylactic corticosteroids on postoperative neurocognitive dysfunction
Bibliographic record
Abstract
We appreciate the authors’ interest in our systematic review and meta-analysis examining the effect of corticosteroids on postoperative neurocognitive disorders (PNCDs).[1,2] In our methodology, PNCD was defined as per the original author and encompassed trials assessing PNCD within one month. It is important to note that studies by Dieleman et al.,[3] Ottens et al.[4] and Sauër et al.[5] employed varying definitions and assessment periods for PNCD, leading to different outcomes. Specifically, Dieleman et al.[3] defined the occurrence of delirium as the use of neuroleptic drugs rather than the use of an assessment tool over 30 days, suggesting delirium might be under-recognised. Ottens et al.[4] determined cognitive outcomes by administering a battery of five neuropsychological tests at one month. Sauër et al.[5] defined PNCD as delirium, and the patient was evaluated using the Confusion Assessment Method 4 days postoperatively. The authors stated, ‘in that study, the presence of delirium was defined by the postoperative use of an antipsychotic medication(s), rather than based on delirium screening using a validated instrument, and thus it is likely that delirium was under-recognised’[3] and used this as an objective for formulating their trial. Consequently, despite some overlap in sample size, each study might have reported a different or added patient population, leading to additional information. In the absence of further clarifications of these issues, we treated these studies as independent samples, as they addressed different clinical outcomes in our analysis. Financial support and sponsorship Nil. Conflicts of interest There are no conflicts of interest.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.004 |
| 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 teacher head, 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".