Bibliographic record
Abstract
We thank Dr. Paraskevas for his interest in our recent publications [1,2] as regards preoperative statin use and outcomes following cardiac surgery. For the benefit of Dr. Paraskevas, and more importantly, the journal readership, I would like to make the following points. Our first analysis and publication [1] looked at the entire cohort of patients in our database, including patients with stable angina and both valvular and isolated coronary artery diseases. This publication was available online on 6 November 2004. Somewhat perplexed and disappointed with the negative results with regards to any benefit of preoperative statin use on short-term outcomes in this heterogeneous patient population, we pondered whether there may be a subset of patients who may derive benefit from preoperative statin use. In this regard, and as outlined in the Introduction section of the second paper, which was available online on 23 March 2005 [2], we hypothesized that it may be the patients who present specifically with unstable angina who are likely, if any, to gain a benefit. Thus, the patient groups reported and the results of the analyses with respect to statistical parameters are distinctly different in the two papers. By necessity, there is an overlap in the Materials and Methods section with respect to patient selection and the Data Analysis and Statistics section because these methodologies indeed were the same! I take great exception to the claim that ‘most of the Results sections are identical’. Clearly, we have analyzed two very different patient populations in our two manuscripts (reason for which is based on sound biologic rationale) and the logistic regression models and the results with respect to the various ‘odds ratios’ and ‘p values’ are not the same. Because we were interested in the potential benefits of statins with regard to their ‘pleiotropic’ effects, the outcomes of interest analyzed in both studies remained the same. Similarly, there is an overlap in the Discussion section because the rationale for assuming a benefit for statins (and potential explanations for our observed negative results in both studies) does not change. Furthermore, the limitations of both studies are expected to be the same because the statistical methods and analyses applied were similar. Finally, and again by necessity, the Reference section is similar because during the time frame of submitting our manuscripts, no new citations of relevance were found. Contrary to Dr. Paraskevas’ contention, we believe our second manuscript [2], published in this Journal, adds importantly to our initial observations [1] by showing that preoperative statin use is not associated with improved short-term outcomes in a group of patients (unstable angina) who theoretically should gain the most!
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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 | 0.008 | 0.066 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.005 | 0.010 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.025 | 0.064 |
| Insufficient payload (model declined to judge) | 0.008 | 0.008 |
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".