Risk prediction in cardiac surgery and reference values of inflammatory indexes derivated from blood cell count
Bibliographic record
Abstract
Cardiac surgery with cardiopulmonary bypass is a treatment option for severe and selected cases of heart disease. Before indicating surgery, it is essential to correctly estimate the individual surgical risk, which currently uses a complex score that uses multiple clinical, laboratory and imaging variables. Current literature has focused on easily calculated mathematical ratios based on blood counts that represent a subclinical inflammatory state. The neutrophil-lymphocyte ratio (NLR) is one of these indices and has already demonstrated good predictive value of risk in several clinical oncological, cardiovascular and surgical contexts. The other indices (DNLR: derived NLR, LMR: lymphocyte-monocyte ratio, MLR: monocyte-lymphocyte ratio, PLR: platelet-lymphocyte ratio, NLPR: neutrophil-platelet-lymphocyte ratio, SII: systemic inflammatory index, SIRI: systemic inflammatory reaction index and AISI: aggregate systemic inflammation index) are still being investigated in increasing studies, with some divergent results or restricted to subtypes of cardiac surgeries. Their reference values (RV) also have previous publications using non-standardized determination methods or with diverse populations. The first part of this study determined the RV of these indices using a method recommended in a healthy population of 197 individuals, namely: PLR (56.07 - 187.49), NLR (0.79 - 3.66), LMR (2.04 - 9.35), SII (141.05 - 939.29), SIRI (0.28 - 1.36) and AISI (55.99 - 690.48). The second stage of this study evaluated the role of these ratios in predicting death and complications in 444 patients undergoing cardiac surgery with CPB, focusing on new ratios not yet studied in this context. With the exception of PLR, all indices were predictors of in-hospital death, with greater accuracy for NLR, NLPR and DNLR. With better accuracy for NLR, NLPR and DNLR. For survivors, these three indices were also shown to be predictors of adverse postoperative outcomes. All BCCII components correlated with length of hospital stay. Mortality rates were 3-4 times higher above the following values: NLR≥3.66, NLPR≥1.28, DNLR>2.68, MLR≥0.49, SII>939, SIRI≥2.36, and AISI≥690.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".